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At least 55 records · Page 3Linked to original sources
USGS2020

Using density surface models to estimate spatio-temporal changes in population densities and trend

Precise measures of population abundance and trend are needed for species conservation; these are most difficult to obtain for rare and rapidly changing populations. We compare uncertainty in densities estimated from spatio–temporal models with that from standard design‐based methods. Spatio–temporal models allow us to target priority areas where, and at times when, a population may most benefit. Generalised additive models were fitted to a 31‐year time series of point‐transect surveys of an endangered Hawaiian forest bird, the Hawai‘i ‘ākepa Loxops coccineus . This allowed us to estimate bird densities over space and time. We used two methods to quantify uncertainty in density estimates from the spatio–temporal model: the delta method (which assumes independence between detection and distribution parameters) and a variance propagation method. With the delta method we observed a 52% decrease in the width of the design‐based 95% confidence interval (CI), while we observed a 37% decrease in CI width when propagating the variance. We mapped bird densities as they changed across space and time, allowing managers to evaluate management actions. Integrating detection function modelling with spatio–temporal modelling exploits survey data more efficiently by producing finer‐grained abundance estimates than are possible with design‐based methods as well as producing more precise abundance estimates. Model‐based approaches require switching from making assumptions about the survey design to assumptions about bird distribution. Such a switch warrants consideration. In this case the model‐based approach benefits conservation planning through improved management efficiency and reduced costs by taking into account both spatial shifts and temporal changes in population abundance and distribution.

Hawaii↗
USGS2020

Multi‐species occupancy models: Review, roadmap, and recommendations

Recent technological and methodological advances have revolutionized wildlife monitoring. Although most biodiversity monitoring initiatives are geared towards focal species of conservation concern, researchers are increasingly studying entire communities, specifically the spatiotemporal drivers of community size and structure and interactions among species. This has resulted in the emergence of multi‐species occupancy models (MSOMs) as a promising and efficient approach for the study of community ecology. Given the potential of MSOMs for conservation and management action, it is critical to know whether study design and model assumptions are consistent with inference objectives. This is especially true for studies that are designed for a focal species but can give insights about a community. Here, we review the recent literature on MSOMs, identify areas of improvement in the multi‐species study workflow, and provide a reference model for best practices for focal species and community monitoring study design. We reviewed 92 studies published between 2009 and early 2018, spanning 27 countries and a variety of taxa. There is a consistent under‐reporting of details that are central to determining the adequacy of designs for generating data that can be used to make inferences about community‐level patterns of occupancy, including the spatial and temporal extent, types of detectors used, covariates considered, and choice of field methods and statistical tools. This reporting bias could consequently result in skewed estimates, affecting conservation actions and management plans. On the other hand, comprehensive reporting is likely to help researchers working on MSOMs assess the robustness of inferences, in addition to making strides in terms of reproducibility and reusability of data. We use our literature review to inform a roadmap with best practices for MSOM studies, from simulations to design considerations and reporting, for the collection of new data as well as those involving existing datasets.

Ecography↗
USGS2020

Assessing year‐round habitat use by migratory sea ducks in a multi‐species context reveals seasonal variation in habitat selection and partitioning

Long‐distance migration presents complex conservation challenges, and migratory species often experience shortfalls in conservation due to the difficulty of identifying important locations and resources throughout the annual cycle. In order to prioritize habitats for conservation of migratory wildlife, it is necessary to understand how habitat needs change throughout the annual cycle, as well as to identify key habitat sites and features that concentrate large numbers of individuals and species. Among long‐distance migrants, sea ducks have particularly complex migratory patterns, which often include distinct post‐breeding molt sites as well as breeding, staging and wintering locations. Using a large set of individual tracking data (n = 476 individuals) from five species of sea ducks in eastern North America, we evaluated multi‐species habitat suitability and partitioning across the breeding, post‐breeding migration and molt, wintering and pre‐breeding migration seasons. During breeding, species generally occupied distinct habitat areas, with the highest levels of multi‐species overlap occurring in the Barrenlands west of Hudson Bay. Species generally preferred flatter areas closer to lakes with lower maximum temperatures relative to average conditions, but varied in distance to shore, elevation and precipitation. During non‐breeding, species overlapped extensively during winter but diverged during migration. All species preferred shallow‐water, nearshore habitats with high productivity, but varied in their relationships to salinity, temperature and bottom slope. Sea ducks selected most strongly for preferred habitats during post‐breeding migration, with high partitioning among species; however, both selection and partitioning were weaker during pre‐breeding migration. The addition of tidal current velocity, aquatic vegetation presence and bottom substrate improved non‐breeding habitat models where available. Our results highlight the utility of multi‐species, annual‐cycle habitat assessments in identifying key habitat features and periods of vulnerability in order to optimize conservation strategies for migratory wildlife.

Land Surrounding Hudson Bay↗
USGS2020

Artificial nightlight alters the predator-prey dynamics of an apex carnivore

Artificial nightlight is increasingly recognized as an important environmental disturbance that influences the habitats and fitness of numerous species. However, its effects on wide‐ranging vertebrates and their interactions remain unclear. Light pollution has the potential to amplify land‐use change, and as such, answering the question of how this sensory stimulant affects behavior and habitat use of species valued for their ecological roles and economic impacts is critical for conservation and land‐use planning. Here, we combined satellite‐derived estimates of light pollution, with GPS‐data from cougars Puma concolor (n = 56), mule deer Odocoileus hemionus (n = 263) and locations of cougar‐killed deer (n = 1562 carcasses), to assess the effects of light exposure on mammal behavior and predator–prey relationships across wildland–urban gradients in the southwestern United States. Our results indicate that deer used the anthropogenic environments to access forage and were more active at night than their wildland conspecifics. Despite higher nightlight levels, cougars killed deer at the wildland–urban interface, but hunted them in the relatively darkest locations. Light had the greatest effect of all covariates on where cougars killed deer at the wildland–urban interface. Both species exhibited functional responses to light pollution at fine scales; individual cougars and deer with less light exposure increasingly avoided illuminated areas when exposed to greater radiance, whereas deer living in the wildland–urban interface selected elevated light levels. We conclude that integrating estimates of light pollution into ecological studies provides crucial insights into how the dynamic human footprint can alter animal behavior and ecosystem function across spatial scales.

Arizona, California, Colorado, Idaho, Nevada, New ↗
USGS2021

Forecasting community reassembly using climate-linked spatio-temporal ecosystem models

Ecosystems are increasingly impacted by human activities, altering linkages among physical and biological components. Spatial community reassembly occurs when these human impacts modify the spatial overlap between system components, and there is need for practical tools to forecast spatial community reassembly at landscape scales using monitoring data. To illustrate a new approach, we extend a generalization of empirical orthogonal function (EOF) analysis, which involves a spatio‐temporal ecosystem model that approximates coupled physical, biological and human dynamics. We then demonstrate its application to five trophic levels for the eastern Bering Sea by fitting to multiple, spatially unbalanced datasets measuring physical characteristics (temperature measurements and climate‐linked forecasts), primary producers (spring and fall size‐fractionated chlorophyll‐a), secondary producers (copepods), juveniles (age‐0 walleye pollock), adult consumers (five commercially important fishes), human activities (seasonal fishing effort) and mobile predators (seabirds). We identify the spatial niche for each ecosystem component, as well as dominant modes of variability that are highly correlated with a known bottom–up driver of dynamics. We then measure spatial overlap between interacting variables (using Schoener's‐D) and identify that age‐0 pollock have decreased spatial overlap with copepods and increased overlap with adult pollock during warm years, and also that adult pollock have increased overlap with arrowtooth flounder and decreased overlap with catcher–processor fishing effort during these warm years. Given the warming conditions that are projected for the coming decade, the model forecasts increased prey and competitor overlap involving adult pollock (between age‐0 pollock, adult pollock and arrowtooth flounder) and decreased overlap with the copepod forage base and with the catcher–processor fishery during future warming. We recommend that joint species distribution models be extended to incorporate ‘ecological teleconnections' (correlations between distant locations arising from known mechanisms) arising from behavioral adaptation by mobile animals as well as passive advection of nutrients and planktonic juvenile stages.

Ecography↗
USGS2021

The climate envelope of Alaska’s northern treelines: Implications for controlling factors and future treeline advance

Understanding the key mechanisms that control northern treelines is important to accurately predict biome shifts and terrestrial feedbacks to climate. At a global scale, it has long been observed that elevational and latitudinal treelines occur at similar mean growing season air temperature (GSAT) isotherms, inspiring the growth limitation hypothesis (GLH) that cold GSAT limits aboveground growth of treeline trees, with mean treeline GSAT ~6–7°C. Treelines with mean GSAT warmer than 6–7°C may indicate other limiting factors. Many treelines globally are not advancing despite warming, and other climate variables are rarely considered at broad scales. Our goals were to test whether current boreal treelines in northern Alaska correspond with the GLH isotherm, determine which environmental factors are most predictive of treeline presence, and identify areas beyond the current treeline where advance is most likely. We digitized ~12 400 km of treelines (>26 K points) and computed seasonal climate variables across northern Alaska. We then built a generalized additive model predicting treeline presence to identify key factors determining treeline. Two metrics of mean GSAT at Alaska's northern treelines were consistently warmer than the 6–7°C isotherm (means of 8.5°C and 9.3°C), indicating that direct physiological limitation from low GSAT is unlikely to explain the position of treelines in northern Alaska. Our final model included cumulative growing degree-days, near-surface (≤1 m) permafrost probability and growing season total precipitation, which together may represent the importance of soil temperature. Our results indicate that mean GSAT may not be the primary driver of treeline in northern Alaska or that its effect is mediated by other more proximate, and possibly non-climatic, controls. Our model predicts treeline potential in several areas beyond current treelines, pointing to possible routes of treeline advance if unconstrained by non-climatic factors.

Alaska↗
USGS2021

Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics

Maintaining functional connectivity is critical for the long-term conservation of wildlife populations. Landscape genomics provides an opportunity to assess long-term functional connectivity by relating environmental variables to spatial patterns of genomic variation resulting from generations of movement, dispersal and mating behaviors. Identifying landscape features associated with gene flow at large geographic scales for highly mobile species is becoming increasingly possible due to more accessible genomic approaches, improved analytical methods and enhanced computational power. We characterized the genetic structure and diversity of migratory mule deer Odocoileus hemionus using 4051 single nucleotide polymorphisms in 406 individuals sampled across multiple habitats throughout Wyoming, USA. We then identified environmental variables associated with genomic variation within genetic groups and statewide using a stepwise approach to first evaluate nonlinear relationships of landscape resistance with genetic distances and then use mixed-effects modeling to choose top landscape genomic models. We identified three admixed genetic groups of mule deer and found that environmental variables associated with gene flow varied among genetic groups, revealing scale-dependent and regional variation in functional connectivity. At the statewide scale, more gene flow occurred in areas with low elevation and mixed habitat. In the southern genetic group, more gene flow occurred in areas with low elevation. In the northern genetic group, more gene flow occurred in grassland and forest habitats, while highways and energy infrastructure reduced gene flow. In the western genetic group, the null model of isolation by distance best represented genetic patterns. Overall, our findings highlight the role of different seasonal ranges on mule deer genetic connectivity, and show that anthropogenic features hinder connectivity. This study demonstrates the value of combining a large, genome-wide marker set with recent advances in landscape genomics to evaluate functional connectivity in a wide-ranging migratory species.

Wyoming↗
USGS2021

SiteOpt: An open-source R-package for site selection and portfolio optimization

Conservation planning involves identifying and selecting actions to best achieve objectives for managing natural, social and cultural resources. Conservation problems are often high dimensional when specified as combinatorial or portfolio problems and when multiple competing objectives are considered at varying spatial and temporal scales. Although analytical techniques such as modern portfolio theory (MPT) have been developed to address these complex problems, open source computational platforms for executing these approaches are not readily available. We present a user-friendly R-package called SiteOpt for optimization of binary decisions while explicitly considering environmental or economic uncertainty and the risk tolerance of decision makers. We illustrate the package with spatially-explicit site selection problems (i.e. spatial conservation planning), including an option for divestment (i.e. selling assets), when accounting for future uncertainties in designing conservation areas. The tool is applicable to both spatial and non-spatial problems, such as budget allocation or species selection. Constraints for spatial design and spatial dependencies (e.g. connectivity among sites) can also be specified in SiteOpt. Users can optimize site selection based on two competing objectives by solving for the Nash bargaining solution. Importantly, by quantifying uncertainty and asset spatial correlation, a measure of risk can be included as one such objective to be traded off against portfolio benefits. Thus, SiteOpt can be used to explicitly manage risk in portfolio-based spatial optimization. This tool facilitates decisions in a variety of problem settings, including reserve selection, invasive species management, allocation of law enforcement activities for conservation, budget allocation and asset selection under uncertainty and risk.

Ecography↗
USGS2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distribution

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k -fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

Ecography↗
USGS2023

Invasion-mediated mutualism disruption is evident across heterogeneous environmental conditions and varying invasion intensities

The impact of a biological invasion on native communities is expected to be uneven across invaded landscapes due to differences in local abiotic conditions, invader abundance, and traits and composition of the native community. One way to improve predictive ability about the impact of an invasive species given variable conditions is to exploit known mechanisms driving invasive species' success. Invasive plants frequently exhibit allelopathic traits, which can be directly toxic to plants or indirectly impact them via disruption of root symbionts, including mycorrhizal fungi. The indirect mechanism – mutualism disruption – is predicted to impact plants that rely on mycorrhizas but not affect non-mycorrhizal plant species. To assess whether invader-driven mutualism disruption explains observed changes in native plant communities, we analyzed long-term (1998–2018) plant cover data from forest plots across the state of Illinois. We evaluated native plant communities experiencing a range of abundance of invasive allelopathic garlic mustard Alliaria petiolata and varying environmental conditions. Consistent with the mutualism disruption hypothesis, we showed that as garlic mustard abundance increased over time in 0.25 m 2 sampling quadrats, the abundance of mycorrhizal plant species decreased, but non-mycorrhizal plant species did not. Over space and time, garlic mustard abundance predicted plant abundances and diversity at the quadrat level, but this relationship was not present at a larger scale when quadrats were aggregated within sites. Garlic mustard's impact on the plant community was highly localized, yet it was as important as abiotic variables for predicting local plant diversity. We showed that garlic mustard abundance was a key predictor of patterns of plant diversity across invasion intensity and environmental heterogeneity in a way that is consistent with mutualism disruption. Our work indicates that the mutualism disruption hypothesis can provide generalizable predictions of the impacts of allelopathic invasive plants that are evident at a broad spatial scale.

Ecography↗
USGS2022

Flood regimes alter the role of landform and topographic constraint on functional diversity of floodplain forests

Understanding patterns of species coexistence is a fundamental challenge in ecology. The physical environment is believed to play an important role, influencing patterns of dispersal and biotic interactions across space and time. Floodplain forest species are presumed to interact strongly with their environment, as evidenced by pronounced spatial variation in forest composition associated with flood-driven abiotic constraints. Questions of how, and to what degree, fine-scale heterogeneity interacts with broad-scale hydrogeomorphology to influence patterns of functional composition remain unresolved. We examined how functional diversity (i.e. richness and range of functional traits) and ecological strategies (i.e. functional trait combinations) of floodplain forest communities varied across regional and local gradients of flooding in a northern temperate region of the United States of America. We found functional diversity of woody overstory species varied across hydrogeomorphic settings and that different settings altered associations between functional diversity and both the relative elevation above and proximity to rivers. Ecological strategies shifted over local gradients of relative elevation and distance to channel with different magnitudes and directions depending on the broader hydrogeomorphic context. We found evidence that interactions among flood regimes and landform position impose different levels of functional constraint. These results indicate patterns of community assembly are not easily discerned from landform type or position alone, but rather from filtering that operates and interacts with biota over multiple spatial scales. Our results imply that it is important to characterize flood dynamics in ways that can be clearly linked to ecological processes and that treatment of floodplain landforms as transferable units across river-valley segments is problematic, even within a single basin.

Ecography↗
USGS2023

A test of the green wave hypothesis in omnivorous brown bears across North America

Herbivorous animals tend to seek out plants at intermediate phenological states to improve energy intake while minimizing consumption of fibrous material. In some ecosystems, the timing of green-up is heterogeneous and propagates across space in a wave-like pattern, known as the green wave. Tracking the green wave allows individuals to prolong access to higher-quality forage. While there is a plethora of empirical support for such behavior in herbivorous taxa, the green wave hypothesis (GWH) is nuanced based on factors such as body morphometrics and digestive capacity. Furthermore, little is known about whether other taxa, such as omnivores, track the green wave. Our objective was to assess whether the GWH can be extended to explain the movements of omnivores. Using GPS collar data from seven populations (n = 127 individuals) of brown bears Ursus arctos across their entire North American range, we first tested whether bears tracked the green wave. Using conditional resource selection functions (RSFs), we found that variation in proxies of vegetative forage quality better explained movement and habitat selection than proxies of forage biomass in over half of the bears in our study, providing evidence of green wave tracking. Second, we assess factors that explained variation in green wave tracking using linear mixed effects models. Green wave tracking in brown bears was explained by the variation in availability of green-up within spring home ranges, and how green-up transitioned across those home ranges. Our results demonstrate that the GWH can partially explain movement of a non-migratory omnivorous species, extending the generality of the GWH as a broad predictor of animal space use. The green wave is another resource wave brown bears track, and our findings help predict brown bear space use, which can be used to guide conservation and habitat restoration efforts.

Alaska, British Columbia, Idaho, Montana, Wyoming↗
USGS2023

A Great Escape: Resource availability and density-dependence shape population dynamics along trailing range edges

Populations along geographical range limits are often exposed to unsuitable climate and low resource availability relative to core populations. As such, there has been a renewed focus on understanding the factors that determine range limits to better predict how species will respond to global change. Using recent theory on range limits and classical understanding of density dependence, we evaluated the influence of resource availability on the snowshoe hare Lepus americanus along its trailing range edge. We estimated variation in population density, habitat use, survival, and parasite loads to test the Great Escape Hypothesis (GEH), i.e. that density dependence determines, in part, a species' persistence along trailing edges. We found that variability in resource availability affected density and population fluctuations and led to trade-offs in survival for snowshoe hare populations in the northeastern USA. Hares living in resource-limited environments had lower and less variable population density, yet higher survival and lower parasitism compared to populations living in resource-rich environments. We suggest that density-dependent dynamics, elicited by resource availability, provide hares a unique survival advantage and partly explain persistence along their trailing edge. We hypothesize that this low-density escape from predation and parasitism occurs for other prey species along trailing edges, but the extent to which it occurs is likely conditional on the quality of matrix habitat. Our work indicates that biotic factors play an important role in shaping species' trailing edges and more detailed examination of non-climatic factors is warranted to better inform conservation and management decisions.

New Hampshire, Vermont↗
USGS2024

Biodiversity promotes urban ecosystem functioning

The proportion of people living in urban areas is growing globally. Understanding how to manage urban biodiversity, ecosystem functions, and ecosystem services is becoming more important. Biodiversity can increase ecosystem functioning in non-urban systems. However, few studies have reviewed the relationship between biodiversity and ecosystem functioning in urban areas, which differ in species compositions, abiotic environments, food webs, and turnover rates. We reviewed evidence of biodiversity–ecosystem functioning relationships in urban environments and assessed factors that influence the relationship direction. Based on 70 studies, relationships between biodiversity and ecosystem functioning were more positive than negative in urban areas, especially for pollination and nutrient cycling and retention. Surprisingly, positive and negative relationships between biodiversity and biomass production and storage were equally not statistically different, perhaps due to extensive plant management in urban areas. The number of studies and geographic coverage of our review was still insufficient to provide a general predictive framework for when biodiversity positively impacts ecosystem functioning. We identify gaps and opportunities to improve urban biodiversity–ecosystem functioning research and discuss how our findings can improve urban green space management.

Ecography↗
USGS2024

Human activity drives establishment, but not invasion, of non-native plants on islands

Island ecosystems are particularly susceptible to the impacts of invasive species. Many rare and endangered species that are endemic to islands are negatively affected by invasions. Past studies have shown that the establishment of non-native species on islands is related to native plant richness, habitat heterogeneity, island age, human activity, and climate. However, it is unclear whether the factors promoting establishment (i.e. the formation of self-sustaining populations) also promote subsequent invasion (i.e. spread and negative impacts). Using data from 4308 non-native plant species across 46 islands and archipelagos globally, we examined which biogeographic characteristics influence established and invasive plant richness using generalized linear models nested within piecewise structural equation models. Our results indicate that anthropogenic land use (i.e. human modification) is strongly associated with establishment but not invasion, that climate (maximum monthly temperature) is strongly associated with invasion but not establishment, and that habitat heterogeneity (represented by maximum elevation and island area) is strongly associated with both establishment and invasion. Island isolation explains native plant richness well, but is not associated with established and invasive plant richness, likely due to anthropogenic introductions. We conclude that anthropogenic land use on islands is likely to be a proxy for the number of introductions (i.e. propagule pressure), which is more important for establishment than invasion. Conversely, islands with more diverse habitats and favorable (warm) climate conditions are likely to contain more available niche space (i.e. ‘vacant niches’) which create opportunities for both establishment and invasion. By evaluating multiple stages of the invasion process, we differentiate between the biogeographic characteristics that influence plant establishment (which does not necessarily lead to ecological impacts) versus those that influence subsequent plant invasion (which does lead to negative impacts).

Ecography↗
USGS2024

Combining past and contemporary species occurrences with ordinal species distribution modeling to investigate responses to climate change

Many organisms leave evidence of their former occurrence, such as scat, abandoned burrows, middens, ancient eDNA or fossils, which indicate areas from which a species has since disappeared. However, combining this evidence with contemporary occurrences within a single modeling framework remains challenging. Traditional binary species-distribution modeling reduces occurrence to two temporally coarse states (present/absent), so thus cannot leverage the information inherent in temporal sequences of evidence of past occurrence. In contrast, ordinal modeling can use the natural time-varying order of states (e.g. never occupied versus previously occupied versus currently occupied) to provide greater insights into range shifts. We demonstrate the power of ordinal modeling for identifying the major influences of biogeographic and climatic variables on current and past occupancy of the American pika Ochotona princeps , a climate-sensitive mammal. Sampling over five years across the species' southernmost, warm-edge range limit, we tested the effects of these variables at 570 habitat patches where occurrence was classified either as binary or ordinal. The two analyses produced different top models and predictors – ordinal modeling highlighted chronic cold as the most-important predictor of occurrence, whereas binary modeling indicated primacy of average summer-long temperatures. Colder wintertime temperatures were associated in ordinal models with higher likelihood of occurrence, which we hypothesize reflect longer retention of insulative and meltwater-provisioning snowpacks. Our binary results mirrored those of other past pika investigations employing binary analysis, wherein warmer temperatures decrease likelihood of occurrence. Because both ordinal- and binary-analysis top models included climatic and biogeographic factors, results constitute important considerations for climate-adaptation planning. Cross-time evidences of species occurrences remain underutilized for assessing responses to climate change. Compared to multi-state occupancy modeling, which presumes all states occur in the same time period, ordinal models enable use of historical evidence of species' occurrence to identify factors driving species' distributions more finely across time.

New Mexico↗
USGS2024

Feedbacks: A new synthesis of causal loops across ecology

Feedbacks are the basic linkages of living systems. In organisms, they regulate the processes of growth and homeostasis, as well as their interactions with their world. Feedback, which Judson (1980) called ‘one of the chief themes of scientific understanding,' is equally important in ecological systems. The ecological literature is rich in papers dealing with the role of feedback in various phenomena. However, we know of no comprehensive synthesis of feedbacks in ecology. Pichon et al. (2024) accomplish this, and for the first time show that ecological feedbacks can be categorized in terms of a small number of fundamental attributes. The paper brings the array of different types of feedbacks into a manageable order, providing not only the relevant theoretical framework but also guidance on methods for applying understanding to practical issues.

Ecography↗
USGS2024

First records distribution models to guide biosurveillance for non-native species

Quickly locating new populations of non-native species can reduce the ecological and economic costs of species invasions. However, the difficulty of predicting which new non-native species will establish, and where, has limited active post-border biosurveillance efforts. Because pathways of introduction underlie spatial patterns of establishment risk, an intuitive approach is to search for new non-native species in areas where many non-native species have first been detected in the past. We formalize this intuition via first records distribution models (FRDMs), which apply species distribution modeling methods to the collection of first occurrence records across species (i.e. one record per species). We define FRDMs as statistical models that quantify environmental conditions associated with species' first naturalized records to predict spatial patterns of establishment risk. We model the first records of non-native plants in the conterminous USA as a proof-of-concept. The novelty of FRDMs is that their inferences apply not just to the species that contributed data; they provide a rigorous framework for predicting hotspots of invasion for new non-native taxa that share a pathway of introduction with the modeled species. FRDMs can guide survey efforts for new non-native taxa at multiple scales and across ecosystems.

conterminous United States↗