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Human land use threatens global biodiversity and compromises multiple ecosystem functions critical to food production. Whether crop yield-related ecosystem services can be maintained by a few dominant species or rely on high richness remains unclear. Using a global database from 89 studies (with 1475 locations), we partition the relative importance of species richness, abundance, and dominance for pollination; biological pest control; and final yields in the context of ongoing land-use change. Pollinator and enemy richness directly supported ecosystem services in addition to and independent of abundance and dominance. Up to 50% of the negative effects of landscape simplification on ecosystem services was due to richness losses of service-providing organisms, with negative consequences for crop yields. Maintaining the biodiversity of ecosystem service providers is therefore vital to sustain the flow of key agroecosystem benefits to society.

The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

The amount of semi‐natural habitat surrounding farm fields is a common but inconsistent predictor of natural enemy populations and predation services. Standard land cover metrics may not accurately capture the actual availability of limiting resources for natural enemies and can miss important dynamics across space and time. Theory from animal movement and landscape ecology predicts that regions with more, spatio‐temporally continuous resources (i.e. food and shelter) should have larger predator populations and enhanced biological control. To test these predictions empirically, we designed a study measuring aphids, lady beetles and predation services in agricultural landscapes in Wisconsin, USA. In two study years, we sampled lady beetles and aphids in 336 crop fields (corn, soybean, alfalfa and small grains) and adjacent semi‐natural habitat patches (grasslands and woodlands) across 24 1.5 km buffer landscapes at four to seven time points each, and in 1 year, we assessed predation rates with sentinel egg cards. We used aphid counts to model habitat‐specific aphid phenologies, from which we calculated landscape indices of prey amount and continuity. These indices, along with semi‐natural habitat area, were used to predict lady beetle abundance. While there were strong differences in the abundance and timing of aphids by habitat, semi‐natural habitat amount was still a better predictor of lady beetle counts and sentinel egg predation than either aphid amount or continuity indices in these landscapes. Synthesis and applications. Our findings confirm the robust relationship between lady beetles and semi‐natural habitat in agricultural landscapes, and highlight the complexities of measuring fine‐scale resource heterogeneity in real landscapes. Retaining or adding woodland and grassland patches in agricultural landscapes is likely to support larger lady beetle populations and enhance predation in crop fields. Our results suggest that these habitats may be more important for shelter than prey continuity, though this mechanism warrants further investigation. Future work should continue to refine experimental methods for the successful integration of landscape ecology and animal behaviour to support conservation goals. [ABSTRACT FROM AUTHOR]

In North America, white‐nose syndrome (WNS) has caused precipitous declines in hibernating bat populations, raising the question of whether the rapid loss of arthropodivorous bats may affect the abundance of their prey. During the summers of 2015–2018 (1 year after the arrival of WNS in Wisconsin, USA), we performed intensive arthropod black‐light trapping, ultrasonic acoustic monitoring, and emergence counts at 10 little brown (Myotis lucifugus) and big brown (Eptesicus fuscus) bat maternity roosts with paired control sites. For little brown bats, which are severely affected by WNS, roost counts declined by 95% over the four‐year period, compared to a 38% decline in big brown bat roost counts. Total arthropod abundance decreased by 49%, although decreases among common little brown bat prey were less severe. Our natural predator exclusion experiment supports existing evidence that bats can have measurable trophic impacts on arthropod communities, primarily via top‐down effects on common prey. [ABSTRACT FROM AUTHOR]

One of the most challenging aspects of bee ecology and conservation is species-level identification, which is costly, time consuming, and requires taxonomic expertise. Recent advances in the application of deep learning and computer vision have shown promise for identifying large bumble bee (Bombus) species. However, most bees, such as sweat bees in the genus Lasioglossum, are much smaller and can be difficult, even for trained taxonomists, to identify. For this reason, the great majority of bees are poorly represented in the crowdsourced image datasets often used to train computer vision models. But even larger bees, such as bumble bees from the B. vagans complex, can be difficult to separate morphologically. Using images of specimens from our research collections, we assessed how deep learning classification models perform on these more challenging taxa, qualitatively comparing models trained on images of whole pinned specimens or on images of bee forewings. The pinned specimen and wing image datasets represent 20 and 18 species from 6 and 4 genera, respectively, and were used to train the EfficientNetV2L convolutional neural network. Mean test precision was 94.9% and 98.1% for pinned and wing images respectively. Results show that computer vision holds great promise for classifying smaller, more difficult to identify bees that are poorly represented in crowdsourced datasets. Images from research and museum collections will be valuable for expanding classification models to include additional species, which will be essential for large scale conservation monitoring efforts. [ABSTRACT FROM AUTHOR]

Loss of natural habitat due to increases in agricultural extent raises the question of whether human‐dominated landscape types can support biodiversity, particularly for declining insect pollinators. Compared to more rural agricultural landscapes, urban areas may confer benefits for bumble bee populations by providing stable and diverse floral resources. However, disentangling the effects of local‐ and landscape‐scale characteristics on bumble bee populations in human‐modified landscapes is challenging.Here, we assessed bumble bee occupancy using a repeated transect sampling design conducted during the summers of 2019 and 2020 within the metropolitan area of Madison, WI, and the surrounding agricultural landscape. We fit hierarchical occupancy models to estimate the detection (p) and occupancy (ψ) probabilities relative to local habitat quality (floral abundance and floral richness) and landscape (agricultural‐urban gradient) features for eight bumble bee species. We hypothesised that bumble bees were more likely to occupy urban areas, serving as refugia, relative to agricultural sites.We found that the detection probability of all bumble bee species was seasonal and influenced by maximum floral abundance at survey sites, independent of the surrounding land cover type. After accounting for species‐specific detection probabilities, the effect of urbanisation on bee occupancy was weak, and no species were less likely to occupy urban than rural agricultural areas.Our findings suggest that bumble bee occupancy is associated with a 'honeypot effect' where local resource availability, in the form of higher floral abundance, is most important in limiting the occupancy of bumble bees across urban and agricultural landscapes. [ABSTRACT FROM AUTHOR]

Insects and other small invertebrates are ubiquitous components of all terrestrial and freshwater food webs, but their cumulative biomass is small relative to plants and microbes. As a result, it is often assumed that these animals make relatively minor contributions to ecosystem processes. Despite their small sizes and cumulative biomass, we suggest that these animals may commonly have important effects on carbon and nutrient cycling by modulating the quality and quantity of resources that enter the detrital food web, with consequences at the ecosystem level. These effects can occur through multiple pathways, including direct inputs of insect biomass, the transformation of detrital biomass, and the indirect effects of predators on herbivores and detritivores. In virtually all cases, the ecosystem effects of these pathways are ultimately mediated through interactions with plants and soil microbes. Merging our understanding of insect, plant and microbial ecology will offer a valuable way to better integrate community-level interactions with ecosystem processes.

Restoration of grassland ecosystems is essential for mitigating global losses of biodiversity and is typically initiated to foster persistent, long‐term increases in biodiversity. Yet, evaluating long‐term impacts of restoration on biodiversity is rare, especially across sites restored using consistent methods. Evaluation of restoration outcomes is particularly important for increasing predictive capacity in restoration ecology to determine the level of restoration effort that is required to achieve both short‐ and long‐term restoration goals. We conducted a multisite study that explicitly compared the impacts of no intervention ("passive" or "natural" recovery), low intervention (seeding native plants), and moderate intervention (seeding native plants and using fire management) at 32 restored prairies differing in the age of restoration (3–23 years). Grasslands with natural recovery have equivalent native plant species richness compared to sites with low and moderate restoration intervention, however, they have significantly lower‐quality vegetation, as measured by Floristic Quality (mean C). We found that managing restored prairies with fire maintains native plant richness over time and is correlated with higher vegetation quality and presence of seeded species. Seed mixes with a high mean C score are positively correlated with plant community quality. However, seed mixes with more species are negatively correlated with the proportion of seeded species present. We found that while the degree of restoration intervention has no effect on the number of native plant species, greater levels of assisted recovery are required to produce restored prairies that resemble high‐quality remnant vegetation and, especially, to maintain these successes over the long term. [ABSTRACT FROM AUTHOR]

Bees provide essential pollination services that are potentially affected both by local farm management and the surrounding landscape. To better understand these different factors, we modelled the relative effects of landscape composition (nesting and floral resources within foraging distances), landscape configuration (patch shape, interpatch connectivity and habitat aggregation) and farm management (organic vs. conventional and local-scale field diversity), and their interactions, on wild bee abundance and richness for 39 crop systems globally. Bee abundance and richness were higher in diversified and organic fields and in landscapes comprising more high-quality habitats; bee richness on conventional fields with low diversity benefited most from high-quality surrounding land cover. Landscape configuration effects were weak. Bee responses varied slightly by biome. Our synthesis reveals that pollinator persistence will depend on both the maintenance of high-quality habitats around farms and on local management practices that may offset impacts of intensive monoculture agriculture.

Agricultural practices and intensification during the past two centuries have dramatically altered the abundance and temporal continuity of floral resources that support pollinating insects such as bumble bees. Long‐term trends among bumble bees within agricultural regions suggest that intensive agricultural conditions have created inhospitable conditions for some species, while other species have maintained their relative abundances despite landscape‐level changes in flower availability. Bumble bee responses to spatiotemporal resource heterogeneity have been explored at the colony and behavioral level, but we have yet to understand whether these conditions drive community structure and ultimately explain the diverging patterns in long‐term species trends. To explore the relationship between landscape‐level floral resource continuity and the likelihood of bumble bee occurrence, we mapped the relative spatial and temporal availability of floral resources within an intensive agricultural region in the US Upper Midwest and related this resource availability with bumble bee species relative abundance. Across the bee community, we found that relative bumble bee occurrence increases in landscapes containing more abundant and more temporally continuous floral resources. Declining species, such as Bombus terricola, exhibited the strongest, positive responses to resource abundance and continuity whereas common, stable species, such as Bombus impatiens, showed no statistical relationship to either. Together with existing experimental evidence, this work suggests that efforts to increase spatiotemporal flower availability, along with overall flower abundance at landscape scales may have positive effects on bumble bee communities in the US Upper Midwest. [ABSTRACT FROM AUTHOR]