Landscape-scale floral resource discontinuity decreases bumble bee occurrence and alters community composition

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.

Situating the parietal memory network in the context of multiple parallel distributed networks using high-resolution functional connectivity

A principle of brain organization is that networks serving higher cognitive functions are widely distributed across the brain. One exception has been the parietal memory network (PMN), which plays a role in recognition memory but is often defined as being restricted to posteromedial association cortex. We hypothesized that high-resolution estimates of the PMN would reveal small regions that had been missed by prior approaches. High-field 7T functional magnetic resonance imaging (fMRI) data from extensively sampled participants was used to define the PMN within individuals. The PMN consistently extended beyond the core posteromedial set to include regions in the inferior parietal lobule; rostral, dorsal, medial, and ventromedial prefrontal cortex; the anterior insula; and ramus marginalis of the cingulate sulcus. The results suggest that, when fine-scale anatomy is considered, the PMN matches the expected distributed architecture of other association networks, reinforcing that parallel distributed networks are an organizing principle of association cortex.

Perennial grassland agriculture restores critical ecosystem functions in the U.S. Upper Midwest

Dominant forms of agricultural production in the U.S. Upper Midwest are undermining human health and well being. Restoring critical ecosystem functions to agriculture is key to stabilizing climate, reducing flooding, cleaning water, and enhancing biodiversity. We used simulation models to compare ecosystem functions (food-energy production, nutrient retention, and water infiltration) provided by vegetation associated with continuous corn, corn-soybean rotation, and perennial grassland producing feed for dairy livestock. Compared to continuous corn, most ecosystem functions dramatically improved in the perennial grassland system (nitrate leaching reduced ~90%, phosphorus loss reduced ~88%, drainage increased ~25%, evapotranspiration reduced ~29%), which will translate to improved ecosystem services. Our results emphasize the need to incentivize multiple ecosystem services when managing agricultural landscapes.

Disease‐related population declines in bats demonstrate non‐exchangeability in generalist predators

The extent to which persisting species may fill the functional role of extirpated or declining species has profound implications for the structure of biological communities and ecosystem functioning. In North America, arthropodivorous bats are threatened on a continent‐wide scale by the spread of white‐nose syndrome (WNS), a disease caused by the fungus Pseudogymnoascus destructans. We tested whether bat species that display lower mortality from this disease can partially fill the functional role of other bat species experiencing population declines. Specifically, we performed high‐throughput amplicon sequencing of guano from two generalist predators: the little brown bat (Myotis lucifugus) and big brown bat (Eptesicus fuscus). We then compared changes in prey consumption before versus after population declines related to WNS. Dietary niches contracted for both species after large and abrupt declines in little brown bats and smaller declines in big brown bats, but interspecific dietary overlap did not change. Furthermore, the incidence and taxonomic richness of agricultural pest taxa detected in diet samples decreased following bat population declines. Our results suggest that persisting generalist predators do not necessarily expand their dietary niches following population declines in other predators, providing further evidence that the functional roles of different generalist predators are ecologically distinct.

Within-Year Effects of Prescribed Fire on Bumble Bees (Hymenoptera: Apidae) and Floral Resources

Despite the importance of bumble bees (genus Bombus Latreille) for their services to natural and agricultural environments, we know little about the relationship between grassland management practices and bumble bee conservation. Prescribed fire is a common grassland maintenance tool, including in areas where endangered and threatened bumble bees are present. Thus, knowledge of the effects of prescribed fire on bumble bees is essential for designing management schemes that protect and bolster their populations. Using nonlethal surveys to record bumble bee species richness, abundance, and community composition, we evaluated the effects of spring controlled burns on summer bumble bee gynes and workers across five sites in southern Wisconsin. In addition, we explored the effects of fire on floral resources by measuring floral genus richness, abundance, ground cover, and proportion of transects containing blooming flowers in adjacent burned and unburned parcels. Prescribed fire had no measurable effects on bumble bee gyne or worker community composition, species richness, or abundance. However, consistent with previous studies prescribed fire increased floral genus richness and ground cover. The disconnect between bumble bee and floral responses to fire highlights some opportunities for improving our understanding of fire's effects on bumble bee diapause, nest site choice, and foraging.

Climate-induced outbreaks in high-elevation pines are driven primarily by immigration of bark beetles from historical hosts

Warming temperatures are allowing native insect herbivores to expand into regions that previously exceeded their thermal tolerance, encounter new host species, and pose significant threats to native communities. However, the dynamics of these expansions remain poorly understood, particularly in the extent to which outbreaks remain reliant on emigration from historical hosts or are driven by local reproduction within novel hosts in the expanded range. We tested these non-mutually exclusive hypotheses using spatially explicit data on mountain pine beetle (Dendroctonus ponderosae), which historically undergoes intermittent outbreaks in low-elevation lodgepole pine (Pinus contorta), but is now causing severe mortality in a high-elevation endangered species, whitebark pine (Pinus albicaulis). We compiled data from 2000 to 2019 across British Columbia, Canada, at 1-km² resolution, and analyzed spatiotemporal patterns of beetle infestations, lodgepole pine distributions, expansion into habitats dominated by whitebark pine, and the likelihood of future outbreaks in all pine communities under simulated conditions. Overall, we found strong support for the hypothesis of emigration from the historical host species continuing to be a major driver of outbreaks in the more recently accessed host. First, beetle population pressure was consistently the best predictor of infestation severity in both lodgepole and whitebark pine, and appeared to be mostly unidirectional from lodgepole to whitebark pine. Second, infestations in lodgepole pine were of a longer duration than those in whitebark pine, which appeared too brief to sustain transitions from endemic to eruptive dynamics. Furthermore, resource depletion appears to drive emigration from lodgepole pine, whereas in whitebark pine drought appears to favor establishment of immigrants although bioclimatic factors and stand structure preclude self-sustaining outbreaks. Finally, we project that most pine in British Columbia will be at risk in the event of a new major outbreak. We describe implications for conserving and protecting whitebark pine and to other climate-driven range expansions.

Historical decrease in agricultural landscape diversity is associated with shifts in bumble bee species occurrence

Agricultural intensification is a key suspect among putative drivers of recent insect declines, but an explicit link between historical change in agricultural land cover and insect occurrence is lacking. Determining whether agriculture impacts beneficial insects (e.g. pollinators), is crucial to enhancing agricultural sustainability. Here, we combine large spatiotemporal sets of historical bumble bee and agricultural records to show that increasing cropland extent and decreasing crop richness were associated with declines in over 50% of bumble bee species in the agriculturally intensive Midwest, USA. Critically, we found that high crop diversity was associated with a higher occurrence of many species pre-1950 even in agriculturally dominated areas, but that current agricultural landscapes are devoid of high crop diversity. Our findings suggest that insect conservation and agricultural production may be compatible, with increasing on-farm and landscape-level crop diversity predicted to have positive effects on bumble bees.

Assessing the potential for deep learning and computer vision to identify bumble bee species from images

Pollinators are undergoing a global decline. Although vital to pollinator conservation and ecological research, species-level identification is expensive, time consuming, and requires specialized taxonomic training. However, deep learning and computer vision are providing ways to open this methodological bottleneck through automated identification from images. Focusing on bumble bees, we compare four convolutional neural network classification models to evaluate prediction speed, accuracy, and the potential of this technology for automated bee identification. We gathered over 89,000 images of bumble bees, representing 36 species in North America, to train the ResNet, Wide ResNet, InceptionV3, and MnasNet models. Among these models, InceptionV3 presented a good balance of accuracy (91.6%) and average speed (3.34 ms). Species-level error rates were generally smaller for species represented by more training images. However, error rates also depended on the level of morphological variability among individuals within a species and similarity to other species. Continued development of this technology for automatic species identification and monitoring has the potential to be transformative for the fields of ecology and conservation. To this end, we present BeeMachine, a web application that allows anyone to use our classification model to identify bumble bees in their own images.

Predator preferences shape the diets of arthropodivorous bats more than quantitative local prey abundance

Although most predators are generalists, the majority of studies on the association between prey availability and prey consumption have focused on specialist predators. To investigate the role of highly generalist predators in a complex food web, we measured the relationships between prey consumption and prey availability in two common arthropodivorous bats. Specifically, we used high-throughput amplicon sequencing coupled with a known mock community to characterize seasonal changes in little brown and big brown bat diets. We then linked spatiotemporal variation in prey consumption with quantitative prey availability estimated from intensive prey community sampling. We found that although quantitative prey availability fluctuated substantially over space and time, the most commonly consumed prey items were consistently detected in bat diets independently of their respective abundance. Positive relationships between prey abundance and probability of consumption were found only among prey groups that were less frequently detected in bat diets. While the probability of prey consumption was largely unrelated to abundance, the community structure of prey detected in bat diets was influenced by the local or regional abundance of prey. Observed patterns suggest that while little brown and big brown bats maintain preferences for particular prey independently of quantitative prey availability, total dietary composition may reflect some degree of opportunistic foraging. Overall, our findings suggest that generalist predators can display strong prey preferences that persist despite quantitative changes in prey availability.

Reducing Native Ant Abundance Decreases Predation Rates in Midwestern Grasslands

Diverse and robust predator communities are important for effective prey suppression in natural and managed communities. Ants are ubiquitous components of terrestrial systems but their contributions to natural prey suppression is relatively understudied in temperate regions. Growing evidence suggests that ants can play a significant role in the removal of insect prey within grasslands, but their impact is difficult to separate from that of nonant predators. To test how ants may contribute to prey suppression in grasslands, we used poison baits (with physical exclosures) to selectively reduce the ant population in common garden settings, then tracked ant and nonant ground predator abundance and diversity, and removal of sentinel egg prey for 7 wk. We found that poison baits reduced ant abundance without a significant negative impact on abundance of nonant ground predators, and that a reduction in ant abundance decreased the proportion of sentinel prey eggs removed. Even a modest decrease (~20%) in abundance of several ant species, including the numerically dominant Lasius neoniger Emery (Hymenoptera: Formicidae), significantly reduced sentinel prey removal rates. Our results suggest that ants disproportionately contribute to ground-based predation of arthropod prey in grasslands. Changes in the amount of grasslands on the landscape and its management may have important implications for ant prevalence and natural prey suppression services in agricultural landscapes.

A global synthesis reveals biodiversity-mediated benefits for crop production

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.

Grassland harvesting alters ant community trophic structure: An isotopic study in tallgrass prairies

Disturbances have long been recognized as important forces for structuring natural communities but their effects on trophic structure are not well understood, particularly in terrestrial systems. This is in part because quantifying trophic linkages is a challenge, especially for small organisms with cryptic feeding behaviors such as insects, and often relies on conducting labor-intensive feeding trials or extensive observations in the field. In this study, we used stable isotopes of carbon and nitrogen to examine how disturbance (annual biomass harvesting) in tallgrass prairies affected the trophic position, trophic range, and niche space of ants, a widespread grassland consumer. We hypothesized that biomass harvest would remove important food and nesting resources of insects thus affecting ant feeding relationships and trophic structure. We found shifts in the feeding relationships inferred by isotopic signatures with harvest. In particular, these shifts suggest that ants within harvest sites utilized resources at lower trophic levels (possibly plant-based resources or herbivores), expanded trophic breadth, and occupied different niche spaces. Shifts in resource use following harvest could be due to harvest-mediated changes in both the plant and arthropod communities that might affect the strength of competition or alter plant nitrogen availability. Because shifts in resource use alter the flow of nutrients across the food web, disturbance effects on ants could have ecosystem-level consequences through nutrient cycling.

An improved method for utilizing high-throughput amplicon sequencing to determine the diets of insectivorous animals

DNA analysis of predator faeces using high-throughput amplicon sequencing (HTS) enhances our understanding of predator-prey interactions. However, conclusions drawn from this technique are constrained by biases that occur in multiple steps of the HTS workflow. To better characterize insectivorous animal diets, we used DNA from a diverse set of arthropods to assess PCR biases of commonly used and novel primer pairs for the mitochondrial gene, cytochrome oxidase C subunit 1 (COI). We compared diversity recovered from HTS of bat guano samples using a commonly used primer pair "ZBJ" to results using the novel primer pair "ANML." To parameterize our bioinformatics pipeline, we created an arthropod mock community consisting of single-copy (cloned) COI sequences. To examine biases associated with both PCR and HTS, mock community members were combined in equimolar amounts both pre- and post-PCR. We validated our system using guano from bats fed known diets and using composite samples of morphologically identified insects collected in pitfall traps. In PCR tests, the ANML primer pair amplified 58 of 59 arthropod taxa (98%), whereas ZBJ amplified 24-40 of 59 taxa (41%-68%). Furthermore, in an HTS comparison of field-collected samples, the ANML primers detected nearly fourfold more arthropod taxa than the ZBJ primers. The additional arthropods detected include medically and economically relevant insect groups such as mosquitoes. Results revealed biases at both the PCR and sequencing levels, demonstrating the pitfalls associated with using HTS read numbers as proxies for abundance. The use of an arthropod mock community allowed for improved bioinformatics pipeline parameterization.

Harvesting effects on wild bee communities in bioenergy grasslands depend on nesting guild

Conversion of annual crops to native perennial grasslands for bioenergy production may help conserve wild bees by enhancing nest and food resources. However, bee response to the disturbance of biomass harvesting may depend on their nesting location, thus their vulnerability to nest destruction, and the response of the forb community on which they forage. Moreover, because bees have long foraging ranges, effects of local harvesting may depend on the amount of natural habitat in the surrounding landscape. We performed a large-scale one- and two-year experiment in Michigan and Wisconsin, USA, respectively, to examine how grassland harvesting, landscape context, and study year affect the forb community, above- and belowground-nesting bee species richness, community composition, trap nest emergence, and visitation rate. In Wisconsin, harvesting increased forb richness, cover, and evenness compared to unharvested control sites. Harvesting negatively affected aboveground-nesting bee richness and emergence from trap nests, possibly because of nest destruction during the previous harvest. By contrast, harvesting positively affected belowground-nesting bee richness, possibly because of the greater food resource availability and reduced thatch allowing greater access to nesting sites in the soil. Harvesting also affected bee community composition, reflecting the increase in belowground-nesting species at harvested sites. Despite harvesting effects on forb and bee communities, there was no effect on flower visitation rate, indicating little effect on pollination function. We did not find a harvest by landscape context interaction, which, in combination with the negative harvesting effect on trap nest emergence, suggests that harvesting can affect local population growth rather than simply affecting forager aggregation in different resource environments. For bees, there was no harvest by study year interaction, indicating a consistent response over a short timescale. Similarly, in Michigan, belowground-nesting species also responded positively to harvesting, which was more pronounced in sandier soils that are preferred for nesting. However, other components of the Michigan bee and forb communities were not significantly affected by biomass harvesting. Overall, our study demonstrates that harvesting grasslands can positively affect the ~80% of bee species that nest belowground by enhancing nest and/or forage resources, but that conserving aboveground nesters may require leaving some area unharvested.

Collaboration Matters: Honey Bee Health as a Transdisciplinary Model for Understanding Real-World Complexity

We develop a transdisciplinary deliberative model that moves beyond traditional scientific collaborations to include nonscientists in designing complexity-oriented research. We use the case of declining honey bee health as an exemplar of complex real-world problems requiring cross-disciplinary intervention. Honey bees are important pollinators of the fruits and vegetables we eat. In recent years, these insects have been dying at alarming rates. To prompt the reorientation of research toward the complex reality in which bees face multiple challenges, we came together as a group, including beekeepers, farmers, and scientists. Over a 2-year period, we deliberated about how to study the problem of honey bee deaths and conducted field experiments with bee colonies. We show trust and authority to be crucial factors shaping such collaborative research, and we offer a model for structuring collaboration that brings scientists and nonscientists together with the key objects and places of their shared concerns across time.

Do managed bees have negative effects on wild bees?: A systematic review of the literature

Managed bees are critical for crop pollination worldwide. As the demand for pollinator-dependent crops increases, so does the use of managed bees. Concern has arisen that managed bees may have unintended negative impacts on native wild bees, which are important pollinators in both agricultural and natural ecosystems. The goal of this study was to synthesize the literature documenting the effects of managed honey bees and bumble bees on wild bees in three areas: (1) competition for floral and nesting resources, (2) indirect effects via changes in plant communities, including the spread of exotic plants and decline of native plants, and (3) transmission of pathogens. The majority of reviewed studies reported negative effects of managed bees, but trends differed across topical areas. Of studies examining competition, results were highly variable with 53% reporting negative effects on wild bees, while 28% reported no effects and 19% reported mixed effects (varying with the bee species or variables examined). Equal numbers of studies examining plant communities reported positive (36%) and negative (36%) effects, with the remainder reporting no or mixed effects. Finally, the majority of studies on pathogen transmission (70%) reported potential negative effects of managed bees on wild bees. However, most studies across all topical areas documented the potential for impact (e.g. reporting the occurrence of competition or pathogens), but did not measure direct effects on wild bee fitness, abundance, or diversity. Furthermore, we found that results varied depending on whether managed bees were in their native or non-native range; managed bees within their native range had lesser competitive effects, but potentially greater effects on wild bees via pathogen transmission. We conclude that while this field has expanded considerably in recent decades, additional research measuring direct, long-term, and population-level effects of managed bees is needed to understand their potential impact on wild bees.

A global synthesis of the effects of diversified farming systems on arthropod diversity within fields and across agricultural landscapes

Agricultural intensification is a leading cause of global biodiversity loss, which can reduce the provisioning of ecosystem services in managed ecosystems. Organic farming and plant diversification are farm management schemes that may mitigate potential ecological harm by increasing species richness and boosting related ecosystem services to agroecosystems. What remains unclear is the extent to which farm management schemes affect biodiversity components other than species richness, and whether impacts differ across spatial scales and landscape contexts. Using a global metadataset, we quantified the effects of organic farming and plant diversification on abundance, local diversity (communities within fields), and regional diversity (communities across fields) of arthropod pollinators, predators, herbivores, and detritivores. Both organic farming and higher in-field plant diversity enhanced arthropod abundance, particularly for rare taxa. This resulted in increased richness but decreased evenness. While these responses were stronger at local relative to regional scales, richness and abundance increased at both scales, and richness on farms embedded in complex relative to simple landscapes. Overall, both organic farming and in-field plant diversification exerted the strongest effects on pollinators and predators, suggesting these management schemes can facilitate ecosystem service providers without augmenting herbivore (pest) populations. Our results suggest that organic farming and plant diversification promote diverse arthropod metacommunities that may provide temporal and spatial stability of ecosystem service provisioning. Conserving diverse plant and arthropod communities in farming systems therefore requires sustainable practices that operate both within fields and across landscapes.

Gut microbiomes of mobile predators vary with landscape context and species identity

Landscape context affects predator–prey interactions and predator diet composition, yet little is known about landscape effects on insect gut microbiomes, a determinant of physiology and condition. Here, we combine laboratory and field experiments to examine the effects of landscape context on the gut bacterial community and body condition of predatory insects. Under laboratory conditions, we found that prey diversity increased bacterial richness in insect guts. In the field, we studied the performance and gut microbiota of six predatory insect species along a landscape complexity gradient in two local habitat types (soybean fields vs. prairie). Insects from soy fields had richer gut bacteria and lower fat content than those from prairies, suggesting better feeding conditions in prairies. Species origin mediated landscape context effects, suggesting differences in foraging of exotic and native predators on a landscape scale. Overall, our study highlights complex interactions among gut microbiota, predator identity, and landscape context.

Distinct Stages of Moment-to-Moment Processing in the Cinguloopercular and Frontoparietal Networks

Control of goal-directed tasks is putatively carried out via the cinguloopercular (CO) and frontoparietal (FP) systems. However, it remains unclear whether these systems show dissociable moment-to-moment processing during distinct stages of a trial. Here, we characterize dynamics in the CO and FP networks in a meta-analysis of 5 decision-making tasks using fMRI, with a specialized "slow reveal" paradigm which allows us to measure the temporal characteristics of trial responses. We find that activations in left FP, right FP, and CO systems form separate clusters, pointing to distinct roles in decision-making. Left FP shows early "accumulator-like" responses, suggesting a role in pre-decision processing. CO has a late onset and transient response linked to the decision event, suggesting a role in performance reporting. The majority of right FP regions show late onsets with prolonged responses, suggesting a role in post-recognition processing. These findings expand upon past models, arguing that the CO and FP systems relate to distinct stages of processing within a trial. Furthermore, the findings provide evidence for a heterogeneous profile in the FP network, with left and right FP taking on specialized roles. This evidence informs our understanding of how distinct control networks may coordinate moment-to-moment components of complex actions.

From pest data to abundance-based risk maps combining eco-physiological knowledge, weather, and habitat variability

Noxious species, i.e., crop pest or invasive alien species, are major threats to both natural and managed ecosystems. Invasive pests are of special importance, and knowledge about their distribution and abundance is fundamental to minimize economic losses and prioritize management activities. Occurrence models are a common tool used to identify suitable zones and map priority areas (i.e., risk maps) for noxious species management, although they provide a simplified description of species dynamics (i.e., no indication on species density). An alternative is to use abundance models, but translating abundance data into risk maps is often challenging. Here, we describe a general framework for generating abundance-based risk maps using multi-year pest data. We used an extensive data set of 3968 records collected between 2003 and 2013 in Wisconsin during annual surveys of soybean aphid (SBA), an exotic invasive pest in this region. By using an integrative approach, we modelled SBA responses to weather, seasonal, and habitat variability using generalized additive models (GAMs). Our models showed good to excellent performance in predicting SBA occurrence and abundance (TSS = 0.70, AUC = 0.92; R²  = 0.63). We found that temperature, precipitation, and growing degree days were the main drivers of SBA trends. In addition, a significant positive relationship between SBA abundance and the availability of overwintering habitats was observed. Our models showed aphid populations were also sensitive to thresholds associated with high and low temperatures, likely related to physiological tolerances of the insects. Finally, the resulting aphid predictions were integrated using a spatial prioritization algorithm ("Zonation") to produce an abundance-based risk map for the state of Wisconsin that emphasized the spatiotemporal consistency and magnitude of past infestation patterns. This abundance-based risk map can provide information on potential foci of pest outbreaks where scouting efforts and prophylactic measures should be concentrated. The approach we took is general, relatively simple, and can be applied to other species, habitats and geographical areas for which species abundance data and biotic and abiotic data are available.

Ecoinformatics (Big Data) for Agricultural Entomology: Pitfalls, Progress, and Promise

Ecoinformatics, as defined in this review, is the use of preexisting data sets to address questions in ecology. We provide the first review of ecoinformatics methods in agricultural entomology. Ecoinformatics methods have been used to address the full range of questions studied by agricultural entomologists, enabled by the special opportunities associated with data sets, nearly all of which have been observational, that are larger and more diverse and that embrace larger spatial and temporal scales than most experimental studies do. We argue that ecoinformatics research methods and traditional, experimental research methods have strengths and weaknesses that are largely complementary. We address the important interpretational challenges associated with observational data sets, highlight common pitfalls, and propose some best practices for researchers using these methods. Ecoinformatics methods hold great promise as a vehicle for capitalizing on the explosion of data emanating from farmers, researchers, and the public, as novel sampling and sensing techniques are developed and digital data sharing becomes more widespread.

Positive feedback between chironomids and algae creates net mutualism between benthic primary consumers and producers

The chironomids of Lake Mývatn show extreme population fluctuations that affect most aspects of the lake ecosystem. During periods of high chironomid densities, chironomid larvae comprise over 90% of aquatic secondary production. Here, we show that chironomid larvae substantially stimulate benthic gross primary production (GPP) and net primary production (NPP), despite consuming benthic algae. Benthic GPP in experimental mesocosms with 140,000 larvae/m² was 71% higher than in mesocosms with no larvae. Similarly, chlorophyll a concentrations in mesocosms increased significantly over the range of larval densities. Furthermore, larvae showed increased growth rates at higher densities, possibly due to greater benthic algal availability in these treatments. We investigated the hypothesis that larvae promote benthic algal growth by alleviating nutrient limitation, and found that (1) larvae have the potential to cycle the entire yearly external loadings of nitrogen and phosphorus during the growing season, and (2) chlorophyll a concentrations were significantly greater in close proximity to larvae (on larval tubes). The positive feedback between chironomid larvae and benthic algae generated a net mutualism between the primary consumer and primary producer trophic levels in the benthic ecosystem. Thus, our results give an example in which unexpected positive feedbacks can lead to both high primary and high secondary production.

Explicit modeling of abiotic and landscape factors reveals precipitation and forests associated with aphid abundance

Increases in natural or noncrop habitat surrounding agricultural fields have been shown to be correlated with declines in insect crop pests. However, these patterns are highly variable across studies suggesting other important factors, such as abiotic drivers, which are rarely included in landscape models, may also contribute to variability in insect population abundance. The objective of this study was to explicitly account for the contribution of temperature and precipitation, in addition to landscape composition, on the abundance of a widespread insect crop pest, the soybean aphid (Aphis glycines Matsumura), in Wisconsin soybean fields. We hypothesized that higher soybean aphid abundance would be associated with higher heat accumulation (e.g., growing degree days) and increasing noncrop habitat in the surrounding landscape, due to the presence of the overwintering primary hosts of soybean aphid. To evaluate these hypotheses, we used an ecoinformatics approach that relied on a large dataset collected across Wisconsin over a 9-year period (2003-2011), for an average of 235 sites per year (n = 2,110 fields total). We determined surrounding landscape composition (1.5-km radius) using publicly available satellite-derived land cover imagery and interpolated daily temperature and precipitation information from the National Weather Service COOP weather station network. We constructed linear mixed models for soybean aphid abundance based on abiotic and landscape explanatory variables and applied model averaging for prediction using an information theoretic framework. Over this broad spatial and temporal extent in Wisconsin, we found that variation in growing season precipitation was positively related to soybean aphid abundance, while higher precipitation during the nongrowing season had a negative effect on aphid populations. Additionally, we found that aphid populations were higher in areas with proportionally more forest but were lower in areas where minor crops, such as small grains, were more prevalent. Thus, our findings support our hypothesis that including abiotic drivers increases our understanding of crop pest abundance and distribution. Moreover, by explicitly modeling abiotic factors, we may be able to explore how variable climate in tandem with land cover patterns may affect current and future insect populations, with potentially critical implications for crop yields and agricultural food webs.

A Landscape View of Agricultural Insecticide Use across the Conterminous US from 1997 through 2012

Simplification of agricultural landscapes is expected to have positive effects on many crop pests and negative effects on their natural enemies, potentially leading to increased pest pressure, decreased crop yield, and increased insecticide use. While many intermediate links in this causal chain have empirical support, there is mixed evidence for ultimate relationships between landscape simplification, crop yield, and insecticide use, especially at large spatial and temporal scales. We explored relationships between landscape simplification (proportion of a county in harvested cropland) and insecticide use (proportion of harvested cropland treated with insecticides), using county-level data from the US Census of Agriculture and a variety of standard and spatiotemporal regression techniques. The best model indicated that insecticide use across the US has increased between 1997 and 2012, was strongly dependent on the crops grown in a county, increased with average farm income and size, and increased with annual growing degree days. After accounting for those variables, and other unidentified spatial and temporal structure in the data, there remained a statistically significant, moderate, positive relationship between insecticide use and landscape simplification. These results lend general support to the causal chain outlined above, and to the notion that a landscape perspective is useful for managing ecosystem services that are provided by mobile organisms and valuable to agriculture.

Flexible foraging shapes the topology of plant-pollinator interaction networks

In plant-pollinator networks, foraging choices by pollinators help form the connecting links between species. Flexible foraging should therefore play an important role in defining network topology. Factors such as morphological trait complementarity limit a pollinator's pool of potential floral resources, but which potential resource species are actually utilized at a location depends on local environmental and ecological context. Pollinators can be highly flexible foragers, but the effect of this flexibility on network topology remains unclear. To understand how flexible foraging affects network topology, we examined differences between sets of locally realized interactions and corresponding sets of potential interactions within 25 weighted plant-pollinator networks in two different regions of the United States. We examined two possible mechanisms for flexible foraging effects on realized networks: (1) preferential targeting of higher-density plant resources, which should increase network nestedness, and (2) context-dependent resource partitioning driven by interspecific competition, which should increase modularity and complementary specialization. We found that flexible foraging has strong effects on realized network topology. Realized connectance was much lower than connectance based on potential interactions, indicating a local narrowing of diet breadth. Moreover, the foraging choices pollinators made, which particular plant species to visit and at what rates, resulted in networks that were significantly less nested and significantly more modular and specialized than their corresponding networks of potential interactions. Preferentially foraging on locally abundant resources was not a strong driver of the realization of potential interactions. However, the degree of modularity and complementary specialization both increased with the number of competing pollinator species and with niche availability. We therefore conclude that flexible foraging affects realized network topology more strongly through resource partitioning than through focusing on high-density resources.

Contrasting Foraging Patterns: Testing Resource-Concentration and Dilution Effects with Pollinators and Seed Predators

Resource concentration effects occur when high resource density patches attract and support more foragers than low density patches. In contrast, resource dilution effects can occur if high density patches support fewer consumers. In this study, we examined the foraging rates of pollinators and seed predators on two perennial plant species (Rudbeckia triloba and Verbena stricta) as functions of resource density. Specifically, we examined whether resource-dense patches (densities of flower and seeds on individual plants) resulted in greater visitation and seed removal rates, respectively. We also examined whether foraging rates were context-dependent by conducting the study in two sites that varied in resource densities. For pollinators, we found negative relationships between the density of flowers per plant and visitation rates, suggesting dilution effects. For seed predators, we found positive relationships consistent with concentration effects. Saturation effects and differences in foraging behaviors might explain the opposite relationships; most of the seed predators were ants (recruitment-based foragers), and pollinators were mostly solitary foragers. We also found that foraging rates were site-dependent, possibly due to site-level differences in resource abundance and consumer densities. These results suggest that these two plant species may benefit from producing as many flowers as possible, given high levels of pollination and low seed predation.

Evidence for Compensatory Photosynthetic and Yield Response of Soybeans to Aphid Herbivory

The soybean aphid, Aphis glycines Matsumura, an exotic species in North America that has been detected in 21 U.S. states and Canada, is a major pest for soybean that can reduce maximum photosynthetic capacity and yields. Our existing knowledge is based on relatively few studies that do not span a wide variety of environmental conditions, and often focus on relatively high and damaging population pressure. We examined the effects of varied populations and duration of soybean aphids on soybean photosynthetic rates and yield in two experiments. In a 2011 field study, we found that plants with low cumulative aphid days (CAD, less than 2,300) had higher yields than plants not experiencing significant aphid pressure, suggesting a compensatory growth response to low aphid pressure. This response did not hold at higher CAD, and yields declined. In a 2013 controlled-environment greenhouse study, soybean plants were well-watered and fertilized with nitrogen (N), and aphid populations were manipulated to reach moderate to high levels (8,000-50,000 CAD). Plants tolerated these population levels when aphids were introduced during the vegetative or reproductive phenological stages of the plant, showing no significant reduction in yield. Leaf N concentration and CAD were positively and significantly correlated with increasing ambient photosynthetic rates. Our findings suggest that, given the right environmental conditions, modern soybean plants can withstand higher aphid pressure than previously assumed. Moreover, soybean plants also responded positively through a compensatory photosynthetic effect to moderate population pressure, contributing to stable or increased yield.

The rise of novelty in ecosystems

Rapid and ongoing change creates novelty in ecosystems everywhere, both when comparing contemporary systems to their historical baselines, and predicted future systems to the present. However, the level of novelty varies greatly among places. Here we propose a formal and quantifiable definition of abiotic and biotic novelty in ecosystems, map abiotic novelty globally, and discuss the implications of novelty for the science of ecology and for biodiversity conservation. We define novelty as the degree of dissimilarity of a system, measured in one or more dimensions relative to a reference baseline, usually defined as either the present or a time window in the past. In this conceptualization, novelty varies in degree, it is multidimensional, can be measured, and requires a temporal and spatial reference. This definition moves beyond prior categorical definitions of novel ecosystems, and does not include human agency, self-perpetuation, or irreversibility as criteria. Our global assessment of novelty was based on abiotic factors (temperature, precipitation, and nitrogen deposition) plus human population, and shows that there are already large areas with high novelty today relative to the early 20th century, and that there will even be more such areas by 2050. Interestingly, the places that are most novel are often not the places where absolute changes are largest; highlighting that novelty is inherently different from change. For the ecological sciences, highly novel ecosystems present new opportunities to test ecological theories, but also challenge the predictive ability of ecological models and their validation. For biodiversity conservation, increasing novelty presents some opportunities, but largely challenges. Conservation action is necessary along the entire continuum of novelty, by redoubling efforts to protect areas where novelty is low, identifying conservation opportunities where novelty is high, developing flexible yet strong regulations and policies, and establishing long-term experiments to test management approaches. Meeting the challenge of novelty will require advances in the science of ecology, and new and creative. conservation approaches.

Trophic cascades in agricultural landscapes: indirect effects of landscape composition on crop yield

The strength and prevalence of trophic cascades, defined as positive, indirect effects of natural enemies (predatory and parasitic arthropods) on plants, is highly variable in agroecosystems. This variation may in part be due to the spatial or landscape context in which hese trophic cascades occur. In 2011 and 2012, we conducted a natural enemy exclusion experiment in soybean fields along a gradient of landscape composition across southern Wisconsin and Michigan, USA. We used structural equation modeling to ask (1) whether natural enemies influence biocontrol of soybean aphids (SBA) and soybean yield and (2) whether landscape effects on natural enemies influence the strength of the trophic cascades. We found that natural enemies (NE) suppressed aphid populations in both years of our study, and, in 2011, the yield of soybean plants exposed to natural enemies was 37% higher than the yield of plants with aphid populations protected from natural enemies. The strength of the :rophic cascade was also influenced by landscape context. We found that landscapes with a higher proportion of soybean and higher diversity habitats resulted in more NE, fewer aphids, and, in some cases, a trend toward greater soybean yield. These results indicate that landscape context is important for understanding spatial variability in biocontrol and yield, but other factors, such as environmental variability and compensatory growth, might overwhelm the beneficial effects of biocontrol on crop yield.

Taking the trophic bypass: aquatic-terrestrial linkage reduces methylmercury in a terrestrial food web

Ecosystems can be linked by the movement of matter and nutrients across habitat boundaries via aquatic insect emergence. Aquatic organisms tend to have higher concentrations of certain toxic contaminants such as methylmercury (MeHg) compared to their terrestrial counterparts. If aquatic organisms come to land, terrestrial organisms that consume them are expected to have elevated MeHg concentrations. But emergent aquatic insects could have other impacts as well, such as altering consumer trophic position or increasing ecosystem productivity as a result of nutrient inputs from insect carcasses. We measure MeHg in terrestrial arthropods at two lakes in northeastern Iceland and use carbon and nitrogen stable isotopes to quantify aquatic reliance and trophic position. Across all terrestrial focal arthropod taxa (Lycosidae, Linyphiidae, Acari, Opiliones), aquatic reliance had significant direct and indirect (via changes in trophic position) effects on terrestrial consumer MeHg. However, contrary to our expectations, terrestrial consumers that consumed aquatic prey had lower MeHg concentrations than consumers that ate mostly terrestrial prey. We hypothesize that this is due to the lower trophic position of consumers feeding directly on midges relative to those that fed mostly on terrestrial prey and that had, on average, higher trophic positions. Thus, direct consumption of aquatic inputs results in a trophic bypass that creates a shorter terrestrial food web and reduced biomagnification of MeHg across the food web. Our finding that MeHg was lower at terrestrial sites with aquatic inputs runs counter to the conventional wisdom that aquatic systems are a source of MeHg contamination to surrounding terrestrial ecosystems.

Modeling pollinator community response to contrasting bioenergy scenarios

In the United States, policy initiatives aimed at increasing sources of renewable energy are advancing bioenergy production, especially in the Midwest region, where agricultural landscapes dominate. While policy directives are focused on renewable fuel production, biodiversity and ecosystem services will be impacted by the land-use changes required to meet production targets. Using data from field observations, we developed empirical models for predicting abundance, diversity, and community composition of flower-visiting bees based on land cover. We used these models to explore how bees might respond under two contrasting bioenergy scenarios: annual bioenergy crop production and perennial grassland bioenergy production. In the two scenarios, 600,000 ha of marginal annual crop land or marginal grassland were converted to perennial grassland or annual row crop bioenergy production, respectively. Model projections indicate that expansion of annual bioenergy crop production at this scale will reduce bee abundance by 0 to 71%, and bee diversity by 0 to 28%, depending on location. In contrast, converting annual crops on marginal soil to perennial grasslands could increase bee abundance from 0 to 600% and increase bee diversity between 0 and 53%. Our analysis of bee community composition suggested a similar pattern, with bee communities becoming less diverse under annual bioenergy crop production, whereas bee composition transitioned towards a more diverse community dominated by wild bees under perennial bioenergy crop production. Models, like those employed here, suggest that bioenergy policies have important consequences for pollinator conservation.

Insects as drivers of ecosystem processes

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.

Perennial grasslands enhance biodiversity and multiple ecosystem services in bioenergy landscapes

Agriculture is being challenged to provide food, and increasingly fuel, for an expanding global population. Producing bioenergy crops on marginal lands--farmland suboptimal for food crops--could help meet energy goals while minimizing competition with food production. However, the ecological costs and benefits of growing bioenergy feedstocks--primarily annual grain crops--on marginal lands have been questioned. Here we show that perennial bioenergy crops provide an alternative to annual grains that increases biodiversity of multiple taxa and sustain a variety of ecosystem functions, promoting the creation of multifunctional agricultural landscapes. We found that switchgrass and prairie plantings harbored significantly greater plant, methanotrophic bacteria, arthropod, and bird diversity than maize. Although biomass production was greater in maize, all other ecosystem services, including methane consumption, pest suppression, pollination, and conservation of grassland birds, were higher in perennial grasslands. Moreover, we found that the linkage between biodiversity and ecosystem services is dependent not only on the choice of bioenergy crop but also on its location relative to other habitats, with local landscape context as important as crop choice in determining provision of some services. Our study suggests that bioenergy policy that supports coordinated land use can diversify agricultural landscapes and sustain multiple critical ecosystem services.

Ecosystem-service tradeoffs associated with switching from annual to perennial energy crops in riparian zones of the US Midwest

Integration of energy crops into agricultural landscapes could promote sustainability if they are placed in ways that foster multiple ecosystem services and mitigate ecosystem disservices from existing crops. We conducted a modeling study to investigate how replacing annual energy crops with perennial energy crops along Wisconsin waterways could affect a variety of provisioning and regulating ecosystem services. We found that a switch from continuous corn production to perennial-grass production decreased annual income provisioning by 75%, although it increased annual energy provisioning by 33%, decreased annual phosphorous loading to surface water by 29%, increased below-ground carbon sequestration by 30%, decreased annual nitrous oxide emissions by 84%, increased an index of pollinator abundance by an average of 11%, and increased an index of biocontrol potential by an average of 6%. We expressed the tradeoffs between income provisioning and other ecosystem services as benefit-cost ratios. Benefit-cost ratios averaged 12.06 GJ of additional net energy, 0.84 kg of avoided phosphorus pollution, 18.97 Mg of sequestered carbon, and 1.99 kg of avoided nitrous oxide emissions for every $1,000 reduction in income. These ratios varied spatially, from 2- to 70-fold depending on the ecosystem service. Benefit-cost ratios for different ecosystem services were generally correlated within watersheds, suggesting the presence of hotspots – watersheds where increases in multiple ecosystem services would come at lower-than-average opportunity costs. When assessing the monetary value of ecosystem services relative to existing conservation programs and environmental markets, the overall value of enhanced services associated with adoption of perennial energy crops was far lower than the opportunity cost. However, when we monitized services using estimates for the social costs of pollution, the value of enhanced services far exceeded the opportunity cost. This disparity between recoverable costs and social value represents a fundamental challenge to expansion of perennial energy crops and sustainable agricultural landscapes.