In the work we present here, we assessed how conventional and organic farming systems affected the water relations of soils and crops in the 2017 and 2018 growing seasons. Our study was conducted in the DOK system comparison trial, established as a collaboration of the Swiss Research Institute of Organic Agriculture and Agroscope in 1978 near Basel, Switzerland.We used the DOK trial to test if soil moisture and soil surface evaporation are affected by conventional and organic farming, and if organically and conventionally grown plants differ in their root water uptake depth, stomatal conductance and leaf area. Based on these assessments, we made a rough evaluation of the total water use of the studied organic and conventional farming systems. The goal of this study was to assess how organic and conventional farming systems affect the water relations of soils and crops. In particular, we tested if organic and conventional farming systems lead to marked differences in soil moisture, soil evaporation, as well as root water uptake depth and the stomatal conductance of crops. Our results suggest no differences with regard to soil water evaporation but higher soil moisture in the rooting zone of organically compared to conventionally managed systems. The differences were statistically significant for wheat but not for soybean. Soil water retention curves suggest that soil physical properties do not explain the observed differences in soil moisture between the two systems at the trial site. Also, no differences in root water uptake depth between plants grown in organically or conventional farming systems was detected. We found, however, that organically grown wheat exhibited a generally lower stomatal conductance compared to conventionally grown wheat. Soybean showed similar tendencies but treatment effects on gs and soil moisture were smaller. In addition,rolling bench we found that winter wheat had lower dry matter yield and leaf area in organic farming systems compared to conventional farming systems.

In summary, our study suggests that lower stomatal conductance and smaller leaf area under organic compared to conventional farming can reduce water use and resulted in higher soil moisture in organically compared to conventionally managed wheat at the DOK trial site. Our study revealed trends of higher volumetric soil moisture in the organic compared to the conventional treatment . Specifically, soil moisture under wheat was higher in the organic compared to the conventional treatment at 10–30 cm in 2018 and a similar tendency was observable for soybean in 2017. Previous studies found higher water holding capacities under organic farming . These studies suggest that organic carbon and higher aggregate stability are responsible for these patterns. Previous analyses of soil properties at the DOK trial have reported higher contents of org C and higher aggregate stability in organic compared to conventional systems . The observed trend in soil moisture between the two treatments in our study could thus be the result of a larger storage capacity in organic compared to conventional soils driven by the previously reported differences in physicochemical properties. Importantly, however, differences in soil moisture between the two treatments were most expressed when soils became dry . This suggests that water holding capacity is not the driver of the observed patterns as differences in water holding capacity should become most evident in wet soils. Interestingly, Kundel et al. found similar soil moisture patterns at the same trial for winter wheat in 2017, but their effects were strongest under ample soil water conditions. Alternatively, the observed trends in volumetric soil moisture between the two treatments could be the result of differences in water retention capacities resulting in a less efficient water extraction from the organic compared to the conventional soils. This would mean that the higher volumetric soil moisture observed in the organic compared to the conventional trials, in particular in drying soils, are merely the result of residual water that is not available to the plants. The water retention capacity of a soil is determined by soil physical properties such as soil texture but also org C content.Given that org C content was higher in organic compared to conventional soils,we determined soil water retention capacities in the two treatments with pF curves.We,however,did not find any difference in the pF-curves between the organic and the conventional treatments .

However, technical limitations only enabled measurements of pF values at volumetric moisture contents greater than 13.7 vol%. But looking at the soil moisture data of wheat in 2018, we already observe treatment differences in moisture contents greater than 40% at − 10 to − 30 cm soil depth. Also, the amount of measured soil moisture contents below 13.7 vol% is relatively small and only observed at − 10 cm. In soybean, moisture values below 13.7 vol% were measured mainly at − 20 cm without resulting in significant treatment differences. As a consequence, we conclude that the observed trends in soil moisture patterns between the two treatments are unlikely a result of differences in soil matrix potentials. Comparing the relationship between δ18O and δ2 H values of soil water with those of precipitation can reveal information on soil hydrological processes such as infiltration, residence time or evaporation . Precipitation stable isotope values of the Basel GNIP station as well as precipitation samples collected at the DOK trial site, i.e. the local meteoric water line , plotted close to the GMWL . In contrast, when soil water δ18O and δ2 H values were plotted in a dual isotope space we observed that the slope of soil water lines was significantly less steep than that of the LMWL . Given that evaporation fractionates oxygen and hydrogen isotopes in water differently, the shallow slopes of the soil water lines suggest evaporative water loss from the soil to the atmosphere . When dividing the soil water line into single soil water lines for individual soil depths, we observed less steep slopes in shallower compared to deeper soil layers . This suggests, that evaporative water loss is more pronounced in shallow compared to deep soil layers . Most importantly, the slopes of these depth-specific evaporation lines did not differ between the organic and conventional treatments , which suggests that evaporative water loss does not differ between the organic and the conventional treatments. In turn, this implies that differences in evaporative water loss cannot explain the observed trend in soil moisture between the two treatments. Amooh and Bonsu suggested a negative correlation between soil organic matter and evaporative water loss. Despite higher soil organic matter contents and higher weed coverage in organic compared to conventional systems , the different farming systems did not affect evaporative water loss in our case. However, soil coverage or tillage did not differ between the treatments investigated in this study. Such measures are often part of sustainable farming approaches and have been shown to considerably affect soil water evaporation.

We used the cryogenic extraction technique to obtain water from soil samples for stable isotope analysis following the procedure described in Newberry et al. . Several previous studies have revealed that the cryogenic extraction method can introduce isotope artefacts to theextracted soil water and that factors such as soil texture can influence the magnitude of these artefacts . As such, soil water isotope values obtained with the cryogenic extraction methods need to be interpreted with the consideration of these methodological artefacts. For the data that we present here, it is unlikely that potential artefacts influence the main findings of our study. This is, because it was the main objective of our study to assess differences in soil hydrology between the organic and the conventional treatment. Potential artefacts associated with the cryogenic extraction of soil water are thus identical for samples from both treatments and although these artefacts might introduce errors in absolute δ18O and δ2 H values, they do not influence the comparison of the two treatments. Given that previous studies have shown higher bulk density and root penetration resistance in conventional compared to organic farming systems , we expected root water uptake depths from deeper soil layers of plants in the organic treatment compared to the conventional treatment. Surprisingly, our results did not confirm our expectations. We detected no significant differences in RWU depth between the two treatments in both years and in both species . This is in line with recent findings of Sun et al. showing no effect of organic and conventional cropping systems on water uptake patterns of pea and barley. However,grow table hydroponic soybean plants in the organic treatment showed slightly deeper RWU depths than plants in the conventional treatment, especially when soil moisture was progressively decreasing between DOY 173 and 214 in 2017. This suggests that soybean plants in the organic treatments have access to deeper soil water and thus a larger soil water pool than soybean plants grown in the conventional treatment. Easier root growth in organic soils which have a lower bulk density or a larger water uptake horizon by greater arbuscular mycorrhizal colonization under the organic regime is a possible explanation for the observed patterns in soybean.

However, it is possible that RWU patterns similar to the ones observed on soybean were not detected on winter wheat since wheat plants in the conventional treatment were treated with the growth regulator chlormequat chloride . CCC has been shown to increase the rooting depth of wheat . It could therefore be possible that effects of organic farming on RWU depth could have been countervailed by the application of CCC in the conventional treatment. Also, the differences in root morphology between wheat and soybean having an adventitious and a tap root system, respectively, may be a possible reason for the contrasting patterns observed between the two crops. We found that stomatal conductance of wheat was significantly lower under the organic compared to the conventional treatment and that there was a similar tendency for soybean . This suggests lower per leaf area transpiration rates of wheat growing in the organic compared to the conventional treatment. Given that water retention did not differ between the treatments and soil moisture under wheat was generally higher in the organic treatment at 10–30 cm soil depth, the observed differences in gs of wheat are most likely not a response to moisture availability. gs as well as photosynthetic assimilation were shown to be positively related to N availability . However, we observed mixed results for plant N concentrations and slightly higher assimilation rates in organically grown wheat in 2018 . Hence, N availability can also not explain gs patterns observed in this study. It is possible that plant intrinsic factors or pathogen-induced differences in hydraulic conductivity or root water uptake resulting from the different pest managements of the organic and conventional treatments were responsible for these patterns. Conventionally grown wheat received two fungicide sprayings per season, while organically grown wheat was not treated with any pesticides during 2017 and 2018 . It is known that pathogens infecting xylem tissue can impair plant water transport and status, resulting in lower gs . However, this explanation is rather speculative, also because conventionally grown crops have been shown to be more vulnerable to xylem cavitation compared to organically grown crops . In soybean, farming systems did not affect gs significantly. Sun et al. already found less pronounced effects of organic and conventional farming systems on hydraulic traits of pea compared to barley. It could therefore be that the ability of N-fixation and thus better N nutrition countervailed farming system effects on legumes also in our experiment. Nevertheless, reducing gs and increasing the transpiration efficiency of crops is of great interest in order to maintain yields under increasingly occurring drought events . Thus, our results showing lower gs of wheat under organic crop management point towards the potential of organic farming as a more sustainable and resistant farming system in a changing climate. We analyzed the bulk δ18O values of winter wheat leaves and soybean beans as an independent measure of treatment effects on gs. δ18O values in plants are driven by the δ18O values of the plants’ source water and the evaporative 18O enrichment of leaf water .

Trial factors included three soil tillage systems completely randomised in four replications in two parallel field experiments.Soil cores were transported from the field to the respective partner institution, stored in a cooling room until further steps and processed by each partner according to an internal standard protocol. After drying the whole sample at 40 ◦C until constant weight, the samples were sieved to 2 mm to separate the coarse and the fine fraction . Coarse soil aggregates were destroyed during this step. The masses of both fractions were determined separately for bulk density determination. An aliquot of 10 g was taken from the fine fraction, weighed, dried in an oven at 105 ◦C until the weight was constant, cooled in a desiccator and weighed again. The residual water content was used to calculate the difference between the 105 ◦C dry mass and the 40 ◦C mass. A representative sub-sample was taken from the 40 ◦C dried fine fraction and finely ground with a ball or mortar mill. The 40 ◦C dried, 2 mm sieved and ground sub-samples were sent to the Research Institute of Organic Agriculture FiBL for further analysis. Reduced tillage clearly increased topsoil SOC stocks and decreased SOC stocks in or just below the old plough layer compared with traditional ploughing. Such a SOC stratification effect can be linked to the lack of mixing of organic matter into deeper soil layers achieved by ploughing and is limited to the topsoil in the case of reduced tillage. It may also be related to a change in root growth. Higher root length densities in the topsoil and lower densities in the layers to 30 cm depth compared with ploughing was found across no-till studies globally and for reduced tillage at the French site of our study . There, hydroponic grow system root abundance under reduced tillage was higher in 0–6 cm and lower in 12–70 cm. This root growth effect was attributed to the stratification of nutrients and a change in bulk density.

Higher bulk densities in soil layers lower than 10/15 cm measured in this study confirm a potentially growth limiting factor for roots into subsoil layers. They also suggest that the SOC stock decrease below the upper soil layer and the large SOC stock increase in the upper soil layer despite no change in bulk densities was mainly driven by changes in SOC content. We found higher SOC stocks in 70–100 cm soil depth across seven sites. Sampling deeper than 70 cm was impossible at two sites due to shallow bedrock. Stone and soil carbonate content increased with depth at some sites and, at the NL site, spots of peat were recorded in the subsoil. This introduces more spatial heterogeneity than in upper soil layers, which is known to challenge interpretation . Roots and macropores of anecic earthworms may be carbon pathways into deeper soil layers. Yet, root abundance was lower under reduced tillage than under ploughing in lower soil layers at the French site and earthworm monitoring in some of our studied sites did not show an effect of tillage systems on anecic species . Whether our observation of higher SOC stocks in 70–100 cm is an effect of spatial heterogeneity or tillage management cannot be answered within this study and offers opportunities for further research. Overall, the SOC stock profile distribution measured in our study resembles the SOC stock distribution of the well assessed no-till – ploughing comparisons compiled by several meta-analyses, e.g. by Luo et al. or Ogle et al. . Regarding the topsoil SOC enrichment, it can be assumed that soil erosion control is also achieved by reduced tillage in organic farming, which has been confirmed with direct erosion measurements at the CH-1 site . Since conservation tillage systems are discussed as climate change mitigation measures, original studies were repeatedly summarised by meta-analyses. Selecting for ones that also include subsoils, Luo et al. reported an insignificant 2.8% increase by no-till globally and Meurer et al. an insignificant increase by 1.2–1.3 Mg C ha− 1 or 0.1 Mg C ha− 1 yr− 1 by no-till in temperate climates. Our study, with a total SOC stock increase by reduced tillage of on average 1.7% after 8–21 years, equivalent to 1.5 Mg C ha− 1 or 0.09 Mg C ha− 1 yr− 1 in 0–50 cm shows a similar SOC sequestration for reduced tillage systems in organic farming. A comparison with other reduced tillage studies is more difficult since they mostly did not sample subsoils.

For instance, the review of K¨ ampf et al. on SOC distribution in topsoils in temperate climates indicates that SOC stocks under reduced tillage are intermediate between no-till and ploughing. Blanco-Canqui et al. sampled two long-term trials in Nebraska after 34 and 39 years under climatic conditions similar to our study. While the 39-year-old site showed an increase in total SOC stocks from ploughing to reduced tillage to no-till, SOC stocks at the 34-year-old site were 22% higher under reduced tillage than ploughing but similar to no-till. In our study after a trial duriation of 8–21 years, total SOC stocks in 0–100 cm accounted for 3.6% or 4.0 Mg C ha− 1 higher SOC stocks with reduced tillage resulting in a far lower increase in SOC stocks than in the study of Blanco-Canqui et al. . We, therefore, confirm that a certain SOC sequestration can be achieved by reduced tillage, even though tillage operations are not entirely stopped. The subsoil SOC processes urgently need further attention in future research. To assess the overall impact of tillage systems regarding climate change mitigation, other aspects like N2O emissions or fuel consumption need to be considered as well , since those emissions continue while a SOC steady state is reached after a certain period. In summary, reduced tillage systems under organic farming conditions can provide some SOC sequestration without the use of herbicides which are of increasing concern . This is an important outlook regarding future efforts to reduce pesticide inputs in conventional agriculture. Yields are, however, most likely lower than in conservation tillage systems with herbicide use, as indicated in the CH-1 field experiment . Cumulative SOC stocks were overall increased with reduced tillage, suggesting that SOC was enriched or losses reduced. The amount of SOC in soils is regulated by SOC turnover and stabilisation and there is evidence that ploughing disrupts soil aggregates exposing SOC to microbial consumption . Measurements in some of our studied sites support the lower level of soil disturbance in reduced tilled soils. At CH-1, a sandy loam, a change in microbial composition favouring fungi in combination with increased aggregate stability was determined.

Though aggregate stability was similar between tillage systems at CH-3 due to the high clay content , fungi in general and arbuscular mycorrhizal fungi that are sensitive to disturbance were more abundant in reduced tilled plots. Tillage systems also impact above ground carbon input, which was assessed by Virto et al. who positively related changes in crop C input to SOC stocks . In our study, regressions of tillage system differences in total crop biomass and weed biomass were slightly but not significantly linked to the SOC stock changes observed. In fact, reduced tillage in the organic farming context of this study decreased crop biomass yields by on average 8% in comparison with ploughing. Such a yield gap was reported by Cooper et al. and is related to increased weed pressure and plant nutrition issues. This is the main difference to conservation tillage practices in conventional farming, where herbicides and mineral fertilisers can sustain productivity. The decrease in crop biomass in our study led to a 0.2 Mg C ha− 1 yr− 1 lower total above ground C input. The lower input may have been outbalanced by i) higher weed pressure which was estimated to provide 0.3 Mg C ha− 1 yr− 1 from above ground biomass or ii) changes in below ground C inputs, which were not assessed in our study. It should be noted that weed data in this study are based on a limited dataset from four out of nine sites. This is, therefore, only a preliminary comparison that indicates that weeds may be an important source of C input which needs future research. Interestingly, tillage induced SOC stock changes were not related to trial duration in our study. Therefore, it seems that site-specific pedoclimatic conditions interact with management practices in a more complex way. Trends in SOC stock drivers were more apparent when sites were compared: Soil texture, especially clay contents, is often identified as an important predictor of SOC as fine mineral particles associate with SOC . However, in our study, silt content was also well correlated to SOC stocks. The clay/silt ratio finally had the best correlation and could be a good predictor of SOC stocks, representing the soil texture triangle in a condensed form. Soil pH ranged from 5.9–7.2 across sites. The positive correlation with SOC stocks may hint to the availability of exchangeable cations that were argued to impact SOM stabilisation and clay mineral behaviour . Apart from soil parameters,indoor garden the positive SOC stock correlation with precipitation is commonly found .

SOC stocks also increased with the amount of organic amendments used.Our study compared SOC stocks that were calculated on a site specific fixed depth approach with stocks that were further modeled on an equivalent soil mass . Site specificity means that we considered a priori knowledge on current and historic tillage depths during sampling and that the layers in the Ap horizon thus differ between sites. The equivalent soil mass approach is widely discussed as the more appropriate method as tillage or other soil management practices influence bulk densities and therefore soil masses. There is, however, no standardised protocol of the modelling procedure, and approaches vary considerably . In our study, the two approaches yielded the same outcome. As the ESM approach relies on the choice of input variables and the quality of the modeled cubic spline fit, we feel that there are more uncertainties added. Beyond, we have seen, just as Blanco-Canqui et al. , that soil sampling depth has a huge impact when assessing tillage system differences on SOC stocks. This suggests that sampling deep enough is more important than the method used to calculate SOC stocks. As farm machinery grows bigger and heavier in pursuit of economies of scale, traffic-induced soil compaction has become widespread. ESDAC defined soil compaction as “. a form of physical degradation resulting in densification and distortion of the soil where biological activity, porosity and permeability are reduced, strength is increased, and soil structure is partly destroyed”. Manifestations of soil compaction are multifaceted . Soil compaction causes a loss of nitrogen from soil resulting in a reduction of soil nitrogen uptake by plants . Yamulki and Jarvis found that compaction had a more profound effect than tillage on the release of gaseous emissions from agriculture. Tullberg et al. 2018 found evidence that trafficked soils have significantly higher N2O emissions than non-trafficked soils . Pangnakorn et al. documented significant difference in earthworm populations between compacted and non-compacted soils. Subsoil compaction can persist over a long time and is costly to eliminate, if elimination is possible at all . Hence, there is a need for smart agricultural techniques to avoid compaction . Managing machinery traffic in terms of: the placement of machinery traffic pathways; the axle loads, tyre sizes and inflation pressures used; and the soil conditions under which trafficking is allowed, can contribute to compaction avoidance. One such approach is to confine field traffic to permanent tracks that are maintained year after year, referred to as Controlled Traffic Farming . Earlier deployment of CTF technology relied on marking permanent tracks and frequently involved the deployment of gantries. The advent of high precision positioning and auto-steering systems, by avoiding the need to physically mark and manually steer along pathways, makes CTF a promising technology in future agriculture . In Chamen , CTF is labeled as “precision farming at its most efficient”. In its strict sense, CTF requires all machinery operations to be in permanent tracks.

Furthermore, all research participants are members of a collective because only members of collectives can participate in the Dutch agri-environment scheme. The farmers were asked to rank themselves according to the levels of nature-inclusive farming as defined in policy.Our interviews included questions about their identity as a farmer, what they considered as a good farmer and a good landscape, how status can be achieved in the local farming community, learning, and their willingness to ‘do even more with nature’ . In each case study area, we first interviewed farmers individually before we brought them together in a focus group. The interviews and focus groups took place as farm visits and physical meetings between September and December 2018. We used a semi-structured approach to retrieve comparable data, but to allow for natural conversations and emphasis on aspects that were important to the farmers. The same issues were discussed in the interviews and the focus groups, but the focus groups allowed us to observe the interaction between farmers and to identify joint constructions. We offered stipends to the farmers to compensate them for their time investment. The interviews and focus groups were recorded and transcribed.The codes relate to the theoretical framework to allow for a structured analysis. In line with Miles and Huberman the interviews and focus group reports were summarized in tables per case study organised with columns for individual farmers and rows for codes. In addition, each case study table included a column for joint constructions. This summary allowed for configuring as well as aggregating analysis : per case study we looked for complementary concepts , while between case studies we looked for similarities and dissimilarities. Each case study table was coded for relations between the concepts and for evidence of change of view or change of cultural norms. Our case studies show many similarities, but also some differences. Table 2 summarizes the findings per case study.

Cultural norms for ‘a good farmer’ and ‘a good agricultural landscape’ seem quite similar between the case studies. In Noordelijke Friese Wouden the attention for circular farming is apparent, ebb flow which is not surprising because the approach was more or less developed here . While diversity among farmers is appreciated in all case studies, Achterhoek stands out for the reluctance to judge other farmers. In addition, no quotations about cultural change were found in Achterhoek, in contrast to the other case studies. The attitude towards nature-inclusive farming and the nature-inclusive themes that are relevant to the farmers are strongly related to the landscape. In Noord-Beveland, the open landscape has very few natural handicaps and the clayey soil is fertile. The intensity of the arable production and especially the crop rotation is seen as relevant to nature-inclusive farming, as well as flower strips, natural pest reduction and soil quality. For farmers in Midden-Limburg, Achterhoek and Noordelijke Friese Wouden, nature-inclusive farming practices come natural to them because these practices suit the landscape . In addition, the Frisian farmers explain this attitude by the local culture and long history of agri-environmental management in their area. They are particularly proud of their agri-environmental collective. In sum, cultural norms regarding ‘a good farmer’ and ‘a good agricultural landscape’ are relevant to farm management decisions in our case studies. However, our findings suggest that the role of self-identity is more important than the role of the opinion of peers. While production-oriented conceptions of ‘a good farmer’ and ‘a good landscape’ are still dominant in the subculture that we studied – the subculture of farmers participating in agri-environmental management – we observed a shift in cultural norms towards a broader conception of both the notions of ‘a good farmer’ and ‘a good landscape’. Part of the embodied cultural capital that is needed for nature-inclusive farming – both for the production and the assessment of a ‘good nature-inclusive landscape’ is still underdeveloped. For the build-up and transfer of such cultural capital, teaching and training are important, but experimenting and social learning even more. Our respondents say that they learn most from colleagues and farmer groups and that the agrienvironmental collective is particularly important for their knowledge of ecology. Our findings diverge from the literature on a number of aspects. First, the combined case studies yield a broader conception of ‘a good farmer’ and ‘a good agricultural landscape’ than reported so far. The literature describes ‘a good farmer’ as hard-working, taking good care of land and livestock, entrepreneurial, a good neighbour and taking responsibility for the environment . Our respondents add innovativeness, responsibility towards biodiversity and society, a good work-life balance, and happiness.

A ‘good agricultural landscape’ is described in literature as a ‘tidy landscape’ . However, according to our respondents, what ‘good land’ should look like depends on its purpose. Land with a biodiversity objective does not need to look so tidy. Biodiversity can be a production objective, just as food. In contrast to Burton we did not find much evidence that Dutch farmers practice ‘roadside farming’. They do drive around andknow that their colleagues do the same, and they do feel their scrutiny, but they say that this does not really influence their management decisions. Self-identity may be more important for farm management decisions than the opinion of local colleagues, and other subcultures may have become more important for the formation of self-identity than the local farming community. Our respondents value and defend diversity of farming styles. While Burton and Wilson and Saunders did not find evidence of changing cultural norms as a result of agri-environmental policies, Burton suggested that new roles and practices could change the meaning of ‘good farming’. Burton and Paragahawewa suggested that group payments could make untidy landscapes to be more easily associated with good farming practice. So far, however, very little empirical evidence has been reported of changing cultural norms in farming. Lavoie and Wardropper observed that conservation tillage was a way for farmers to link conservation values as well as production values to the good farming identity. Sutherland found that well-visible ‘professional and orderly’ organic practice fostered a slight shift in the perception of organic farming amongst conventional farmers. Sutherland and Darnhofer report changing views with farmers as a result of their experience with implementing flower strips or organic farming. In Cusworth farmers report a ‘change of mind’ as a result of participation in agri-environmental management. They have learned the point of the measures and disapprove of poor agri-environmental management of their colleagues. In our study we observed changing cultural norms as a result of participation in and visibility of agri-environmental management. This is most in line with McGuire et al. , who found changing notions of the ‘good farmer’ identity in a group of farmers participating in agri-environmental management, monitoring and social learning. It is also in line with Riley , who found changed cultural norms after long term participation in agri-environmental management. Sutherland and Burton demonstrate how cultural capital in the form of status as ‘good farmer’ can yield social capital in the sense of trust of and collaboration with neighbours.

Our case studies suggest, in line with Bourdieu , that social capital can also support the development of cultural capital. In our case studies, collective agri-environmental management contributed to the build-up and transfer of nature-inclusive cultural capital through introducing nature-inclusive farming practices, increasing the visibility of nature-inclusive practices in the landscape, and facilitating learning by farmers. Membership of a group yielded new skill to produce a different kind of landscape as well as to recognize this skill on the land of others. In addition, in this group, nature-inclusive skill yielded appreciation of peers. These findings are in line with those of Runhaar and Polman who describe how farmers who were active in meadow bird protection found recognition in a national farmer network organised by Birdlife Netherlands while they did not find it among their neighbours. The agri-environmental collectives form a subculture in which nature-inclusive cultural capital yields social capital and vice versa. This way, the collectives have become key agents in cultural change. This explorative study provides an indication of the relevance of cultural norms for farmers’ behaviour in relation to biodiversity. For a more complete understanding of what is needed to support natureinclusive choices of farmers other factors should also be studied, such as access to land, relationship with land owners, market demand, the influence of regulation, level playing field, education and finance . In addition, as our focus was on cultural norms within the farming community, we did not study how cultural images of ‘the good farmer’ and ‘a good agricultural landscape’ as held by other, non-farming stakeholders affect these cultural norms. Nevertheless, some of the respondents brought up the issue themselves. Most likely, non-farmers’ understandings of ‘a good farmer’ and ‘a good agricultural landscape’ do play a role in shaping farmers’ self-identity and cultural norms and this role warrants further research . There is a broad understanding of the need to develop rural areas and sustainable food systems that preserve the environment and ensure food security for future generations . Organic production is seen as an approach that can promote both of these goals. Due to lower environmental impact organic farming has potential to support transformation towards more sustainable agricultural systems . More specifically, increasing organic farming has been identified as a means to reduce greenhouse gas emissions . In addition, organic farming potentially plays an important role in reducing exposure to pesticides , greenhouse benches supporting beneficial insects and decreasing soil erosion . From the rural development perspective, organic agriculture may also promote employment in rural areas .

Darnhofer concluded that the beneficial impacts of organic farming on rural regions can be more diverse than the general focus on food chains, landscapes, and environmental considerations. However, the benefits of organic farming have also been contested. Smith et al. and Squalli and Adamkiewicz published opposing results about the possible benefits associated with reducing greenhouse gas emissions. Reganold and Wachter underlined the need for other innovative approaches in addition to organic farming. Meta-analyses by Tuomisto et al. and Mondelaers et al. have demonstrated that while organic farming generally has lower environmental impacts per unit of area, the results can differ when examining the impacts per product unit. Furthermore, Meemken and Qaim noted that there are several disadvantages associated with a widespread increase in organic agriculture, for example, a rise in food prices. The impact on rural development is also controversial. Lobley et al. noted that there are factors other than farming methods that may have a greater influence on rural or regional development. Despite these contested views, the benefits of organic farming have been widely accepted, and it is generally promoted as a desirable agricultural system. The growth of organic farming involves shifts in human values and therefore relates to societal change as well as agricultural change . Consequently, previous literature has emphasised the role of governments in increasing organicfarming. Argiles and Brown stated that government decisions are key factors that affect the future of organic farming. Lesjak also revealed correlations between policy decisions and the development of organic farming. Hence, many European countries have set targets to increase the share of organic farmland. In addition, the EU’s Farm to Fork strategy included a target to have 25% of agricultural land under organic farming by 2030. The targets have been set, for example, in order to enhance sustainability and to meet the growing demand for organic products . Increases in direct subsidies further strengthen these types of policy decisions, as they have been shown to exert a positive impact on the conversion to organic farming . Despite an encouraging political and economic climate, the development of organic farming can vary greatly between the different regions of a country . To better understand the complexity of the longitudinal development of organic farming, Ilbery et al. highlighted the need for more studies with a regional focus. To date, however, the research has not adequately addressed the possible connection between subsidies and the regional distribution of organic farming, despite indications that subsidies may have a range of influences across different yield-level land areas .

Previous research on fin-fish aquaculture has suggested that there is some utility to the models of SLO that have emerged from research of the mining sector. For example, work by Sinner et al. on the SLO of New Zealand aquaculture echoed what was found by Moffat and Zhang, that trust and contact quality were crucial parts of SLO . Sinner et al. also found that the quality of contact with communities was a significant predictor of SLO for fin fish farming. The contact made between community and industry needed to be informative, respectful and positive . This aligns with the idea that SLO cannot be determined simply through acting in a way that creates credibility, but needs to include successful and positive relationship building. Sinner et al’s., work also highlights the prevalent role that culture can play in the creation of SLO . The importance of building relationships is reflected again in further work by Baines and Edward, again in New Zealand, discerning that relational foundations of relationships were key in building trust, and therefore SLO between the aquaculture industry and communities.Research has shown is that a lack of social license cannot just be attributed to conservationist motivations of local communities concerned with the environmental impacts of the industry.Opposition to aquaculture can arise from a multitude of concerns including; environmental, cultural concerns and the identity of the industry itself.Baines and Edwards found that perceptions of company ownership and the scale at which the company was working were a determinant of whether social license was achieved.

It appeared that local ownership was preferred, and ownership outside of the local was viewed more suspiciously.Portrayals in Norwegian papers of the Atlantic salmon industry being run by profiteers and capitalists have also been used as examples of how the perceived identity of the industry could be an important influence on its SLO . Increasingly aquaculture companies are undertaking greater efforts to portray themselves as sustainable.Despite these pledges Young and Liston suggest that the aquaculture industry has previously faced failure at addressing organised opposition to the industry at national and international scales, potted blackberry plant with these campaigns against aquaculture influencing the social license of an aquaculture development.Through outlets such as social media, environmental campaigns now have much greater reach. There is evidence that social license to operate is being utilised in campaigns against fish farms, by environmental nongovernmental organisation,with enough success to bring about change.Murphy-Gregory showed how in campaigns against a Tasmanian fish farm development, social license was utilised by an ENGO to put pressure upon the state to improve their regulatory governance of the industry . ENGOs have also been found to be an influential agent in whether aquaculture developments gain social license, through the sharing of information.Third-party certification has been suggested as another influence that could be impactful in whether an aquaculture development is granted a social license to operate. However, Mather and Fanning suggest that social license to operate is not a strong component of these certification schemes, which instead tend to focus upon environmental performance .Carson and Rønningen further suggest that when an aquaculture company’s focus is too broad, then they may end up remaining ignorant of the importance of local relationships . Instead of putting resources into sustainability schemes industry may be better placed in building relationship with community, if they want gain a social license to operate. In 2019 there were around 300 active sites associated with Atlantic salmon production in Scotland , with 92% of production undertaken by just 5 companies.

Eighty-two percent of sites are producing over 1,000 tons of fish per annum.Atlantic salmon is the major species produced, accounting for 95% of fin-fish production by volume . However, other species are produced in the Scottish fin-fish farming sector, such as Rainbow Trout and Atlantic Halibut . The sector directly employs around 1,880 people in both full-time and part-time jobs across Scotland . These jobs are deemed as essential in rural areas, many of which are undergoing depopulation . The success of the industry has prompted a push for it to grow further, and strategies, such as Aquaculture Growth to 2030, lay out a pathway which would see the sector at least double in size by 2030 . Subsequent estimates suggest that such growth would increase the numbers of jobs tied to the industry to 18,000 and the economic contribution to as much as £3.6 billion . In 2018, the Scottish parliament conducted two reviews into the Scottish fin-fish aquaculture sector, in response to growing concerns at the expansion of the industry and the perceived negative impacts associated with it . Both committees made recommendations that covered a range of topics from fish health and welfare, expansion of the industry to workforce, skills and infrastructure. The overarching conclusion of the inquiry was that the current status quo of the fin-fish farming industry in Scotland was not acceptable. However, the committees stopped short at proposing a moratorium on the expansion of the sector . Multiple ENGOs have also taken positions against the industry, due to concerns about its environmental impacts on Scottish marine and coastal spaces . At a local level, the fin-fish farming sector has seen a loss in SLO, as shown through cases where objecting comments outweighing supporting cases in new farm proposals. Opposition to fish farms have been at an individual level but has also been seen to create collective action through the creation of several community groups, whose specific purpose originated in opposing fish farming . These community groups have galvanized community members together and have also become sources of information about fish-farming.

The resulting debate between these community groups and the fish-farming industry has become polarized in some areas around Scotland. This has led to the consultation process for new sites becoming a contested space, which in some cases has led to walk outs and protests . Consequently, questions have been raised as to whether the Scottish fin-fish is facing a crisis of social license to operate. The current climate around Scottish fin-fish farming suggests a crises of social acceptance, ultimately questioning whether the industry has a SLO. This study takes an exploratory, qualitative approach to examining the dimensions of this crisis, using the SLO framework, in the geographical communities of Lewis & Harris and Argyll & Bute. A case study approach, looking at these two geographic areas, allows for an indepth exploration of the contextual conditions that could influence SLO . Alongside this, applying a qualitative approach within this supports identification of context, as well as allowing for the nuance of relationships and perceptions that might relate to SLO to be investigated. The central question for this work is therefore, how is the fish farming industry perceived and experienced at a community level? This research was conducted as part of larger study, using a grounded theory approach. In keeping with this an inductive, thematic analysis methodology was applied to semi-structured interview response. Constructivist grounded theory is based upon inductive theoretical analyses of data, with data analysis and collection informing each other through the process. The foundation of analysis is the creation of qualitative codes based upon what is seen in the data .A constructivist grounded theory approach is an appropriate methodology to answer the research question as it focuses upon attempting to understand local people’s perceptions of the Scottish fin-fish aquaculture industry. As such, it is vital to have an inductive methodology that has enough scope so that the varying components that make up an individual’s perceptions of the fin-fish industry can be included in the analysis.

A small study sample means that these results cannot be generalized outside of the context in which they were researched. However,tall pot stand in line with conceptions of SLO, being dependent upon social and contextual factors this method is still appropriate. The focus upon stakeholders, again can be seen as further limitation of this work, as such the results in the following section cannot be seen as reflective of the general population as a whole, even of the two case study sites. However, assessing those who have a particular “stake” in fin-fish farming or its impacts allows for insights into the experiences that are affecting the SLO of fin-fish farming in the two cases. In line with Charmaz’s approach a flexible interview guide was developed .This interview guide was developed after reviewing the literature, in line with the idea that it can “set the stage” for the development of interview guides .The interview guide was developed to try to cover the expansive range of components thought to be part of SLO for aquaculture Table 1. The interview guide began with discussion around the participant’s background and connections to the local coastal spaces, to both examine the contextual factors that could be influential and to examine the access the individual has to local coastal spaces. Following questions upon the industry examined the knowledge and response to the current industry, with the inclusion of questions around opportunities and challenges of the industry meant to highlighted perceptions of environmental challenges, benefits provided to communities and the current ownership structures. The final questions focused upon the relationship between companies and participants, to again examine SLO and the measures the industry might be taking to improve SLO. The questions were kept open in nature and were used as a guide for the conversation with participants. This allowed for the interviewee to bring up new issues and new themes to be explored with further questions . The interview guide can be seen in Table 2. Interviewees were initially contacted through a purposive sampling strategy . The criteria for participant selection was engagement or involvement with the aquaculture industry, maritime stakeholders or community representatives.

This was because these groups are the most likely to have interacted with the aquaculture statistics, the council area of the Outer Hebrides is undergoing depopulation with around 0.4% decrease in population in the area from 2017 to 2018 . Reliance upon the land, coast and ocean has been a central part of the history of life on Lewis and Harris, but this relationship to the land and coast also has a history of disruption and turmoil, the most impactful of which was The Land Clearances in the 18th and 19th century . The Scottish Land Reform Bill, passed in 2003, was a fundamental shift in land ownership, reversing some of the consequences of the clearances, and number of community trusts have since developed to purchase land, beginning with the North Harris Trust in 2002. In terms of use of coastal and marine environments, currently commercial fishing is made up of mostly shellfish species, with 90% of landings being shellfish species, using inshore under-15m boats . However, the industry is in decline, with the number of 10-15m boats decreasing in the last decade Aquaculture and Fisheries, 2021. Outside of the fishing industry, the marine environment is a draw for tourists. As a result, tourism makes a significant contribution to the islands economy. The marine environment also has potential for marine renewable energy developments as the Outer Hebrides has one the most energetic wave resources in the world . Salmon farming makes up the majority of aquaculture on Lewis and Harris, with a small amount of mussel and oyster farming also taking place. There are two major salmon producers with 32 active sites for salmon farming across the islands. Stornoway also has a salmon processing plant, which processes and packages a Hebridean salmon branded product. The town contains a smokehouse which smokes salmon using a traditional, double smoking process. The industry provides 237 full time jobs and 18-part time jobs, directly in fin-fish farming across the Western Isles . This is 1.9% of the total employment in the area . The fish-farming sector on Lewis and Harris has faced controversy in recent years, struggling with disease and sea lice burdens .

El-Sayed et al. accounted feed cost as the highest operational cost like the present study findings. The selected farms’ average annual production, cost, and income were 10kg/decimal, 1435/decimal, and 433/decimal . Details of the economic analysis are presented in Table 2. Hossain et al. found 16.5 kg/decimal/year as maximum production 12.7 kg/decimal/year as minimum production from the traditional polyculture, which is close to present study findings. Polyculture practiced farms showed more production and revenue among the selected farm. The findings related to farming cost, fish production and income meant that feed cost should be minimized to improve fish production and revenue. A community-based feed mill establishment in the study area is highly recommended to balance the production cost and revenue. Different water quality parameters were measured to identify the suitability of fish farming in the study area. Parameters were measured, and mean values were present in Table 3. Dewan et al. recorded a temperature range of 25.9–34.5 ◦C in a fish polyculture pond. TDS showed greater value, especially in the poultry cum fish farm due to the uses of the poultry litter in the fish pond, The ideal range of temperature, dissolve oxygen, transparency, and pH for the fish farming in the pond mentioned by Bhatnagar and Devi also agreed with present study findings. The findings suggest that the research area’s water quality parameters are suitable for aquaculture. The present study identified the feasibility of integrated farming in hilly regions to produce multiple crops simultaneously. Integrated fish farming is ecologically sound and improves soil fertility by making nitrogen and phosphorous available . Rural women might contribute to fisheries-related activities besides their household works. According to Allison,barley fodder system aquaculture and fisheries can contribute to the employment generation for youths.

Identified prospects in this study necessitate the establishment of community-based aquaculture to get maximum outcomes from these prospects. Rahman et al. reported the lack of proper initiatives to conduct training for fish farmers in the aquaculture sector of Bangladesh. Insufficient supply and low-graded seed, inadequate loan facilities, lack of technical knowledge and training, and multiple ownership were significant constraints for fish farming. All the cited findings above show similarities with the limitations of aquaculture found in the present study. Thus, the present study’s findings infer the adoption of proper strategies toovercome the constraints of aquaculture in the study area. After analyzing the collected data, a community-based aquaculture model was formulated based on the problems, prospects, and SWOT analysis of the present fish farming of the study area . As there was no hatchery in the study area, farmers usually depended on remote sources for collecting seed. Transportation of seeds from remote areas reduced seeds’ quality and increased cost . So, the establishment of hatcheries in the study area was essential to overcome the seed supply constraint for fish farming. Moreover, the local peoples were not financially capable of establishing hatcheries in private ownership. Therefore, a community-based initiative is required to establish a hatchery in the study area. A well-established hatchery might be ensured seed costs by reducing average travel distance. Besides the local source of good quality seed, local people’s employment will be secured. In the study area, 75% of farmers said feed cost was the 2nd most crucial problem in aquaculture because they lacked capital for feed purchasing . Moreover, there was no local feed mill and feed manufacturer in the study area. Feed cost was estimated highest operational cost of the total cost . A community-based feed mill establishment might be an appropriate solution to this problem. A community-based feed mill may ensure the availability of fish feed, reduce the transportation cost, and reduce the total production cost of fish farming. It can confirm the proper and specific ratio of feed ingredients for particular fish species and create employment opportunities for local people.

A community-based feed mill can be established using a low-cost pellet machine. Fish-feed can be prepared from locally available raw materials using such feed mills. Farmers themselves can operate the feed mill when they are trained on the machine operation and proper ratio of the feed ingredients. A community-based feed mill may ensure the best use of locally available feed ingredients and help the farmers with a continuous feed supply. Consequently, local farmers are expected to increase fish production. Moreover, it creates a market for the raw materials sellers of fish feed . Most fish farmers were not interested in integrated aquaculture in the study area. Poultry cum fish culture, denoted as poultry fish farm, was found 25% of the total selected farm . In some cases, practiced poultry fish farming in the study was not safe as they directly deposited poultry litter in the fish pond to minimize feed cost. According to FAO , livestock-fish farming is needed to be more precisely designed or managed to avoid health risks for humans. Adeyemi et al. raised health concerns about poultry cum fish farms as there is a possibility of transferring pathogens to humans. Integrated aquaculture could be reduced overall production costs and generate higher profits, but it must be practiced safely. So, introducing a safe integrated aquaculture system in the study area is required to increase fish production, profit and improve the natural productivity of the soil and water. Linkage among stakeholders is considered essential for the aquaculture and fisheries sector. In the research area, lack of adequate linkage was identified as one of the major problems . Efficient linkage among stakeholders is necessary to achieve sustainable fish production. The collaborative effort and strong linkage will ensure the stakeholders’ knowledge, experience, and resources. Yeasmin et al. recommended training of farmers to get fish farming guidelines in four villages of Mymensingh. As the present study was conducted in marginal areas, engaging farmers with the government and non-governmental training stakeholders could be helpful to improve aquaculture production. Lack of education in fish farmers hinder them from utilizing resources, using technologies and getting the desired production in the study area. Fishermen’s education could improve fish production by using resources, applying aquaculture technology, understanding harvesting and post-harvesting methods, product marketing, and social advancement.

Communication among producers, processors, traders, and other interested parties was crucial for successful fish farming in the study area. If two ways of communication could be established, it would significantly increase the facilities for the fish farmers and traders of the study area. A comprehensive market chain should be developed through community-based incentives to ensure more profit, fair distribution of profits, and most importantly, reduce the extortions by mediators in the market chain. Consequently, the involvement of people in fish farming will be increased, and sustainable livelihoods will be ensured. Sea-based fish farming can be exposed to certain events and conditions that have negative impacts on fish welfare . Some of these hazards can lead to situations necessitating vessel responses such as moving, delousing or slaughtering the fish . In 2016 Chile experienced the most severe harmful algae bloom to date, killing 100,000 metric tons of Atlantic salmon . In the early summer of 2019 a HAB killed an estimated 8 million farmed salmon along the Norwegian coast, and in 2021 Chile saw another HAB that resulted in the transfer of 5.4 million salmon to safer sites away from the affected area . The following winter, sea-based fish farmers on the Faroe Islands lost approximately 1 million fish to winter ulcer at one single occasion . However, the severity of hazards may vary, and locations can experience situations with no serious effects on the fish welfare, such as minor algae blooms. Thus, in this paper the term “emergency” is reserved for serious realizations of the hazards, which will lead to loss of biomass if the emergency response is inadequate. After the mentioned emergencies in Norway and the Faroe Islands the lack of emergency preparedness was said to contribute to the high losses . Hence analyzing the response preparedness for large scale biomass emergencies in sea-based aquaculture systems could help operators enhance their emergency preparedness and response capabilities. Improvements in emergency management in sea-based aquaculture systems is becoming more important, given changes in the risk picture induced by the move of fish farms into more exposed locations and the impact of rising sea temperatures. The traditional way of assessing the emergency response capability of a system is through expert opinion and rules based on experience. For example, Wang et al. determines the emergency response capability for oil-spills in an area based on rules for the necessary amount of available resources. Haixiang et al. breaks down the rescue capability into subcomponents, and grade them based on expert opinion. A similar approach is used in Kang et al. where linguistic variables are used to evaluate oil-spill emergency response capability.

Omorodion et al. use expert opinion to assess safety terms of the failure probability of operations performed by Emergency Rescue andResponse Vessels. A method for combining machine learning and historical accident data to predict emergency scenarios,hydroponic barley fodder system and thereby support emergency response decision-making is presented in Li et al. . An alternative to experience-based assessment is to test the emergency response performance. Siljander et al. proposes the use of geographic information system based methods for evaluating the response times in maritime search and rescue to support strategic planning in Finnish waters. The presented approach considers weather conditions and vessel types. Zhou et al. present a three-step framework for assessing maritime search and rescue capabilities, covering response times, demand, and coverage. Response time is estimated using GIS. Simulation models are used to evaluate system design under environmental impacts in Berle et al. , Bergstr¨ om et al. and Brachner.Berle et al. assesses the vulnerability of a maritime liquid natural gas transportation system by quantifying the impact of disruption scenarios and mitigating measures. Bergstr¨ om et al. proposes an approach for the design of robust arctic maritime transportation systems where the system performance is tested for different ice conditions and ice mitigation strategies. Brachner presents a model for evaluating the response capacity to helicopter ditches in the Barents Sea for different configurations of response unit positioning over a year with changing weather conditions. The fleet deployment with maximal covering problem and epoch-era analysis is combined in Pettersen et al. to optimize allocation of emergency response vessels, thereby providing insights into the effectiveness of alternative fleet designs. In another paper, Pettersen et al. study how latent capabilities can support large-scale emergency response. While they look at the case of the Macondo oil spill, the principle of repurposing assets for novel emergency situations can also be useful in aquaculture, e.g., the role of live fish carriers in emergency response. This paper contributes to the literature by applying simulation-based performance analysis to determine the emergency preparedness for large scale biomass emergencies in sea-based fish farming.

The presented method analyzes three stages of emergency response and covers both non-dedicated emergency response vessels and dedicated emergency response vessels . DERVs are not used by the industry today, but could provide additional benefits in emergency response. Sea-based fish farming systems can be defined as sets of hatcheries, fish cages, slaughterhouses, and vessels, where the vessels constantly change both status and position according to the various operations they perform in the system. Operation types cover daily maintenance and routine tasks performed by small vessels belonging to the location, more complex operations necessitating the assistance of larger external vessels, and finally operations directly handling large volumes of fish which are performed by large, specialized vessels such as live fish carriers. For responding to large-scale fish welfare emergencies, only large vessels handling large volumes of fish are of interest due to the scale of such emergencies. Therefore, the presented method is intended for live fish carriers, stun & bleed vessels, processing vessels, and the likes. These vessels follow work schedules set up by the fish farmers, meaning that the emergency response capability they provide is time dependent and hard to estimate for a given point in time without considering the dynamics of the system. They may be busy performing planned operations at the time emergency response is initiated, in which case they must complete their current operations before responding to the emergency event.

The limited forest cover creates economic problems associated with the cost of timber . According to some reports, a large part of Iran was covered by forests 73 years ago , 2017. This has been reduced to 14.2 million ha at present due to poor management . In the northern forests of the country, severe logging has destroyed about 12,000 ha annually . Because of widespread destruction in the northern forests of Iran, industrial logging was stopped in 2017 in the name of “forest rest” strategy . Importing wood is expensive, in part because of the country’s economic problems, and demand is being met by producing wood from fast-growing tree species. Therefore, wood-farming is one of the most important strategies for meeting Iran’s demand for wood despite deforestation, economic problems, global warming, and changing climates . Iran has a diversity of climatic and ecological conditions and certain woody species have adapted to certain ecological zones of the country. For successful wood-farming, tree species must be chosen carefully . Therefore, prediction of the best places for farming fast-growing trees in each ecologic zone is very important. In this regard, investigation of habitat suitability for fast-growing trees is very important. Habitat suitability for some species has been investigated in different regions around the world. Reza et al. integrated GIS and expert judgment in a multi-criteria analysis to map and develop a habitat suitability index in peninsular Malaysia. The suitability of habitat patches for each species was measured by integrating GIS data with expert opinions. Expert opinions provided information about the stresses faced by the species because ground surveys provided insufficient information on their own. Their results revealed that many habitat patches have become unsuitable for certain species. Arvola et al. mapped the future market potential of timber from small-scale tree farmers in Tanzania.

Primary qualitative data were collected to determine the importance of smallholder tree growers in the forest transition process and wood value chain. Sixty semi-structured interviews with tree farmers in four villages and discussions with timber buyers and processors yielded expert data. The results showed that strong market demand created dual markets,blueberry grow pot where higher quality industrial plantations supply larger industries and small enterprises acquire wood from lower-quality small-holder plantations. For wood-farming in in agro-ecosystems, restoration plans considering vegetation and fauna is also essential in agro-ecosystems. In some regions around the world, semi-natural vegetation and farming ecosystem have created proper conditions for wildlife conservation . Wade et al. stated that sustainable agricultural practices along with ecological restoration methods can reduce the detrimental effects of agriculture. Restoration methods must be technically achievable and socially acceptable and spread over a range of locations. One option for this type of mutual benefit is the use of agri-environmental schemes to provide financial incentives to landholders for providing conservation services and other benefits. Benayas and Bullock provided a practitioner’s perspective related to landsharing restoration actions in the central Spain and concluded that practical restoration projects are essential to improve biodiversity and to return of wildlife in agricultural landscapes. Barral et al. investigated ecological restoration and its effectiveness against biodiversity losses in agro-ecosystems globally by analyzing the results of several studies from 20 countries. Their results showed that restoration in agroecosystems increased the biodiversity of all types of organism by an average of 68%. There has, however, been no effort to model the ideal lands for farming fast-growing woody species anywhere in the world. There are more than 700 species of eucalyptus, a fast-growing genus of Myrtaceae.

The tree is endemic to Australia , Philippines, Papua New Guinea, Indonesia, and Timor . Eucalyptuses grow in diverse ecological conditions . Some species have industrial value , while others are used primarily for landscaping, and green space . Eucalyptus is used to produce wood products like paper, charcoal, and timber. This wood of this genus is hard, heavy, and durable . The primary benefits of farming eucalyptus are that it grows rapidly and can be harvested repeatedly and more frequently than conventional trees. They can be cultivated on poor lands. They are used for secondary successional remediation and post-fire regeneration. Eucalyptus can be used architecturally , for nonstructural wood products like pulp, rayon, and for sleepers , and are used to produce high-value medicines . Eucalyptus is tolerant to a range of environmental conditions . They are relatively tolerant to salinity and high temperatures, and are drought resistant . Many studies have found that eucalyptuses are hearty and have adapted to many semi-arid and tropical areas throughout Africa, in India, and in Brazil . Eucalyptus is grown in semi-arid Iran, as well . Because they are salt tolerant and their resistant to drought, eucalyptuses are fit for southern Iran . This species was imported into Iran more than a century ago. It was planted in the country’s south . There have been some studies that have examined the compatibility and fit of several eucalyptus species for wood production in southern Iran . The results can guide selection of the best eucalyptus species for farming in southern Iran. Although, the use of eucalyptus in southern Iran has been investigated, there has not been an assessment of the spatial extent of conditions conducive to eucalyptus wood-farming. So far, no comprehensive study has identified the best locations for eucalyptus wood-farming in Iran, while identifying the lands that are best fit for eucalyptus wood farming is a critical step toward meeting Iran’s wood demands . Planning wood-farming development in Iran has many informational challenges as many geographical data are lacking. Therefore, a manager’s knowledge of the geographic, hydrologic, ecologic, edaphic, and climatic conditions of areas of the country is needed to fit specific species to specific places. To assess the ecological priorities of eucalyptus for wood-farming, a large volume of data is needed. Acquiring, organizing, and integrating the data is only possible using tools like remote sensing and geographic information systems.

Satellite data can provide evidence of the dimensions of the factors that are important to growing trees because they are gathered over vast areas, they reduce time and financial costs of field investigations, and they are repeatedly and frequently collected . GIS can also aid mapping and analysis of spatial data and can be used to integrate digital layers . This study pioneers the examination of land suitability for fastgrowing wood species. Specifically, Khuzestan Province, Iran, is assessed for its capacity to support eucalyptus wood-farming. The fuzzy analytic hierarchy process , RS, and GIS, are used to spatially examine the most critical controls on eucalyptus wood-farming. Past studies have shown that E. camaldulensis possesses a great capacity to adapt to drought, salinity, and heat . Therefore, this species is used as a benchmark for the conditions that may support eucalyptus farming. The hypothesis is that Khuzestan Province possesses high ecological potential for eucalyptus wood farms. The multi-criteria decision-making method used in this study was fuzzy AHP which combines AHP and fuzzy sets . This method has been used to rank effective factors in diverse environmental assessment studies and to identify lands that are ideal for specific purposes. This method has been used by decision makers for land management . However, this study is the first to use fuzzy AHP to determine the best lands for wood-farming. Since for many MCDM methods , the availability of empirical field data is required as a first step, the use of these methods was impossible because of the nonexistence of a eucalyptus plantation map at the start of the study. This project filled that gap and used the FAHP approach. It has been shown to be a powerful modeling process . Studies have also recommended the use of expert judgment in an MCDM method to determine the importance of the effective factors used for habitat suitability mapping when field data are not available prior to the research.Therefore, the advantage of this method is that the field data were not required at the start of the study, but they were required for validation of the final wood-farming potential map.

An error matrix was created based on the comparison of the classified pixels in the eucalyptus wood-farming potential map to the corresponding pixels in the actual eucalyptus plantations map  and the validation results were determined . The error matrix contains two rows and two columns reflecting eucalyptus plantations and non-eucalyptus plantations.The first is the number of pixels suitable for eucalyptus plantation in both the classification and in the reality. The second is the number of pixels that are unsuitable for eucalyptus in both data sets. The subsidiary diameter indicates that the FAHP method ignored 77,518 pixels in the classification. The number 11,023 is the number of pixels that are not eucalyptus plantation, but the FAHP classified them incorrectly as suitable for eucalyptus plantation. OA and k were obtained from the error matrix and the results revealed that OA of the map is 82% and k is 0.71. These indicate that the eucalyptus wood-farming potential map is suitably accurate.This study identified the lands that are suitable for eucalyptus wood farming in southern Iran. It is the first time that eucalyptus wood farming potential map has been provided in southern Iran. Land cover, ecological, climatic, hydrologic, hydroponic bucket and edaphic factors were weighted using the FAHP method to combine these factors in GIS to produce a wood-farming potential map. The fuzzy weights for the water, land cover, soil, and climate factors were 0.34, 0.32, 0.24, and 0.10, respectively. Water had the most weight and was therefore the most important factor in determining suitability of parcels for eucalyptus wood-farming. Other studies performed in southern Iran also determined that water influences the diameters and heights of eucalyptus, and therefore it is very important in eucalyptus growth . Eucalyptus needs at least 4000 m3 /ha/yr water to establish itself in southern Iran . There are many eucalyptus species and their water demands vary considerably. E. camaldulensis, for instance, requires more water than E. microtheca . E. camaldulensis was selected as the baseline for analysis of eucalyptus ecological needs because it has shown to be very productive in the conditions of southern Iran . Regarding soil sub-factors, salinity was the most important. The others, soil depth , soil texture , and soil pH , were thus ranked. Though eucalyptus can tolerate semi-saline soils , salinity limits growth in diameter and height. A few species of eucalyptus can tolerate higher levels of salinity.

The resulting ranks of the soil sub-factors, therefore, seem reasonable. Among eucalyptus species, E. camaldulensis and E. microtheca are known to be the most tolerant of salinity and are thus recommended for wood production in Khuzestan Province . Soil salinity below 4 ds/m is the most desirable conditions for E. camaldulensis growth . Suitable lands, in terms of soil salinity, can be found in the northwestern part of the study area . Soil depth and soil texture were of moderate importance. Eucalyptus has thrived on deep soils in Semnan, Qom, Ilam, and Lorestan provinces in Iran . This confirms the relative importance of soil depth on eucalyptus farming. On the other hand, eucalyptus is sensitive to “heavy” soil and doesn’t grow very well in clay soils . The tree does much better in sandy soils . Fortunately, most of study area in Khuzestan Province has deep soil and clay sandy, sandy loam clay, and loam textures , suitable soil texture for E. camaldulensis farming. Soil pH is the least important soil sub-factors. As soil pH ranged from 7.0 to 8.9 in the study area, and as eucalyptus tolerates pH between 7.0 and 8.5 , pH is not a limiting factor for eucalyptus farming in the study area. Most soils in the study area have pH between 7.0 and 8.5 which makes them suitable, for eucalyptus farming . Among the water sub-factors, annual volume of water accessible by plants was determined to be the most important subfactors and is followed by distance from river , surface-water salinity , groundwater depth and groundwater salinity . In fact, sufficient surface water within a useful distance is important for any type of farming.

The seed germination assays continued approximately 5 months from April to September in 2020. Environmental factors influenced the species composition of soil seed banks differently between two plant community types.RDA showed that the environmental variables explained 83.4% and 61.0% of the total variations in species composition in Carex and Phragmites sites . Soil pH explained the most variation , followed by TN , SSC , AP and SWC in Carex sites. Species that germinated from soil seed banks in the Carex-dominated natural wetlands were on the right side of the graph, whereas the farmed fields were on the left . However, soil nutrients including TP , NO3-N and TN , and SSC explained most variation in species composition of soil seed banks in Phragmites sites. Species that are common in Phragmites-dominated natural wetlands were distributed on the lower part of the graph, whereas species from the farmed Phragmites sites are on the upper part of the graph.Many wetlands were lost for agricultural reclamation in China due to their fertile soils and plentiful water.Modern agriculture expanded rapidly with producing much more food and feeding larger population but sacrificing natural wetlands. More than 50% of wetlands have been lost and agricultural activities have been identified as primary drivers for these changes.The rapid conversion of natural wetlands to agricultural lands drained water, affected circulation of materials and eventually changed soil–water environment of wetlands. In our study, land reclamation on Carex-dominated wetlands reduced available nutrients of soils such as SOC, NH4-N, but increased the degree of soil salinization from non-salinity to moderate salinity compared with natural wetlands . These changes could deteriorate soil fertility, productivity and nutrient content,nft hydroponic system and would make restoration more difficult even if the hydrology could be restored.

On the contrary, agricultural reclamation on Phragmites-dominated wetlands relieved stress of soil salinization and improved the capacity of soil nutrient through human intervention such as application of organic fertilizer to satisfy the growth of crops. Therefore, land reclamation caused by agricultural activities in wetlands of the Songnen Plain changed the soil characteristics. The success of converting farmlands into wetlands with ecosystem functions and biodiversity similar to their original position depends on the availability and potential of seeds in soils . The agricultural reclamation on Carex-dominated wetlands decreased seed density and species richness of soil seed banks . The dominated sedges were missing from the seed banks after farming and seeds of these species could not disperse to restored sites because the hydrological connection was interrupted . Previous studies suggested that critical components of the vegetation were missing from farming lands , which was identical with our result. Furthermore, Echinochloa crusgalli and Typha angustifolia dominated in the farming fields and might expand because of their vast ecological amplitude and the absence of native wetland species, which would further reduce biodiversity . Moreover, the seed germination was prevented by the stress of soil salinization, the decreasing availability of water and soil nutrient after farming.Thus, our result indicates that dominant species were not retained in seed banks, which may make sedge meadows difficult torestore via natural recolonization. The composition and structure of soil seed banks changed after farming in Phragmites-dominated wetlands even if there was no significant difference of seed density and species richness of soil seed banks . The similarity between the soil seed banks and above ground vegetation increased after farming . This phenomenon might be caused by following reasons: firstly, Phragmites australis is one of the most widespread species all over the world. Phragmites australis has a wide ecological amplitude and both sexual and asexual reproductions , so it is more adaptable in the variable environmental conditions, particularly the disturbance like farming.

Secondly, Typha angustifolia, Phragmites australis and Scirpus planiculmis dominated in the natural wetlands , which have better tolerance to high soil salinization, retain vitality in the soil seed banks, and survive with tillage from the deep to the surface . Thirdly, the agricultural reclamation improved soil fertility by irrigation and fertilization with alleviating soil salinization and increasing available soil nutrient, which reduced the gap of seed germination from soil seed banks . Overall, there are potentials to restore the farmed wetlands using soil seed banks, but the landscapes have a low probability of resembling those that existed historically. The Songnen Plain serves as one of largest saline-sodic areas around the world, and is experiencing threaten of soil salinization because of climate change and farmland irrigation . Recently, hydrological projects have been carried out in the Songnen Plain to supply water and facilitate vegetation restoration in wetlands, but the results were still not satisfactory. Our research found that saline-alkaline stress was an important factor which restricted the potential of wetland restoration using soil seed banks in the Songnen Plain . The saline-alkaline stress significantly decreased seed density and species richness of soil seed banks through limiting or preventing germination of seeds, especially freshwater species like sedges in the farmed Carex fields . However, the soil seed banks were not significantly affected by saline-alkaline stress in the Phragmites fields. That is because as an invasive species, Typha angustifolia dominated in the soil seed banks and it adapted to conditions with slight salinealkaline stress. Saline-alkaline stress is harmful for the growth of plant and germination of seed mainly through ion toxicity and osmotic stress, which can restrict availability of water and damage plant cells and tissues.

The seeds are devitalized by serious soil salinization or remain dormant until the soil quality and environmental condition are improved . Our research indicates that even slight saline-alkaline stress could affect seed germination and restrict the potential of vegetation restoration in the Songnen Plain. Agriculture in the European Union is generally highly specialized and intensive , resulting in an abundant food production, but also often leading to the degradation of natural resources . In addition, labor productivity and farm income is low in many farming systems in the EU . From a social point of view, quality of life in rural areas in the EU is often perceived to be low as well, especially in the poorer countries . To improve sustainability, a balanced attention for social, environmental and economic system dimensions is important . Inadequate management of natural resources, for instance, can be seen as a failure to understand how social, economic and environmental dimensions are interrelated . Interrelation of these dimensions often results in feedback loops in a system, resulting in non-linear behavior. This makes it challenging to assess and interpret the effect of shocks, stresses and management options on the provision of system functions. In response to this challenge, several resilience frameworks have been developed to study agricultural systems . Sustainability and resilience can be seen as two complementary concepts . Resilience in the form of robustness, adaptability or transformability is needed to maintain or improve sustainability. At the same time, sustainability is needed to ensure the access, availability and quality of resources to buffer shocks and set in motion adaptation or transformation. For the context of a farming system , Meuwissen et al. define resilience as the ability to ensure the provision of the system functions in the face of increasingly complex and accumulating shocks and stresses. By emphasizing the importance of system functions, Meuwissen et al. , provide a practical way to combine the concepts of resilience and sustainability in a complementary way.

To better understand the potential dynamics of farming systems, current as well as future sustainability and resilience need to be studied. Current resilience of European farming systems was for instance studied by Nera et al.,Meuwissen et al., Paas et al.,and Reidsma et al..Towards the future, system behavior may differ according to the development of factors that are exogenous to the farming system, especially when shocks and stresses increase or when enabling conditions for changes are realized. Trespassing critical thresholds could for instance initiate cascading effects leading to a system decline.To avoid this,hydroponic nft system institutional actors may deliberately aim at changing threshold levels to enable innovation that provides an alternative to the dominant ways of producing.Quantitative models are often used to assess, ex-ante, system performance and behavior.Different types of studies and associated models can be distinguished . Based on statistical models, projections or predictions can be made about the average and probable performance for future conditions . However, because statistical models depend on patterns from the past, only a limited range of all possible futures will be captured. Including a broader range of possible futures increases the opportunity to evaluate farming system resilience under different exogenous conditions that are all possible to happen. Incompatibility of farming systems with certain futures can be seen as a sign of non-resilience in case those systems have no capacity to adapt or transform. In itself, comparing farming systems with a broad range of futures directly contributes to foresight information supporting the capacity to anticipate shocks, which is seen as important for resilience . In so-called explorations, optimization models and system dynamics models can consider multiple possible futures, using scenarios capturing uncertainty on climate change and socio-economic developments. However, these models need parameters which are sometimes also derived from statistical models based on past and current trends. Moreover, optimization models are of limited use for modelling dynamic transformations, as they are generally static. Participatory methods can take into account multiple scenarios and allow for input regarding transformational change and resilience concepts such as critical and interacting thresholds . It should be noted, however, that qualitative methods also are influenced by input from statistical sources and experts that extrapolate past trends into the future.

We argue that quantitative and qualitative approaches can be complementary. Participatory methods can be quick, interactive and flexible to start discussions about sustainability and resilience in the future, thus laying a base for further discussions and quantitative model-based analyses.Participatory methods allow for taking into account the voice of individual stakeholders as well as support stakeholder discussions to arrive at a common understanding and a shared vision for improvement of the system or problem under study. Stakeholder participation is important as stakeholders are usually involved in follow-up processes and thus need to agree with the problem definition and proposed action plan.Participatory input is valuable because system actors are able to provide empirical knowledge about their system that reduce knowledge gaps of researchers.Vice versa, participatory methods are also important to identify the boundaries of local knowledge.Stakeholder’s perceptions are particularly precious, as they can explain or drive system dynamics as stakeholders are important components of socio-ecological systems.Hence, participatory methods can provide a first exploration of farming system structure, mechanisms, performance and behavior in possible futures. Discussions with stakeholders about future change can be challenging because stakeholder’s mental models usually focus on maintaining the status quo with little imagination of alternative futures.Other limitations for discussing farming system transformations may relate to the focus of experts on improving efficiency, vested interests, co-dependencies among system actors and institutional path dependence. Participatory methods should therefore provide opportunities to go beyond the usual extent of stakeholder’s mental models. Alternative systems, that avoid critical thresholds and increase sustainability and resilience simultaneously, should be explored, and new strategies to realize those alternative systems identified. To ensure the soundness of intended pathways towards the future, alternative systems need to be compatible with possible future developments of exogenous factors as projected in different future scenarios. High compatibility of desired alternative systems with future scenarios increases the likelihood that those more sustainable and resilient systems will be realized. Consequently, this also decreases the likelihood that critical thresholds will be exceeded, resulting in farming systems with even lower sustainability and resilience levels. We argue that a quick and flexible assessment of future resilience and sustainability of farming systems is still lacking in literature. In response to this research gap, this paper presents a participatory, integrated and indicator-based method to improve understanding of farming system sustainability and resilience.

Though there is interest in developing this industry path in the Bergen region, to date no trigger point for its establishment has been reached. It is reasonable to assume, based on reviewed documents and our interviews, that large-scale production is possible. The key bottleneck is the industry’s ability to compete with traditional salmon farming in terms of production cost and value chain maturity. Production cost is mainly driven by the cost of growth medium, and thus one can argue that the trigger point for the cell-based seafood industry will be the development of media that is sufficiently inexpensive as to bring down production costs. The knowledge bases for these industries also have distinct origins. The region’s salmon aquaculture industry is based mainly on experience-based knowledge and a hands-on approach. Knowledge is generally transferred by word of mouth and through business-to business interactions. This exemplifies a synthetic knowledge base. Yet some industry activities are more analytical knowledge-based, such as production of feed and vaccines and other efforts towards solving environmental issues. By contrast, cell-based seafood industry activity is based strongly on research and carefully measured experiments that are conducted by scientists at research institutions. This type of knowledge is codified and transferable, exemplifying an analytical knowledge base. When it comes to innovation modes, the Bergen region’s salmon industry is quite practical and production oriented. Much of its innovation activity is the DUI type, in which experience and tacit knowledge dominate, and incremental product innovations is the main output. The STI mode elements are mainly linked to innovation collaboration projects between the industry and R&D institutions.

By contrast, the cell based seafood industry is highly dependent on an STI mode in which much of the research and technology are developed in-house among the main industry actors. These firms are also more frequently involved in innovation collaboration with R&D institutions,grow table hydroponic through testing, experimentation, and piloting new solutions. Regarding geographical configuration, the salmon farming industry is clearly tied to coastal areas. The Bergen region has become globally positioned as a salmon hub through a combination of crucial, beneficial geographical factors that make salmon farming possible, as well as from governmental investments in R&D institutions and the region’s development of a strong supplier industry. Together, these industry actors form a competitive cluster characterized by specialization, collaboration and knowledge sharing. Thus, the industry has developed a spatially sticky innovation system. By contrast, cell-based seafood production will not be strongly tied to any specific geographical area, as it will take place in facilities that can be established anywhere in the world with the required infrastructure . Countries such as the US, the Netherlands, China and Japan all have startups, venture capital and/or governmental backing to support establishing the clean meat industry. Thus, clean meat is associated with a footloose innovation system . Through our interviews with cell-based seafood industry representatives, we discovered that they are interested in gaining access to knowledge and animal biology expertise from the Bergen region salmon cluster: “their knowledge of fish embryology, fish genetics would be super helpful” . As the salmon industry has matured, the value chain has diverged into specialized companies occupying specific niches; thus, genetics companies may be of specific interest. At this stage, other areas of potential collaboration with salmon industry actors in the Bergen region may be more relevant.

Almost all cell based seafood industry activity is centered around companies’ R&D into launching their products on the market.Thus, the Bergen region’s strong marine research environment and expertise are advantageous for triggering the development of a new, related seafood industry niche. Other potential areas for collaboration with the Bergen region’s salmon farming industry are down-stream value chain activities such as distribution and marketing. Being included in the distribution and marketing of a large, diversified seafood product portfolio would clearly be advantageous for the cell-based industry. It could speed up the introduction of cell-based seafood to consumers: “If they see it as an important thing to be a part of an aquaculture industry, then it has to be seen as a fish product portfolio more than synergies in production” . Salmon compete against other animal proteins, e.g., beef, through being a supposedly healthier and more ethical choice. Government and regulatory institutions within salmon farming are keen to promote sustainable seafood production as a better choice to red meat, which is another pull factor for the Bergen region, and Norway generally. While there has been no official statement regarding the Norwegian government’s stance on cell-based seafood, it is plausible to assume that when the industry grows, there will be a positive response based on the environmental sustainability, production increase potential and animal welfare benefits of cell-based seafood while delivering a health profile closely matching that of farmed salmon. The introduction of cell-based seafood may also help diversifying the seafood industry portfolio in the region as well as providing knowledge “spill-over” effects from the biotechnological advancements in alternative protein production. Our objective herein has been to explore the opportunities and obstacles for introducing a new, related industry niche through co-evolution with an established regional industry. Empirically, we investigated industry development in the Bergen region of western Norway, with the cell-based seafood sector representing the new industry niche and the salmon industry representing the established regional industry. Cell-based seafood has large potential to diversify the seafood sector and contribute to increased sustainability by providing highly controlled seafood production without animals. Large investments, entrepreneurial experimentation and interest organization initiatives have been undertaken globally to rapidly mature the industry niche.

There are visions and expectations among actors connected to the potential of cell-based seafood and the observed interest in the Bergen region seafood sector may provide opportunities for industry co-evolution in the future. However, our main observation is that co-evolution between the cell-based seafood sector and the salmon industry in the Bergen region are challenging at the present moment. Despite growing popularity of the co-evolution concept, there is scarce literature to explain why co-evolution between two adjacent industry paths can be difficult. Through our study we found two explanations for this. First, co-evolution is difficult when the dominant path is in a stable state. High profitability and a stable state mean that this industry absorbs investors, technology suppliers and research milieus that may otherwise have been on the lookout for alternatives and supplementary business opportunities. It also means that incumbents within the dominant path will not be looking for diversification alternatives. Our findings echo observations by, who argued that the most productive and skilled workers and entrepreneurs in a region tend to flock to the most attractive regional industry. Second, heterogeneity between the two adjacent industry paths also makes co-evolution difficult. As cell-based seafood and salmon farming are both affiliated with the seafood sector, one might expect that cognitive and technological relatedness would promote co-evolution. However, there are distinct differences between the two industry paths when it comes to knowledge base, innovation mode and geographical configurations at the present time, making actor mobility, knowledge spillover and resource sharing between the two industry paths challenging. We also introduce the concept of industrial convergent co-evolution to discuss potential co-evolution between industry paths that at the present are unrelated.

As the cell-based seafood industry matures more opportunities for co-evolution may occur as downstream value chains of farmed salmon and cell-based production may intertwine through convergent evolutionary mechanisms. The cell-based seafood industry aims to create similar products and reach similar customers as the salmon farming industry. Thus, the cell-based seafood industry may eventually imitate and utilize the established logistics and marketing system for salmon, making the value chain of the two industries more similar in the mature stages of industry path development. Our study has implications for policy formulation. The Bergen region lacks some of the infrastructure needed for cell-based seafood to emerge as an industry path. The industry is reliant on specialized R&D facilities such as laboratories and other test facilities. Though there is a strong seafood R&D infrastructure in Bergen, with public research institutions and established pharmaceutical companies, these are markedly oriented to the needs of the salmon industry . Thus, policy initiatives mobilizing for development of a new industry niche are needed. In such path creating processes regional innovation support organizations can play a proactive role. The regional interest organization NCE Seafood Innovation Cluster have for instance a particular interest in creating a more sustainable and diversified seafood sector in the region. They can connect large seafood firms with startups and research to access cutting-edge innovation as well as interfacing with European policy initiatives to ensure increased focus on sustainable seafood development. Vestlandets Innovasjonsselskap , a business incubator and technology transfer offices in the region, provide research infrastructure and expertise toward better integration between biotechnology and aquaculture.Moreover, these regional innovation support organizations should work towards triggering the interest for cell-based seafood among the region’s established salmon farming producers and suppliers. This could unleash more resources towards innovation and experimentation, which would likely increase the probability of the development of a new industry path in the Bergen region. The result could be a more environmentally sustainable and diversified regional salmon sector, including both traditional salmon farming and an emerging cell-based seafood production. This would also make the seafood sector in the region more resilience to external turbulence triggered by governmental initiated growth barriers for salmon farming,grow table changing consumer preferences or environmental challenges. Our study was not without limitations. First, co-evolution has been investigated through the potential establishment of a new industry niche in a region.

If cell-based seafood activities were already in place, we could have examined realized and unrealized co-evolution dynamics, rather than potential co-evolution dynamics. Future research should also include empirical studies in other sectors and regions, to gain a more comprehensive understanding of why potential co-evolution between adjacent industry paths does, or does not, materialize. The concepts of nature-based solutions and the utilization of coastal green-gray infrastructure are attracting increasing attention from both policy and practical perspectives. Shallow coastal ecosystems,such as mangroves, salt marshes, seagrass meadows, and macroalgal beds,are good examples of these concepts, considering their roles as part of the global carbon cycle and as a natural defense against sea level rise. Blue infrastructure and ocean-based NbS projects can lead to sustainable revenue-generating opportunities. Furthermore, they can help in realizing a blue economy for local communities through comprehensive investments in the conservation of coastal ecosystems and biodiversity, as well as in optimal blue infrastructure . In a report jointly published in 2009 by the United Nations Environment Programme Planning Unit; the United Nations Food and Agriculture Organization ; and the United Nations Educational, Scientific, and Cultural Organization, “blue carbon” is defined as carbon captured by marine organisms. The ocean is a particularly important carbon reservoir because blue carbon stored in seafloor sediments can remain undecomposed and unmineralized for long periods of time . The role of blue carbon in SCEs as a climate mitigation measure has attracted attention worldwide. Typical SCEs, including mangroves, tidal marshes, and seagrass meadows, are now being called “blue carbon ecosystems”. Blue carbon initiatives are currently moving from the advocacy stage to the social penetration, policy making, and implementation stages . Approximately 20% of the countries that have joined the Paris Agreement have pledged to use SCEs as a climate change mitigation option in their nationally determined contributions. These countries are moving towards measuring national blue carbon amounts and are accounting for them in their greenhouse gas inventories. Approximately 40% of those countries also have pledged to use SCEs to adapt to climate change as part of conservation, protection, and reforestation initiatives, as well as through planning efforts such as integrated coastal zone management and fisheries management. Australia and the United States have also begun including blue carbon in their numerical emissions reduction targets and calculating blue carbon according to the 2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands . The 25th Conference of the Parties , or COP25, to the United Nations Framework Convention on Climate Change , held in Spain in 2019 was positioned as a “Blue COP”.

For the high threshold scenario this is exactly the opposite. This indicates that when there is a higher likelihood of influence, craftsmen and entrepreneurs become more positive towards organic, while idealists less. A lower likelihood of negative social influence leads to more organic idealists in the low threshold scenario, and it leads to more organic craftsmen and organic entrepreneurs in the high threshold scenario. In the baseline scenario, a higher likelihood of negative social influence leads to more organic idealists, organic craftsmen and organic entrepreneurs. This indicates that disassociation actually stimulates organic farming diffusion. All experts thought market factors to be the most important factor for the size of the organic market. Their explanations were different: one argued that farm gate price stability in the organic market is the most important factor , and two thought demand by consumers would be most important . Experts differed on the second most important factor. One expert thought that this was social influence among farmers, another expert thought social influence among consumers , and the third expert thought that shocks or events in the conventional market was the second most important factor. The third most important factor, according to all experts, was farm succession. According to these experts, most recently converted organic farmers are young farmers who think differently than their predecessors. This research aimed to gain insight in what factors influence the size of organic pig farming and the diversity of farming styles among organic pig farmers, by considering social influence mechanisms, market price dynamics and farmer heterogeneity. The exploratory analysis showed that when there is a higher likelihood of influence in interaction , the numbers of organic farmers and organic pigs increase, as well as the diversity of organic farmers’ farming styles. The latter also happens when similarity in farmers’ farming style does not affect the credibility of another farmer. The sensitivity analysis showed that the most influential factor on the size of the organic market is the trend in demand.

The most influential factors on the distribution of farming styles in the organic market were similar to the factors that affect the size of the organic market, except for the successors’ farming style which was important for the diversity of farming styles, mobile vertical grow tables while trend in the demand was not. In addition, the importance and effect of parameters on outputs differed between number of organic idealists versus number of organic craftsmen and organic entrepreneurs. Experts categorised and confirmed that demand is the most important factor stimulating diffusion. They furthermore pointed to the importance of successors in the diffusion of organic farming, a trend also found in the model. One of the innovations in this model, compared to previous agent based models on organic farming diffusion is inclusion of market factors in the farmer decision-making process in addition to their personal and social factors. The importance of including demand is in line with previous research by Smith and Marsden and Rose et al. who argued that the wider agricultural system should be taken into account , including consumer demand , to understand diffusion processes of alternative farming strategies in general , or organic farming in particular . They both argued that considering other actors and components in the system, diminishes, though does not kill, the importance of individual farmer behaviour. Both our model results and experts judgement confirm that an increase in the trend in demand is the most important factor to stimulate organic market diffusion. In addition, increase in demand is related to an increase in the diversity of organic farmers’ farming styles according to model results and expert discussion. Another component of demand is the price elasticity of demand for organic meat, which we used to account for volatility in organic meat price as a consequence of imbalances in supply and demand. Interviewed experts, however, argued that gains or losses caused by imbalances in supply and demand are currently taken by supply-chain actors instead of consumers, which basically hints towards a low price elasticity.

To this end, further research focusing on dynamic price mechanism in an agent-based modelling framework might either be to model stakeholders, such as the role of slaughterhouses in the formation of prices as outlined by experts, or confirm the current level of price elasticity of demand for organic meat through empirical studies. Additionally, it would be interesting to identify and quantify factors that affect price elasticity of demand for organic meat. In particular, the growing supply of substitutes might affect both demand for organic meat and its price elasticity . Due to more available environment-friendly alternatives, e.g., plant-based meat, it can be hypothesized that the current level of price elasticity of demand for organic meat is higher than the one we adopted from Bunte et al. , meaning that an increase in price of organic meat would force more consumers to switch to substitutes. Another point which affect the organic meat price is when organic farmers do not have a successor: the organic meat price will go up as these organic pigs disappear from the model. In reality, they might have been taken over by another farmer, which could be an interesting addition to the model. Although one of the experts believed risk preferences related to meat price volatility to be an important factor for organic market conversion, we did not consider it in the model. In line with the observation of the expert, an hypothesis could be that risk-averse farmers in a less volatile organic market context, would have more incentives to convert to organic farming. Yet, quantification of the effect usually requires quite strong assumptions on the level of risk aversion, which is rather difficult to estimate. Furthermore, even in the farm-level context, research on dynamic decisions under uncertainty and risk preferences is limited . Hence, including risk preferences in agent based modelling requires, first of all, further methodological research. The same applies to learning mechanism linked to organic farming, which has proven to be an important factor in conversion . Instead, we assumed that intrinsic motivation shaped by the Social Identity Approach in interactions is the most important prerequisite to consider conversion to organic farming, discussed further below. The social identity approach was the theoretical backbone of the social interaction mechanism between farmers in the model.

Four reference groups were distinguished which differed in importance between innovative and conservative farmers: farmers who have a high status compared to one’s own status were more credible for innovative farmers, while similar farmers were more credible for conservative farmers. In addition, following the social identity approach, farmers who were respectively low in status or dissimilar were considered out groups and disassociation followed through negative social influence. Model parameters were operationalised to determine how much credibility was necessary before influence takes place , the magnitude of influence when influence takes place, and a threshold for the value of attitude before a farmer continues to calculate the expectation income in the alternative market. Model results showed that the likelihood of influence in interaction affected organic market diffusion, and that similarity in farming styles obstructs diffusion of organic farming and diversity of organic farmers’ farming styles.It also leads to fewer organic idealists, and more organic craftsmen and organic entrepreneurs in the organic market. This indicates that when different types of farmers influence each other more easily, i.e. are more open to each others’ ideas, it favours the attitude towards organic of craftsmen and entrepreneurs, but disfavours the attitude of conventional idealists. Taking expert observations into account,mobile vertical farm a more positive attitude of entrepreneurs and craftsmen regarding organic is indeed the case. But, probably more importantly, the effect of threshold values on output supports the argument made by Flache et al. that in agent-based models attention should be paid to the technical implementation of interaction between agents and the sensitivity of the outcome on the parameterisation of the interaction mechanism. In other words, model operationalisation of a conceptual model on influence affects model outcomes. An important model assumption, following from the social identity approach, was negative social influence to avoid association with out groups. In this research, the effect of disassociation between farmers on number of organic farmers and organic pigs depend on the likelihood of influence: when there was a higher likelihood of influence , negative social influence was actually a motivation for craftsmen and entrepreneurs to convert, while when there was a smaller likelihood of influence , negative social influence was a motivation for conventional idealists to convert to organic farming. This means that disassociation was an incentive for craftsmen and entrepreneurs to stay conventional in the scenario with a smaller likelihood for influence , which is in line with empirical research that showed that craftsmen and entrepreneurs oppose idealistic motivations .

It also means that disassociation with out groups was an incentive for craftsmen and entrepreneurs to convert to organic farming in the scenarios with a higher likelihood for influence. This is in contrast with empirical research, which showed that craftsmen and entrepreneurs oppose idealistic motivations for organic farming . The question is whether disassociation can be an incentive to consider market conversion in real life. So far, empirical evidence for or against negative social influence is poor . A way forward on this discussion would be to further explore model results with only positive social influence in accordance with the critique by Flache et al. . Given the results, it is likely that this would lead to fewer organic farmers in the scenarios with less likelihood for influence , and it would lead to fewer organic craftsmen and entrepreneurs in the scenarios with more likelihood for influence . According to the social identity theory, influence occurs through similarity . The results of the model showed that the three factors that defined similarity hardly affected the number of organic farmers, whereas similarity in farming style did affect the organic farmers’ farming styles: if similarity in farming style did not influence the credibility of another farmer, the number of organic craftsmen and organic entrepreneurs increased, while the number of organic idealists decreased. Similarity in farming style, therefore, obstructs diffusion of organic farming from idealists to craftsmen and entrepreneurs, given that the initial organic farmers were idealists. This social identity mechanism can, therefore, explain the finding by de Rooij et al. that entrepreneurs and craftsmen oppose organic farming because of idealist organic farmers. According to the experts, this mechanism mainly applies to the older generation farmers, since young farmers seem to have another rationale for converting than existing farming styles. The rationale used by the young farmers, mentioned by experts, fits the constructivist discourse identified by de Rooij et al. : they accept changes in societal norms regarding animal welfare and recognise the need to respond to this. Young farmers are, therefore, not obstructed by organic farmers’ farming styles. In addition, it is likely that similarity in farming styles does not weigh heavily within the decision-making process for some entrepreneurs and craftsmen, since they did enter the organic market according to the experts. Finally, experts also mentioned that most organic idealists changed from a dominant idealist rationale to a dominant craftsmen rationale to professionalise organic farming. This is interesting input for further refinement of the social influence mechanism: e.g., multiple farming style reference groups exist within one farmer , and the dominant farming style is flexible to the context.The effect of status on the number of organic idealists was seen by the relatively high number of organic idealists in the scenarios with a lower likelihood for influence: organic farmers had a high idealist status compared to the idealist status of conventional farmers. This triggered especially idealist farmers in the higher credibility threshold scenarios to convert. The effect of the status mechanism was, furthermore, seen in the relative importance of the price elasticity parameter on the number of organic entrepreneurs whose status is dependent on income: in the scenario with a small likelihood for influence, a decrease in price elasticity increased organic entrepreneurs ; in the scenarios with a larger likelihood for influence, a decrease in price elasticity resulted in fewer organic entrepreneurs .

Based on the domain analysis introduced above, the next section describes the conceptual framework developed for designing and implementing Digital Twins. Control is a basic concept in system dynamics. It ensures that the system’s objectives are achieved, even if disturbances occur. The basic idea of control is the introduction of a controller that measures system behaviour and corrects if measurements are not compliant with system objectives . Farm processes are ‘in control’ if the performance of its operations remain in a steady state. Therefore, the activities of these processes must include the cybernetic control functions necessary to demonstrate ‘cybernetic validity’. Basically, this implies that they must have a feedback loop in which a norm, sensor,discriminator, decision maker, and effector are present . Fig. 5 depicts these control functions in a basic control model.In farming systems these are the business processes of the involved actors that transform input material to final products at the end customer’s location. The sensor function measures the actual performance of the object system. The discriminator function compares the measured performance with the norms that specify the desired performance and signals deviations to the decision-making function. Based on a control model of the object system, the decision-making function selects the appropriate intervention to remove the signalled disturbances. Finally, the effector implements the chosen intervention to correct the object system’s performance. Digital Twins allow farmers to decouple the physical flows from information aspects of farm operations . Decoupling of control means that the measurements of the object system’s state are translated into a Digital Twin as visualized in Fig. 6.

The control cycle starts with measuring the object system’s state by the sensor function and with acquiring relevant external data.These data are then translated into a virtual representation of the controlled object system on the basis of a meta model. The Digital Twin includes all information relevant for the supported purposes of usage as specified in a meta model. Dependent on a specific purpose of usage, a virtual view may then filter irrelevant information and present it in such a way that it can be processed optimally by specific users on the basis of a meta model. The next control function is the decision-making function, dutch bucket for tomatoes which compares a virtual view on the object system with a specific control norm. Next, the decision-making function selects appropriate interventions for deviations based on its Decision Support Model, similarly as in conventional control systems. Lastly, the selected intervention is communicated with the effector function, either directly or via the Digital Twin using remote actuator systems. The previous sections have defined distinct control mechanisms of six Digital Twin categories. Fig. 8 incorporates these mechanisms into the control model. This model integrates all six Digital Twin defined categories, but not all elements will be relevant if less categories are applied. The integrated control model especially adds different types of the representation, i.e. imaginary, present, future and past digital objects. Imaginary digital objects represent reference objects that do not yet exist. Present digital objects represent the current state and behaviour of real-life, physical objects. Future digital objects project the expected state and behaviour of objects. Past digital objects represent the historical state and behaviour of real-life objects or objects that no longer exist in the real-world. Furthermore a reference object is added to allow for the representation of conceptual entities that come into existence in the design phase of the product life cycle. Once the conceptual entity is materialized, the real object can be connected to the virtual object.

This conceptual entity remains after the disposal of the real-life object at the end of the lifecycle. Reference object can also be relevant during the usage phase. An example is the usage of imaginary resources for planning purposes, which specify the type of resources and the properties necessary to do the job. Think of, for example, a virtual harvest machine having a certain capacity in specific weather and soil conditions. When the harvesting schedule becomes actual, a physical machine is chosen to do the job for the virtual one . Finally, the interaction between the decision-maker function and the Digital Twins is elaborated. In prescriptive Digital Twins, intervention proposals based on decision support models are transformed into future Digital Twins. As such, the expected object changes of virtual interventions are simulated. The decision maker uses this simulated interventions to decide on the final intervention. Autonomous Digital Twins also translate this intervention decision into planned object changes and subsequently into actuator instructions. Autonomous twins remotely control the effector function that executes these instructions. So far, the concept of Digital Twins and its underlying complexity were defined. The next section will present a technical model that is designed to implement this concept. This section proposes a technical model for the implementation of Digital Twins. A technical architecture describes the components of a system, interactions among components, and the interaction of a system as a whole with its environment . It is usually not drawn in one diagram but separated in multiple so-called architecture views each of which describes an architecture according to specific stakeholders’ concerns . For the purpose of this paper, we focus on visualizing main functionalities that are needed to implement the control model as developed in the previous section. Several technical architectures for Digital Twins are introduced recently. Schleich et al. proposed an abstract reference architecture that addresses some basic modelling principles for ‘twinning’ between the physical and virtual world properties, such as model scalability, interoperability, expansibility, and fidelity.

Alam and Saddik developed a specific a Digital Twin architecture, that analytically describes key properties of cloud-based cyber-physical systems. Redelinghuys et al. designed an architecture for Digital Twins of manufacturing cells comprising six layers, including local data, gateways, cloud-based databases and a layer for emulations and simulations. These authors consider Digital Twins as a next step in IoT-based cyber-physical systems. As a consequence the proposed architectures are similar to reference architectures developed in the IoT domain, in which virtual representation of objects have an important role. Important IoT reference architectures include IoT-A, ITU-T and AIOTI . The Internet of Things—Architecture provides a very in-depth definition of IoT’s information technology aspects . The International Telecoms Unions has developed an IoT Reference Model which provides a high level capability view of an IoT infrastructure . The Alliance for IoT Innovation has defined a High Level IoT Architecture to achieve IoT semantic interoperability . In the present paper we adopted the IoT-A reference architecture because it most explicitly addresses virtual entities as a core element of the architecture. The remainder of this section will introduce the IOT-A reference architecture and how it supports the implementation of Digital Twins. The Architectural Reference Model for the Internet of Things is developed by the European project IoT-A . Besides establishing a common understanding of the IoT domain, IoT-A aimed to provide essential building blocks and design choices for developing interoperable IoT system architectures. The reference model includes five different sub models: an IoT domain model, IoT information model, IoT functional model, IoT communication model and an IoT trust, security and privacy model . The ontological foundation is formed by the IoT Domain Model, which defines main concepts of the Internet of Things like Devices, IoT Services and Virtual Entities , and how these concepts are related. Building upon these concepts, the IoT information model defines the structure of IoT related information in an IoT system on an abstract level. The Functional Model decomposes the main functionalities of IoT-based systems into groups in a layered view. The IoT Communication Model elaborates the technical communication for connecting the different elements of an IoT-based system, including a reference set of communication rules to build interoperable stacks. The sub models are elaborated in very detailed architectural views and accompanied by guidelines. It can be concluded that the IoT-A is a very in-depth and rigorous reference model.

It is beyond the scope of this paper to describe it into detail, but we focus on its IoT functional model . For more details and the further technical implementation we refer to Bauer et al. and Carrez et al. .Basically, a Digital Twin architecture is composed of a physical object in real space, a digital representation of this object in the virtual space and the connection between the virtual and real space for transferring data and information . As argued previously, IoT technologies enable this synchronization of the physical and virtual worlds. The implementation model of our conceptual framework, based on the IoT-A functional model, addresses eight layers . These layers range from a device layer, blueberry grow pot which is attached to physical objects, to an application layer, which includes interaction with Digital Twin Users . The Device layer provides the hardware components that are attached to and directly interact with physical objects such as tags for unique identification, sensors and actuators. Important identification technologies used in agriculture include barcodes and RFID tags . Furthermore, a multitude of different sensors is used to measure dynamic properties of physical things including temperature, crop size, humidity, light, moisture, CO2, ammonia and pH values. Object sensing is also supported by mobile devices such as barcode/RFID readers and smartphones, which enable farmers to perform additional actions such as visual quality inspections. Furthermore, this layer includes remote sensing by satellites, aerial vehicles, and ground based platforms. Small unmanned aerial systems are increasingly used to realize a high spatial and temporal resolution and a high flexibility in image acquisition. Finally, in the device layer actuators are used to remotely operate objects such as tractor implements, climate control, irrigation, coolers, and lights. The Communication layer manages the interactions between different components and enables the communication from the devices to the IoT services. It provides capabilities for networking, connectivity and data transport and enables end-to-end communication that crosses different networking environments. The IoT Service layer contains services and functionalities for discovery, look-up and name resolution of IoT Services. It can be used to get information retrieved from a sensor device or to deliver information to control actuator devices. The Digital Twin Management layer contains functions for interacting with the IoT System on basis of virtual entities. It can give access to all the information about the Digital Twin, from sensor devices, databases or applications. Furthermore, it contains all the functionality needed for managing associations with the physical objects and monitoring their validity.

The IoT Process Management layer provides an environment for the modelling and execution of IoT-aware processes. Deployment of process models to the execution environments is achieved by utilizing IoT Services that are orchestrated in the Service Organisation layer. This layer acts as a communication hub between several other layers by composing and orchestrating services of different levels of abstraction. The Security layer is responsible for the security and privacy of the systems and its users. It includes components like authorization, authentication and identity management. The Management layer is focussed on the configuration of the system. It also reports faults and determines the overall state of the system. Finally, the Application layer provides the intelligence for specific control tasks based on virtual objects. It includes capabilities for usage of Digital Twins across its lifecycle. The different categories of Digital Twins are enabled by diverse technologies, including simulation and optimization tools, statistical forecasting, simulation and machine learning. This layer also includes the user interface for interacting with Digital Twins. The types of user interfaces can vary from 2D graphical user interfaces, as commonly used in personal computers, smartphones and tablets, to advanced 3D interfaces for Virtual and Augmented Reality glasses. The remainder of this paper will illustrate the application of Digital Twins in agriculture by some cases of the IoF2020 project. The framework as presented in the previous sections is applied to five smart farming use cases of the IoF2020 project . It is beyond the scope of this paper to exhaustively deal with the applied models for all cases. Therefore, we provide in Table 4 an overview of the applied control models and in Table 5 the applied implementation models.