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Results for “Advances in Ecological Research”

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At least 19 recordsLinked to original sources
USGS2010

Geographic variation in the plumage coloration of willow flycatchers Empidonax traillii

The ability to identify distinct taxonomic groups of birds (species, subspecies, geographic races) can advance ecological research efforts by determining connectivity between the non-breeding and breeding grounds for migrant species, identifying the origin of migrants, and helping to refine boundaries between subspecies or geographic races. Multiple methods are available to identify taxonomic groups (e.g., morphology, genetics), and one that has played an important role for avian taxonomists over the years is plumage coloration. With the advent of electronic devices that can quickly and accurately quantify plumage coloration, the potential of using coloration as an identifier for distinct taxonomic groups, even when differences are subtle, becomes possible. In this study, we evaluated the degree to which plumage coloration differs among the four subspecies of the willow flycatcher Empidonax traillii, evaluated sources of variation, and considered the utility of plumage coloration to assign subspecies membership for individuals of unknown origin. We used a colorimeter to measure plumage coloration of 374 adult willow flycatchers from 29 locations across their breeding range in 2004 and 2005. We found strong statistical differences among the mean plumage coloration values of the four subspecies; however, while individuals tended to group around their respective subspecies' mean color value, the dispersion of individuals around such means overlapped. Mean color values for each breeding site of the three western subspecies clustered together, but the eastern subspecies' color values were dispersed among the other subspecies, rather than distinctly clustered. Additionally, sites along boundaries showed evidence of intergradation and intermediate coloration patterns. We evaluated the predictive power of colorimeter measurements on flycatchers by constructing a canonical discriminant model to predict subspecies origin of migrants passing through the southwestern U.S. Considering only western subspecies, we found that individuals can be assigned with reasonable certainty. Applying the model to migrants sampled along the Colorado River in Mexico and the U.S. suggests different migration patterns for the three western subspecies. We believe that the use of plumage coloration, as measured by electronic devices, can provide a powerful tool to look at ecological questions in a wide range of avian species.

Journal of Avian Biology↗
USGS2026

Advances and applications of Unoccupied Aerial Systems (UAS) research in landscape ecology

Landscape ecologists have long depended on satellite and aerial remote sensing to address questions about landscape pattern and process, structure, and change (Foody 2023 ). Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) technology is becoming an increasingly popular research tool in environmental sciences allowing scientists to generate low-cost, high-quality, and high-resolution imagery on demand that can be tailored to specific research questions. While satellite data are of a fixed resolution and temporal interval, UAS offer researchers control and flexibility to design studies and collect data at resolutions and scales that provide ecologically relevant information at finer spatial resolutions (e.g., < 30 cm) than what is currently available from satellite platforms (typically > 3m), thus helping capture objects such as individual plant canopies, micro-topography, and individual animals. Unlike satellites with fixed orbits, UAS can be deployed at more optimal temporal frequencies for ecological monitoring. We organized the special collection “Advances and Applications of Unoccupied Aerial Systems (UAS) Research in Landscape Ecology” to showcase the many ways that UAS tools and technologies are currently applied to advance landscape ecological research. When we announced the collection in 2023, only 11 papers published in the journal Landscape Ecology used UAS data, which was a notably small number compared to many other general ecology, environmental science and remote sensing journals. In an attempt to understand why UAS were not more widely used in landscape ecology and provide possible solutions, we published a review article (Villarreal et al. 2025) that identified the challenges, knowledge gaps, and obstacles for the adoption of UAS technologies in landscape ecology research. The main issues we identified include: (1) an abundance of UAS methods papers in the existing literature, with comparatively few studies demonstrating how UAS can be applied to address ecological questions; (2) a perceived scale mismatch between the geographic extent of UAS data collection (local) compared to larger study areas (landscapes) and a need to design robust scaling approaches to connect fine-scale UAS data with broader ecological patterns; and (3) a need for improved integration of UAS data with other commonly used remote sensing datasets including historical high resolution aerial imagery. Additionally, researchers new to UAS remote sensing may be discouraged or overwhelmed by the general lack of scientific consensus and standardized protocols for typical tasks such as data collection, vegetation classification, and change detection, as well as restrictive and/or confusing policy, regulatory, and legal issues surrounding UAS operations (Villarreal et al. 2025).

Landscape Ecology↗
USGS2025

Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities

Context Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) have become an increasingly popular tool for ecological research. But much of the recent research is concerned with developing mapping and detection approaches, with few studies attempting to link UAS data to ecosystem processes and function. Landscape ecologists have long used high resolution imagery and spatial analyses to address ecological questions and are therefore uniquely positioned to advance UAS research for ecological applications. Objectives The review objectives are to: (1) provide background on how UAS are used in landscape ecological studies, (2) identify major advancements and research gaps, and (3) discuss ways to better facilitate the use of UAS in landscape ecology research. Methods We conducted a systematic review based on PRISMA guidelines using key search terms that are unique to landscape ecology research. We reviewed only papers that applied UAS data to investigate questions about ecological patterns, processes, or function. Results We summarize metadata from 161 papers that fit our review criteria. We highlight and discuss major research themes and applications, sensors and data collection techniques, image processing, feature extraction and spatial analysis, image fusion and satellite scaling, and open data and software. Conclusion We observed a diversity of UAS methods, applications, and creative spatial modeling and analysis approaches. Key aspects of UAS research in landscape ecology include modeling wildlife micro-habitats, scaling of ecosystem functions, landscape and geomorphic change detection, integrating UAS with historical aerial and satellite imagery, and novel applications of spatial statistics.

Landscape Ecology↗
USGS2005

Ecological science and sustainability for the 21st century

Ecological science has contributed greatly to our understanding of the natural world and the impact of humans on that world. Now, we need to refocus the discipline towards research that ensures a future in which natural systems and the humans they include coexist on a more sustainable planet. Acknowledging that managed ecosystems and intensive exploitation of resources define our future, ecologists must play a greatly expanded role in communicating their research and influencing policy and decisions that affect the environment. To accomplish this, they will have to forge partnerships at scales and in forms they have not traditionally used. These alliances must act within three visionary areas: enhancing the extent to which decisions are ecologically informed; advancing innovative ecological research directed at the sustainability of the planet; and stimulating cultural changes within the science itself, thereby building a forward-looking and international ecology. We recommend: (1) a research initiative to enhance research project development, facilitate large-scale experiments and data collection, and link science to solutions; (2) procedures that will improve interactions among researchers, managers, and decision makers; and (3) efforts to build public understanding of the links between ecosystem services and humans.

Frontiers in Ecology and the Environment↗
USGS2019

An analysis of autocorrelation and bias in home range estimation

Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function AKDE, Silvermans rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area ) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area . To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animals movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area . While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area , AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.

Ecological Monographs↗
USGS2023

Toward conciliation in the habitat fragmentation and biodiversity debate

Landscape-scale conservation planning is urgent given the extent of anthropogenic land-use change and its pervasive impacts on Earth’s biodiversity. However, such efforts are hindered by disagreements over the effects of habitat fragmentation on biodiversity that have persisted since the mid-1970s. We contend that nearly 50 years later, these disagreements have become a locked-in debate characterized by polarized, unproductive discourse and a lack of consistent guidance for landscape managers and policy makers. Here, we highlight the need for a unified set of principles regarding conservation in fragmented landscapes, identify potential reasons for disparate conclusions in fragmentation research, and suggest ways for the ecological community to advance research that leads to consensus rather than the perpetuation of disagreement. Explicit efforts to develop and test multiple competing hypotheses, inter-laboratory collaborations, and acknowledgement of multiple interacting effects will be vital for moving the fragmentation debate forward. We argue that we in the ecology community should be responsible for helping to reconcile different views across scales, systems, and methodological approaches to advance conservation planning within a landscape ecology framework.

Landscape Ecology↗
USGS2022

Toward improved prediction of streamflow effects on freshwater fishes

Understanding the effects of hydrology on fish populations is essential to managing for native fish conservation. However, despite decades of research illustrating streamflow influences on fish habitat, reproduction and survival, biologists remain challenged when tasked with predicting how fish populations will respond to changes in flow regimes. This uncertainty stems from insufficient understanding of the context-dependent mechanisms underlying fish responses to, for example, periods of reduced flow or altered frequency of high-flow events. We aim to address this gap by drawing on previous research to hypothesize mechanisms by which low- and high-flows influence fish populations and communities, identifying challenges that stem from data limitations and ecological complexity, and outlining research directions that can advance an empirical basis for prediction. Focusing flow-ecology research on testing and refining mechanistic hypotheses can help narrow management uncertainties and better support species conservation in changing flow regimes.

Fisheries Magazine↗
USGS2023

A synergistic future for AI and ecology

Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in computational and ecological research, we foresee a critical need for intentional synergy to meet current societal challenges against the backdrop of global change. These challenges include understanding the unpredictability of systems-level phenomena and resilience dynamics on a rapidly changing planet. Here, we spotlight both the promise and the urgency of a convergence research paradigm between ecology and AI. Ecological systems are a challenge to fully and holistically model, even using the most prominent AI technique today: deep neural networks. Moreover, ecological systems have emergent and resilient behaviors that may inspire new, robust AI architectures and methodologies. We share examples of how challenges in ecological systems modeling would benefit from advances in AI techniques that are themselves inspired by the systems they seek to model. Both fields have inspired each other, albeit indirectly, in an evolution toward this convergence. We emphasize the need for more purposeful synergy to accelerate the understanding of ecological resilience whilst building the resilience currently lacking in modern AI systems, which have been shown to fail at times because of poor generalization in different contexts. Persistent epistemic barriers would benefit from attention in both disciplines. The implications of a successful convergence go beyond advancing ecological disciplines or achieving an artificial general intelligence—they are critical for both persisting and thriving in an uncertain future.

Proceedings of the National Academy of Sciences↗
USGS2019

Employing an ecosystem services framework to deliver decision ready science

Public land managers have limited information to allow for the integration and balancing of multiple objectives in land management decisions including the social (cultural and health), economic (monetary and nonmonetary), and environmental aspects. In this article, we document an approach to consider the many facets of decision making by incorporating them into a decision context using an ecosystem services framework. This analysis is based on a multi-partner project led by the US Geological Survey and the US Fish and Wildlife Service to provide land management decision support for the Great Dismal Swamp National Wildlife Refuge. It is an integrated ecologic-economic analysis of baseline (current) and potential future quantities, qualities, and values of selected ecosystem services from the Refuge. Alternative management scenarios are modeled to consider the impact of specific management actions or natural disturbances on priority ecosystem services. We examine the benefits and challenges of using this framework. Key lessons learned from this effort include the mismatch in timing between physical and social science; the challenge of integrating methods from multiple disciplines; the importance of frequent communication to overcome siloed research; and the utility of an integrating framework for ecosystem services and supporting tools such as the dynamic ecosystem model.

Advances in Ecological Research↗
USGS2018

A method to detect discontinuities in census data

The distribution of pattern across scales has predictive power in the analysis of complex systems. Discontinuity approaches remain a fruitful avenue of research in the quest for quantitative measures of resilience because discontinuity analysis provides an objective means of identifying scales in complex systems and facilitates delineation of hierarchical patterns in processes, structure, and resources. However, current discontinuity methods have been considered too subjective, too complicated and opaque, or have become computationally obsolete; given the ubiquity of discontinuities in ecological and other complex systems, a simple and transparent method for detection is needed. In this study, we present a method to detect discontinuities in census data based on resampling of a neutral model and provide the R code used to run the analyses. This method has the potential for advancing basic and applied ecological research.

Ecology and Evolution↗
USGS2025

Spatial regimes provide ample early warning of tipping points

Accelerating global change is a hallmark of the Anthropocene, and the interaction of rapid change in climate, land use and land cover makes understanding the response of social-ecological systems to global change difficult to predict. Global change directly and indirectly affects both social-ecological systems and the landscapes in which they are embedded. Spatial heterogeneity in the location, manifestation of, and responses to global change makes spatially explicit approaches to management and conservation necessary. Spatial regimes, a concept derived from resilience theory, are at the forefront of attempts to operationalize and quantify resilience of dynamic landscapes. Spatial regimes are defined as dynamic landscape units that are shaped by a self-organizing set of processes and structures. They have identifiable spatial extents with discrete boundaries at a given scale that exhibit relative homogeneity in process, structure and composition maintained by feedback mechanisms. Here, we describe the concept of, evidence for, and applications of spatial regimes and how spatial regimes relate to scale and telecoupling of change across social-ecological systems. We emphasize the utility of the concept as an early warning of regime change, one that can provide ample early warning. We discuss methods that can be used to detect spatial regimes and uses of the concept for understanding and managing the spatio-temporal response of social-ecological systems to global change.

Advances in Ecological Research↗
USGS2009

Modeling individual animal histories with multistate capture–recapture models

Many fields of science begin with a phase of exploration and description, followed by investigations of the processes that account for observed patterns. The science of ecology is no exception, and recent decades have seen a focus on understanding key processes underlying the dynamics of ecological systems. In population ecology, emphasis has shifted from the state variable of population size to the demographic processes responsible for changes in this state variable: birth, death, immigration, and emigration. In evolutionary ecology, some of these same demographic processes, rates of birth and death, are also the determinants of fitness. In animal population ecology, the estimation of state variables and their associated vital rates is especially problematic because of the difficulties in sampling such populations and detecting individual animals. Indeed, early capture–recapture models were developed for the purpose of estimating population size, given the reality that all animals are not caught or detected at any sampling occasion. More recently, capture–recapture models for open populations were developed to draw inferences about survival in the face of these same sampling problems. The focus of this paper is on multi‐state mark–recapture models (MSMR), which first appeared in the 1970s but have undergone substantial development in the last 15 years. These models were developed to deal explicitly with biological variation, in that animals in different “states” (classes defined by location, physiology, behavior, reproductive status, etc.) may have different probabilities of survival and detection. Animal transitions between states are also stochastic and themselves of interest. These general models have proven to be extremely useful and provide a way of thinking about a remarkably wide range of important ecological processes. These methods are now at a stage of refinement and sophistication where they can readily be used by biologists to tackle a wide range of important issues in ecology. In this paper, we draw together information on the state of the art in multistate mark–recapture methods, explaining the models and illustrating their use. We provide a modeling philosophy and a series of general principles on how to conduct analyses. We cover key issues and features, and we anticipate the ways in which we expect the models to develop in the years ahead.

Advances in Ecological Research↗
USGS2010

Understanding behavioral responses of fish to pheromones in natural freshwater environments

There is an abundance of experimental studies and reviews that describe odorant-mediated behaviors of fish in laboratory microcosms, but research in natural field conditions has received considerably less attention. Fish pheromone studies in laboratory settings can be highly productive and allow for controlled experimental designs; however, laboratory tanks and flumes often cannot replicate all the physical, physiological and social contexts associated with natural environments. Field experiments can be a critical step in affirming and enhancing understanding of laboratory discoveries and often implicate the ecological significance of pheromones employed by fishes. When findings from laboratory experiments have been further tested in field environments, often different and sometimes contradictory conclusions are found. Examples include studies of sea lamprey (Petromyzon marinus) mating pheromones and fish alarm substances. Here, we review field research conducted on fish pheromones and alarm substances, highlighting the following topics: (1) contradictory results obtained in laboratory and field experiments, (2) how environmental context and physiological status influences behavior, (3) challenges and constraints of aquatic field research and (4) innovative techniques and experimental designs that advance understanding of fish chemical ecology through field research.

Journal of Comparative Physiology A↗
USGS2024

Using citizen scientists to collect oxygen and hydrogen isotope data in southern Nevada

What is Citizen Science? Citizen science programs provide a means for Federal and non-Federal government agencies to make science more engaging, transparent, and accessible by partnering with the public for the purpose of problem solving, data collection, and monitoring. Public volunteers become directly involved in local research, thereby engaging in scientific projects. The public has already been included in existing citizen science programs that cover a broad range of disciplines, such as ecology, hydrology, and tectonics. Citizen science advances research while simultaneously fostering a sense of involvement and interest from the public. Beginning in 2017, the U.S. Geological Survey (USGS), U.S. Forest Service, Bureau of Land Management, U.S. Fish and Wildlife Service, and National Park Service collaborated with private, non-profit partners to inventory, survey, and rehabilitate springs in Clark County, Nevada. The USGS maintains the National Water Information System (NWIS), a publicly available online database of water-resources data for the Nation, and the agency is interested in using citizen science to add geochemical data from springs in southern Nevada. From 2021 to 2023, the USGS directly worked with citizen science partners, including the Springs Stewardship Institute and the Friends of Nevada Wilderness, to collect stable isotope and tritium samples from southern Nevada springs. The citizen science volunteers were provided the training and supplies for proper sample collection by USGS staff. As the citizen science partners traveled and hiked to the remote spring sites to complete spring surveys and perform restoration activities, they collected stable isotope and tritium samples for the USGS. Samples were shipped to national USGS laboratories for analysis, and the results were uploaded to the NWIS database (U.S. Geological Survey, 2024).

Nevada↗
USGS2011

Functional ecology of free-living nitrogen fixation: A contemporary perspective

Nitrogen (N) availability is thought to frequently limit terrestrial ecosystem processes, and explicit consideration of N biogeochemistry, including biological N 2 fixation, is central to understanding ecosystem responses to environmental change. Yet, the importance of free-living N 2 fixation—a process that occurs on a wide variety of substrates, is nearly ubiquitous in terrestrial ecosystems, and may often represent the dominant pathway for acquiring newly available N—is often underappreciated. Here, we draw from studies that investigate free-living N 2 fixation from functional, physiological, genetic, and ecological perspectives. We show that recent research and analytical advances have generated a wealth of new information that provides novel insight into the ecology of N 2 fixation as well as raises new questions and priorities for future work. These priorities include a need to better integrate free-living N 2 fixation into conceptual and analytical evaluations of the N cycle's role in a variety of global change scenarios.

Annual Review of Ecology, Evolution, and Systemati↗
USGS2011

Predicting phenology by integrating ecology, evolution and climate science

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology – the timing of life‐history events. Phenology has well‐demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species’ reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

Global Change Biology↗
USGS2015

Plant phenolics and absorption features in vegetation reflectance spectra near 1.66 μm

Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 &mu;m is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic C- H bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf ( r 2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf ( r 2 = 0.79, RMSE = 2.1%, n = 56), and canopy ( r 2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 &mu;m, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the spectral influences of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin).

International Journal of Applied Earth Observation↗