Geomembranes are generally welded in the field.The seam is considered a critical point for possible injuries and future leaks in the barrier system.Rollin et al.reported that the total number of faults in geomembranes occurred in landfills, ponds and basins, and 55% of them were found at the seams.Stark et al.evaluated seams made by industry and in the field of a polyolefin geomembrane for a water reservoir project.According to the authors, the seams made by industry can minimize dirt and moisture in the seam, ambient temperature changes and wind.After good statistical data work, the results of this research showed that the seams made by industry were 9% stronger than field seams for peel strength and 10% stronger for shear strength.Moreover, seams according to industry data showed less variability.Lavoie et al.evaluated two different HDPE geomembrane samples exhumed from a municipal landfill leachate pond and a sewage treatment aeration pond.The authors conducted thermal, physical and mechanical analyses.The thermogravimetric analyses showed an altered decomposition behavior for the landfill leachate pond sample, probably caused by the interaction with the leachate.The sewage pond sample presented low stress cracking resistance and low tensile elongation at break, compatible with the dynamic mechanic analysis , which showed an increase in the stiffness.Ewais and Rowe studied an HDPE geomembrane with 1.0 mm of the thickness of about five years immersed in synthetic leachate at different temperatures and in air and water at 55 ◦C.The authors observed changes in the sample’s stress crack resistance values before chemical degradation and before antioxidant depletion for temperatures lower than 70 ◦C.The major SCR value decrease was noted for the sample immersed in leachate at 55 ◦C, reaching 26% of the SCR value of the virgin sample.

This behavior was attributed to morphological changes during aging that affected the interlamellar connections due to the annealing that increased the strength of the inter-lamellar connections and the proposed chain disentanglement mechanism.HDPE geomembranes are often utilized as a flow barrier in landfills, mining facilities, canals, waste liquid ponds,mobile vertical farm and farm ponds.This research evaluated three exhumed high-density polyethylene geomembrane samples from two different shrimp farming ponds after 8.25 years of field exposure for the first pond and 3.0 years of field exposure for the second pond.Thermoanalytical and physical analyses were used to understand the final conditions of the HDPE geomembrane samples.Analyses such as thickness, density, carbon black content, melt flow index , tensile properties, stress crack resistance, oxidative-induction time , thermogravimetry,differential scanning calorimetry,and dynamic mechanical analysis were performed.Using an HDPE geomembrane as a liner of a shrimp farming pond is limited to some places globally, such as the northeast region of Brazil.This work aims to provide new data on the HDPE geomembrane performance in shrimp farming pond applications.This work evaluated three high-density polyethylene geomembrane samples exhumed from two different shrimp farming ponds in the northeast of Brazil with 0.8 mm of nominal thicknesses.The samples called “CAM” and “CAM1′′ represent the same geomembrane installed in a shrimp farming pond and were collected after 8.25 years of field exposure.The CAM sample was exhumed from the bottom liner and had been in contact with the salinized water.The CAM1 sample was exhumed from the same pond as the CAM sample, but it was taken from the slope liner and had been in contact for 8.25 years with environmental conditions.The third sample was exhumed from another shrimp farming pond after 3.0 years of service.This pond has the particularity of being covered with an agricultural plastic film.Figs.1 and 2 show, respectively, the shrimp farming pond representing the CAM and CAM1 samples and the shrimp farming pond representing the CAM2 sample.Table 1 presents the salinized water parameters used for shrimp cultivation.

However, nesting habitats and foraging resources for pollinating insects have decreased severely due to intensification in agricultural landscapes.Developing effective mitigation tools to counteract pollinator losses is essential for satisfactory pollinator diversity and sustainable agriculture.In Europe, agri-environment schemes are among the most valuable instruments to reduce the pressure of agriculture on the environment.The new Common Agricultural Policy of the EU also aims at increasing their share by targeting one-fourth of the direct payments to subsidise eco-schemes.AES offer two main tool types to support biodiversity and thus pollination, i.e.productive and non-productive schemes.Organic farming is one of the most favoured productive management systems where farming intensity is reduced with a preference for mechanical methods over agrochemicals.In their meta-analysis, Tuck et al.found that organic farming increased overall species richness by 30 %, with plants benefiting the most.Pollinator insects also profit from organic farming.Flower strips are flower-rich non-crop landscape features created at arable field edges.The annual or perennial strips are formed to enhance invertebrate pest control and pollination by providing forage, shelter, and nesting places.As AES schemes differ in concept, they should be evaluated against each other to prioritise them for benefits to biodiversity.Functional trait-based assessments offer an effective tool for studying community functionality, redundancy and stability in agroecosystems.Different management types can support various arthropod taxa by maintaining specific plant functional traits and high functional trait diversity.Plant traits associated with visibility, quantity, and quality of floral resources are the most important traits shaping pollinator communities.For example, plants with large, conspicuous inflorescences attract pollinators efficiently , while floral patterns resulting from UV reflection are also important signals to several major pollinator groups.Nectar is the primary reward for pollination; therefore, spatial and temporal variation in nectar volume influences pollinator behaviour and survival.As land-use significantly affects pollination-related flower traits , their diversity can indicate the quality and quantity of floral resources and can be used to evaluate AES schemes for pollinators.Different field parts with different management regimes can support biodiversity and pollination to varying degrees.The interior of arable fields covers the largest area of agricultural landscapes; therefore, its ecological condition may be decisive for biodiversity at the landscape scale.Intensive management within field interiors favours plants with ruderal strategies , and selects for species with early flowering and selfing.Crop edges are also shown to be keystone transitional zones for pollinators and support increased plant diversity compared to field interiors as they are expected to contain both typical arable weeds and species originating from grassy margins.

Linear non-crop landscape elements such as grassy margins along field edges are less intensively managed than field interiors and also provide important shelter and forage resources for various taxa in agricultural landscapes.The overall performance of AES schemes on pollination should be quantified by assessing all characteristic parts of the agricultural fields.Landscape-scale factors should also be considered beside local factors when studying the effects of AES schemes on pollinators and their services.The effectiveness of AES varies by landscape heterogeneity that has two main components.Compositional heterogeneity describes the relative amount of habitats in the landscape, whereas configurational heterogeneity refers to their spatial arrangement.Most studies assessed the effect of landscape composition on pollinator communities and found that pollinator abundance and richness were higher in landscapes comprising more high-quality habitats.The role of landscape configuration is less studied, though it may also be very important as landscapes with smaller fields have higher structural connectivity and more edges providing more floral resources for pollinators.Given this research gap, here we focus on the role of the less studied configurational heterogeneity by assessing landscape-scale mean arable field size.Our study presents a trait-based approach to estimate the potential of two agri-environmental schemes to support pollinators based on floristic composition.For this, we studied plant traits associated with pollinator attraction and reward accessibility.We calculated community-weighted trait means and functional trait diversity in organic and conventional winter wheat fields complemented with sown flower strips and compared them to conventional fields along a gradient of landscape configurational heterogeneity.We tested whether management intensity and landscape heterogeneity select for specific pollination-related plant traits, and result in differing trait diversity by using literature data on species traits.Our specific hypotheses were the following: Pollination-related plant trait diversity is reduced with increasing mean field size within the landscape.Flower strips and organic farming maintain functionally more diverse plant trait composition than control conventional fields.Pollination-related plant trait diversity decreases from grassy margins to field interiors in both conventional and organic fields.We considered only insect-pollinated plant species that may attract pollinators and provide nectar resources.We assessed the following traits: flower size, flower colour, UV pattern in the flower,vertical farming racks reward quantity, and flowering duration.Trait values were collected from the BiolFlor database and identification books.Flower size was expressed as flower diameter.For zygomorphic flowers, the mean of the longest and shortest diameter was calculated.In the case of compact inflorescences that can be regarded as one functional pollination unit, we used the size of the whole inflorescence.We expressed flower colours on a continuous wavelength scale.White-flowered species got the mean value of the visible light spectrum.The presence of UV pattern in the flower was treated as a binary variable.In the case of reward quantity, we considered only nectar resources because of no available information about pollen resources for the majority of the species.Nectar quantity was provided on an ordinal scale with four categories.

The average flowering duration was coded as a continuous variable.For each transect, we calculated the total number and average percentage cover of insect-pollinated plant species.We quantified transect-level community-weighted means for each trait by averaging trait values weighted by species abundance.We tested the effects of management type , transect position , mean field size on the species richness and cover of insect-pollinated plant species, Rao’s quadratic entropy and the CWM and FD values for each trait by using linear mixed-effects models.We used generalized mixed-effects models for species richness with Poisson error distribution and log link function.For each response variable, we started with a model with all two-way interactions of the fixed effects and then selected the minimum adequate model from all possible nested models with the minimum Akaike Information Criterion value.The effect of years was not assessed per se but was treated as a random effect in the analyses.The field, farmer, and landscape identities were also used as random effects nested within each other and crossed with year.We used log transformation for cover values and square root transformation for CWM and FD values if necessary to fulfil test assumptions.We restricted our assessment on those 151 transects that harboured at least one insect-pollinated plant species for flower colour analyses to have meaningful results.We derived marginal and conditional coefficients of determination of the models to estimate the variance explained by the fixed effects and the entire model including both fixed and random effects using the MuMIn.We conducted multiple GLMM tests, therefore, we controlled for the false discovery rate.Post hoc pairwise comparisons were made with the em means package , and were presented in the figures.All analyses were conducted in the R environment.We found that flower strips and organic farming outperformed conventionally farmed fields, as they had the highest insect pollinated plant species richness and supported higher trait diversity favourable for pollinators.Flower strips were superior with the highest cover of insect-pollinated plants and the highest ratio of flowers showing UV patterns.Although annual flower strips doubled the insect-pollinated plant species richness in the grassy margins, the benefits of flower strips completely diminished in neighbouring field interiors.In contrast, organic field interiors could be considered the most favourable pollinator habitat among the studied field interiors based on plant pollination traits.Thus organic farming can enhance pollinators at a larger spatial scale with more environmentally friendly crop production on the whole area of the arable land.We did not find any effect of configurational heterogeneity expressed as mean arable field size.We showed that organic farming outperformed conventional farming practices regarding insect-pollinated species richness, flower attractiveness, and food resources provided for pollinators.This is primarily due to lower overall farming intensity in organic fields.Even organic field interiors offer abundant and diverse flower resources to pollinators compared to conventional farms.Thus, we can consider organic farming the most beneficial method based on pollinators’ resources.In contrast, intensively managed conventional fields supported the lowest richness of insect-pollinated plant species showing that only a few plant species could establish here randomly.Annual flower strips sustained the most favourable vegetation for pollinators, considering the quantity and quality of flower resources.They had six times higher cover of insect-pollinated plants than the edges of the other two farming methods.