Shifts in competitive structures can drive variation in species' phenology.

For many species, a well documented response to anthropogenic climate change is a shift in various aspects of its life history, including its timing or phenology. Often, these phenological shifts are associated with changes in abiotic factors used as proxies for resource availability or other suitable conditions. Resource availability, however, can also be impacted by competition, but the impact of competition on phenology is less studied than abiotic drivers. We fit generalized additive models (GAMs) to a long-term experimental dataset on small mammals monitored in the southwestern United States and show that altered competitive landscapes can drive shifts in breeding timing and prevalence, and that, relative to a dominant competitor, other species exhibit less specific responses to environmental factors. These results suggest that plasticity of phenological responses, which is often described in the context of annual variation in abiotic factors, can occur in response to biotic context as well. Variation in phenological responses under different biotic conditions shown here further demonstrates that a more nuanced understanding of shifting biotic interactions is useful to better understand and predict biodiversity patterns in a changing world.

A general deep learning model for bird detection in high-resolution airborne imagery.

Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it requires large amounts of human-labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting. This limits application across space and time. One solution is developing generalized models that can be applied across species and ecosystems. Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increases these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. Retraining from the general model improves local predictions even when moderately large annotation sets are available and makes model training faster and more stable. Our results demonstrate that general models for detecting broad classes of organisms using airborne imagery are achievable. These models can reduce the effort, expertise, and computational resources necessary for automating the detection of individual organisms across large scales, helping to transform the scale of data collection in ecology and the questions that can be addressed.

Maintenance of community function through compensation breaks down over time in a desert rodent community.

Understanding the ecological processes that maintain community function in systems experiencing species loss, and how these processes change over time, is key to understanding the relationship between community structure and function and predicting how communities may respond to perturbations in the Anthropocene. Using a 30-year experiment on desert rodents, we show that the impact of species loss on community-level energy use has changed repeatedly and dramatically over time, due to (1) the addition of new species to the community, and (2) a reduction in functional redundancy among the same set of species. Although strong compensation, initially driven by the dispersal of functionally redundant species to the local community, occurred in this system from 1997 to 2010, since 2010, compensation has broken down due to decreasing functional overlap within the same set of species. Simultaneously, long-term changes in sitewide community composition due to niche complementarity have decoupled the dynamics of compensation from the overall impact of species loss on community-level energy use. Shifting, context-dependent compensatory dynamics, such as those demonstrated here, highlight the importance of explicitly long-term, metacommunity, and eco-evolutionary perspectives on the link between species-level fluctuations and community function in a changing world.

Empirical abundance distributions are more uneven than expected given their statistical baseline.

Exploring and accounting for the emergent properties of ecosystems as complex systems is a promising horizon in the search for general processes to explain common ecological patterns. For example the ubiquitous hollow-curve form of the species abundance distribution is frequently assumed to reflect ecological processes structuring communities, but can also emerge as a statistical phenomenon from the mathematical definition of an abundance distribution. Although the hollow curve may be a statistical artefact, ecological processes may induce subtle deviations between empirical species abundance distributions and their statistically most probable forms. These deviations may reflect biological processes operating on top of mathematical constraints and provide new avenues for advancing ecological theory. Examining ~22,000 communities, we found that empirical SADs are highly uneven and dominated by rare species compared to their statistical baselines. Efforts to detect deviations may be less informative in small communities-those with few species or individuals-because these communities have poorly resolved statistical baselines. The uneven nature of many empirical SADs demonstrates a path forward for leveraging complexity to understand ecological processes governing the distribution of abundance, while the issues posed by small communities illustrate the limitations of using this approach to study ecological patterns in small samples.

Evaluating probabilistic ecological forecasts.

Probabilistic near-term forecasting facilitates evaluation of model predictions against observations and is of pressing need in ecology to inform environmental decision-making and effect societal change. Despite this imperative, many ecologists are unfamiliar with the widely used tools for evaluating probabilistic forecasts developed in other fields. We address this gap by reviewing the literature on probabilistic forecast evaluation from diverse fields including climatology, economics, and epidemiology. We present established practices for selecting evaluation data (end-sample hold out), graphical forecast evaluation (times-series plots with uncertainty, probability integral transform plots), quantitative evaluation using scoring rules (log, quadratic, spherical, and ranked probability scores), and comparing scores across models (skill score, Diebold-Mariano test). We cover common approaches, highlight mathematical concepts to follow, and note decision points to allow application of general principles to specific forecasting endeavors. We illustrate these approaches with an application to a long-term rodent population time series currently used for ecological forecasting and discuss how ecology can continue to learn from and drive the cross-disciplinary field of forecasting science.

Declines in rodent abundance and diversity track regional climate variability in North American drylands.

Regional long-term monitoring can enhance the detection of biodiversity declines associated with climate change, improving future projections by reducing reliance on space-for-time substitution and increasing scalability. Rodents are diverse and important consumers in drylands, regions defined by the scarcity of water that cover 45% of Earth's land surface and face increasingly drier and more variable climates. We analyzed abundance data for 22 rodent species across grassland, shrubland, ecotone, and woodland ecosystems in the southwestern USA. Two time series (1995-2006 and 2004-2013) coincided with phases of the Pacific Decadal Oscillation (PDO), which influences drought in southwestern North America. Regionally, rodent species diversity declined 20%-35%, with greater losses during the later time period. Abundance also declined regionally, but only during 2004-2013, with losses of 5% of animals captured. During the first time series (wetter climate), plant productivity outranked climate variables as the best regional predictor of rodent abundance for 70% of taxa, whereas during the second period (drier climate), climate best explained variation in abundance for 60% of taxa. Temporal dynamics in diversity and abundance differed spatially among ecosystems, with the largest declines in woodlands and shrublands of central New Mexico and Colorado. Which species were winners or losers under increasing drought and amplified interannual variability in drought depended on ecosystem type and the phase of the PDO. Fewer taxa were significant winners (18%) than losers (30%) under drought, but the identities of winners and losers differed among ecosystems for 70% of taxa. Our results suggest that the sensitivities of rodent species to climate contributed to regional declines in diversity and abundance during 1995-2013. Whether these changes portend future declines in drought-sensitive consumers in the southwestern USA will depend on the climate during the next major PDO cycle.

InsectChange: a global database of temporal changes in insect and arachnid assemblages.

Insects are the most ubiquitous and diverse group of eukaryotic organisms on Earth, forming a crucial link in terrestrial and freshwater food webs. They have recently become the subject of headlines because of observations of dramatic declines in some places. Although there are hundreds of long-term insect monitoring programs, a global database for long-term data on insect assemblages has so far remained unavailable. In order to facilitate synthetic analyses of insect abundance changes, we compiled a database of long-term (≥10 yr) studies of assemblages of insects (many also including arachnids) in the terrestrial and freshwater realms. We searched the scientific literature and public repositories for data on insect and arachnid monitoring using standardized protocols over a time span of 10 yr or longer, with at least two sampling events. We focused on studies that presented or allowed calculation of total community abundance or biomass. We extracted data from tables, figures, and appendices, and, for data sets that provided raw data, we standardized trapping effort over space and time when necessary. For each site, we extracted provenance details (such as country, state, and continent) as well as information on protection status, land use, and climatic details from publicly available GIS sources. In all, the database contains 1,668 plot-level time series sourced from 165 studies with samples collected between 1925 and 2018. Sixteen data sets provided here were previously unpublished. Studies were separated into those collected in the terrestrial realm (103 studies with a total of 1,053 plots) and those collected in the freshwater realm (62 studies with 615 plots). Most studies were from Europe (48%) and North America (29%), with 34% of the plots located in protected areas. The median monitoring time span was 19 yr, with 12 sampling years. The number of individuals was reported in 129 studies, the total biomass was reported in 13 studies, and both abundance and biomass were reported in 23 studies. This data set is published under a CC-BY license, requiring attribution of the data source. Please cite this paper if the data are used in publications, and respect the licenses of the original sources when using (part of) their data as detailed in Metadata S1: Table 1.

Macroevolution of dimensionless life-history metrics in tetrapods.

Life-history traits represent organisms' strategies to navigate the fitness trade-offs between survival and reproduction. Eric Charnov developed three dimensionless metrics to quantify fundamental life-history trade-offs. Lifetime reproductive effort (LRE), relative reproductive lifespan (RRL) and relative offspring size (ROS), together with body mass can be used to classify life-history strategies across the four major classes of tetrapods: amphibians, reptiles, mammals and birds. First, we investigate how the metrics have evolved in concert with body mass within tetrapod lineages. In most cases, we find evidence for correlated evolution among body mass and the three dimensionless metrics. Second, we compare life-history strategies across the four classes of tetrapods and find that LRE, RRL and ROS delineate a space in which the major tetrapod classes occupy mostly unique subspaces. These distinct combinations of life-history strategies provide us with a framework to understand the impact of major evolutionary transitions in energetics, physiology and ecology.

Ten Simple Rules for a successful remote postdoc.

Postdocs are a critical transition for early-career researchers. This transient period, between finishing a PhD and finding a permanent position, is when early-career researchers develop independent research programs and establish collaborative relationships that can make a successful career. Traditionally, postdocs physically relocate-sometimes multiple times-for these short-term appointments, which creates challenges that can disproportionately affect members of traditionally underrepresented groups in science, technology, engineering, and mathematics (STEM). However, many research activities involving analytical and quantitative work do not require a physical presence in a lab and can be accomplished remotely. Other fields have embraced remote work, yet many academics have been hesitant to hire remote postdocs. In this article, we present advice to both principal investigators (PIs) and postdocs for successfully navigating a remote position. Using the combined experience of the authors (as either remote postdocs or employers of remote postdocs), we provide a road map to overcome the real (and perceived) obstacles associated with remote work. With planning, communication, and creativity, remote postdocs can be a fully functioning and productive member of a research lab. Further, our rules can be useful for research labs generally and can help foster a more flexible and inclusive environment.

Established rodent community delays recovery of dominant competitor following experimental disturbance.

Human activities alter processes that control local biodiversity, causing changes in the abundance and identity of species in ecosystems. However, restoring biodiversity to a previous state is rarely as simple as reintroducing lost species or restoring processes to their pre-disturbance state. Theory suggests that established species can impede shifts in species composition via a variety of mechanisms, including direct interference, pre-empting resources or habitat alteration. These mechanisms can create transitory dynamics that delay convergence to an expected end state. We use an experimental manipulation of a desert rodent community to examine differences in recolonization dynamics of a dominant competitor (kangaroo rats of the genus Dipodomys) when patches were already occupied by an existing rodent community relative to when patches were empty. Recovery of kangaroo rat populations was slow on plots with an established community, taking approximately 2 years, in contrast with rapid recovery on empty plots with no established residents (approx. three months). These results demonstrate that the presence of an established alternate community inhibits recolonization by new species, even those that should be dominant in the community. This has important implications for understanding how biodiversity may change in the future, and what processes may slow or prevent this change.

Temporal changes in species composition affect a ubiquitous species' use of habitat patches.

Across landscapes, shifts in species composition often co-occur with shifts in structural or abiotic habitat features, making it difficult to disentangle the role of competitors and environment on assessments of patch quality. Using over two decades of rodent community data from a long-term experiment, we show that a small, ubiquitous granivore (Chaetodipus penicillatus) shifted its use of different experimental treatments with the establishment of a novel competitor, C. baileyi. Shifts in residency, probability of movement between patches, and the arrival of new individuals in patches altered which treatment supported the highest abundances of C. penicillatus. Our results suggest that the establishment of a new species worsened the quality of the originally preferred treatment, likely by impacting resource availability. Paradoxically, the presence of the new species also increased C. penicillatus' use of the less preferred treatment, potentially through shifts in the competitive network on those plots.

Developing a modern data workflow for regularly updated data.

Over the past decade, biology has undergone a data revolution in how researchers collect data and the amount of data being collected. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. Regularly updated data present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow leverages tools from software development, including version control and continuous integration, to create a modern data management system that automates the pipeline.

Process-based allometry describes the influence of management on orchard tree aboveground architecture.

We evaluated allometric relationships in length, diameter, and mass of branches for two variably managed orchard tree species (tart cherry, Prunus cerasus; apple, Malus spp.). The empirically estimated allometric exponents (a) of the orchard trees were described in the context of two processed-based allometry models that make predictions for a: the West, Brown and Enquist fractal branching model (WBE) and the recently introduced Flow Similarity model (FS). These allometric models make predictions about relationships in plant morphology (e.g., branch mass, diameter, length, volume, surface area) based on constraints imposed on plant growth by physical and physiological processes. We compared our empirical estimates of a to the model predictions to interpret the physiological implications of pruning and management in orchard systems. Our study found strong allometric relationships among the species and individuals studied with limited agreement with the expectations of either model. The 8/3-power law prediction of the mass ∼ diameter relationship by the WBE, indicative of biomechanical limitations, was marginally supported by this study. Length-including allometric relationships deviated from predictions of both models, but shift toward the expectation of flow similarity. In this way, managed orchard trees deviated from strict adherence to the idealized expectations of the models, but still fall within the range of model expectations in many cases despite intensive management.

Long-term community change through multiple rapid transitions in a desert rodent community.

While studies increasingly document long-term change in community composition, whether long-term change occurs gradually or via rapid reorganization events remains unclear. We used Latent Dirichlet Allocation (LDA) and a change-point model to examine the long-term dynamics of a desert rodent community undergoing compositional change over a 38-yr span. Our approach detected three rapid reorganization events, where changes in the relative abundances of dominant and rare species occurred, and a separate period of increased variance in the structure of the community. These events coincided with time periods, possibly related to climate events, where the total abundance of rodents was extremely low. There are a variety of processes that could link low abundance events with a higher probability of rapid ecological transitions, including higher importance of stochastic processes (i.e., competitive interactions or priority effects) and the removal of structuring effects of competitive dominants or incumbent species. Continued study of the dynamics of community change will provide important information not only on the processes structuring communities, but will also provide guidance for forecasting how communities will undergo change in the future.

Integrating community assembly and biodiversity to better understand ecosystem function: the Community Assembly and the Functioning of Ecosystems (CAFE) approach.

The research of a generation of ecologists was catalysed by the recognition that the number and identity of species in communities influences the functioning of ecosystems. The relationship between biodiversity and ecosystem functioning (BEF) is most often examined by controlling species richness and randomising community composition. In natural systems, biodiversity changes are often part of a bigger community assembly dynamic. Therefore, focusing on community assembly and the functioning of ecosystems (CAFE), by integrating both species richness and composition through species gains, losses and changes in abundance, will better reveal how community changes affect ecosystem function. We synthesise the BEF and CAFE perspectives using an ecological application of the Price equation, which partitions the contributions of richness and composition to function. Using empirical examples, we show how the CAFE approach reveals important contributions of composition to function. These examples show how changes in species richness and composition driven by environmental perturbations can work in concert or antagonistically to influence ecosystem function. Considering how communities change in an integrative fashion, rather than focusing on one axis of community structure at a time, will improve our ability to anticipate and predict changes in ecosystem function.

Bees without Flowers: Before Peak Bloom, Diverse Native Bees Find Insect-Produced Honeydew Sugars.

Bee foragers respond to complex visual, olfactory, and extrasensory cues to optimize searches for floral rewards. Their abilities to detect and distinguish floral colors, shapes, volatiles, and ultraviolet signals and even gauge nectar availability from changes in floral humidity or electric fields are well studied. Bee foraging behaviors in the absence of floral cues, however, are rarely considered. We observed 42 species of wild bees visiting inconspicuous, nonflowering shrubs during early spring in a protected Mediterranean habitat. We determined experimentally that these bees were accessing sugary honeydew secretions from scale insects without the aid of standard cues. While honeydew use is known among some social Hymenoptera, its use across a diverse community of solitary bees is a novel observation. The widespread ability of native bees to locate and use unadvertised, nonfloral sugars suggests unappreciated sensory mechanisms and/or the existence of an interspecific foraging network among solitary bees that may influence how native bees cope with scarcity of floral resources and increasing environmental change.

Community assembly and the functioning of ecosystems: how metacommunity processes alter ecosystems attributes.

Recent work linking community structure and ecosystem function has primarily focused on the effects of local species richness but has neglected the dispersal-dependent processes of community assembly that are ultimately involved in determining community structure and its relation to ecosystems. Here we combine simple consumer-resource competition models and metacommunity theory with discussion of case studies to outline how spatial processes within metacommunities can alter community assembly and modify expectations about how species diversity and composition influence ecosystem attributes at local scales. We argue that when community assembly is strongly limited by dispersal, this can constrain ecosystem functioning by reducing positive selection effects (reducing the probability of the most productive species becoming dominant) even though it may often also enhance complementarity (favoring combinations of species that enhance production even though they may not individually be most productive). Conversely, excess dispersal with strong source-sink relations among heterogeneous habitats can reduce ecosystem functioning by swamping local filters that would normally favor better-suited species. Ecosystem function is thus most likely maximized at intermediate levels of dispersal where both of these effects are minimized. In this scenario, we find that the selection effect is maximized, while complementarity is often reduced and local diversity may often be relatively low. Our synthesis emphasizes that it is the entire set of community assembly processes that affect the functioning of ecosystems, not just the part that determines local species richness.

Species-level and community-level responses to disturbance: a cross-community analysis.

Communities are comprised of individual species that respond to changes in their environment depending in part on their niche requirements. These species comprise the biodiversity of any given community. Common biodiversity metrics such as richness, evenness, and the species abundance distribution are frequently used to describe biodiversity across ecosystems and taxonomic groups. While it is increasingly clear that researchers will need to forecast changes in biodiversity, ecology currently lacks a framework for understanding the natural background variability in biodiversity or how biodiversity patterns will respond to environmental change. We predict that while species populations depend on local ecological mechanisms (e.g., niche processes) and should respond strongly to disturbance, community-level properties that emerge from these species should generally be less sensitive to disturbance because they depend on regional mechanisms (e.g., compensatory dynamics). Using published data from terrestrial animal communities, we show that community-level properties were generally resilient under a suite of artificial and natural manipulations. In contrast, species responded readily to manipulation. Our results suggest that community-level measures are poor indicators of change, perhaps because many systems display strong compensatory dynamics maintaining community-level properties. We suggest that ecologists consider using multiple metrics that measure composition and structure in biodiversity response studies.

Patterns of maximum body size evolution in Cenozoic land mammals: eco-evolutionary processes and abiotic forcing.

There is accumulating evidence that macroevolutionary patterns of mammal evolution during the Cenozoic follow similar trajectories on different continents. This would suggest that such patterns are strongly determined by global abiotic factors, such as climate, or by basic eco-evolutionary processes such as filling of niches by specialization. The similarity of pattern would be expected to extend to the history of individual clades. Here, we investigate the temporal distribution of maximum size observed within individual orders globally and on separate continents. While the maximum size of individual orders of large land mammals show differences and comprise several families, the times at which orders reach their maximum size over time show strong congruence, peaking in the Middle Eocene, the Oligocene and the Plio-Pleistocene. The Eocene peak occurs when global temperature and land mammal diversity are high and is best explained as a result of niche expansion rather than abiotic forcing. Since the Eocene, there is a significant correlation between maximum size frequency and global temperature proxy. The Oligocene peak is not statistically significant and may in part be due to sampling issues. The peak in the Plio-Pleistocene occurs when global temperature and land mammal diversity are low, it is statistically the most robust one and it is best explained by global cooling. We conclude that the macroevolutionary patterns observed are a result of the interplay between eco-evolutionary processes and abiotic forcing.