We classified beetles as macropterous if the wing length was equal to abdomen length and the wings were folded at the apex or longer and as brachypterous if the wings were reduced or not apparent. We did not examine flight muscles. Thus some beetles categorized as macropterous based on wing length may not be able to fly. Carabid species were classified as monomorphic if all of the individuals had the same wing type and dimorphic if individuals had both wing types. We used body length and wing morphology as a surrogate for dispersal ability and designated three groups: large beetles with brachypterous wings as low dispersal ability; large beetles with macropterous wings, or small beetles with brachypterous wings as medium dispersal ability; and, small beetles with macropterous wings as high dispersal ability. We used three functional traits—size , wing morphology , and wing syndrome —to assign beetles to functional groups. The individual functional groups were based on unique combinations of trait values for a total of eight possible functional groups. We used the number of functional groups that are present in each garden as a measure of functional group richness.All of the statistical analysis was conducted in R version 1.1.456. To determine how activity density, species richness, and functional group richness vary with the local and landscape factors, cannabis grow systems we used generalized linear models and a model selection approach based on Akaike’s Information Criterion .
We determined total activity density, species richness, average body size, dispersal class activity density, and functional group richness for each site across all of the sampling periods. Rather than include all local and landscape variables measured, we ran Pearson’s correlations to select variables that were uncorrelated and biologically relevant given other studies on carabids. Thus, we included garden size , county , percent bare soil cover, percent mulch cover, percent leaf litter cover, floral abundance , number of crop species, number of weed species, and the amount of urban land cover within 2 km, and amount of agriculture land cover within 2 km as the explanatory variables for each model. To determine the landscape scale to use in the model, we performed stepwise model selection comparing the model fits at each scale. We selected 2 km because it had the best model score and is a comparable scale to carabid studies in other systems. Although garden age might impact carabid communities , we did not include garden age because this factor positively correlates with garden size. We did not include any random terms in the models. The models were fit with Poisson error distributions. We used the “glmulti” package version 1.0.7 to identify the best fit model using AICc. If the best fitting models differed by <2 points, we averaged the top models . Models with significant predictors of variables were visualized with the “visreg” package version 2.5-0. To assess which local and landscape factors drive carabid community composition, we examined the patterns and graphics with the “vegan” package version 2.5-3. We used a permutational multivariate analysis of variance with the “adonis2” function.
We calculated the Bray–Curtis distance and used the “metaMDS” function to transform and visualize the community structure in each garden. We included the county as a random factor. To visualize the results, we plotted non-metric multidimensional scaling plots with the “ordiplot” function, and used the “envfit” function to fit the local and landscape factors to the ordination. To determine how local and landscape factors influence carabid traits, we used a combined RLQ and a fourth corner approach with the “ade4” package version 1.7-11 . We used the RLQ method to summarize the joint structure between the local and landscape factors, carabid distribution among gardens, and carabid traits, and then used the fourth corner to test for correlations between local and landscape factors and carabid traits . We created three matrices: R matrix , Q matrix , and L matrix . We performed a correspondence analysis and principal component analysis and then used two permutation models to evaluate whether garden factors influence the distribution of carabid traits , and if traits influence the composition of species assemblages that are found in gardens. We created an RLQ biplot to assess the relationships between species traits and local and landscape factors and determined the significance of each trait-factor relationship using the fourth corner analysis. For trait analyses, we removed the singleton species and transformed species abundance with a Hollinger transformation . We included the same local and landscape factors that were used in the GLMs for activity and taxonomic richness.
We used Monte-Carlo permutations to test for correlations between quantitative variables and used the “D2” correlation coefficient to test for associations between quantitative variables and each categorical value separately. We collected 149 carabid individuals from 14 genera and 20 species . Trechus obstusus was the most abundant , followed by Laemostenus complanatus , Pterostichus californicus , and Harpalus pensylvanicus . We recorded low abundance of several species that often occupy disturbed habitats, including Microlestes nigritus and Axinopalpus biplagiatus. We collected two species that feed on seeds and pollen—Bradycellus nubifer and B. nitidus . Carabids varied in body length . Two species exhibited dimorphic wing—M. nigritus and T. obtusus ; all other species were monomorphic . Carabids were low , medium , or high dispersers . Carabid activity density responded to several local factors and one landscape factor. Local factors, including crop species richness and leaf litter influenced carabid activity, and they were important in models predicting species and functional group richness. A diverse crop assemblage could provide food and shelter , promoting carabid activity in gardens. Crop species richness may benefit carabids by directly providing an array of seeds, fruit, and pollen. In rural agriculture, seed additions increase the abundance of seed-feeding carabids. In addition, crop diversity could indirectly attract and support carabid richness by providing habitat and resources for carabid prey. Documented increases in carabid activity density with more leaf litter corroborate previous results . Interestingly, landscape factors predicted carabid activity but not species richness in gardens. Agricultural land cover positively correlated with carabid activity, potentially due to high activity of T. obtusus, a species frequently associated with agriculture. We did not find significant local or landscape predictors of species or functional group richness, which was perhaps due to influences on species traits. Species traits were correlated with urban land cover, suggesting that carabids with different trait combinations persist in urban areas, and highlighting the importance of considering functional group richness and trait composition in arthropod communities.Specific local and landscape features influenced carabid traits in the gardens. Ground cover features and flowers were important for carabids across multiple analyses. In our study, ebb and flow tables community composition significantly influenced leaf litter cover, and larger carabids associated with sites with more leaf litter. In forest systems, carabid composition can differ with natural variation or manipulation of litter depth . At least two studies have found larger carabid body size in forest sites with more litter. However, not all sites document the differences in carabid communities or traits with changes in litter depth along urban to rural gradients . Leaf litter may influence carabids by providing additional prey resources, or it may strongly alter microhabitat conditions. Larger beetles utilize leaf litter for shelter and gardens with more leaf litter may provide refuges from predation. In contrast, smaller beetles may have difficulty moving across areas with high leaf litter. Large carabids with reduced wings were associated with gardens with more leaf litter. Smaller carabids with high dispersal ability were associated with high floral abundance, as were carabid species with dimorphic wing morphology . We are not aware of other studies that have documented differences in carabid size distributions or wing morphology specifically as a result of changes in floral abundance. Carabid researchers have often predicted a higher abundance of smaller carabids in highly disturbed sites . Some studies found that the smaller carabid species were dominant in more disturbed urban environments, while larger species were dominant in more rural environments. However, at least one study found that forest disturbance fostered species diversity. In our study system, greater amounts of urban cover in the landscape promoted abundance of larger carabids; therefore, we do not have evidence to support the stress hypothesis.
Our results suggest that gardens surrounded by urban cover—often considered tobe inhospitable habitat—may have local features that can support large beetles with brachypterous wings that cannot disperse across long distances. Our study results on the local and landscape drivers of carabid activity, richness and trait distribution in gardens can contribute useful information to gardeners who often lack knowledge regarding pest management in urban agroecosystems. Most carabid beetles are predatory, but carabids can feed on a wide range of prey and plant material, depending on the life stage. Predators with broad host ranges, like carabid beetles, are important contributors to biological control and lower pest abundances. Two species that are common in our sites, Pterostichus lustrans and T. obtusus, are predators of common crop pests. We found that gardens with greater crop species richness support a higher activity of carabids, and that large brachypterous beetles are affected by landscape surroundings. Further, a larger carabid body size boosts prey attack and prey consumption rates. Although carabid traits influence the dispersal ability and associated pest control, wing morphology and size alone do not determine carabid dispersal. Reproductive traits are also important; carabid females often lose functional flight musculature as their ovaries develop. While large size is tied to higher prey consumption, small body size indicates a high reproductive rate, which is of high ecological importance for carabids in urban gardens. Although pest control by carabids has been directly measured in rural systems , these nuances of carabid ecology call for future research that measures pest predation by carabids in urban agroecosystems.As the human population continues to grow, demand for seafood will rise. Globally, wild capture production has remained relatively steady since the late 1980s as aquaculture production has increased around the world. Today, roughly half of all seafood is farmed and aquaculture is the fastest-growing global food sector. The greatest potential for expanding aquaculture production can be found in land-based, indoor, recirculating systems and in open ocean marine aquaculture, i.e. offshore aquaculture. This report analyzes the latter of these, with a specific focus on offshore fin fish aquaculture. Some large, vertically-integrated, salmon farming companies in Norway, China, and Japan are collaborating with the offshore oil and gas industry to develop methods of farming fish in the open ocean using floating net pens designed after oil rigs. In some Latin American countries, smaller, independent companies are farming fish offshore using fully submersible cages. The United States is home to one such farm – operating offshore from Hawaii – and several projects have been proposed around the country. This report explores the potential for offshore fin fish aquaculture in the United States, the key barriers that have inhibited industry development, and strategies for overcoming those barriers. Information was gathered through a thorough literature review and expert consultation via phone interviews, in-person meetings, and conference attendance. Representatives from the aquaculture industry, federal and state agencies, advocacy groups, scientific research institutions, and NGOs were consulted. Opportunities for offshore aquaculture development in the U.S. include the country’s large and productive exclusive economic zone, the presence of high-quality research institutions, a large domestic seafood market, a skilled workforce, political support from the current administration, and well-developed coastal infrastructure. Barriers include prohibitive statutes and regulatory uncertainty at the state level, a complex permitting process, market competition with imported seafood, the industry’s small scale, and the challenge of earning a social license to operate. Two key barriers have inhibited U.S. industry development: the complex permitting process and the public’s perception of offshore fish farming. While existing statutes give several federal agencies authority to regulate aspects of offshore aquaculture, none has been designated as the lead permitting agency for aquaculture. The result is that applicants must navigate a complex system that involves multiple federal, state, and local agencies. This process is costly and can take years. There is also inherent risk for investors because there is no guarantee a permit will be issued.More than 3 billion people around the world rely on seafood as a primary source of protein; that’s almost 40% of the human population.