To our knowledge, no other study has tested whether naturally occurring soil biotas from multiple undisturbed habitats affect flowering phenology and selection on flowering time, nor has any study of the relationship between soil microbes and phenology explicitly accounted for genetic variation among undomesticated plant populations.Sterilized potting soil was saturated with inoculum and sterilized field soils were saturated with buffer for 10 days. Then, 48 accessions of Boechera stricta were transplanted as gnotobiotic seedlings into all treatments . All pots were randomized into blocks of 200 and maintained under controlled greenhouse conditions throughout the experiment, except for 7 weeks of 4°C vernalization in a growth chamber. We measured plant height and leaf number on the date of first flowering. Here we focus on phenology and fecundity of the 51% of plants that flowered successfully. Among those plants that flowered, the experimental design exhibited only modest imbalance, with substantial sample sizes remaining in every subspecies × treatment cell . Factors influencing probability of flowering and other fitness components are beyond the scope of this paper; we found no evidence that any experimental treatments affected flowering probability of surviving plants . Reproductive fitness was estimated as the number of fruits on each individual at 33 weeks of age; in B. stricta, fruit set is strongly and positively correlated with seed production in the greenhouse .Soils were collected from four natural Boechera stricta habitats in central Idaho, USA, separated by ~26 to ~92 km and differing in elevation, temperature, water availability, density and diversity of vegetation, and many soil properties .

Collection locations were named ‘Jackass Meadow’ , ‘Mahogany Valley’ , ‘Parker Meadow’ , and ‘Silver Creek’ . These remote sites have little history of disturbance by humans, are home to endogenous B. stricta populations, hydroponic net pots and function well as common gardens for B. stricta field experiments . Therefore, they are legitimate potential habitats that B. stricta likely encountered during its evolutionary history in this region. Each soil collection comprised five sub-samples from the four corners and approximate center of a ~150 m2 area, at a depth of ~10 to 30 cm. Subsamples were combined and mixed thoroughly, sieved through ~1.25 cm wire mesh to remove rocks and coarse detritus, shipped to Duke University, and stored in plastic bags at 4°C for ~3 months until use. We also collected seven ~1 mL soil vouchers from each site for microbial community analysis: three in August 2011, and at all sites except PAR, four in August 2012. Vouchers were frozen at -20°C until DNA extraction in late 2012. B. stricta seeds were collected from 48 natural populations, including four from the soil collection sites. Their sites of origin span over 1,000 m in elevation and are separated by between ~1 km and ~350 km, with the exception of the “SAD12” genotype from Colorado. Because B. stricta is naturally inbred and exhibits high FIS and FST , each population was represented by a distinct genotype. This diverse collection of genotypes included 24 from each of the ecologically divergent “east” and “west” subspecies . We used seeds from a single mother descended from the original field-collected accession, self-pollinated in the greenhouse for at least one generation, to minimize maternal effects; i.e. individuals within a genotype were self-full sibs .To create four soils that were identical except for their microbial communities, we extracted microbes from field soils into sterile buffer and soaked sterilized potting soil in the resulting suspensions.

We prepared inocula from 75 g sub-samples of each field-collected soil stirred into 1 L of 2.5 mM MES monohydrate in sterile diH2O . After settling for 30 min the suspensions were vacuum filtered to remove particulates. Filtrates were centrifuged 30 min at 3,000×G at room temperature to pellet microorganisms. To remove dissolved nutrients, we discarded the supernatants and re-suspended the microbe-enriched pellets in 1 L sterile 2.5 mM MES. This process mostly eliminated variation in chemical properties that differentiate the field soils . Each rack of 200 pots was bottom-saturated with 400 mL of one of the microbial suspensions, 6 g 20-10-20 fertilizer, and sterile diH2O for a total treatment volume of 4 L. The fertilizer was added to encourage seedling survival and to counteract possible soil impoverishment due to autoclaving . An additional 1 mL of undiluted microbial suspension was pipetted into each pot. Treatments derived by this process are termed “biotic” or “microbial treatments” throughout. It is possible that the filtration and re-colonization processes somewhat altered community structures; however, the differences between our experimental inocula—and their effects on the plants—originate from corresponding differences between real Boechera habitats.We sterilized soils from four natural habitats to create growth substrates with different physical and chemical properties, but without their natural microbiomes. After sub-sampling to extract microbial communities , we sterilized the four field-collected soils via autoclaving . These soils were loosely packed into clean pots and bottomsaturated with 400 mL sterile 2.5 mM MES, 6 g 20-10-20 fertilizer, and sterile diH2O to bring the treatment volume to 4 L.

An additional 1 mL sterile 2.5 mM MES was pipetted into each pot. Treatments derived by this process are termed “abiotic” or “sterilized field soils”. Although it is likely that autoclaving these soils changed their fertility, they appear to have retained at least some of their natural chemical variation .Surface-sterilized seeds of 48 genotypes were stratified on auto claved filter paper at 4°C in the dark for two weeks, then placed in a growth chamber to germinate for one week . Four germinated seedlings per genotype were transplanted into each of the eight experimental soils described above, one seedling per pot. Eight pots per treatment were left unplanted as controls. All pots were immediately rearranged into randomized blocks and maintained in controlled greenhouse conditions for the duration of the experiment. Plants were top-watered as needed with RO water, and received an additional 4 mL 20-10-20 fertilizer via pipet when one month old. Two-month-old plants were transferred to a 4°C vernalization treatment, where they remained for seven weeks. After vernalization, plants were returned to the greenhouse, checked three times weekly for flowers and allowed to set fruit. Flowering was defined as sufficient separation of the corollasuch that four distinct petals could be identified. The number of days between end of vernalization and first flowering is termed interchangeably “flowering time” and “flowering phenology” throughout. On the day of first flower for each plant we measured the individual’s height and number of leaves. The last census was done eight weeks post-vernalization; the 749 plants that had not flowered by this date were excluded from all future analyses. The experiment ended two months after the final flowering census, when almost all fruits had matured and dehisced. These cutoffs for flowering time and fruit production are realistic given the short growing season observed in the field. At this time we counted the number of fruits produced by each individual.Due to current methodological limitations, in this study we focus on the prokaryotic component of the soil microbiome . We extracted DNA from field collected soil vouchers using the MoBioTM PowerSoil DNA Isolation Kit and amplified variable region 4 of the bacterial 16S rRNA gene using established primer pairs 515F and 806R and PNA PCR clamps to reduce plastid and mitochondrial contamination . Paired-end 2×250bp sequencing of barcoded amplicons was performed on a MiSeq machine running v2 chemistry at the Joint Genome Institute . The primer sequences were trimmed from the paired-end sequences, blueberry grow pot which were then overlapped and merged using FLASH . Merged sequences were grouped into operational taxonomic units based on 97% sequence identity, and chimeric sequences were removed, using the UPARSE pipeline . Taxonomies were assigned as in Lundberg et al. . Unclassifiable OTUs at the kingdom level, OTUs matching Viridiplantae, mitochondrial, or plastid sequences were excluded by using BLAST to compare them to a custom database of contaminant sequences . Unclassifiable OTUs at the kingdom level and rare or non-reproducible OTUs were also excluded as in Lundberg et al. , resulting in 7,844 OTUs. To control for unequal sequencing effort, we normalized data by rarefaction to 40,000 reads/sample using QIIME-1.7.0 . Diversity analyses were performed after correcting data for 16S gene copy number variation using scripts provided in Kembel et al. ; OTUs without taxonomic information were assigned the mean copy number . Linear regressions were performed before this correction but the resulting parameter estimates were adjusted as necessary.To test the hypothesis that soil properties affect flowering time, we used restricted maximum likelihood linear mixed models with treatment, subspecies, and treatment × subspecies as fixed factors; block, genotype nested within subspecies, and treatment × genotype as random factors; and elongation rate , height at first flowering , and leaves per mm stem as covariates .

To test for treatment effects on overall plant size we used MANOVA with treatment, subspecies, and treatment × subspecies as fixed factors. We analyzed the parallel “biotic” and “abiotic” experiments separately, i.e. one model tested only for effects of soil microbiomes on flowering time, and another identical model tested only for effects of physical soil differences; we did not directly compare the effects of these two types of soil variation. These models were run using JMP® Pro version 10.0.0 . Statistical significance of random effects was determined by REML likelihood ratio test and results were graphed using ggplot2 in R version 3.0.2 . To test the hypothesis that soil properties alter selection on flowering time, we used a REML linear mixed model with the same terms as above, plus flowering time and flowering time × treatment as additional fixed effects. The response variable was number of fruits. Thus, the flowering time term describes the change in fecundity attributed to a change in flowering time, i.e. selection. We analyzed the parallel “biotic” and “abiotic” experiments separately as above. We performed these models both with and without including elongation rate, height at first flowering, and leaves per mm stem as covariates; the former model describes the selection gradient on flowering time , and the latter model describes the selection differential . Introducing a quadratic term did not improve fit, so our model considers only linear effects . Sample sizes were slightly smaller than for the flowering time models because 17 individuals were accidentally discarded after flowering. Main models were performed in JMP; selection differentials and selection gradients were calculated in R. For some models, non-uniformly distributed residuals might have influenced judgments about significance. In general, results with and without covariates were similar, suggesting that significance was robust to heteroscedasticity in the standard model. For the sake of caution, for all of our major results, we performed permutation tests to verify the results of the standard ANOVA. Rarefied microbial communities were analyzed in the R package ‘vegan’ . Principal coordinates of Bray-Curtis pairwise dissimilarities were identified using the vegan function ‘capscale’. Similarity of samples within vs. among sites was tested using the non-parametric permutation test ADONIS with 9,999 permutations constrained by collection year. To ask which components of microbial communities affect flowering phenology and selection, we regressed mean flowering time in each biotic Treatment onto the mean PCo score from the corresponding Site. To ask which OTUs underlie the observed phenotypic effect, we identified the ten OTUs most highly correlated with the PCo axes and regressed the same flowering time residuals on the OTUs’ mean abundances at each site. We used the Wilcoxon rank-sum test to compare relative abundances of common taxa between groups of samples associated with extreme phenotypes. P-values were adjusted using Benjamini-Hochberg false discovery rate. Our method of searching for microbial community members that underlie our phenotype of interest is described in more detail in Appendix S3.Selection on flowering time depended on soil microbiome. This result held both for selection gradients and selection differentials . The most extreme change was between the PAR and SIL soil biotas , with selection differentials of +0.034 and -0.043 fruits/day , respectively. The magnitude of this difference in selection is 1.2 times the selection differential measured in a nearby field site .

This finding is consistent with a report that both supine and standing HRs were significantly increased 1h and 3h after a 790 kcal meal in the morning after an overnight fast. However, the calorie content in mango and white bread in this current study was only 298 kcal. Studies regarding the consumption of fruits and postprandial BP and HR are scarce. Future research is encouraged to investigate whether fruit intake will induce similar hemodynamics as meals. In study I, the 2h change in blood glucose was not different between mango or no mango intake, despite the difference in sugar intake from the fruit. This observation was reinforced further in study II, where the blood glucose was significantly increased 1h after white bread intake but not after eating an isocalorically-matched amount of mango. The insulin level was also significantly increased 1h after white bread intake compared to 1h after no mango or mango intake. In addition, although the 2h change in blood glucose after eating white bread returned to a level similar to baseline values, the 2h change of insulin was still significantly elevated compared to the 2h value seen in the no mango group. These data are consistent with other reports regarding mango consumption and glucose regulation. For example, in obesity-prone mice fed a high-fat diet, dutch bucket hydroponic the fasting blood glucose, insulin, and homeostatic model assessment for insulin resistance score were significantly decreased after 10 weeks of mango fruit powder intake ateach of three levels .

In obese male C57BL/6J mice consuming a high-fat diet, daily supplementation freeze-dried mango at either 1% or 10% of the weight of the diet significantly reduced body fat compared to those consuming a non-supplemented control diet. Curiously, only the 1% mango group showed significantly decreased fasting blood glucose and postprandial blood glucose responses after tolerance tests, but no difference was noted for insulin or HOMA-IR, compared to those consuming the 10% supplementation or control diets.30 In overweight and obese humans, plasma insulin was significantly increased 45 min after consuming 100 kcal of mango , compared to their baseline levels, but did not increase as much as when the participants consumed an to isocaloric low-fat cookie. The same study also noted that capillary blood glucose levels were significantly elevated 30 min after mango intake compared to their baseline values, while returning to the baseline range at 60, 90, or 120 min after intake, whereas intake of the low-fat cookie showed significantly increased blood glucose at both 30 and 60 min, which is consistent with trends from our study. However, the above study measured insulin at baseline and 45 min after food intake, so the postprandial insulin levels cannot be compared directly with our study. Future research may consider assessing the association between postprandial BP, glucose, and insulin resistance at multiple time points. This study has several limitations. The Ataulfo mangos were not analyzed for nutrients or phenolic contents. Different mango cultivars vary in macronutrients, micronutrients, as well as phytonutrient content.

Among commonly consumed mango cultivars, Ataufo mango pulp contains the highest concentration of β-carotene, ascorbic acid, total phenolics, gallotannins, and mangiferin, in comparison to Haden, Keitt, Kent, and Tommy Atkins. The high concentrations were used in the selection of Ataulfo. The amount of white bread as an isocaloric control was calculated based on the USDA food database, which does not identify the cultivar or cultivars that were tested. Finally, the postprandial blood glucose and insulin responses in study II were not measured at 30 min, which may have missed the possible peak levels. Future studies may take the measurements at more frequent time points, as well as insulin resistance indicators, such as HOMA-IR, to better understand the role of mango in blood glucose management. In conclusion, two weeks of daily mango intake was associated with a decrease in SBP and PP. The glucose and insulin responses after mango intake were also moderated, compared to ingesting of an isocaloric amount of white bread. While the effects of mango intake on microvascular function were not as significant as the response from other whole foods, other measures of cardiovascular health, as well as glucoregulatory benefits, warrant further study.Epidemiological studies suggest that diets rich in carotenoids can be beneficial for vision, heart, bone health, cognitive performance, and cancer prevention. The current review focuses on the potential role of the xanthophyll carotenoids lutein and zeaxanthin in eye health, specifically their potential role in reducing risk of age-related macular degeneration .

We review the absorption, distribution, and metabolism of L and Z, and the current dietary recommendations for these carotenoids, then speculate about their putative role in maternal and infant health. Lastly, we discuss the potential value of goji berry within the diet as a food with the highest known amount of Z. Carotenoids contribute to the bright red, orange, and yellow color in plants. These fat-soluble phytochemicals are classified into two categories: carotenes, which include only hydrocarbons, and xanthophylls that also contain oxygen. While some dietary carotenoids serve as vitamin A precursors most of the approximately 100 carotenoids found in plants do not. Among the carotenoids devoid of vitamin A activity are L and Z, along with meso-zeaxanthin , a stereoisomeric metabolite of L. Absorption involves enterocyte uptake by CD36, scavenger receptor class B type I , and Niemann-Pick C1-like transporter 1 at the apical membrane. Xanthophylls are then secreted through the basolateral membrane of the enterocyte, mainly by ATP binding cassette A1 and carried by lipoproteins to target tissues. SR-B1, SR-B2, and CD36 transport L and Z into the tissues. Steroidogenic acute regulatory domain protein 3 has been identified as a binding protein for L in the retina, and glutathione S-transferase pi isoform for Z. Lutein, Z, and meso-Z impart a distinctive yellow color to the fovea of primates – the specialized central area of the macular region of the retina that is rich in cone photoreceptors and optimized for high-acuity central color vision. The compounds have a maximal absorbance at a wavelength near 460 nm and are most concentrated in the inner and outer plexiform layers, which consists primarily of axonal connections between the retinal layers. Their combined density is greatest in the center of the macula and decreases with increasing retinal eccentricity. In the central fovea, the concentration of Z and meso-Z is higher than L at a ratio of 2.4:1. Lutein is most abundant in the peripheral macula, with a Z + meso-Z to L ratio of 1:2 when measured by high performance liquid charomatography. However, a newer technique, confocal resonance Raman microscopy suggests that the Z + meso-Z to L ratio is as high as 9:1 at the central fovea.16 Protection from blue light is critical for eye health. Compared to longer wavelengths of visible light, short blue wavelengths are higher in energy and generate reactive oxygen species . Zeaxanthin can provide stronger oxidant defense than L during photooxidation, while lutein has a greater capacity to absorb short wavelength light irradiation in lipid membranes. Compared to other carotenoids , L and Z are more effective in scavenging ROS and can also reduce phospholipid peroxidation. The photoreceptor-retinal pigment epithelium complex in the outer retina is particularly susceptible to ROS damage due to its high polyunsaturated lipid content . Quenching of singlet oxygen appeared best when L, Z, and meso-Z were mixed in equal ratios rather than separately when assessed in an eye tissue model, suggesting some synergy between the these macular pigments in their antioxidant properties. The most common method to quantify xanthophylls in the retina is to assess macular pigment optical density . This parameter is measured through techniques such as heterochromatic flicker photometry , a non-invasive psychophysical technique, fundus reflectometry, resonance Raman spectroscopy, or autofluorescence imaging. The MPOD index is associated with plasma levels of L and Z, and has been used to assess the risk for AMD. However, some studies report no correlation between MPOD and risk of AMD,31 which suggests that other ocular measures may be useful to obtain a more complete profile of AMD risk. In human donor eyes, dutch buckets system the amount of L and Z was inversely associated with AMD. Supplementation of L, Z, and meso-Z have been shown to significantly increase MPOD in both healthy individuals and patients diagnosed with AMD. However, studies using foods rich in L and Z have produced inconsistent results, which may be due to the relatively modest amounts of these carotenoids in foods compared to supplements.

Importantly, the plasma concentration of L and Z has been more strongly associated with MPOD than the correlation between MPOD and dietary intake. Age-related macular degeneration is the third leading cause of blindness worldwide after uncorrected refractive errors and cataracts. An estimated 288 million people worldwide are projected to suffer from AMD by 2040. In the United States, the prevalence of early-stage AMD was 9.1 million in 2010, and this number is projected to increase to 17.8 million by 2050. AMD is characterized by a gradual loss of eyesight from the central visual field. Although the exact etiology of AMD is not clear, common pathologic progress includes oxidative stress, lipofuscin toxicity, lipid accumulation, immune dysregulation, and choroidal hyperperfusion. Age-related processes such as a decrease in retinal neuronal elements, alterations in the size and shape of RPE cells, and thickening of Bruch’s membrane also participate in the pathology of AMD. Damage to mitochondria in RPE cells has also been suggested to play a role. Dry AMD, also termed non-exudative AMD, involves the formation of drusen, which are mainly lipid and protein deposits that accumulate between the RPE and Bruch’s membrane in the macula. In contrast, wet AMD, also termed exudative or neovascular AMD, is a consequence of abnormal blood vessel formation arising from the choroid, known as choroidal neovascularization . Clinically, AMD is classified as early or intermediate stage based on the size and number of drusen, as well as presence of pigmentary changes. The AMD is considered late or advanced stage in the presence of CNV, where fluid accumulation may result in damage to the neurosensory retina and fibrous scarring, or geographic atrophy , where loss of the RPE result in damage to overlying photoreceptors and underlying choriocapillaris causing irreversible vision loss. The main risk factors for AMD are aging and smoking, although some studies have shown no difference in MPOD between healthy older individuals and healthy young. Other risk factors may include race, obesity, previous cataract surgery, presence of cardiovascular disease, and hypertension. According to the U.S. National Institutes of Health, the prevalence of AMD is highest among Caucasians as compared to other races, and higher in females than in males. Genetic factors are also associated with AMD, with several high-risk single-nucleotide polymorphisms identified from genome wide association studies. The strongest risk variants include the Y402H variant of complement factor H gene as well as those in the age-related maculopathy susceptibility 2 locus. Whether the color of the iris or sunlight exposure are related to the risk of AMD is still being explored. Dietary interventions using L- and Z-rich foods have generated inconsistent results regarding the risk of AMD. In a cohort study that assessed dietary carotenoid consumption among individuals without AMD at baseline over more than 20 years, increased predicted plasma carotenoid score of L, Z, β-carotene, α-carotene and β-cryptoxanthin were associated with a lower risk of advanced, but not early or intermediate AMD. Similarly, a meta-analysis of six longitudinal cohort studies found that the dietary intake of L and Z significantly reduced the risk of GA by 26% and CNV by 32%, with no apparent impact on early stages. Another metaanalysis concluded that supplementation with L, Z, and meso-Z significantly increased MPOD levels in both AMD patients and healthy individuals in a dose-response manner. However, whether the improvement in MPOD could be sustained after L and Z supplementation is discontinued remains unclear. The Age-Related Eye Disease Study was a multi-center study that assessed the efficacy of a dietary anti-oxidant supplements on subjects who are 50 to 80 years old, with and without AMD or cataracts, for more than seven years. The initial study used a formula containing 15 mg of β-carotene, 500 mg of vitamin C, 400 IU of vitamin E, with or without 80 mg of zinc and 2 mg of copper. Lutein and Z were not included because the scientific evidence to include these two carotenoids was not yet clear.

Climate change, including climate variability, must be considered as this may change extant regional dynamics of both coffee and CBB, and their interactions. Increased temperature may generate conditions favorable for coffee and CBB allowing range extensions to new areas, and changes in CBB damage levels in its current geographical distribution. Increased dry “El Niño” climatic events in some countries could increase CBB populations, while “La Niña” events with prolonged wet seasons would limit CBB populations. Te effects of such phenomena differ across geographical region, and the coffee/coffee berry borer system model provides a framework for analyzing the potential effect of variation in weather, climates and of climate change on coffee yield, and the dynamics of CBB across diverse bio-geographical zones. As an aside, the high pest status of this species in monocultures is a consequence of an evolutionary background, similar to what have been observed in other systems . From the prospective of the ecological theory, the large female bias appears to have had high adaptive value in the African tropical forest where it evolved so that large numbers of the small females with low searching rates could find scattered patches of suitable age berries. This adaptation would appear to occur at the expense of reduction in genetic variability caused by sib-mating and reported pseudo-arrhenotoky. As a final note, our C. arabica PBDM can easily be modified to include other species of coffee , strawberry gutter system and has transferability enabling its use in a bio-economic analysis on larger, albeit global scale, and in the face of climate change.Agriculture is a key human activity in terms of food production, economic importance and impact on the global carbon cycle.

As the human population heads toward 9 billion or beyond by 2050, there is an acute need to balance agricultural output with its impact on the environment, especially in terms of greenhouse gas production. An evolving set of tools, approaches and metrics are being employed under the term “climate smart agriculture” to help—from small and industrial scale growers to local and national policy setters—develop techniques at all levels and find solutions that strike that production-environment balance and promote various ecosystem services. California epitomizes the agriculture-climate challenge, as well as its opportunities. As the United States’ largest agricultural producing state agriculture also accounted for approximately 8% of California’s greenhouse gas emissions statewide for the period 2000–2013. At the same time, California is at the forefront of innovative approaches to CSA . Given the state’s Mediterranean climate, part of an integrated CSA strategy will likely include perennial crops, such as winegrapes, that have a high market value and store C long term in woody biomass. Economically, wine production and retail represents an important contribution to California’s economy, generating $61.5 billion in annual economic impact. In terms of land use, 230,000 ha in California are managed for wine production, with 4.2 million tons of winegrapes harvested annually with an approximate $3.2 billion farm gate value. This high level of production has come with some environmental costs, however, with degradation of native habitats, impacts to wildlife, and over abstraction of water resources. Although many economic and environmental impacts of wine production systems are actively being quantified, and while there is increasing scientific interest in the carbon footprint of vineyard management activities, efforts to quantify C capture and storage in annual and perennial biomass remain less well-examined.

Studies from Mediterranean climates have focused mostly on C cycle processes in annual agroecosystems or natural systems. Related studies have investigated sources of GHGs, on-site energy balance, water use and potential impacts of climate change on productivity and the distribution of grape production. The perennial nature and extent of vineyard agroecosystems have brought increasing interest from growers and the public sector to reduce the GHG footprint associated with wine production. The ongoing development of carbon accounting protocols within the international wine industry reflects the increased attention that industry and consumers are putting on GHG emissions and offsets. In principle, an easy-to-use, wine industry specific, GHG protocol would measure the carbon footprints of winery and vineyard operations of all sizes. However, such footprint assessment protocols remain poorly parameterized, especially those requiring time-consuming empirical methods. Data collected from the field, such as vine biomass, cover crop biomass, and soil carbon storage capacity are difficult to obtain and remain sparse, and thus limit the further development of carbon accounting in the wine sector. Simple yet accurate methods are needed to allow vineyard managers to measure C stocks in situ and thereby better parameterize carbon accounting protocols. Not only would removing this data bottleneck encourage broader participation in such activities, it would also provide a reliable means to reward climate smart agriculture.

Building on research that has used empirical data to compare soil and above ground C stocks in vineyards and adjacent oak woodlands in California, this study sought to estimate the C composition of a vine, including the relative contributions of its component parts . By identifying the allometric relationships among trunk diameter, plant height, and other vine dimensions, growers could utilize a reliable mechanism for translating vine architecture and biomass into C estimates. In both natural and agricultural ecosystems, several studies have been performed using allometric equations in order to estimate above ground biomass to assess potential for C sequestration. For example, functional relationships between the ground-measured Lorey’s height and above ground biomass were derived from allometric equations in forests throughout the tropics. Similarly, functional relationships have been found in tropical agriculture for above ground, below ground, and field margin biomass and C. In the vineyard setting, however, horticultural intervention and annual pruning constrain the size and shape of vines making existing allometric relationships less meaningful, though it is likely that simple physical measurements could readily estimate above ground biomass. To date, most studies on C sequestration in vineyards have been focused on soil C as sinks and some attempts to quantify biomass C stocks have been carried out in both agricultural and natural systems. In vineyards, studies in California in the late 1990s have reported net primary productivity or total biomass values between 550 g C m−2 and 1100 g C m−2. In terms of spatial distribution, some data of standing biomass collected by Kroodsma et al. from companies that remove trees and vines in California yielded values of 1.0–1.3 Mg C ha−1 year−1 woody C for nuts and stone fruit species, and 0.2–0.4 Mg C ha−1 year−1 for vineyards. It has been reported that mature California orchard crops allocate, on average, one third of their NPP to the harvested portion and mature vines 35–50% of the current year’s production to grape clusters. Pruning weight has also been quantified by two direct measurements which estimated 2.5 Mg of pruned biomass per ha for both almonds and vineyards. The incorporation of trees or shrubs in agroforestry systems can increase the amount of carbon sequestered compared to a monoculture field of crop plants or pasture. Additional forest planting would be needed to offset current net annual loss of above ground C, representing an opportunity for viticulture to incorporate the surrounding woodlands into the system. Astudy assessing C storage in California vineyards found that on average, grow strawberry in containers surrounding forested wildlands had 12 times more above ground woody C than vineyards and even the largest vines had only about one-fourth of the woody biomass per ha of the adjacent wooded wildlands.The objectives of this study were to: measure standing vine biomass and calculate C stocks in Cabernet Sauvignon vines by field sampling the major biomass fractions ; calculate C fractions in berry clusters to assess C mass that could be returned to the vineyard from the winery in the form of rachis and pomace; determine proportion of perennially sequestered and annually produced C stocks using easy to measure physical vine properties ; and develop allometric relationships to provide growers and land managers with a method to rapidly assess vineyard C stocks. Lastly, we validate block level estimates of C with volumetric measurements of vine biomass generated during vineyard removal.The study site is located in southern Sacramento County, California, USA , and the vineyard is part of a property annexed into a seasonal floodplain restoration program, which has since removed the levee preventing seasonal flooding. The ensuing vineyard removal allowed destructive sampling for biomass measurements and subsequent C quantification.

The vineyard is considered part of the Cosumnes River appellation within the Lodi American Viticultural Area, a region characterized by its Mediterranean climate— cool wet winters and warm dry summers—and by nearby Sacramento-San Joaquin Delta breezes that moderate peak summer temperatures compared to areas north and south of this location. The study site is characterized by a mean summer maximum air temperature of 32 °C, has an annual average precipitation of 90 mm, typically all received as rain from November to April. During summer time, the daily high air temperatures average 24 °C, and daily lows average 10 °C. Winter temperatures range from an average low 5 °C to average high 15 °C. Total heating degree days for the site are approximately 3420 and the frost-free season is approximately 360 days annually. Similar to other vineyards in the Lodi region, the site is situated on an extensive alluvial terrace landform formed by Sierra Nevada out wash with a San Joaquin Series soil . This soil-landform relationship is extensive, covering approximately 160,000 ha across the eastern Central Valley and it is used extensively for winegrape production. The dominant soil texture is clay loam with some sandy clay loam sectors; mean soil C content, based on three characteristic grab samples processed by the UC Davis Analytical Lab, in the upper 8 cm was 1.35% and in the lower 8–15 cm was 1.1% . The vineyard plot consisted of 7.5 ha of Cabernet Sauvignon vines, planted in 1996 at a density of 1631 plants ha−1 with flood irrigation during spring and summer seasons. The vines were trained using a quadrilateral trellis system with two parallel cordons and a modified Double Geneva Curtain structure attached to T-posts . Atypically, these vines were not grafted to rootstock, which is used often in the region to modify vigor or limit disease .In Sept.–Oct. of 2011, above ground biomass was measured from 72 vines. The vineyard was divided equally in twelve randomly assigned blocks, and six individual vines from each block were processed into major biomass categories of leaf, fruit, cane and trunk plus cordon . Grape berry clusters were collected in buckets, with fruit separated and weighed fresh in the field. Leaves and canes were collected separately in burlap sacks, and the trunks and cordons were tagged. Biomass was transported off site to partially air dry on wire racks and then fully dried in large ventilated ovens. Plant tissues were dried at 60 °C for 48 h and then ground to pass through a 250 μm mesh sieve using a Thomas Wiley® Mini-Mill . Total C in plant tissues was analyzed using a PDZ Europa ANCA-GSL elemental analyzer at the UC Davis Stable Isotope Facility. For cluster and berry C estimations, grape clusters were randomly selected from all repetitions. Berries were removed from cluster rachis. While the berries were frozen, the seeds and skins were separated from the fruit flesh or “pulp”, and combined with the juice . The rachis, skins and seeds were dried in oven and weighed. The pulp was separated from the juice + pulp with vacuum filtration using a pre-weighed Q2 filter paper . The largest portion of grape juice soluble solids are sugars. Sugars were measured at 25% using a Refractometer PAL-1 . The C content of sugar was calculated at 42% using the formula of sucrose. Below ground biomass was measured by pneumatically excavating the root system with compressed air applied at 0.7 Mpa for three of the 12 sampling blocks, exposing two vines each in 8 m3 pits. The soil was prewetted prior to excavation to facilitate removal and minimize root damage. A root restricting duripan, common in this soil, provided an effective rooting depth of about 40 cm at this site with only 5–10 fine and small roots able to penetrate below this depth in each plot. Roots were washed, cut into smaller segments and separated into four size classes , oven-dried at 60 °C for 48 h and weighed.

Nesting substrate, therefore, has a smaller or negligible effect on bacterial abundance compared to differences among states. Ceratina calcarata foraged from a slightly greater phylogenetic richness of floral genera in New Hampshire than in Georgia. The phylogenetic richness of floral genera in Missouri did not significantly differ from either Georgia or New Hampshire, perhaps because of its mid-lying geographic position and climate. As expected, our reanalysis of the New Hampshire data with 99% ESV matching recovered fewer genera than in McFrederick and Rehan, who found 110 genera compared to this study with 65. We identified the same five genera as being the most abundant , these genera accounting for 92% of the reads . Despite this more conserved estimate of genera, the floral resources used in New Hampshire are still rich compared to those utilized in Georgia. We also found that foraging females in Missouri foraged from more plants to form a single pollen provision mass than those in Georgia . This suggests that suitable floral resources at the time of brood provisioning may not be as diverse in Georgia as more northern areas of Ceratina’s range, or that they were simply not locally abundant in the area around the collected nests. Across its geographic range, C. calcarata encounters a broad variety of possible forage. Diets in Georgia, Missouri and New Hampshire were dominated by pollen from different plant genera . Out of the 96 floral genera found in provisions in this study, only Rubus was found in more than 1% of reads across all three states . All other genera, even if abundant in one or two states, were rare in provisions from the third. For example, grow bucket sumac was a key floral resource in New Hampshire but made up less than 10% of the reads in Georgia and was hardly utilized at all in Missouri .

It is important to note that while read counts have been correlated with microscopy pollen counts in many studies, factors such as pollen morphology can skew the abundance estimate obtained from DNA sequences. Our study uses the marker rbcl, which has shown strong correlation with pollen counts, outperforming trnL and ITS2. With this in mind, comparison of relative abundance between sites shows state-wise differences in diet. Many of these plant genera are common to all three states, so perhaps these dietary variations are due to differences in bee and floral phenologies, as well as possible microhabitat distinctions in floral assemblages in proximity to the bee nest. While we do not have data on floral distributions within each collecting site, our records of nest substrate allow us to determine that foraging was not skewed towards the host plants. Rubus was a common pollen source but even nests formed within Rubus plants did not show a bias in pollen collection. Different pollens vary in nutritional qualities, which may influence foraging decisions. Pollen can also have toxic constituents, and some generalist foragers appear to actively utilize a broad range of floral resources to alleviate the effects these may have on brood development. How these factors influence C. calcarata foraging is unknown but our results suggest that spatial orientation of floral resources alone does not determine foraging preferences. The presence of a consistent core microbial community despite the variation in pollen sources suggests that many of the most common bacterial genera do not have specific floral associations. We identified a number of tentative bacteria–plant correlations, but these were not consistent among states . In the overall analysis, the tupliptree genus Liriodendron was correlated with Lactobacillus, while the same plant genus was correlated with Sphingomonas in Georgia. In Missouri, Wolbachia was correlated with four plant genera: Brunia, Camptotheca, Rhus and Smilax but this bacterium was not correlated with plants in the other states or the overall analysis.

The correlations found in Georgia and Missouri also differ to those previously identified in New Hampshire, following the same methodology. These correlations broadly suggest that plants and bacteria are co-occurring but the variance in results between the overall dataset and the state-level analyses indicates these relationships are facultative or transient. Using read data to identify co-occurrence correlations is statistically challenging and further experiments sampling pollen bacterial communities with and without pollinator visitation, such as the study by McFrederick et al., are needed to directly test for plant–bacteria associations. Whether plants harbor certain microbes over others or not, there are many factors altering microbial floral communities. Long-term artificial warming of grassland plots was found to alter the microbial communities of plant leaves, including microbial groups common to bees. Aydogan et al. found Acinetobacter and Wolbachia increased in frequency, while Sphingomonas frequency decreased, these three bacterial genera being common to C. calcarata pollen provision and adult gut microbiomes. These temperature based microbial changes could translate into changes in insect microbiomes, and indeed climate has been correlated with changes in microbiome composition in some species such as the red palm weevil, the chestnut weevil and a spider mite. Flower visitation by bees can transfer microbes to flowers, but herbivorous insects, other pollinators including thrips and wind are thought to contribute to microbe dispersal as well. Similarly, the presence of potentially predatory or competitive species such as ants can reduce floral visitation and this in turn alters the microbes present on flowers. Any and all of these could be important factors influencing the observed microbiome variation in C. calcarata and are important considerations when concerned with wild bee health generally. Our study shows that the diet of C. calcarata varies widely with geography, with only Rubus found in more than 1% of reads at all three sites, indicating that this generalist bee species is able to utilize different resources as floral communities change. However, it seems that floral preference may not be simply determined by the proximity of the floral resource to the nest.

The same six bacterial genera consistently dominated provisions in all sites but the relative abundance of these fluctuated widely. There are still many unknowns regarding how microbes are acquired, both in the pollen provisions and subsequently the bees themselves. Flowers appear to be general points of bacterial transmission,but so far specific associations have not been identified. The current lack of knowledge on microbial associates is a major hindrance in our ability to maintain diverse wild bee populations.The fresh market berry industry in Santa Cruz and Monterey counties is an excellent example of transformation in the business of agriculture over the last 50 years. Located along the Central Coast of California, the two counties span the fertile Pajaro and Salinas valleys, and are well known for their amenable climate and production conditions, their diverse crop mix and grower demographics, and their developed agricultural infrastructure and support industries. The majority of the berry sector is comprised of strawberries , raspberries and blackberries , with blueberries and other miscellaneous berries produced on a much more limited basis. Substantial research-based literature and historical information is available for Central Coast strawberries; however, despite the area’s move towards greater production of raspberries and blackberries, less information exists for these crops. We seek here to provide a more complete portrayal and historical context for the berry industry in the Santa Cruz and Monterey area, which is the origin of the berry industry in California. While the berry industry has been very successful in recent decades, it now faces new challenges, such as invasive pests and the phaseout of the soil fumigant methyl bromide. This article draws on previous and more recent research to discuss some of the influences that have contributed to the berry industry’s dramatic expansion in Santa Cruz and Monterey counties, including selected innovations in agricultural practices and heightened consumer demand. Berry industry growth During the 1960s and 1970s, dutch bucket for tomatoes the number of acres planted to berries, tons produced and value of production fluctuated. The fluctuations can be partly explained by farm management: in the past growers often rotated berry and vegetable crops to assist with soil and pest management, thereby influencing these statistics. However, annual crop reports from the county agricultural commissioners show that since the 1980s, berries have become increasingly important to each county’s overall value of production, and by 2014 accounted for 64% and 17% of the total value of all agricultural products in Santa Cruz and Monterey counties, respectively . The industry’s growth can be explained by a shift of some acreage out of tree fruits and field crops , among others, into berries, and by additional acreage put into agricultural production.Strawberries are the undisputed leader in the berry sector and in 2014 represented 58% and 94% of the value of all berry production in Santa Cruz and Monterey counties, respectively , and 50% and 93% of all berry acreage . Table 2 documents the remarkable expansion of the strawberry industry over time in both counties with respect to acreage, tons produced and value of production. Between 1960 and 2014, acreage more than tripled and production increased tenfold. The value of production, in real dollars, increased by 424% in Monterey County and by 593% in Santa Cruz County, reaching an astonishing combined value of nearly $1 billion in both 2010 and 2014. The gains in all statistical categories in Monterey County were enabled in part by an expansion of production into the southern reaches of the county where more and larger blocks of farmland are available, and where land rents are lower than in Santa Cruz and northern Monterey counties.

However, from 2010 to 2014 Monterey County’s tonnage and production values declined, possibly because the area has recently experienced a shortage of labor to harvest fresh market crops. Tonnage was also lower in Santa Cruz County, but production values increased. This may be because of the county’s greater emphasis on local agriculture, organic production and direct market sales, which are often associated with higher crop values. For raspberries, the acreage, tons produced and value of production grew steadily and most strikingly in Santa Cruz County , where production conditions for caneberries are optimal. For example, caneberry fields in Santa Cruz County are situated in areas that have well-drained soils and are protected from damaging winds. Also, fields are planted to take advantage of the growth and yield gains associated with southern exposures. Moreover, field-to-cooler travel distances are shorter in Santa Cruz County, which is critical for safeguarding the quality and marketability of these highly perishable crops. By 2014, raspberries represented 33% of the county’s total value of production for all berries. In contrast, Monterey County raspberry production accounted for only 6% of the county’s total berry value. Blackberries have not been consistently reported as a separate category in archived statistical analyses, but instead were often included under the terms “bush- or miscellaneous berries”. Therefore, similar data for blackberry acreage and value of production cannotbe reported here. However, between 1990 and 2010, Santa Cruz County agricultural commissioner crop reports reported an upward trend for the broad category with respect to acreage planted and value of production . In 2010, blackberries were promoted to a position of prominence in the report and shown as a separate statistic; at the same time, the miscellaneous berry category was shown to be very small indeed. Between 2010 and 2014, however, blackberry acreage and value of production leveled off and have shown only modest gains . This may be because there has been less emphasis on production and market research and promotion for blackberries than for strawberries or raspberries. No comparable data are available for Monterey County. The two counties have contributed significantly to California’s total berry sector: in 2014, area strawberry acreage represented 35% of the statewide total, 37% of the total tons produced and 38% of the total value of production . Area raspberry acreage represented 43% of the statewide total, 42% of the total tons produced and 39% of the total value of production. Comparable statewide statistics are not available for blackberries. County agricultural commissioners’ reports show that the majority of all berries produced in the two counties — up to 98% — are sold as fresh market fruit . In years with adverse production conditions or low prices, a higher percentage of the crop may be diverted to the freezer or processed products market. Fresh market fruit is handled and sold primarily through local grower-shippers; a much smaller share is sold directly to consumers through farmers markets, community supported agriculture operations, farm stands and other direct and intermediated market channels such as restaurants, independent grocers and schools.

It should be noted that results of experiments on young plants, which may be highly susceptible to drought and drought-related mortality due to limited carbon reserves, may not scale directly to large, mature individuals in the field . This study showed high mortality in 2-year-old A. glauca exposed to a fungal pathogen with and without drought, in contrast with field observations of diseased, large adults exhibit severe canopy dieback and are ridden with fungal cankers, yet still survive . Previous studies have yielded similar results: for instance, photosynthesis was shown to be greatly reduced in oak seedlings compared to adults in drought years compared to wet years , and He et al. reported that responses of red maple and paper birch saplings to a 1995 drought were significantly different than those of mature adults. Similarly, since hosts are often able to allocate carbon reserves to compartmentalize canker-causing agents like N. australe within carbon-rich barriers , larger individuals with more biomass and greater carbon stores are able to utilize and direct more resources to defense than younger, smaller individuals. Thus, mature plants can better persist through biotic attack during environmental stress than their younger counterparts and experience various levels of canopy dieback rather than full mortality. Arctostaphylos glauca are obligate seeders, meaning they are killed by fire and must maintain populations by individuals recruiting from seed rather thanresprouting from their base. Therefore, young, small individuals may be of greatest concern for future populations of this species. Because current research is predicting more frequent and extreme drought events , more exotic pathogens , and more frequent fire in these southern California shrublands , hydroponic nft channel populations of A. glauca could decline because small individuals may be highly susceptible to disease and mortality.

A valuable next step for understanding these risks and predicting future shifts in vulnerable chaparral communities would be to monitor young recruiting populations of A. glauca for N. australe for signs of stress, infection, and mortality in the wild.In the face of rapid climate change, it is increasingly important to understand the abiotic and biotic mechanisms driving ecological landscape change. Large plant dieback events can produce major ecological consequences, including changes in vegetation cover , increased fire risk , and changes in hydrology , all of which affect ecosystem structure and functioning . Furthermore, the loss of even a few species can trigger effects on the local food web structure , and increase risk of invasion . The results of this study suggest that small individuals of A. glauca, one of the most common and widespread species the southern California chaparral community, are at high risk of disease and dieback due to opportunistic pathogens and extreme drought. The potential for dieback of Arctostaphylos spp., which provide food for animals such as mice, rabbits, and coyotes and are an important component of post-fire woody regeneration in chaparral, raises concerns regarding changes to ecosystem structure and functioning in the coming decades. Many ecosystems today are facing unprecedented drought ; yet, the interactions of drought and pathogens in wildland settings are difficult to study because the multitude of confounding variables and the challenges of manipulating both the pathogens themselves and climate. Thus, greenhouse studies such as this one are increasingly essential to understand the influences of drought and pathogens as they relate to dieback events, as well as to understand the relationship between stress and shrub/tree ontogeny . Critical questions remain regarding the relative tipping points for large-scale dieback among historically drought-tolerant species such as A. glauca that today are facing the combination of extreme drought and novel pathogens.

These pathogens may not express themselves until there is drought, highlighting the need for broader field surveys and long-term monitoring of wildland ecosystems. An important step to understanding the role of disease in contributing to vegetation change is also to isolate pathogens and test their pathogenicity under varying controlled conditions. This study provides one such step for what appears to now be a widespread, opportunistic introduced pathogen in an important native California chaparral shrub.Extreme drought events from climate change have produced immediate and dramatic effects in recent years, with costs often exceeding $1 billion due to their widespread economic and ecological impacts . Among the ecological consequences is widespread tree mortality, event within plant systems that have historically been considered drought-tolerant . While seasonal droughts are known to be a natural and regular occurrence in arid and semi-arid regions, the increased frequency, duration, and intensity with which they have occurred in recent years is highly unusual . Such extreme droughts, referred to as “global-change type drought” , are predicted to continue, and even become the norm, as a result of human-induced climate change . Consequently, species that are typically capable of withstanding regular drought stress may be susceptible to canopy dieback, and mortality, as a result of shifts in drought regimes . One such plant community that may be vulnerable to extreme climatic change is chaparral. Chaparral shrublands, which occupy approximately 7 million acres throughout California , are a dominant vegetation community in southern California, composed primarily of evergreen, drought tolerant shrubs and subshrub species including manzanita , ceanothus , and chamise . These species are well adapted to the seasonal variations intemperature and precipitation typical of mediterranean climates where hot, rainless summers are the norm . However, mediterranean-type regions like southern California are predicted to experience rapid increases in temperature , and increased drought occurrence and severity ; IPCC, 2013, resulting from human-caused climate change. These regions have thus been designated as worldwide global change “hot spots” .

Indeed, recent studies have reported extensive mortality of chaparral shrub species resulting from global-change type drought throughout southern California . Thus, climate change represents a significant threat to native plant community persistence in this region. A critical topic for ecological research is understanding where, how, and to what extent plant communities will change as a result of increased drought . Studies aimed at understanding the physiological mechanisms behind drought-related plant mortality – and why some plants suffer mortality from drought while others survive – have elucidated a variety of complex mechanisms of plant mortality . These include loss of hydraulic conductance , exhausted carbon reserves , and susceptibility to pests and pathogens due to being in a weakened state from drought . Measuring xylem pressure potential can be a useful index of soil water availability , and dark-adapted fluorescence can be a quick and accurate indicator of plant stress, as values drop significantly in water-stressed plants,. Together, these may be useful tools for predicting plant vulnerabilities to drought and biotic invasion. Landscape variables such as elevation, slope, and aspect have also been shown to correlate with plant water stress and mortality , and can be useful for predicting vulnerabilities during drought. However, major knowledge gaps still remain, and studies combining field mortality patterns with physiological data on plant water stress are rare . Plants employ a variety of complex strategies to cope with drought stress, but generally fall along a continuum of “drought avoiders” or “drought tolerators”. Drought avoidance, also known as “isohydry”, refers to plants that regulate stomatal conductance to maintain high minimum water potentials as soil dries out . While this strategy reduces the risk of xylem cavitation and subsequent hydraulic failure, it may increase the likelihood of carbon starvation, as C assimilation is greatly reduced . Conversely, drought tolerant plants maintain higher Gs, even at very low water potentials, which allows for continued C assimilation but with greater risk of xylem cavitation . These different strategies can have significant implications for ecosystem level consequences of severe drought ; indeed, nft growing system recent studies have linked anisohydry with greater levels of mortality in chaparral systems . An historic drought in southern California provided an opportunity to simultaneously measure physiological stress and dieback severity along an elevational gradient in aclassically drought-tolerant evergreen chaparral shrub, big berry manzanita . A. glauca is one of the largest and most widely-spread members in a genus consisting of nearly 100 species. Its range extends as far north as the Cascade mountains and south into Baja California, though it is most dominant in southern California shrublands . They frequently occur on exposed ridges and rocky outcroppings. In the chaparral shrublands of Santa Barbara County, it occurs from elevations of about 500- 1200m. A. glauca are obligate seeders, and must recruit from the seedbank following fire .

Compared to resprouters, which regenerate from a carbohydrate-rich burl at their base following fire, seeders tend to be fairly shallowrooted , and are thus less able to access deep water sources . Seeders are generally considered to be more tolerant of seasonal drought than resprouters , possibly a mechanism for shallow rooted seedlings to survive summer drought in an open post-fire environment following germination . However, this strategy has also been linked to higher mortality during extreme drought . A. glauca are also known to exhibit anisohydric mechanisms of drought tolerance , and can exhibit extremely low water potentials and high resistance to cavitation during seasonal drought . In 2014, we observed sudden and dramatic dieback in A. glauca in the Santa Ynez mountain range of Santa Barbara, California during an historic drought . The drought that lasted from 2012 to 2018 in southern California was themost severe to hit the region in 1,200 years , with 2014 being the driest year on record . Preliminary field observations indicated greater levels of canopy dieback at lower elevation stands compared to higher elevations. Dieback also seemed to be more prevalent on exposed and southwest-facing slopes, which in this region experience direct sunlight for most of the day. Other studies have reported significant Arctostaphylos spp. dieback and even mortality during periods of extreme drought stress, further suggesting species in this genus are vulnerable to drought-related mortality. Additionally, we observed widespread symptoms of fungal infection – including branch cankers and brown/black leaf discoloration – later identified as members of the opportunistic Botryosphaeriaceae family , suggesting multiple factors may be driving canopy dieback in this species. Drought-related mortality has previously been associated with opportunistic fungal pathogens in A. glauca and other chaparral shrubs , yet few studies have sought to understand the relative levels of drought stress incurred by plants infected with these pathogens, or how stress is related to canopy dieback and/or mortality. A. glauca shrubs are important members of the chaparral ecosystem, providing habitat and food for wildlife through their nectar and berries . Their structure and fire-induced germination strategies also make them significant components of the chaparral fire regime and post-fire successional trajectories . Large-scale mortality of this species could reduce resource availability for wildlife, as well as alter fuel composition and structure in the region, resulting in an increased risk of more intense, faster burning fires. Therefore, the potential continued dieback of A. glauca is of great concern for both ecosystem functioning and human populations alike. Yet because of the heterogeneity of landscapes in this rugged region, it is possible that portions of the landscape will act as refugia for drought-susceptible species. We hypothesized that A. glauca dieback severity is associated with areas of increased water stress across the landscape. To better understand the patterns and trajectory of A. glauca stress and dieback across a topographically diverse region of coastal California, we asked the following specific questions: How severe is drought-related stress and dieback in this region? How do plant stress and dieback severity vary with elevation and aspect across the landscape? How does dieback change across the landscape as a multi-year drought progresses? We chose xylem pressure potential as an indicator of plant water availability, and measured dark-adapted fluorescence and net photosynthesis as proxies for drought-related plant stress and physiological function. To address Question 1, we conducted an initial survey measuring general levels of canopy dieback, shrub water availability, and stress in the region. To address Questions 2 and 3, we conducted a more in-depth study of how shrub water relations and dieback vary with aspect and along an elevational gradient, and tracked changes in dieback severity for the four final years of the seven-year drought. We expected to find areas of low XPP correlated with greater physiological stress responses, and more severe dieback in lower elevation sites and on southwest aspects.

The area selected should be readily accessible to farm equipment for site preparation and maintenance. The site should not disrupt normal farming operations or be in an area that could be easily overlooked and accidentally disked or sprayed. In addition, the site should be well drained to prevent ponding of water or plant die back.To prepare the area selected for a vegetated ditch, disk and shape the land to carry water and prepare a normal seedbed. Grasses should be planted in the fall when establishment is favored by cool weather and subsequent winter rains. After the seedbed is prepared, allow the winter rains to bring up the first flush of winter weeds. These should be either sprayed with Roundup or disked. The grasses should then be direct-seeded with a grain drill at 15 pounds per acre by late fall. They can also be broadcast at 20 to 25 pounds per acre and incorporated with a chain harrow followed by rolling. Buctril , MCPA , or 2,4-D can be used to control broad leaf weeds once the grasses have established and have been allowed to grow at least 3 to 4 inches tall to avoid injury to newly emerged seedlings. Be sure to contact the local agricultural commissioner for restrictions on the use of herbicides. For example, the phenoxys MCPA and 2,4-D cannot be used after March 1 in many counties. Once the grasses are established, they will compete well with weeds, requiring only occasional use of herbicides, hand weeding, or mowing.Since most of the sedimentation or particle retention occurs at the beginning of the filter strip, this area should be closely monitored, round pot for plants and excess sediment should be removed to keep water from diverting to new and easier drainage routes or channels. This may involve reestablishing the grasses by over seeding the area to ensure that a sheetlike flow is maintained as the water comes off farm fields.

Gophers and ground squirrels should be controlled and repairs made where channelization of water occurs. Irrigation runoff should supply the water needs of the vegetation in the ditches. Grasses may need to be mowed occasionally to prevent thatch from building up and to deter weeds. If the vegetated drain is grazed, the animals should be watched to prevent overgrazing and stand loss, especially on wet soils. Plant tissue testing may also be needed to ensure that nutrients concentrated in the filter strips have not built up to unhealthy levels for the animals.One method promoted for improving surface water quality runoff from furrow-irrigated agricultural fields is to apply a polyacrylamide to the irrigation water. PAM stabilizes the soil to minimize erosion and promotes the settling of suspended particles. PAM comes in tablet, granular, and liquid formulations. By itself, PAM is not toxic to aquatic life; however, the carriers in oil-based PAM can be toxic to aquatic life at recommended field application rates. For this reason, water-based formulations are recommended . In research trials conducted by the authors at the University of California, Davis, liquid PAM in a loam soil significantly reduced suspended sediment concentrations compared with a control of untreated water in surface runoff at PAM concentrations of 2.1 ppm and 7 ppm in the source irrigation water . Similar behavior occurred in a clay loam soil at a second field site at California State University, Chico, with a PAM concentration of 1.1 ppm. Terminating the liquid PAM injection once the water reaches the end of the furrows can be as effective as continuous PAM dosing, but this effect may depend on soil texture.Studies on tablet and granular PAM at Davis and Chico showed a similar response to the liquid PAM, with significant reductions in suspended sediment concentrations compared to untreated water . However, proper placement of dry PAM in the furrows was critical for efficacy. In studies in Idaho conducted by the USDA, dry PAM placed at the head of the furrow was effective.

However, at Davis and Chico similar placement of dry PAM at the furrow head resulted in the material being quickly covered by eroded sediment during irrigation, and the PAM lost its efficacy. In contrast, dry PAM material placed 100 to 300 feet down the field was not covered by sediment and was effective in reducing the sediment concentrations. Proper placement of dry PAM is particularly important for gated pipe systems, where water discharged from gates may cause considerable erosion at the head of the furrow. One way to lesson this erosion is to place irrigation socks over the gates. PAM applications had no effect on irrigation water infiltration rates for the soil types evaluated in the Sacramento Valley, whereas infiltration increased with the addition of PAM in an Idaho study .The cost of applying PAM depends on how it is applied to the field. The cost of dry PAM formulations placed in the furrows depends on the material cost, the furrow spacing, and the number of tablets per furrow. PAM application rates are based on recommended rates for each type of PAM material . The smaller the row spacing , the larger the cost will be for a given acreage. Whether to apply dry PAM directly into the irrigation water or use liquid PAM depends on the target PAM concentration in the irrigation water, the material cost, the flow rate of water into the field, and the injection time. Table 4 shows cost comparisons using different rates and formulations of PAM on an 80-acre furrow-irrigated row crop planted on 5-foot beds using data provided by a grower. Costs per acre are based on the total field acreage . In this field example, the time for the water to reach the end of 1,200-foot furrows is 12 hours; there are four irrigation sets ; a flow rate of 1,320 gallons per minute; and a furrow flow rate of 11 gallons per minute.

The lowest cost occurred for granules placed in the furrow, while the highest cost was for using liquid PAM. The high cost of liquid PAM reflected the cost of the material and the long injection time. Terminating the injection before complete advance to the end of the furrow would reduce the cost per acre but may increase sediment levels. While the cost per acre of applying liquid PAM in irrigation water is higher than the cost of dry PAM formulations, especially at a concentration of 5 ppm , our studies at Chico and Davis showed PAM concentrations of 1 to 2 ppm in the irrigation water to be effective in reducing the sediment load on loam and clay loam soils. As a result, growers should experiment with liquid PAM application rates to determine what works best on their farms, since the efficacy depends on sediment loads as affected by factors such as soil type and irrigation flow rates. The differences in field responses to PAM may be why the NRCS recommends a higher concentration of 10 ppm in irrigation water to reduce sediment loads in surface irrigation runoff; this rate should cover most sediment loads, but it would not be economical.Groundwater is an important water supply for more than two billion people around the world . It also provides more than 40% of the irrigation supply for global agricultural production on approximately 500 million ha of cropland . Given such intense use, it is not surprising that depletion of the resource is occurring in many parts of the world including the United States and California . Excessive groundwater extraction can decrease water levels, reduce surface-water flows, cause seawater intrusion, spread contaminants, and cause land subsidence . Sustainable resource management requires a combination of reduced extraction and increased recharge . Some reduced extraction may occur by increasing water use efficiency ; however, large round pot pronounced rates of extraction in many areas will likely necessitate modifying cropping patterns and fallowing cropland to address problems from over-pumping . Such changes will cause economic distress and likely bring political resistance. While avoiding strong measures to correct groundwater budget imbalances may not be possible, disruption might be reduced by increasing recharge where possible. Elements for successful artificial recharge projects have been reviewed in detail and may be programmatic or site-specific. Programmatic elements include sourcing, conveyance and placement of recharge water. Sources of recharge water may include urban storm water runoff and recycled water as wellas, notwithstanding water rights and permitting considerations , stormflows from streams and releases from reoperated surface-water reservoirs. Considerations include access to either existing canals and ditches, or the land required to construct these structures, as well as routing and capacity specifications. Options for placing water in recharge facilities range from constructing dedicated basins to repurposing existing gravel pits.

The recharge water could also be released to lands primarily used for other purposes but available on a seasonal basis such as sandy-bottomed drainage features, unlined canals and ditches, or croplands. Site-specific details include: location relative to conveyance and favorable hydrogeology, topography of the ground surface and presence of existing berms, type of irrigation technology present, timing of site availability relative to water available for recharge and cost to use the land under purchase, rent or option arrangements. Site-specific details regarding favorable hydrogeology directly relate to characteristics of the groundwater basin under consideration. Spatial variability of infiltration capacity is heavily influenced by the hydraulic conductivities of the soil and shallow geology as well as interconnectedness of higher hydraulic conductivity deposits at depth . Groundwater storage space is determined by the unsaturated zone thickness and its variations across the basin. The fate of recharged water over time relative to the recharge location can also be important . Recharge at some locations may offset local pumping and increase groundwater storage. At other locations, water entering the subsurface can quickly discharge from the groundwater system to surface water or flow across basin boundaries that are based on governance rather than physical characteristics. Data on the performance of managed aquifer recharge on croplands is limited and largely focuses on California and western USA. Dokoozlian et al. conducted a four-year pilot study flooding vineyards in the San Joaquin Valley of California during seasonal grapevine dormancy, observed no impact on crop yield, and concluded that the approach was viable for MAR. Bachand et al. performed a single-season pilot study for on-farm flood flow capture and recharge, also in the San Joaquin Valley, with both perennial and annual crops. They observed no impacts to crop yield and estimated the unit cost for the on-farm recharge as ~3–30 times cheaper than surface-water storage or dedicated recharge basins. Dahlke et al. investigated effects of winter flooding on established alfalfa fields at two locations in the Sacramento Valley of California and found that significant amounts of water could be applied without decreasing crop yield. Additional unpublished studies indicate that almonds may tolerate at least 2 ft of cumulative applied recharge water in a season without detrimental effects and some grapes have shown little to no productivity decline after more than 20 ft of recharge in one season . Some analysis on scaling up on-farm recharge for larger scale groundwater management has also occurred. Harter and Dahlke discussed the potential for on-farm recharge projects to improve conditions in California where groundwater has been stressed by overuse and drought. O’Geen et al. considered requirements for successful projects and presented a spatially explicit soil-agricultural-ground water banking index for recharge project suitability on agricultural lands in California. Niswonger et al. examined potential benefits from on-farm MAR for a hypothetical groundwater sub-basin in the semi-arid western USA. They developed an integrated surface-water diversion and subsurface flow model to simulate recharge operations and benefits to the groundwater system over a 24-year period. Scenarios considered recharge water from snowmelt in excess of water rights during wet years applied to croplands during two winter months each year. Among other points, the work concluded that increases in groundwater storage from AgMAR operations were spatially related to variations in groundwater depth and withdrawals across a basin as well as proximity to natural discharge areas and supported greater pumping supplies for agriculture. This work addresses planning-level analysis of Ag-MAR using water from reservoir reoperation for periodic flooding of croplands during winter months.

An additional advantage of this strategy is that exogenous ACE2 would compensate for lower ACE2 levels in the lungs during infection, thereby contributing to the treatment of acute respiratory distress. Several companies in the United States and the EU have developed recombinant ACE2 and ACE2-Fc fusion proteins for preclinical and clinical testing, although all these products are currently produced in mammalian cell lines . The impact of plant-specific complex glycans on the ability of ACE2-Fc to bind the RBD has been studied using molecular dynamic simulations and illustrates the important role that glycosylation may play in the interaction between the S protein and ACE2 .Griffithsin is a lectin that binds high-mannose glycans, and is currently undergoing clinical development as an antiviral against HIV-1. However, it also binds many other viruses that are pathogenic in humans, including HSV , HCV , Nipah virus , Ebola virus, and coronaviruses including SARS-CoV and MERS , and as recently determined, also SARSCoV-2. A clinical product in development by University of Louisville is currently manufactured in N. benthamiana by Kentucky Bioprocessing using a TMV vector. The API is also undergoing preclinical development as a nasal spray for use as a non-vaccine prophylactic against coronaviruses, with clinical evaluation planned for 2020 . This candidate PMP antiviral could be deployed under the EUA pathway if found effective in controlled clinical studies. Griffithsin is an interesting example of a product that is ideally matched to plant-based manufacturing because it is naturally produced by a marine alga. Griffithsin has been expressed with limited success in E. coli and tobacco chloroplasts, black plastic garden pots but better results have been achieved by transient expression in N. benthamiana using A. tumefaciens infiltration or TMV vectors, with expression levels of up to 1 g kg−1 fresh mass and recoveries of up to 90% .

A TEA model of griffithsin manufactured in plants at initial commercial launch volumes for use in HIV microbicides revealed that process was readily scalable and could provide the needed market volumes of the lectin within an acceptable range of costs, even for cost-constrained markets . The manufacturing process was also assessed for environmental, health, and safety impact and found to have a highly favorable environmental output index with negligible risks to health and safety.In addition to COVID-19 PCR tests, which detect the presence of SARS-CoV-2 RNA, there is a critical need for protein-based diagnostic reagents that test for the presence of viral proteins and thus report a current infection, as well as serological testing for SARS-CoV-2 antibodies that would indicate prior exposure, recovery, and possibly protection from subsequent infection. The most common formats for these tests are the ELISA and lateral flow assay. The design and quality of the binding reagents , along with other test conditions such as sample quality, play a key role in establishing the test specificity and selectivity, which determine the proportion of false positive and false negative results. Although the recombinant protein mass needed for diagnostic testing is relatively small , the number of tests needed for the global population is massive, given that many individuals will need multiple and/or frequent tests. For example, 8 billion tests would require a total of ~2.5 kg purified recombinant protein, which is not an insurmountable target. However, although the production of soluble trimeric full-length S protein by transient transfection in HEK293 cells has been improved by process optimization, current titers are only ~5 mg L−1 after 92 h . Given a theoretical recovery of 50% during purification, a fermentation volume of 1,000 m3 would be required to meet the demand for 2.5 kg of this product. Furthermore, to our knowledge, the transient transfection of mammalian cells has only been scaled up to ~0.1 m3 .

The transient expression of such protein-based diagnostic reagents in plants could increase productivity while offering lower costs and more flexibility to meet fluctuating demands or the need for variant products. Furthermore, diagnostic reagents can include purification tags with no safety restrictions, and quality criteria are less stringent compared to an injectable vaccine or therapeutic. Several companies have risen to the challenge of producing such reagents in plants, including Diamante , Leaf Expression Systems , and a collaborative venture between PlantForm, Cape Bio Pharms, Inno-3B, and Microbix.Resilience is the state of preparedness of a system, defining its ability to withstand unexpected, disastrous events , and to preserve critical functionality while responding quickly so that normal functionality can be restored . The concept was popularized by the 2011 Fukushima nuclear accident but received little attention in the pharmaceutical sector until COVID-19. Of the 277 publications retrieved from the National Library of Medicine22 on July 9th 2020 using the search terms “resilience” and “pandemic,” 82 were evenly distributed between 2002 and 2019 and 195 were published between January and July 2020. Resilience can be analyzed by defining up to five stages of a resilient system under stress, namely prevent , prepare, protect, respond, and recover . Here, prevent includes all measures to avoid the problem all together. In the context of COVID-19, this may have involved the banning of bush meat from markets in densely populated areas . The prepare stage summarizes activities that build capacities to protect a system and pre-empt a disruptive event. In a pandemic scenario, this can include stockpiling personal protective equipment but also ensuring the availability of rapid-response bio-pharmaceutical manufacturing capacity. The protect and respond stages involve measures that limit the loss of system functionality and minimize the time until it starts to recover, respectively. In terms of a disease outbreak, the former can consist of quarantining infected persons, especially in the healthcare sector, to avoid super-spreaders and maintain healthcare system operability .

The response measures may include passive strategies such as the adjustment of legislation, including social distancing and public testing regimes, or active steps such as the development of vaccines and therapeutics . Finally, the recover phase is characterized by regained functionality, for example by reducing the protect and response measures that limit system functionality, such as production lockdown. Ultimately, this can result in an increased overall system functionality at the end of a resilience cycle and before the start of the next “iteration” . For example, a system such as society can be better prepared for a pandemic situation due to increased pharmaceutical production capacity or platforms like plants. From our perspective, the production of recombinant proteins in plants could support the engineering of increased resilience primarily during the prepare and respond stages and, to a lesser extent, during the prevent and recover stages . During the prepare stage, it is important to build sufficient global production capacity for recombinant proteins to mount a rapid and scalable response to a pandemic. These capacities can then be used during the response stage to produce appropriate quantities of recombinant protein for diagnostic , prophylactic , or therapeutic purposes as discussed above. The speed of the plant system will reduce the time taken to launch the response and recovery stages, and the higher the production capacity, square plastic plant pots the more system functionality can be maintained. The same capacities can also be used for the large-scale production of vaccines in transgenic plants if the corresponding pathogen has conserved antigens. This would support the prevent stage by ensuring a large portion of the global population can be supplied with safe and low-cost vaccines, for example, to avoid recurrent outbreaks of the disease. Similarly, existing agricultural capacities may be re-directed to pharmaceutical production as recently discussed . There will be indirect benefits during the recover phase because the speed of plant-based production systems will allow the earlier implementation of measures that bring system functionality back to normal, or at least to a “new or next normal.” Therefore, we conclude that plant-based production systems can contribute substantially to the resilience of public healthcare systems in the context of an emergency pandemic.The cost of pharmaceuticals is increasing in the United States at the global rate of inflation, and a large part of the world’s population cannot afford the cost of medicines produced in developed nations . Technical advances that reduce the costs of production and help to ensure that medicines remain accessible, especially to developing nations, are, therefore, welcome. Healthcare in the developing world is tied directly to social and political will, or the extent of government engagement in the execution of healthcare agendas and policies . Specifically, community-based bodies are the primary enforcers of government programs and policies to improve the health of the local population . Planning for the expansion of a bio-pharmaceutical manufacturing program to ensure that sufficient product will be available to satisfy the projected market demand should ideally begin during the early stages of product development.

Efficient planning facilitates reductions in the cost and time of the overall development process to shorten the time to market, enabling faster recouping of the R&D investment and subsequent profitability. In addition to the cost of the API, the final product form , the length and complexity of the clinical program for any given indication , and the course of therapy have a major impact on cost. The cost of a pharmaceutical product, therefore, depends on multiple economic factors that ultimately shape how a product’s sales price is determined . Plant-based systems offer several options in terms of equipment and the scheduling of upstream production and DSP, including their integration and synchronization . Early process analysis is necessary to translate R&D methods into manufacturing processes . The efficiency of this translation has a substantial impact on costs, particularly if processes are frozen during early clinical development and must be changed at a subsequent stage. Process-dependent costs begin with production of the API. The manufacturing costs for PMPs are determined by upstream production and downstream recovery and purification costs. The cost of bio-pharmaceutical manufacturing depends mostly on protein accumulation levels, the overall process yield, and the production scale. Techno-economic assessment models for the manufacture of bio-pharmaceuticals are rarely presented in detail, but analysis of the small number of available PMP studies has shown that the production of bio-pharmaceuticals in plants can be economically more attractive than in other platforms . A simplified TEA model was recently proposed for the manufacture of mAbs using different systems, and this can be applied to any production platform, at least in principle, by focusing on the universal factors that determine the cost and efficiency of bulk drug manufacturing .Minimal processing may be sufficient for oral vaccines and some environmental detection applications and can thus help to limit process development time and production costs . However, most APIs produced in plants are subject to the same stringent regulation as other biologics, even in an emergency pandemic scenario . It is, therefore, important to balance production costs with potential delays in approval that can result from the use of certain process steps or techniques. For example, flocculants can reduce consumables costs during clarification by 50% , but the flocculants that have been tested are not yet approved for use in pharmaceutical manufacturing. Similarly, elastin-like peptides and other fusion tags can reduce the number of unit operations in a purification process, streamlining development and production, but only a few are approved for clinical applications . At an early pandemic response stage, speed is likely to be more important than cost, and production will, therefore, rely on well characterized unit operations that avoid the need for process additives such as flocculants. Single-use equipment is also likely to be favored under these circumstances, because although more expensive than permanent stainless-steel equipment, it is also more flexible and there is no need for cleaning or cleaning validation between batches or campaigns, allowing rapid switching to new product variants if required. As the situation matures , a shift toward cost-saving operations and multi-use equipment would be more beneficial.An important question is whether current countermeasure production capacity is sufficient to meet the needs for COVID-19 therapeutics, vaccines, and diagnostics. For example, a recent report from the Duke Margolis Center for Health Policy24 estimated that ~22 million doses of therapeutic mAbs would be required to meet demand in the United States alone , assuming one dose per patient and using rates of infection estimated in June 2020. The current demand for non-COVID-19 mAbs in the United States is >50 million doses per year27, so COVID-19 has triggered a 44% increase in demand in terms of doses.

Nearly half of the farmers expressed they were at a big turning point in their personal lives when they decided to farm full time. For example, these farmers had either moved across the country to an unfamiliar place, had quit their office job, and/or had lost an important family member or their childhood home.Farmers interviewed possess embedded knowledge, which is knowledge that comes from living on the land and observing natural processes . To situate this type of knowledge in this particular place , the farmers described their relationship to the land they farmed. Not surprisingly, many of the farmers initially responded with personifications of their land . Initial responses also spoke to farmer perception of their role within the land as well as an expression of romanticism for their land . Among farmers who owned most of the land that they farmed , there was a distinct lack of reference to land ownership; these farmers described their relationship both as a responsibility and as part of a larger human inheritance.All farmers interviewed mentioned direct experience as being one of the most important modes for understanding their landscape, their farming system, and management practices essential to their farm operation. The farmers described this accumulation of experience as “learning by doing,” being “self-taught,” or learning by “trial and error” . These farmers added that in learning by experience, they made “a lot of mistakes” and/or faced “many failures” but also learned from these mistakes and failures – and importantly, that this cycle was crucial to their chosen learning process.

More than half of the farmers interviewed maintained that no guidebook or manual for farming exists; while reading books was viewed as valuable and worked to enhance learning for individual farmers, to farm required knowledge that could only be gained through experience.Moreover, square pots plastic nearly all the farmers also explicitly commented on the fact that they have never stopped learning to farm . Overall, farmers in this study learned primarily through personal experience and over time, making connections and larger conclusions from these experiences. On-farm experimentation was a critical component of knowledge building as well. Experimentation consisted of methodical trials that farmers implemented at small scales on their farms, and most often directly on a small portion of their fields. Experimentation was often incited by observation , a desire to learn or to increase alignment with their own values, or a need to pivot in order to adapt to external changes. The farmers experimented to test the feasibility of implementing specific incremental changes to their current farming practices before applying these changes across their entire farm. For example, one farmer relied exclusively on trucking in urban green waste compost as part of the farm’s fertility program when she first started farming. However, one year, she decided to allow chickens to roam in a few of the fields; within a few years, those fields were outproducing any other field on her farm in terms of crop yield. She quickly transitioned the entire farm away from importing green waste compost to rotating chickens on a systematic schedule throughout all fields on her farm. This form of experimentation allowed this farmer to move from relying on external inputs for fertility to cycling existing resources within the farm and creating an internally regulated farming system . For this farmer, this small experiment was monumental and shifted her entire farm toward a management system that was more in alignment with her personal farming values.

As she described, “When you look at everything on the farm from a communal perspective and apply that concept of community to everything on the farm . . . it literally applies to every aspect of your life too.”Though this farmer had initially used direct observation to implement raised beds on his farm, as he learned the purpose of raised beds through his own direct experience, he slowly realized – over the course of decades – that raised beds served no purpose for his application. One year, he decided not to shape some of his beds. At the end of the season, he evaluated no real impact on his ability to cultivate or irrigate the row crops on flat ground, and no impact on yield or crop health. In fact, he observed less soil compaction and more aeration due to fewer passes with heavy machinery; and, he saved time and fuel. The transition to farm on flat ground took several seasons for this farmer, but over time, his entire farm operation no longer used raised beds to grow row crops. This breakthrough in farming for this particular farmer was informed by personal experience and guided by careful experimentation.Second to experience, observation also influenced the farmer learning process. Whereas direct experience is usually immersive, and embedded within a larger social context, observation is a detached, mechanical form of knowledge production, where a farmer registers what they perceive to transpire . For example, farmers cited observing other farmers in a multitude of ways: “By watching other farmers, I really mean I’d just drive around and look. I’d see what tools they were using;” or “If I saw someone working in the field, I would stop my car on the side of the road to see what people are doing;” or “I really would just observe my father farm,”) as well as making observations about the status of their land . Several of the farmers summed up their cycle of learning as a cycle of observation, trial, feedback, observation, trial, feedback, etc . The farmers frequently mentioned fellow farmers as a source of learning as well. However, several of the farmers clarified that this type of learning did not necessarily involve talking to fellow farmers. One farmer shared that he learned certain farming practices from a neighbor farmer through distant observation and then borrowed ideas he subsequently applied on his farm; to achieve this, he admitted that he had never really talked to the other farmer directly.

Another farmer noted that he would “go back at night if they [another farmer] left their equipment in the field and just study how it was set up, so I [he] could see what was going on.” Based on interviews with other farmers, farmer-to-farmer knowledge exchange often consisted of detached observation rather than personal conversation or direct contact with another farmer.During the initial field visit, the farmers shared their definitions of soil health. Across all farmers interviewed , responses appeared mechanical and resembled language disseminated by government entities such as the Natural Resources Conservation Service . As such, most responses emphasized building soil organic matter, promoting biological activity, maximizing diversity, and minimizing soil disturbance. During the in-depth interview, farmers shared specific indicators used to evaluate soil health on their farms. These responses were varied compared to definitions of soil health and were generally based on observation and personal experience. Generally speaking, the farmers relied heavily on their crops and on the health of their crops to inform them about the basic health of their soil. In fact, the farmers cited using their crop as their foremost indicator for gauging optimum soil health. One farmer shared, “Mostly, I’m looking at the plants, if the color of green on a particular leaf goes from shiny to matte, plastic grow pots or slightly gray undertone to it. These subtle cues, I pick up from just looking at my crops.” The growth habit of weeds within and around fields was also cited as an indicator of soil health. For example, one farmer explained, “I’m looking at how the weeds are growing at the edges of the field; in the middle of the field. Is there a difference between what’s happening around the edges and what’s happening in the field?” Some farmers also frequently relied on cover crops as indicators for determining soil health and soil behavior. When acquiring new fields, for example, the farmers tended to first grow cover crops to establish a baseline for soil health and also understand soil behavior and/or soil type. The farmers also used cover crop growth habits to gauge the status of soil health and soil fertility for a particular field before planting the next iteration of crops. As one farmer elaborated, “I’m judging a field based on how a cover crop grows. It’s one thing if you’re planting a nutrient-intensive crop in a field, but if you have a cover crop in the field and there’s a swath that’s this tall and another swatch that’s only this short, then you know there’s something seriously different about that section of field and the soil there.”In addition to crop health and cover crop growth patterns, the farmers used other biological and physical indicators to determine the health of their soils. Presence of “soil life,” including earthworms, arthropods, fungi, was used as a key biological indicator of soil health by most farmers . For most of the farmers, this was often both a visual and tactile experience, as one farmer described, “Being able to pick up a bunch of soil and see the life in it.

If I can see earthworms, if I can see arthropods, if I can see lots of fungus, then I know that’s pretty good soil, that that’s working well.” Soil structure and soil crumble were also flagged as good physical indicators of soil health by more than half of the farmers . Farmers interviewed determined soil structure in a variety of ways, which included: 1) observing soil behavior while on the tractor; 2) touching soil directly, by hand; 3) digging a small hole to observe its vertical profile; or 4) observing how water drains in a field following rain or irrigation. A majority of the farmers explicitly stated that they did not rely on soil tests to provide information regarding the health or status of their soils; only a handful of the farmers communicated that they actively used soil tests. The farmers who did not use soil tests noted that commercially available soil tests were often inaccurate, not calibrated to their scale and/or type of operation, lacked enough data points to be useful, and/or did not provide any additional information that they were not able to already readily observe day-to-day or long term on the farm.The organic farmers in Yolo County that were interviewed for this study demonstrated wide and deep knowledge of their soil and farming systems. Results show that white, first- and second-generation farmers that farm alternatively accumulate substantive local knowledge of their farming systems – even within a decade or two of farming. These particular organic farmers demonstrated a complex understanding of their physical environments, soil ecosystems, and local contexts that expands and complements other knowledge bases that inform farming systems. While the content and application of farmer knowledge may be locally specific , below we consider aspects of this case study that may be more broadly applicable. First, we discuss emergent mechanisms for farmer knowledge formation using existing frameworks in the social-ecological systems literature, and also summarize key features of farmer knowledge that coalesced from the results of this study.To further examine how farmers in this study acquire and incorporate their knowledge within their farm operation, we first explore emergent mechanisms that underpin farmer knowledge formation. Because farmer knowledge encompasses knowledge of both social and ecological systems – and the interactions thereof – it is useful to draw upon existing frameworks from the social-ecological systems literature in order to trace the process of farmer knowledge formation among farmers in our case study. Briefly, social-ecological systems recognize the importance of linking social and ecological processes to capture interactions between humans and the environment; importantly, existing literature within SES studies also emphasizes the interactive and adaptive feedback among social and ecological processes that link social and ecological system dynamics . Boons offers a conceptual guide for identifying social-ecological mechanisms, which adapted to our case study provides a starting point for tracing aspects of farmer knowledge formation. Here, social-ecological mechanisms for farmer knowledge formation refer to – on the one hand, social and cultural phenomena that influence farmer knowledge and their personal values – on the other, farmers’ observations of and experiences with environmental conditions and ecological processes on their farms that influence their knowledge and their values – and the interactions thereof .

Later in the essay, I model the evolution of crop-based knowledge and its application to other crops explicitly. New ideas generated from growing one crop benefit farm operators in producing other crops as well. The more crops have in common, the more benefit farmers obtain from applying knowledge across crops. If knowledge evolves independently across crops, producers are less likely to master the production of a large number of crops. For example, if learning about almond production is independent of learning about strawberry production, the probability that a farmer is knowledgeable about both is small. So, learning will lead to specialization. Specialization can also be manifested as focusing on a subset of crops that are similar in agronomic characteristics because farmers can apply knowledge across these crops. Following the same reasoning, this model has implications for the number of farms. Assuming there is a minimum acreage required for each crop to establish production, farmers will exit production if their optimal land demand is smaller than the crop-specific threshold. A faster learning process results in a larger variation in productivity because farmers have a larger probability to increase their knowledge. If we consider the number of farms that produce a specific crop, a larger variation in productivity means that there are more farms exited from production due to lack of knowledge. If the demand of a crop is fixed or increases more slowly than the evolution of knowledge, more farms will exit and the number of farms will decrease. The model and implications are presented in section 2. Numerical simulations illustrating the effect of demand- and supply-side factors on the equilibrium path of farm structure are included in section 3 and section 4 concludes.Hens housed in conventional cage systems produce the majority of eggs worldwide, square plant pots however in recent years many countries have shifted to alternative production systems, such as cage-free aviaries .

Conventional cages house small groups of about 6-7 hens in cages with about 67-86 square inches of space per bird . Cage-free aviaries, on the other hand, house hens in large flocks with approximately 144 square inches of space per hen . The shift away from conventional cages is due to increasing consumer preference for cage-free eggs, resulting from consumers’ concerns about the welfare of laying hens housed in conventional cages . Consumers perceive hens from cage-free systems to have enhanced welfare when compared to hens in conventional cages, despite many consumers being unaware of the meaning behind egg labels or the differences between different production systems . This public perception has also coincided with several states passing legislation that aims to phase out the use of conventional cages. California’s Proposition 12 mandates that all eggs produced and sold in California are cage-free by 2022. Similar legislation has followed, including bills passed in Colorado , Michigan , Oregon , and Washington . Cage-free systems have numerous welfare benefits when compared to conventional cages, including the opportunity to perform natural behaviors such as wing flapping, dust bathing, perching, and flying . However, cage-free systems also come with drawbacks. Adult hens housed in commercial aviaries are prone to injuries including keel bonefractures, which may occur during collisions with tiers, perches, and other features of the aviary . There is a great need to determine why collisions are so common in cage-free aviary systems and what management solutions can be implemented to reduce injuries in cage-free flocks. Young hens, or pullets, are housed in a rearing system for the first 15 to 18 weeks of life before being moved to their adult laying system. The complexity of the pullet rearing environment and early access to vertical space has been shown to play a role in reducing keel bone fracture prevalence in adult hens .

Gunnarsson et al. proposed that rearing chicks on the floor, without access to perches or platforms, impairs the development of spatial cognition. One possibility is that this impairment to spatial cognition could contribute to failed landings and navigation of commercial aviaries, increasing the incidents of fractures. Many studies since Gunnarsson et al. have continued to provide evidence that the complexity of rearing environment influences performance on spatial cognition tasks . However, none of these studies have specifically looked at the development of depth perception and its potential relation with early exposure to vertical space. A deficit in precision of depth perception could explain the occurrence of failed landings and falls, due to an inability to properly gauge the distance to fly or jump.The visual cliff has been used for the evaluation of depth perception and differential visual depth threshold since its invention by Walk et al. in 1957. It utilizes two depths, a shallow side and a deep side, and can be adapted for a variety of species. The subject is placed between the shallow and deep side, in the center of the table. The shallow side is typically level or about a few centimeters below the starting point of the subject, however, the bottom of the deep side is far below the subject. The deep side is covered with a sheet of plexiglass so the subject can perceive this depth but, unbeknownst to the subject, is not in danger of falling. Many designs employ the use of checkerboard patterns to provide visual perspective, allowing for an easy determination of depth. The behavior of the subject is recorded to determine their ability to differentiate the depths and avoid “falling down” the perceptual precipice created by the deep side of the visual cliff.

The visual cliff is a widely used test of depth perception that has the advantage of involving a clear, straightforward choice: Does the animal move to the shallow or deep side? The test is not physically challenging for the subject and there is no training required. Therefore, many animals can be tested and there are no confounding variables of learning or physical ability. Despite these advantages, the visual cliff is not free of flaws. The plexiglass over the “deep side” of the cliff can provide tactile information about the presence of a barrier if the subject comes in contact with the surface. There is also a potential for reflection on the plexiglass, giving a visual indicator of an additional surface over the “deep side.” If the subject can detect the plexiglass barrier through either visual or tactile information, the illusion of a cliff ceases and the test no longer compares the subjects’ reaction to differential depths. Using the visual cliff paradigm, garden pots square chickens have been found to have excellent depth perception, preferring the shallow side of a visual cliff significantly more than the deep side from as early as one day of age . Additionally, four day old chicks readily jump down a drop off of less than 10 inches to join their companions but hesitate if the drop is more than 16 inches . Chicks demonstrate a 2 inch threshold for differential visual depth, meaning, chicks perceive a difference in depth only when the discrepancy is 2 or more inches . Unlike humans, chickens do not require binocular vision, or stereopsis, to perceive depth. Chicks with monocular vision are able to perceive depth as well as their binocular counterparts, with both groups choosing the shallow over the deep side of the visual cliff significantly more . Although all birds have binocular vision, there is no evidence that birds other than certain birds of prey use stereopsis to acquire information on relative depth . Instead, birds use monocular cues such as motion parallax and interposition to judge relative depth . Walk and Gibson provided evidence that the ability to perceive depth is innate in multiple species. However, certain factors during development, such as light and monocular deprivation, can cause impairments in depth perception . This raises an interesting question: can other differences in visual experience, such as reduced experience with height and depth, alter depth perception abilities?The relationship between spatial cognition and rearing environment in laying hens has been evaluated in previous studies using a variety of tests including the jump test, hole board task, radial maze, and detour paradigm. In order to better understand these tests, the definition of spatial cognition must be addressed. Spatial cognition is defined as a multifaceted topic entailing the perception, processing, and interpretation of objects, space, and movement . Spatial cognition encompasses many different aspects of visual perception such as spatial memory and navigation, determining the orientation of objects, and perceiving depth . Despite this diverse array of topics under this broad term, many researchers outside the field of cognition discuss spatial cognition without specifying which aspect they are investigating. By failing to properly define terms or control for a precise aspect of spatial cognition, researchers can inadvertently measure unintended variables and make inaccurate conclusions. Over the last two decades there has been a great deal of interest in how the complexity of rearing environments may affect the development of spatial cognition skills/abilities of laying hens. Multiple tests have been used to evaluate different aspects of spatial cognition, including: jump test, hole board test, radial maze, and detour task.

Each test has targeted objectives aimed at specific cognitive processes, and comes with advantages and disadvantages.Gunnarsson et al. developed a jump test to evaluate spatial cognition in laying hens, however the specific aspect of spatial cognition being explored was not addressed. The jump test involves placing a feeder on an elevated platform with or without a second, lower platform to assist in access. Pullets’ latency to reach the food reward is measured to assess their ability to navigate elevated structures. Chicks were raised with either early access or late access to perches of varying heights. At 9 weeks old, all birds were placed on perches 2 to 4 times daily to encourage perch use. At 15 weeks all food in the home pen was placed on a 60 cm high tier, which the pullets could access from the ground or via nearby perches. At 16 weeks old, food deprived birds were presented with a feeder on an elevated tier in a testing pen. The height of this tier increased by 40 cm each trial up to 160 cm high and an intermediate tier was provided to aid in access for two of these trials. The time it took for the birds to reach the food after entering the testing pen was recorded and used to measure their success and ease at reaching the elevated food reward. There was no difference in the time that it took birds from different rearing treatments to successfully reach the food on the 40 cm tier. However, there was a significant difference between the treatments when the difficulty of the task increased, with more successes and shorter latencies to access the food from the early access to perch group. The number of birds that successfully reached the tier decreased with increasing difficulty for both rearing treatments. Norman et al. also conducted a jump test with chicks reared from hatching in either a control or enriched treatment. The control treatment had no elevated structures while the enriched treatment had eight wooden perches arranged in an A-frame structure and a ramp leading up to a platform with additional perches. Like the Gunnarsson et al. study, this test also utilized staggered tiers that could be used to reach a reward, however the tiers were opaque and companion chicks were used as a reward instead of food. Chicks were tested at 14- 15 and 28-29 days of age by placing them in a compartment with familiar chicks from their home pen in a mesh holding container. For the first test the companion chicks were on a 20 cm high tier and there were no other tiers present. For the second test, the 20 cm tier remained, however the companion chicks were placed on an additional 40 cm high tier. Norman et al. found that there was a significant difference between age groups on success of reaching the reward, however there was no effect of rearing treatment. In addition, there were no significant differences in the latency to complete the jump test between treatment or age.

It established national standards for organic certification and took enforcement actions if there were violations of the standards. Organic growers are prohibited from using certain production practices that have significant negative environmental impacts. However, the regulation of organic agriculture is process-based, not outcome-based, and the regulatory agency does not monitor or enforce standards on environmental outcomes such as biodiversity and soil fertility . Another source of concern comes from the way organic farming practices may change as the sector grows. As pointed out by Läpple and Van Rensburg , late adopters of organic agriculture are more likely to be profit driven and care less about the environment than early adopters. And, the prices of organic products remained at least 20% higher than their conventional counterparts in 2010 , which could encourage additional entry. Therefore, unintended consequences might emerge and organic agriculture could be less environmentally friendly than commonly perceived. There is some evidence of this in the scientific literature. Organic agriculture has been reported to have higher nitrogen leaching and larger nitrous oxide emissions per unit of output than conventional agriculture . Certain pesticide active ingredients used in organic agriculture have been found to be more toxic than conventional AIs in laboratory environments and field experiments . For example, Racke reviewed the discovery and development of spinosad, a natural substance used to control a wide variety of pests, grow bags garden and observed that spinosad was approved based on its low mammalian toxicity. However, Biondi et al. found that spinosad is more harmful to natural predators than pesticides used commonly in conventional agriculture. As the case of spinosad demonstrates, pesticide use in organic agriculture could impose more environmental impact than conventional agriculture in one or more dimensions.

Therefore more evidence is needed to evaluate the environmental impact of organic farming practices and its determinants. In this essay, I provide novel evidence regarding the impact of pesticide use in organic and conventional agriculture on different dimensions of environmental quality, and quantify the difference between the environmental impacts of pesticide use in the two production systems in California. In addition, I examine the relationships between farmers’ pesticide-use decisions and their experience and farm size. California is the leading state for organic agriculture in the U.S., accounting for 12% of certified organic cropland and 51% of certified organic crop value nationally in 2016 . The number of certified operations and cropland acreage in California doubled between 2002 and 2016. State organic crop sales increased almost tenfold at the farm level, in real terms, during the same time period . This essay uses field-level pesticide application records and a fixed-effects model to analyze changes in the environmental impacts of pesticide use for both organic and conventional fields over 21 years. The database covers all registered agricultural pesticide applications in California, and contains over 48 million pesticide application records for over 64,000 growers and 781,000 fields from 1995 to 2015. In total, data from more than 55,000 organic fields and 11,000 growers who operated organic fields are analyzed in this essay. The Pesticide Use Risk Evaluation model is used to assess the environmental impacts of pesticide use . The results show that the environmental impact of pesticide use per acre is lower in organic fields across all of the environmental dimensions for which PURE indexes are defined: surface water, groundwater, soil, air, and pollinators. The difference in the impact on air is the smallest because natural pesticides are not systematically different from synthetic pesticides in terms of volatile organic compound emissions.

The measure of farmer experience is positively correlated with estimated impacts per acre on surface water and groundwater, and negatively correlated with estimated impacts on soil, air, and pollinators but the difference associated with variation experience are smaller than the estimated effect of whether the field is organic or not by orders of magnitude. Environmental impacts and the difference between organic and conventional production vary by crop. Four major California crops, lettuce, strawberries, processing tomatoes, and wine grapes, are examined in detail.The benefit from organic agriculture is partially paid by consumers through a price premium for organic products . Whether organic production is the most cost effective way to reduce the environmental impacts of agriculture is not the focus of this essay. However, readers can gain some insight into the performance of organic agriculture by comparing the cost of alternative tools and their effects on environmental quality. The contribution of this essay is threefold. First, it links the environmental impacts of organic crop production directly to pesticide applications. To the best of my knowledge, no other studies have examined this relationship. Previous literature provided abundant evidence on the environmental impact of organic agriculture as a system but failed to quantify the impact of specific farming practices . Here, AIs and their contributions to environmental impacts are identified individually, which enhances the understanding of the differences in pesticide use between organic and conventional agriculture and how they vary across crops. Second, this essay uses the PURE model to assess the environmental impacts of pesticide use . Compared to the risk quotient approach, which is another common method in the literature , the PURE model provides a more salient measure of environmental impacts by incorporating additional environmental information, such as the distance from the pesticide application to the nearest surface water. The PURE model calculates risk indices for five environmental dimensions: surface water, groundwater, soil, air, and pollinators.Third, by using the Pesticide Use Report database, this essay’s findings are based on the population of pesticide application data.

Prior works include meta-analyses that cover numerous field experiments and commercial operations examined for a crop or a small geographic area over a limited period of time. California’s agriculture is characterized by many crops and diverse climate and soil conditions. The comprehensive coverage of the PUR database eliminates any sample selection issue. The rest of the essay is organized as follows: section 2 introduces the PUR database and PURE model and presents summary statistics of historical pesticide use, section 3 provides the identification strategy to tackle grower heterogeneity, section 4 presents industry level and crop-specific estimation results, and section 5 concludes.The Pesticide Use Reports database, created and maintained by the California Department of Pesticide Regulation, is the largest and most complete database on pesticide and herbicide use in the world. Growers in California have reported information about every pesticide application since 1990. In this essay, pesticide uses prior to 1995 are not evaluated due to data quality issues identified previously . More than 3 million applications are reported annually. Reports include information on time, location, grower id, crop, pesticide product, AIs, quantity of product applied, treated acreage and other information, for every agricultural pesticide application. A “field” is defined as a combination of grower_id and site_location_id, which is a value assigned to each parcel by its grower. To obtain the USDA organic certification, growers must meet requirements on several aspects of production: pesticide use, fertilizer use, and seed treatment. The requirement on pesticide use is burdensome because pesticides approved in organic agriculture are expensive and have less efficacy. Pesticide and fertilizer AIs used in organic agriculture undergo a sunset review by the National Organic Standards Board every five years and the main criterion is whether the ingredient is synthetic or not. In general, grow bag for tomato it is not reasonable for growers to use those pesticides exclusively but not apply for the organic certification, given higher price and lower efficacy of those pesticides. Therefore, growers who comply with the NOP’s requirement on pesticide use can be viewed as equivalent to certified organic growers for the data sorting purpose. In Wei et al. , authors located individual organic fields using this approach. Namely, any field without a prohibited pesticide applied for the past three years is considered organic. Their paper compared organic crop acreage from PUR to other data sources and showed that pesticide use records alone can be used to identify organic crop production. Environmental conditions for each field and toxicity values for each chemical are used to calculate the value of the PURE index developed by Zhan and Zhang . The PURE index has been used in previous studies to represent environmental impacts of pesticide use . The PURE index indexes environmental impacts of pesticide use in five dimensions: surface water, groundwater, soil, air, and pollinators. For each dimension, the PURE index is calculated on a per acre basis and it varies from 0 to 100, where 0 indicates trivial impact and 100 rep-resents the maximum impact. Excluding air, the PURE index is the ratio of the predicted environmental concentration to toxicity to the end organisms. The PEC estimates the effect of the pesticide application on the concentration level for chemicals in the environmental sample. The toxicity values cover both acute measures, such as LD50, and long-term measures, such as No Observed Effect Concentration and acceptable daily intake for humans. End organisms are fish, algae, and water fleas for surface water, humans for groundwater, earthworms for soil, and honeybees for pollinators. The PURE index for air is calculated based on potential VOC emissions, which is a common measure of airborne pollutants emitted from agriculture production .

The emission of VOCs is defined as the percentage of mass loss of the pesticide sample when heated. Unlike toxicity, VOC emissions do not have a strong link to whether the AIs are synthetic or natural. For example, the herbicide Roundup®, which contains glyphosate, has zero VOC emissions because there is no evaporation or sublimation. Meanwhile, sulfur products, which are widely used in organic agriculture, also have zero VOC emissions. The PURE index only captures impact from active ingredients in pesticides. Inert ingredients, which are not covered in this essay, are also found to have negative impacts on the environment and on pollinators in particular .Conventional and organic growers adopt different pest management practices. As specified by the NOP, organic growers shall use pesticides only when biological, cultural, and mechanical/physical practices are insufficient. Chemical options remain essential for organic pest management programs. Currently over 7,500 pesticide products are allowed for use in organic crop and livestock production, processing, and handling. In Figure 1.1, the acreage treated with different types of pesticides is shown on the left y-axis for both conventional and organic fields. Treated acreage is divided evenly among types for AIs that belong to multiple pesticide types, such as sulfur, which is both a fungicide and an insecticide. The average number of pesticide applications per acre, which is defined as the total treated acreage divided by the total planted acreage, is plotted against the right y-axis in both panels. This is a common measure of pesticide uses that controls for differences in application rate among pesticide products . If multiple AIs are used in a single application, the treated acreage is counted separately for each AI. Planted acreage remained stable for conventional agriculture over the study period, so changes in the average number of applications per acre were due to changes in treated acreage. Organic planted acreage grew dramatically, but treated acreage increased even more. The number of applications per organic acre rose from 2 to 7. Figure 1.1 provides a highly aggregated view of pesticide use as different pesticide products with different AIs and application rates are used in conventional and organic fields. Examining the Figure 1.1 , insecticide is the most used pesticide type, accounting for 36% and 44% of total treated acreage in conventional and organic agriculture respectively in 2015. Herbicide is the second most used type of pesticide in conventional fields. In contrast, organic growers’ use of herbicides is limited. Fungicide is another major pesticide type, and sulfur is the most used fungicide AI in both conventional and organic fields. Sulfur is an important plant nutrient, fungicide, and acaricide in agriculture. The pesticide group “others” primarily includes plant growth regulators and pheromones. Disaggregating insecticide use provides more detailed insight into the nature of the difference between conventional and organic production. Figure 1.2 plots the insecticide treated acreage by physiological functions affected . Only three groups of insecticides are available to organic growers, while six are available to conventional growers. In conventional agriculture, 67% of treated acreage in 2015 was treated with insecticides that targeted nerves or muscles, which include organophosphates, pyrethroids, and neonicotinoids.