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USGS2021

Bridging the research-implementation gap in avian conservation with translational ecology

The recognized gap between research and implementation in avian conservation can be overcome with translational ecology, an intentional approach in which science producers and users from multiple disciplines work collaboratively to co-develop and deliver ecological research that addresses management and conservation issues. Avian conservation naturally lends itself to translational ecology because birds are well studied, typically widespread, often exhibit migratory behaviors transcending geopolitical boundaries, and necessitate coordinated conservation efforts to accommodate resource and habitat needs across the full annual cycle. In this perspective, we highlight several case studies from bird conservation practitioners and the ornithological and conservation social sciences exemplifying the 6 core translational ecology principles introduced in previous studies: collaboration, engagement, commitment, communication, process, and decision-framing. We demonstrate that following translational approaches can lead to improved conservation decision-making and delivery of outcomes via co-development of research and products that are accessible to broader audiences and applicable to specific management decisions (e.g., policy briefs and decision-support tools). We also identify key challenges faced during scientific producer–user engagement, potential tactics for overcoming these challenges, and lessons learned for overcoming the research-implementation gap. Finally, we recommend strategies for building a stronger translational ecology culture to further improve the integration of these principles into avian conservation decisions. By embracing translational ecology, avian conservationists and ornithologists can be well positioned to ensure that future management decisions are scientifically informed and that scientific research is sufficiently relevant to managers. Ultimately, such teamwork can help close the research-implementation gap in the conservation sciences during a time when environmental issues are threatening avian communities and their habitats at exceptional rates and at broadening spatial scales worldwide.

Ornithological Applications↗

USGS2012

Ecology of zoonotic infectious diseases in bats: current knowledge and future directions

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics.

Zoonoses and Public Health↗

USGS2004

Ecology for a crowded planet

Within the next 50 to 100 years, the support and maintenance of an extended human family of 8 to 11 billion people will be difficult at best. The authors of this Policy Forum describe changes that are required if we hope to meet the needs and aspirations of humans while improving the health of our planet's ecosystems. Problems as diverse as disease transmission and global climate change have benefited substantially from advances in ecology. Such advances have set the stage for emergence of a proactive ecological science in which social and political realities are acknowledged and attention is turned decisively toward the future. The ecological sciences must chart an understanding of how ecosystem services can persist given their extensive human use. Innovative research on the sciences of ecosystem services, ecological restoration, and ecological design must be massively accelerated and must be accompanied by more effective communication of ecological knowledge to society.

Science↗

USGS2022

Bayesian applications in environmental and ecological studies with R and Stan

Modern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis, as they enable information from different sources to be brought into the modelling process. Bayesian Applications in Evnironmental and Ecological Studies with R and Stan provides a Bayesian framework for model formulation, parameter estimation, and model evaluation in the context of analyzing environmental and ecological data. Features: An accessible overview of Bayesian methods in environmental and ecological studies Emphasizes the hypothetical deductive process, particularly model formulation Necessary background material on Bayesian inference and Monte Carlo simulation Detailed case studies, covering water quality monitoring and assessment, ecosystem response to urbanization, fisheries ecology, and more Advanced chapter on Bayesian applications, including Bayesian networks and a change point model Complete code for all examples, along with the data used in the book, are available via GitHub The book is primarily aimed at graduate students and researchers in the environmental and ecological sciences, as well as environmental management professionals. This is a group of people representing diverse subject matter fields, who could benefit from the potential power and flexibility of Bayesian methods.

Book↗

USGS2016

The automated reference toolset: A soil-geomorphic ecological potential matching algorithm

Ecological inventory and monitoring data need referential context for interpretation. Identification of appropriate reference areas of similar ecological potential for site comparison is demonstrated using a newly developed automated reference toolset (ART). Foundational to identification of reference areas was a soil map of particle size in the control section (PSCS), a theme in US Soil Taxonomy. A 30-m resolution PSCS map of the Colorado Plateau (366,000 km 2 ) was created by interpolating ∼5000 field soil observations using a random forest model and a suite of raster environmental spatial layers representing topography, climate, general ecological community, and satellite imagery ratios. The PSCS map had overall out of bag accuracy of 61.8% (Kappa of 0.54, p < 0.0001), and an independent validation accuracy of 93.2% at a set of 356 field plots along the southern edge of Canyonlands National Park, Utah. The ART process was also tested at these plots, and matched plots with the same ecological sites (ESs) 67% of the time where sites fell within 2-km buffers of each other. These results show that the PSCS and ART have strong application for ecological monitoring and sampling design, as well as assessing impacts of disturbance and land management action using an ecological potential framework. Results also demonstrate that PSCS could be a key mapping layer for the USDA-NRCS provisional ES development initiative.

Soil Science Society of America Journal↗

USGS2017

Southern Great Plains Rapid Ecoregional assessment—Volume I. Ecological communities

The Southern Great Plains Rapid Ecoregional Assessment was conducted in partnership with the Bureau of Land Management (BLM) and the Great Plains Landscape Conservation Cooperative . The overall goal of the Rapid Ecoregional Assessments (REAs) is to compile and synthesize regional datasets to facilitate evaluation of the cumulative effects of change agents on priority ecological communities and species. In particular, the REAs identify and map the distribution of communities and wildlife habitats at broad spatial extents and provide assessments of ecological conditions. The REAs also identify where and to what degree ecological resources are currently at risk from change agents, such as development, fire, invasive species, and climate change. The REAs can help managers identify and prioritize potential areas for conservation or restoration, assess cumulative effects as required by the National Environmental Policy Act, and inform landscape-level planning and management decisions for multiple uses of public lands. Management questions form the basis for the REA framework and were developed in conjunction with the BLM and other stakeholders. Conservation elements are communities and species that are of regional management concern. Core management questions relate to the key ecological attributes and change agents associated with each conservation element. Integrated management questions synthesize the results of the primary core management questions into overall landscape-level ranks for each conservation element. The ecological communities evaluated as conservation elements are shortgrass, mixed-grass, and sand prairies; all grasslands; riparian and nonplaya wetlands; playa wetlands and saline lakes; and prairie streams and rivers. Species and species assemblages evaluated are the freshwater mussel assemblage, Arkansas River shiner ( Notropis girardi ), ferruginous hawk ( Buteo regalis ), lesser prairie chicken ( Tympanuchus pallidicinctus ), snowy plover ( Charadrius nivosus ), mountain plover ( Charadrius montanus ), long-billed curlew ( Numenius americanus ), interior least tern ( Sternula antillarum athalassos ), burrowing owl ( Athene cunicularia hypugaea ), black-tailed prairie dog ( Cynomys ludovicianus ), bat assemblage, swift fox ( Vulpes velox ), and mule deer ( Odocoileus hemionus ). The Southern Great Plains REA is summarized in a series of three reports and associated datasets. The pre-assessment report (available online at https://pubs.usgs.gov/of/2015/1003/ ) summarizes the process used by the REA stakeholders to select management questions, conservation elements, and change agents. It also provides background information for each conservation element. Volume I of the Southern Great Plains REA report (this volume) addresses the ecological communities. Volume II will address the species and species assemblages. All source and derived datasets used to produce the maps and graphs for REAs are available online at the BLM Landscape Approach Data Portal ( https://landscape.blm.gov/geoportal/catalog/REAs/REAs.page ).

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, ↗

USGS2020

Understanding and documenting the scientific basis of selenium ecological protection in support of site-specific guidelines development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada

Modeling of ecosystems is a part of the U.S. Environmental Protection Agency’s protocol for developing site-specific selenium guidelines for protection of aquatic life. Selenium as an environmental contaminant is known to bioaccumulate and cause reproductive effects in fish and wildlife. Here we apply a modeling methodology—ecosystem-scale selenium modeling—to understand and document the scientific basis for predicting and validating ecological protection for Lake Koocanusa, a transboundary reservoir between Montana and British Columbia. A comprehensive set of site-specific data compiled from public databases (Federal, State, and Provincial) and reports by Teck Coal Ltd., is available in a companion U.S. Geological Survey data release. The tissue guideline used within modeling here to assess protection is the U.S. Environmental Protection Agency’s national selenium guideline for whole-body fish (dry weight); however, other numeric values for a whole-body guideline or other tissue types may be assumed if applicable tissue-to-tissue conversion factors are available. We consider the report assembled here as a working document that presents a model that can effectively address and structure the needs of (1) scientific understanding in representing the lake’s ecosystem and selenium biodynamics and (2) policy and management development during a decision-making process, but it is open to modification and updating as more ecologically detailed data become available. The approach brings together the main concerns involved in selenium toxicity: likelihood of high exposure, inherent species sensitivity, and close connectivity of ecosystem characteristics and behavioral ecology of predators. Detailed site-specific modeling equations are provided to document the linked factors that determine the responses of ecosystems to selenium. A series of scenarios quantifies the implications of choices of site-specific variables including food-web species, bioavailability of particulate material, and partitioning between the dissolved and particulate phases at the base of food webs. A gradient mapping tool applied to Lake Koocanusa provides a precedent for ecosystem-scale modeling of lakes by recognizing the importance of lake strata and hydrodynamics as components of modeling. Data requirements for ecosystem modeling, including ecological and hydrological process information fundamental to the dietary biodynamics of selenium in site-specific food webs, were assessed as a precursor to model validation for Lake Koocanusa. Understanding these relationships is necessary to connect modeling outcomes to reproductive effects and establish boundaries, in the case of Lake Koocanusa, for the influences of dam operation, fish-community viability, and its Clean Water Act impaired 303(d)-listing status on ecosystem function. We find that an assemblage of conditions affects the representation of Lake Koocanusa’s ecosystem within modeling scenarios but that the constructed gradient maps, mechanistic model, and associated bioaccumulation potentials portray and quantify the variables that are determinative to protection of predator species. Ecological and hydrological sorting of compiled individual data points on a site- and species-specific basis helps identify and address model uncertainties. Sources of uncertainty include (1) the scarcity of data for some environmental media compartments across time and locations, (2) the complexity of hydrodynamic conditions that can lead to seasonal ecological disconnects such as in selenium partitioning from water into particulates, and (3) the functional status of Lake Koocanusa’s ecosystem because of cumulative effects of various environmental stresses (for example, fish-community changes, flow regime changes, parasites, gonadal dysfunction, and increasing mining input-selenium concentrations since 1984). To this last point, it is important to determine where Lake Koocanusa is in an impairment-restoration cycle so as not to base protection on survivor bias, the maintenance of a currently degraded ecosystem, or normalized toxicity. In a broader context, one of the overall consequences of revised selenium regulations is that their derivation is now dependent on being able to define and understand the status of the ecosystem on which protection is based.

Montana, British Columbia↗

USGS2026

An overview and participatory framework for choosing spatial boundaries in social–ecological systems modeling

A common challenge when modeling social–ecological systems (SESs) is defining the spatial extent of the system. Boundaries that do not adequately capture both social and ecological processes and their interactions can lead to mischaracterization of the system, while expanding boundaries too widely can impact model complexity and required resources. Socially, boundaries can invoke and influence identity, culture, power, and sense of place. Boundary decisions benefit from flexible, iterative approaches and the expertise of local communities. Here, we use a structured database search supplemented with citation searching to identify and review the literature that addresses choosing or defining spatial boundaries in SESs mapping or modeling and, when applicable, how participatory methods were used in the research process. In a review of the resulting 79 studies, we discovered that pre-existing social or ecological boundaries were used most frequently (36 and 18 publications, respectively). Twenty-one publications combined social and ecological boundaries or data to create custom boundaries, and four studies used an alternative approach to conventional boundaries. Informed by the literature review, we present a general framework for defining boundaries at the outset of SES research. We then connect the framework to a specific case study based on a collaborative project with Tribal, university, and federal scientists to develop a social–ecological climate adaptation plan. We present guiding questions alongside candidate boundaries for our study system and explore the tradeoffs of these boundary options, which can function as a useful template for other social–ecological research collaborations.

ISPRS International Journal of Geo-Information↗

USGS2014

Identifying legal, ecological and governance obstacles and opportunities for adapting to climate change

Current governance of regional scale water management systems in the United States has not placed them on a path toward sustainability, as conflict and gridlock characterize the social arena and ecosystem services continue to erode. Changing climate may continue this trajectory, but it also provides a catalyst for renewal of ecosystems and a window of opportunity for change in institutions. Resilience provides a bridging concept that predicts that change in ecological and social systems is often dramatic, abrupt, and surprising. Adapting to the uncertainty of climate driven change must be done in a manner perceived as legitimate by the participants in a democratic society. Adaptation must begin with the current hierarchical and fragmented social-ecological system as a baseline from which new approaches must be applied. Achieving a level of integration between ecological concepts and governance requires a dialogue across multiple disciplines, including ecologists with expertise in ecological resilience, hydrologists and climate experts, with social scientists and legal scholars. Criteria and models that link ecological dynamics with policies in complex, multi-jurisdictional water basins with adaptive management and governance frameworks may move these social-ecological systems toward greater sustainability.

Sustainability↗

USGS2014

Social-ecological resilience and law in the Platte River Basin

Efficiency and resistance to rapid change are hallmarks of both the judicial and legislative branches of the United States government. These defining characteristics, while bringing stability and predictability, pose challenges when it comes to managing dynamic natural systems. As our understanding of ecosystems improves, we must devise ways to account for the non-linearities and uncertainties rife in complex social-ecological systems. This paper takes an in-depth look at the Platte River basin over time to explore how the system's resilience—the capacity to absorb disturbance without losing defining structures and functions—responds to human driven change. Beginning with pre-European settlement, the paper explores how water laws, policies, and infrastructure influenced the region's ecology and society. While much of the post-European development in the Platte River basin came at a high ecological cost to the system, the recent tri-state and federal collaborative Platte River Recovery and Implementation Program is a first step towards flexible and adaptive management of the social-ecological system. Using the Platte River basin as an example, we make the case that inherent flexibility and adaptability are vital for the next iteration of natural resources management policies affecting stressed basins. We argue that this can be accomplished by nesting policy in a resilience framework, which we describe and attempt to operationalize for use across systems and at different levels of jurisdiction. As our current natural resources policies fail under the weight of looming global change, unprecedented demand for natural resources, and shifting land use, the need for a new generation of adaptive, flexible natural resources govern-ance emerges. Here we offer a prescription for just that, rooted in the social , ecological and political realities of the Platte River basin. Social-Ecological Resilience and Law in the Platte River Basin (PDF Download Available) . Available from: https://www.researchgate.net/publication/273678974_Social-Ecological_Resilience_and_Law_in_the_Platte_River_Basin [accessed Oct 18 2017].

Idaho Law Review↗

USGS2005

Development of ecological indicator guilds for land management

Agency land-use must be efficiently and cost-effectively monitored to assess conditions and trends in ecosystem processes and natural resources relevant to mission requirements and legal mandates. Ecological Indicators represent important land management tools for tracking ecological changes and preventing irreversible environmental damage in disturbed landscapes. The overall objective of the research was to develop both individual and integrated sets (i.e., statistically derived guilds) of Ecological Indicators to: quantify habitat conditions and trends, track and monitor ecological changes, provide early warning or threshold detection, and provide guidance for land managers. The derivation of Ecological Indicators was based on statistical criteria, ecosystem relevance, reliability and robustness, economy and ease of use for land managers, multi-scale performance, and stress response criteria. The basis for the development of statistically based Ecological Indicators was the identification of ecosystem metrics that analytically tracked a landscape disturbance gradient.

Report↗

USGS2024

Declining ecological resilience and invasion resistance under climate change in the sagebrush region, United States

In water-limited dryland ecosystems of the Western United States, climate change is intensifying the impacts of heat, drought, and wildfire. Disturbances often lead to increased abundance of invasive species, in part, because dryland restoration and rehabilitation are inhibited by limited moisture and infrequent plant recruitment events. Information on ecological resilience to disturbance (recovery potential) and resistance to invasive species can aid in addressing these challenges by informing long-term restoration and conservation planning. Here, we quantified the impacts of projected future climate on ecological resilience and invasion resistance (R&R) in the sagebrush region using novel algorithms based on ecologically relevant and climate-sensitive predictors of climate and ecological drought. We used a process-based ecohydrological model to project these predictor variables and resulting R&R indicators for two future climate scenarios and 20 climate models. Results suggested widespread future R&R decreases (24%–34% of the 1.16 million km 2 study area) that are generally consistent among climate models. Variables related to rising temperatures were most strongly linked to decreases in R&R indicators. New continuous R&R indices quantified responses to climate change; particularly useful for areas without projected change in the R&R category but where R&R still may decrease, for example, some of the areas with a historically low R&R category. Additionally, we found that areas currently characterized as having high sagebrush ecological integrity had the largest areal percentage with expected declines in R&R in the future, suggesting continuing declines in sagebrush ecosystems. One limitation of these R&R projections was relatively novel future climatic conditions in particularly hot and dry areas that were underrepresented in the training data. Including more data from these areas in future updates could further improve the reliability of the projections. Overall, these projected future declines in R&R highlight a growing challenge for natural resource managers in the region, and the resulting spatially explicit datasets provide information that can improve long-term risk assessments, prioritizations, and climate adaptation efforts.

western United States↗

USGS2022

Partial observability and management of ecological systems

The actual state of ecological systems is rarely known with certainty, but management actions must often be taken regardless of imperfect measurement (partial observability). Because of the difficulties in accounting for partial observability, it is usually treated in an ad hoc fashion, or simply ignored altogether. Yet incorporating partial observability into decision processes lends a realism that has the potential to improve ecological outcomes significantly. We review frameworks for dealing with partial observability, focusing specifically on dynamic ecological systems with Markovian transitions, i.e., transitions among system states that are influenced by the current system state and management action over time. Fully observable states are represented in an observable Markov decision process (MDP), whereas obscure or hidden states are represented in a partially observable process (POMDP). POMDPs can be seen as a natural extension of observable MDPs. Management under partial observability generalizes the situation for complete observability, by recognizing uncertainty about the system's state and incorporating sequential observations associated with, but not the same as, the states themselves. Decisions that otherwise would depend on the actual state must be based instead on state probability distributions (“belief states”). Partial observability requires adaptation of the entire decision process, including the use of belief states and Bayesian updates, valuation that includes expectations over observations, and optimal strategy that identifies actions for belief states over a continuous belief space. We compare MDPs and POMDPs and highlight POMDP applications to some common ecological problems. We clarify the structure and operations, approaches for finding solutions, and analytic challenges of POMDPs for practicing ecologists. Both observable and partially observable MDPs can use an inductive approach to identify optimal strategies and values, with a considerable increase in mathematical complexity with POMDPs. Better understanding of POMDPs can help decision makers manage imperfectly measured ecological systems more effectively.

Ecology and Evolution↗

USGS2017

Sustainability of utility-scale solar energy – critical ecological concepts

Renewable energy development is an arena where ecological, political, and socioeconomic values collide. Advances in renewable energy will incur steep environmental costs to landscapes in which facilities are constructed and operated. Scientists – including those from academia, industry, and government agencies – have only recently begun to quantify trade-offs in this arena, often using ground-mounted, utility-scale solar energy facilities (USSE, ≥1 megawatt) as a model. Here, we discuss five critical ecological concepts applicable to the development of more sustainable USSE with benefits over fossil-fuel-generated energy: (1) more sustainable USSE development requires careful evaluation of trade-offs between land, energy, and ecology; (2) species responses to habitat modification by USSE vary; (3) cumulative and large-scale ecological impacts are complex and challenging to mitigate; (4) USSE development affects different types of ecosystems and requires customized design and management strategies; and (5) long-term ecological consequences associated with USSE sites must be carefully considered. These critical concepts provide a framework for reducing adverse environmental impacts, informing policy to establish and address conservation priorities, and improving energy production sustainability.

Frontiers in Ecology and the Environment↗

USGS2018

A social–ecological perspective for riverscape management in the Columbia River Basin

Riverscapes are complex, landscape-scale mosaics of connected river and stream habitats embedded in diverse ecological and socioeconomic settings. Social–ecological interactions among stakeholders often complicate natural-resource conservation and management of riverscapes. The management challenges posed by the conservation and restoration of wild salmonid populations in the Columbia River Basin (CRB) of western North America are one such example. Because of their ecological, cultural, and socioeconomic importance, salmonids present a complex management landscape due to interacting environmental factors (eg climate change, invasive species) as well as socioeconomic and political factors (eg dams, hatcheries, land-use change, transboundary agreements). Many of the problems in the CRB can be linked to social–ecological interactions occurring within integrated ecological, human–social, and regional–climatic spheres. Future management and conservation of salmonid populations therefore depends on how well the issues are understood and whether they can be resolved through effective communication and collaboration among ecologists, social scientists, stakeholders, and policy makers.

Columbia River Basin↗

USGS2023

Informing management of recovering predators and their prey with ecological diffusion models

The reintroduction and recovery of predators can be ecologically beneficial as well as socially and economically controversial. However, the growth and expansion of predator populations, and thus their ecological, social, and economic impacts, are not static but rather they vary in space and time. We propose a spatiotemporal statistical modeling framework based on ecological diffusion to better inform the ecology and management of recovering predators and their prey. We demonstrate its utility by applying it to a recovering sea otter ( Enhydra lutris ) population in Southeast Alaska, where sea otters were reintroduced in the late 1960s and have exhibited unprecedented population growth. Estimated parameters yield inferences about movement and population ecology, and our approach provides useful derived quantities, such as local abundance and carrying capacity as well as a quantity we term the equilibrium differential. We used our model to examine how density dependence and carrying capacity of sea otters vary spatially across a region. The diffusion modeling approach we present can be generalized for use in other instances of (re)colonization across taxa to inform management and conservation efforts.

Alaska↗

USGS2010

Ecological hierarchies and self-organisation - Pattern analysis, modelling and process integration across scales

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an 'across-scale-approach', closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems. ?? 2010 Gesellschaft f??r ??kologie.

Basic and Applied Ecology↗

USGS2020

Testing prediction accuracy in short-term ecological studies

Applied ecology is based on an assumption that a management action will result in a predicted outcome. Testing the prediction accuracy of ecological models is the most powerful way of evaluating the knowledge implicit in this cause-effect relationship, however, the prevalence of predictive modeling and prediction testing are spreading slowly in ecology. The challenge of prediction testing is particularly acute for small-scale studies, because withholding data for prediction testing (e.g., via k -fold cross validation) can reduce model precision. However, by necessity small-scale studies are common. We use one such study that explored small mammal abundance along an elevational gradient to test prediction accuracy of models with varying degrees of information content. For each of three small mammal species, we conducted 5000 iterations of the following process: (1) randomly selected 75 % of the data to develop generalized linear models of species abundance that used detailed site measurements as covariates, (2) used an information theoretic approach to compare the top model with detailed covariates to habitat type-only and null models constructed with the same data, (3) tested those models’ ability to predict the 25 % of the randomly withheld data, and (4) evaluated prediction accuracy with a quadratic loss function. Detailed models fit the model-evaluation data best but had greater expected prediction error when predicting out-of-sample data relative to the habitat type models. Relationships between species and detailed site variables may be evident only within the framework of explicitly hierarchical analyses. We show that even with a small but relatively typical dataset ( n = 28 sampling locations across 125 km over two years), researchers can effectively compare models with different information content and measure models’ predictive power, thus evaluating their own ecological understanding and defining the limits of their inferences. Identifying the appropriate scope of inference through prediction testing is ecologically valuable and is attainable even with small datasets.

Maine, New Hampshire↗