Semi‐natural habitat surrounding farms promotes multifunctionality in avian ecosystem services

DNA metabarcoding diet analysis in a generalist omnivore: feeding trials reveal the efficacy of extraction kits and a multi-locus approach for identifying diverse diets

Metabarcoding-based diet analysis is a valuable tool for understanding the feeding behavior of a wide range of species. However, many studies using these methods for wild animals assume accuracy and precision without experimental evaluation with known positive control food items. Here, we conducted a feeding trial experiment with a positive control community in pasture-raised chickens and assessed the efficacy of several commonly used DNA extraction kits and primer sets. We hand-fed 22 known food items, including insects and plants, to six backyard laying hens and collected their excreta for eight h. We evaluated the efficacy of three DNA extraction kits, three primer sets for plant identification (targeting rbcL, trnL, and internal transcribed spacer 2 [ITS2]), and three primer sets for arthropod identification (targeting cytochrome oxidase subunit I [COI]). The detection success rate of our positive control food items was highly variable, ranging from 2.04% to 93.88% for all kit/primer combinations and averaging 37.35% and 43.57% for the most effective kit/primer combination for plants and insects, respectively. Extraction kits using bead-based homogenization positively affected the recovery proportion of plant and insect DNA in excreta samples. The minimum time to detect known food items was 44 min post-feeding. Two COI primer sets significantly outperformed the third, and both recovery proportion and taxonomic resolution from ITS2 were significantly higher than those from rbcL and trnL. Taken together, these results display the potential variability that can be inherently present in DNA-based diet analyses and highlight the utility of experimental feeding trials in validating such approaches, particularly for omnivores with diverse diets.

Prevalence and molecular characterization of Salmonella isolated from wild birds in fresh produce environments

Wild birds pose a difficult food safety risk to manage because they can avoid traditional wildlife mitigation strategies, such as fences. Birds often use agricultural fields and structures as foraging and nesting areas, which can lead to defecation on crops and subsequent transfer of foodborne pathogens. To assess the food safety risk associated with these events, wild bird feces were collected from produce fields across the southeastern United States during the 2021 and 2022 growing seasons. In total 773 fecal samples were collected from 45 farms across Florida, Georgia, South Carolina, and Tennessee, and 2.1% (n = 16) of samples were Salmonella-positive. Importantly, 75% of Salmonella were isolated from moist feces, showing reduced Salmonella viability when feces dry out. 16S microbiome analysis showed that presence of culturable Salmonella in moist feces correlated to a higher proportion of the Enterobacteriaceae family. From the Salmonella-positive samples, 62.5% (10/16) contained multi-serovar Salmonella populations. Overall, 13 serovars were detected, including six most commonly attributed to human illness (Enteriditis, Newport, Typhimurium, Infantis, Saintpaul, and Muenchen). PCR screening identified an additional 59 Salmonella-positive fecal samples, which were distributed across moist (n = 44) and dried feces (n = 15). On-farm point counts and molecular identification from fecal samples identified 57 bird species, including for 10 Salmonella-positive fecal samples. Overall, there was a low prevalence of Salmonella in fecal samples, especially in dried feces, and we found no evidence of Salmonella transmission to proximal foliage or produce. Fecal samples collected in farms close together shared highly related isolates by whole genome sequencing and also had highly similar Salmonella populations with comparable relative frequencies of the same serovars, suggesting the birds acquired Salmonella from a common source.

Scenario modeling of ecosystem service trade-offs and bundles in a semi-arid valley basin

Amidst the rapid urbanization process, substantial transformations have emerged within ecosystem services, exerting profound ramifications on the sustainability of ecosystems. Nevertheless, an existing dearth persists in delineating the intricate interplay of trade-offs and synergies, as well as ecosystem services bundles under diverse future scenarios. This study harnesses the Convolutional neural network-Long and short-term memory-Cellular automata model to prognosticate and dissect the temporal and spatial dynamics of four distinct ecosystem services (soil retention, water yield, carbon storage, and habitat quality) across the semi-arid valley city of Lanzhou from 2000 to 2030 under multiple scenarios. The SPSS model methodically quantifies the intricate trade-offs and synergies interwoven among these services, while cluster analysis reveals ecosystem services bundles across varying scales. Notably, (1) convolutional neural network-long and short-term memory-cellular automata model demonstrates remarkable proficiency in accurately forecasting land use, boasting an elevated precision level of 0.93. (2) The trajectories of carbon storage and water yield demonstrate a diminishing pattern between 2000 and 2020, against the ascending trends observed in soil retention and habitat quality. Within the ecological priority scenario for 2030, water yield experiences a sluggish decrease, while the abatement of soil retention, carbon storage, and habitat quality degradation is maximized. (3) The trade-offs (3 pairs) and synergies (3 pairs) among ecosystem services within the study locale exhibit a state of relative equilibrium. Noteworthy among these interactions is the prominent trade-off correlation (-0.101) between soil conservation and carbon storage within the city priority scenario. (4) Four discernible ecosystem services bundles manifest at the grid scale from 2000 to2030. Conversely, three bundles at the county scale in 2000, eventually decrease to two bundles between 2010 and 2030, hinting at a diminishing trend concerning the number of ecosystem services bundles as spatial scales coarsen. Furthermore, whereby these bundles progressively aggregate spatially over time.

Avian regulation of crop and forest pests, a meta-analysis

BACKGROUND

Birds have been shown to reduce pest effects on various ecosystem types. This study aimed to synthesize the effect of birds on pest abundance, product damage and yield in agricultural and forest systems in different environments. Our hypothesis is that birds are effective pest regulators that contribute to a reduction in pest abundance, enhancement of yield quality and quantity and economic profit, and that pest regulation may depend on moderators such as the type of ecosystem, climate, pest, and indicator (ecological or economic).

RESULTS

We performed a systematic literature review of experimental and observational studies related to biological control in the presence and absence of regulatory birds. We retained 449 observations from 104 primary studies that were evaluated through qualitative and quantitative analyses. Of the 79 studies with known effects of birds on pest regulation, nearly half of the 334 observations showed positive effects (49%), 46% showed neutral effects, and very few (5%) showed negative effects. Overall effect sizes were positive (mean Hedges' d = 0.38 ± 0.06). A multiple model selection retained only ecosystem and indicator types as significant moderators.

CONCLUSION

Our results support our hypothesis that there is a positive effect of avian control of pests for each analyzed moderator and this effect was significant for both ecological and economic indicators. Avian regulation of pests is a potential effective approach for environmentally friendly pest management that can reduce pesticide use regardless of the context of implementation. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.