USGS Science⌕ Search

SEARCH · USGS Science

Results for “Ecological Research”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49Linked to original sources
USGS2022

Seasonal and long-term clarity trend assessment of Lake Tahoe, California–Nevada

The clarity of Lake Tahoe, observed using a Secchi disk on a regular basis since the late 1960s, continues to be a sentinel metric of lake health. Water clarity is influenced by physical and biological processes and has declined in the five decades of monitoring, revealing differences between summer (June–September) and winter (December–March). This document summarizes key findings of a study of Lake Tahoe water clarity, including long-term variability and the relative importance of several influencing variables and processes. This study, prepared in cooperation with the Nevada Division of Environmental Protection, focused on (1) an apparent divergence in clarity trends between summer and winter periods, (2) observed changes in in-lake physical and ecological variables that may influence or control seasonal and annual clarity trends, and (3) five research hypotheses regarding lake clarity that were developed by Lake Tahoe management agencies. Previously collected data were used to complete this study. Trend analysis confirmed that winter clarity stabilized (that is, there is no longer a statistically significant trend up or down) during the last 20 years. Evaluation of clarity for selected months in the 50-year Secchi disk clarity dataset showed that only two summer months, July and August, had statistically significant decreases in clarity from 2000–19. Different subsets of available data were analyzed to reveal the presence or absences of trends for each season, decade, and month. Five hypotheses related to lake clarity were part of the study described by this report. Hypothesis 1 stated that clarity is controlled predominantly by the distribution and volumetric density of fine particles in suspension. This hypothesis was studied using available data describing in-lake fine (0–20 micrometers) particles from 2008–19. Water clarity was negatively correlated with in-lake particle abundance, with particles in the 1.0-4.6 μm range having the greatest effect, consistent with light-scattering theory. Estimated abundances of diatoms of the genus Cyclotella also were found to be negatively correlated with clarity. Data limitations precluded a complete investigation of hypothesis 2, which stated that the observed improvements in winter water clarity are a response to decreasing fine suspended-sediment concentrations in the lake resulting from load reductions from upland sources in and near urbanized areas. Data describing fine-sediment loading from urban areas to the lake were only available since 2014, and only once or twice per month. A slight, statistically significant, negative correlation was identified between urban fine-particle loading and monthly lake clarity with a 4-month lag. Particle abundance in monitored streams is highly correlated with simultaneous particle abundance in the lake. Hypothesis 3 stated that changing hydrodynamic conditions in the lake are increasing thermal stability and resistance to mixing. Trend analyses performed on stability index and buoyancy frequency time series computed from long-term observations of lake temperatures support the hypothesis that hydrodynamic conditions have evolved since 1969 to increase the lake’s resistance to mixing. The date of maximum mixing in winter has become progressively earlier in the year. Lake density stratification, defined using the stability index, is commencing earlier in the year and extending a month longer than in the early years of the monitoring program. Hypothesis 4 stated that the trend of decreasing summer clarity is a result of earlier, prolonged, and more intense stratification. Statistically significant correlations were found between summer clarity and (1) date of onset of stratification, (2) duration of stratification, and (3) buoyancy frequency. Hypothesis 5 stated that ecological (food web) interactions are causing changes in the trends of seasonal or annual clarity; data supporting hypothesis 5 were limited to examples from other systems and to intermittent monitoring of Lake Tahoe and Emerald Bay. The resulting narrative assessment was motivated by a 6-year study of Mysis shrimp disappearance and return in Emerald Bay. The available data and a large body of published literature are consistent with the inference that Mysis shrimp-induced food web changes are causing changes in the trends of seasonal or annual clarity. This food-web study focused on the relations between introduced Mysis shrimp, the native cladocerans ( Daphnia and Bosmina ) that were largely eliminated following Mysis introduction, and the effect on fine particles within the lake. The records of Mysis and other zooplankton data for Lake Tahoe are episodic and have large gaps. Consequently, statistical analyses could not be conducted to compare zooplankton data with other variables. The long-term record, however, indicates that the key effect was a change to the phytoplankton assemblage, where larger diatoms disappeared, likely due to Mysis grazing, only to be replaced by Cyclotella that are an order-of-magnitude smaller and have increased the abundance and volumetric density of total fine particles in suspension (biotic and abiotic).

California↗
USGS2020

Climate‐change refugia: Biodiversity in the slow lane

Climate‐change adaptation focuses on conducting and translating research to minimize the dire impacts of anthropogenic climate change, including threats to biodiversity and human welfare. One adaptation strategy is to focus conservation on climate‐change refugia (that is, areas relatively buffered from contemporary climate change over time that enable persistence of valued physical, ecological, and sociocultural resources). In this Special Issue, recent methodological and conceptual advances in refugia science will be highlighted. Advances in this emerging subdiscipline are improving scientific understanding and conservation in the face of climate change by considering scale and ecosystem dynamics, and looking beyond climate exposure to sensitivity and adaptive capacity. We propose considering refugia in the context of a multifaceted, long‐term, network‐based approach, as temporal and spatial gradients of ecological persistence that can act as “slow lanes” rather than areas of stasis. After years of discussion confined primarily to the scientific literature, researchers and resource managers are now working together to put refugia conservation into practice.

Frontiers in Ecology and the Environment↗
USGS2023

U.S. Geological Survey science vision for native freshwater mussel research in the United States

Executive Summary North America is a global center for native freshwater mussel (order Unionida, hereinafter “mussels”) diversity, with more than 350 species. Mussels are among the most imperiled fauna on the planet. Reasons for both local and widespread declines in mussels are mostly unknown, although the threats may include habitat loss and fragmentation, diseases, environmental contaminants, altered flow regimes, migration barriers to larval hosts, non-native species, and climate change. Over the past three decades, research on mussels has been substantial. Nevertheless, current conservation and management efforts are limited by significant information gaps. For example, the effects of emerging stressors on mussels are largely unknown and identifying when habitats are rehabilitated and suitable for reestablishment of mussels remains challenging. Additionally, historical and current information on the distribution, taxonomy, and life histories are often unreliable or lacking altogether, and more reliable information is needed for many species. We identified focal research themes, goals, and objectives where research on mussels is needed based on information gaps identified through conversations with resource partners across local, regional, and national organizations. Research on biodiversity seeks to enhance the diversity of mussel species and populations to support healthy aquatic ecosystems. Research on emerging stressors seeks to improve the understanding of how mussel species, populations, and communities respond to emerging stressors, including environmental contaminants and climate change. Research on conservation seeks to enhance the recovery of species and populations and to identify data gaps limiting the conservation of mussels and their habitats. Mussels are in urgent need of proactive conservation because they are an integral part of our natural heritage, enhance biodiversity, and provide vital ecological services that support freshwater ecosystems. The U.S. Geological Survey (USGS) has been, and continues to be, a leader in mussel research. Although the USGS is well suited to address the broad-scale multidisciplinary research needed to conserve mussels, the USGS has had substantial loss of scientists with mussel expertise over the past 20 years. However, the breadth of the USGS expertise on mussels can be leveraged internally across other USGS mission and program areas and externally across research partners. Given the breadth and scope of the issues facing mussels across the United States, the research themes outlined in this science vision can only be accomplished through extensive collaborations between the USGS and the full spectrum of natural resource partners, including other Federal and State agencies, Tribal organizations, universities, industries, and nongovernmental organizations.

Circular↗
USGS2025

U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward

This “U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward” (“Pollinator Science Strategy”) describes the science vision of the U.S. Geological Survey (USGS) to support management, conservation, and policy decisions on animal pollinators and their habitats. As the science arm of the Department of the Interior, the USGS has a primary role in providing scientific information to natural resource managers and policymakers across the United States. This “Pollinator Science Strategy” was drafted by a team of USGS pollinator researchers and was further developed through feedback from Federal, State, Tribal, nongovernmental organizations, and industry partners. This “Pollinator Science Strategy” highlights the USGS’s role in the research to promote healthy pollinator populations and address partner information gaps so they can make more informed management decisions. By outlining the importance of USGS science in addressing the information needs of other agencies, organizations, and the public, the “Pollinator Science Strategy” reaffirms the USGS’s commitment to pollinator research and showcases our research priorities for 2025–35. With more than 300 research centers nationally, the USGS is equipped to address pollinator science across scales of complexity and geographic range. USGS pollinator science is organized according to the following five thematic areas: Assessing species ecology, distributions, and natural history requirements. Tracking species status and trends. Understanding species threats and stressors. Informing restoration and management actions. Developing novel methods for improving pollinator research, monitoring, and population outcomes that can benefit our Nation. Our pollinator information products and associated data are made widely available to the public to ensure scientific transparency and accessibility. This “Pollinator Science Strategy” concludes with several research goals that the USGS will work towards from 2025 to 2035, representing our vision for USGS science. These research goals include synthesizing and modernizing the latest information on pollinator threats, developing research that assists managers with habitat design and restoration, providing training to partners on native bee identification and monitoring design, and developing new technologies for assessing the status and trends of our nation’s pollinators.

Circular↗
USGS2017

Ecological impacts of winter water level drawdowns on lake littoral zones: A review

Freshwater littoral zones harbor diverse ecological communities and serve numerous ecosystem functions that are controlled, in part, by natural water level fluctuations. However, human alteration of lake hydrologic regimes beyond natural fluctuations threaten littoral zone ecological integrity. One type of hydrologic alteration in lakes is winter water level drawdowns, which are frequently employed for hydropower, flood control, and macrophyte control, among other purposes. Here, we synthesize the abiotic and biotic responses to annual and novel winter water level drawdowns in littoral zones of lakes and reservoirs. The dewatering, freezing, and increased erosion of exposed lakebeds drive changes in the littoral zone. Shoreline-specific physicochemical conditions such as littoral slope and shoreline exposure further induce modifications. Loss of fine sediment decreases nutrient availability over time, but desiccation may promote a temporary nutrient pulse upon re-inundation. Annual winter drawdowns can decrease taxonomic richness of macrophytes and benthic invertebrates and shift assemblage composition to favor taxa with r-selected life history strategies and with functional traits resistant to direct and indirect drawdown effects. Fish assemblages, though less directly affected by winter drawdowns (except where there is critically low dissolved oxygen), experience negative effects via indirect pathways like decreased food resources and spawning habitat. We identify eight general research gaps to guide future research that could improve our understanding about the complex effects of winter drawdowns on littoral zone ecology.

Aquatic Sciences↗
USGS2025

Detection of Giardia and Cryptosporidium in surface water of a subarctic city

Giardia and Cryptosporidium spp. are globally distributed protozoan parasites that can cause gastrointestinal disease in humans and animals. These zoonotic parasites and their ecological relationships have been understudied in Alaska and elsewhere, despite being identified as priority zoonotic pathogens. We aimed to detect and characterize Giardia and Cryptosporidium spp. in waterbodies within Anchorage, Alaska, USA using two methods, including the Environmental Protection Agency (EPA) Method 1623 that relies on microscopy and a molecular detection approach. The molecular approach was ultimately unsuccessful and therefore only data obtained using Method 1623 are presented. Giardia or Cryptosporidium spp. was detected from nine of 15 urban streams and lakes sampled (60%), six of which were positive for both parasites (40%). Fewer than 10 cysts or oocysts were detected in 10 L of surface water. Further research to characterize Giardia and Cryptosporidium beyond the genus level would help elucidate the zoonotic potential and ecology of these parasites within the region and more broadly in Alaska.

Alaska↗
USGS2008

A Landscape Indicator Approach to the Identification and Articulation of the Ecological Consequences of Land Cover Change in the Chesapeake Bay Watershed, 1970-2000

The advancement of geographic science in the area of land surface status and trends and land cover change is at the core of the current geographic scientific research of the U.S. Geological Survey (USGS) (McMahon and others, 2005). Perhaps the least developed or articulated aspects of USGS land change science have been the identification and analysis of the ecological consequences of land cover change. Changes in land use and land cover significantly affect the ability of ecosystems to provide essential ecological goods and services, which, in turn, affect the economic, public health, and social benefits that these ecosystems provide. One of the great scientific challenges for geographic science is to understand and calibrate the effects of land use and land cover change and the complex interaction between human and biotic systems at a variety of natural, geographic, and political scales. Understanding the dynamics of land surface change requires an increased understanding of the complex nature of human-environmental systems and will require a suite of scientific tools that include traditional geographic data and analysis methods, such as remote sensing and geographic information systems (GIS), as well as innovative approaches to understanding the dynamics of complex systems. One such approach that has gained much recent scientific attention is the landscape indicator, or landscape assessment, approach, which has been developed with the emergence of the science of landscape ecology.

Fact Sheet↗
USGS2014

Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations

Many applications in ecological genetics involve sampling individuals from a mixture of multiple biological populations and subsequently associating those individuals with the populations from which they arose. Analytical methods that assign individuals to their putative population of origin have utility in both basic and applied research, providing information about population-specific life history and habitat use, ecotoxins, pathogen and parasite loads, and many other non-genetic ecological, or phenotypic traits. Although the question is initially directed at the origin of individuals, in most cases the ultimate desire is to investigate the distribution of some trait among populations. Current practice is to assign individuals to a population of origin and study properties of the trait among individuals within population strata as if they constituted independent samples. It seemed that approach might bias population-specific trait inference. In this study we made trait inferences directly through modeling, bypassing individual assignment. We extended a Bayesian model for population mixture analysis to incorporate parameters for the phenotypic trait and compared its performance to that of individual assignment with a minimum probability threshold for assignment. The Bayesian mixture model outperformed individual assignment under some trait inference conditions. However, by discarding individuals whose origins are most uncertain, the individual assignment method provided a less complex analytical technique whose performance may be adequate for some common trait inference problems. Our results provide specific guidance for method selection under various genetic relationships among populations with different trait distributions.

PLoS ONE↗
USGS2022

Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat

Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high-quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30 m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30 m spatial resolution from Landsat.

Frontiers in Remote Sensing↗
USGS2025

Increased mortality rates caused by highly pathogenic avian influenza virus in a migratory raptor

Highly pathogenic avian influenza virus (HPAIV) has caused extensive mortalities in wild birds with a disproportionate impact on raptors since 2021. The population-level impact of HPAIV can be informed by telemetry studies that track large samples of initially healthy, wild birds. We leveraged movement data from 71 rough-legged hawks ( Buteo lagopus ) across all major North American migratory bird flyways concurrent with the 2022–2023 HPAIV outbreak and identified a total of 29 mortalities, of which 11 were confirmed, and an additional ~9 were estimated to have been caused by HPAIV. We estimated a 28% HPAIV cause-specific mortality rate among rough-legged hawks during a single year concurrent with the HPAIV outbreak in North America. Additionally, the overall mortality rate during the HPAIV outbreak (47%) was significantly higher than baseline annual mortality rates (3%–17%) suggesting that HPAIV-caused deaths were additive above baseline mortality levels. HPAIV mortalities were concentrated within the Central and Atlantic flyways during prebreeding migration and peaked in April 2022 when large-scale HPAIV mortalities were reported in other wild birds throughout North America. HPAIV exposure was most likely caused by scavenging or preying on infected waterfowl, as rough-legged hawks are known to opportunistically scavenge during the nonbreeding season. We utilized movement data to identify a continental-scale HPAIV cause-specific mortality event in rough-legged hawks that has the potential to exacerbate ongoing population declines. Our study highlights the usefulness of monitoring movement data to pinpoint sources of mortality that can help better understand the drivers of population change, even if studies are focused on other research questions.

Ecology and Evolution↗
USGS2025

Characterizing the niche of Phalaris arundinacea (reed canarygrass) in floodplain forests of the Upper Mississippi River

Information on the favorable conditions for invasive species as well as potential constraints to their distribution can be valuable for management efforts. We used a niche modeling approach to analyze the patterns of species distributions along gradients of hypothesized influential environmental variables. Many ecological datasets may have incomplete coverage across the environmental gradients, infrequent sampling under some conditions, insufficient time for an invasive species to occupy all sites, and complex interactions among environmental variables (measured or unmeasured) that may result in species response curves that are difficult to interpret and may be ecologically misleading. To ensure the model and species response curves aligned with ecological niche theory, shape constraints were imposed to guarantee relationships follow a unimodal distribution to reflect the fundamental niche (where a species could occur). We compared a shape-constrained model to an unconstrained model and interpreted the species response curves from the constrained model to better characterize the ecological niche of reed canarygrass in floodplain forests of the Upper Mississippi River, USA. We found the probability of reed canarygrass occurrence decreases with increasing tree canopy cover, tree species richness, distance from forest edge, distance from invaded wet meadows, and island isolation. Probability of reed canarygrass presence exhibited bell-shaped curves in response to hydrology (inundation depth, frequency, and duration) and forest stress metrics indicating an optimum with less favorable conditions on either end of the ecological gradients. This information could be used to prioritize restoration efforts and enhance landcover change research in forested floodplains.

upper Mississippi River↗
USGS2016

Hierarchical species distribution models

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

Current Landscape Ecology Reports↗
USGS2020

The Fire and Tree Mortality Database, for empirical modeling of individual tree mortality after fire

Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research.

Scientific Data↗
USGS2000

The land cover trends project: A strategy for monitoring land cover change at a national scale

Policy-makers and scientists often require comprehensive data on the types and rates of land use and land cover change at a variety of scales. However, there is generally a lack of local, regional, and national land use and land cover data of sufficient reliability and temporal and geographic detail for providing accurate estimates of landscape change. The U.S. Geological Survey's EROS Data Center and the Landscape Ecology Branch of the U.S. Environmental Protection Agency are collaborating on a four-year research project to document the types, distributions, rates, drivers, and consequences of land cover change for the conterminous United States over the past 30 years. The project is using an ecoregion framework as a geographic stratifier. Both regional and national characteristics of change are determined by sampling land cover change for each of 84 ecoregions using five selected epochs of data from the nearly 30-year record of Landsat 1-7 data. Three types of land cover variables are being mapped or derived: (1) general land cover type; (2) landscape biophysical properties; and (3) landscape pattern. Assessments of the drivers and consequences of change within each ecoregion are then prepared. A pilot phase focusing on the analysis of five selected ecoregions is well underway and will be completed by the end of 2000. Methodologies established during the pilot phase will then be applied to the remaining ecoregions.

Conference Paper↗
USGS2024

Thinking beyond the closure assumption: Designing surveys for estimating biological truth with occupancy models

Occupancy models estimate distributions of imperfectly detected species, but violations of the closure assumption can bias results. However, researchers working with mobile animals may find it impossible to eliminate such violations. Here, we tested the hypothesis that occupancy models fit to realistic sampling data can generate unbiased occupancy estimates for an itinerant Wood Thrush ( Hylocichla mustelina ) population. In 2013 and 2014, we tracked movements of 41 breeding Wood Thrush males. We modelled territory shift probabilities using logistic exposure models and within-territory movements using continuous-time stochastic process models. We then constructed an individual-based model, simulated (1000 iterations) spatiotemporal locations for individuals and simulated sampling these populations using 162 different point count protocols with variable spatial (sampling radius and point placement method), and temporal (survey length, between-survey intervals and number of surveys) characteristics. We compared occupancy estimates with true values of instantaneous, daily and seasonal occupancy from the simulations. We parameterized continuous time stochastic process models based on movements within 34 unique territories and estimated a daily territory shift probability of 0.0099 (95% CI: 0.0060, 0.0152). Simulated data indicated that estimates of occupancy ranged from 0.18 (0.06, 1.00) to 0.80 (0.71, 0.89) depending on protocol characteristics. Occupancy estimates increased with increasing survey radius, survey length and between-survey interval. Protocols using shorter surveys and between-survey intervals were good estimators for instantaneous occupancy (low bias and mean-squared error) but poor estimators for daily and seasonal occupancy; longer surveys and intervals generated unbiased estimators of daily occupancy but underestimated seasonal occupancy. Logistic regression models that ignored imperfect detection outperformed occupancy models for estimating instantaneous occupancy but not daily or seasonal occupancy. For mobile animals, occupancy of sampling sites changes in space and time. Consequently, the spatial and temporal aspects of a sampling protocol have strong, but predictable, effects on occupancy model parameter estimates. Our results demonstrate that how these factors interact is critical for designing surveys that produce occupancy estimates representative of the biological process of interest to a researcher.

Methods in Ecology and Evolution↗
USGS2026

Epigenetics in captivity: Restoring wild phenotypes in captive-reared salmonids

Captive rearing is a common practice for the stocking, conservation, and supplementation of fish species worldwide, but captive-reared fish can exhibit altered phenotypes leading to reduced fitness in nature compared to wild conspecifics. In salmonids, certain studies have found limited genetic differentiation between wild and captive-reared fish. However, documented changes in gene expression in hatchery fish have led scientists to investigate epigenetic mechanisms, such as DNA methylation, as a source of these differences. In this binational collaborative piece, we synthesize the knowledge and efforts of academics and government scientists to highlight how interactions between captive rearing and the epigenome elicit parallel phenotypic changes across salmonid species. We examine the known and potential links between DNA methylation and the phenotypic effects of captive rearing including changes in behavior, color, gut microbiomes, and developmental abnormalities. We review efforts to minimize these phenotypic and epigenetic effects including attempts to modify the hatchery environment and rearing protocols. We provide a framework to integrate epigenetic considerations into hatchery rearing protocols by weighing the heritable nature of DNA methylation with the goals of different captive rearing programs and explore whether minimizing the phenotypic and epigenetic effects of captive rearing is worthwhile. We examine heritability and persistence of epigenetic effects, and we propose the exploitation of heritable bet-hedging as an epigenetic buffer to increase post-release survival. We also suggest novel applications of epigenomic biomarkers as a non-lethal method for post-release monitoring. Ultimately, collaborative multi-disciplinary research across species is needed to understand the comprehensive effects of captive rearing, reduce the ecological impacts of captive fish in the wild, and increase population resilience. Integrating epigenetics into fish hatchery management will provide new opportunities for optimizing and improving captive rearing.

Evolutionary Applications↗
USGS2011

Detection biases yield misleading patterns of species persistence and colonization in fragmented landscapes

Species occurrence patterns, and related processes of persistence, colonization and turnover, are increasingly being used to infer habitat suitability, predict species distributions, and measure biodiversity potential. The majority of these studies do not account for observational error in their analyses despite growing evidence suggesting that the sampling process can significantly influence species detection and subsequently, estimates of occurrence. We examined the potential biases of species occurrence patterns that can result from differences in detectability across species and habitat types using hierarchical multispecies occupancy models applied to a tropical bird community in an agricultural fragmented landscape. Our results suggest that detection varies widely among species and habitat types. Not incorporating detectability severely biased occupancy dynamics for many species by overestimating turnover rates, producing misleading patterns of persistence and colonization of agricultural habitats, and misclassifying species into ecological categories (i.e., forest specialists and generalists). This is of serious concern, given that most research on the ability of agricultural lands to maintain current levels of biodiversity by and large does not correct for differences in detectability. We strongly urge researchers to apply an inferential framework which explicitly account for differences in detectability to fully characterize species-habitat relationships, correctly guide biodiversity conservation in human-modified landscapes, and generate more accurate predictions of species responses to future changes in environmental conditions.

Las Cruces Biological Station↗
USGS2007

Characteristics of roost sites used by burrowing owls (Athene cunicularia) wintering in Southern Texas

The western burrowing owl (Athene cunicularia hypugaea) is threatened in Mexico, endangered in Canada, and declining in most of the western United States. Most previous research has focused on burrowing owl breeding biology, and little is known about its winter ecology. We determined characteristics of roost sites used by western burrowing owls in southern Texas during winter. Data on 46 winter roost sites were collected from 15 November 2001 to 15 February 2002. Of these roost sites, 87% were located on agricultural land, 80% were along roads, and 74% were concrete, steel, or cast-iron culverts. Mean diameter (??SE) of roost site openings was 22 ?? 1.5 cm. Most roost sites (70%) were located on inaccessible private lands. Bare ground comprised 61% of ground cover within a 10-m radius of roost sites. We recommend that landowners and public-land managers should be encouraged to use smaller-diameter culverts when building roads or replacing old or damaged culverts and to graze livestock or mow around these culverts during winter.

Texas↗