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At least 235 records · Page 13Linked to original sources
USGS2015

Growth responses of five desert plants as influenced by biological soil crusts from a temperate desert, China

In almost all dryland systems, biological soil crusts (biocrusts) coexist alongside herbaceous and woody vegetation, creating landscape mosaics of vegetated and biocrusted patches. Results from past studies on the interaction between biocrusts and vascular plants have been contradictory. In the Gurbantunggut desert, a large temperate desert in northwestern China, well-developed lichen-dominated crusts dominate the areas at the base and between the sand dunes. We examined the influence of these lichen-dominated biocrusts on the germination, growth, biomass accumulation, and elemental content of five common plants in this desert: two shrubs ( Haloxylon persicum , Ephedra distachya ) and three herbaceous plants ( Ceratocarpus arenarius , Malcolmia africana and Lappula semiglabra ) under greenhouse conditions. The influence of biocrusts on seed germination was species-specific. Biocrusts did not affect percent germination in plants with smooth seeds, but inhibited germination of seeds with appendages that reduced or eliminated contact with the soil surface or prevented seeds from slipping into soil cracks. Once seeds had germinated, biocrusts had different influences on growth of shrub and herbaceous plants. The presence of biocrusts increased concentrations of nitrogen but did not affect phosphorus or potassium in tissue of all tested species, while the uptake of the other tested nutrients was species-specific. Our study showed that biocrusts can serve as a biological filter during seed germination and also can influence growth and elemental uptake. Therefore, they may be an important trigger for determining desert plant diversity and community composition in deserts.

Ecological Research↗
USGS2016

Study of biological communities subject to imperfect detection: Bias and precision of community N -mixture abundance models in small-sample situations

Community N -mixture abundance models for replicated counts provide a powerful and novel framework for drawing inferences related to species abundance within communities subject to imperfect detection. To assess the performance of these models, and to compare them to related community occupancy models in situations with marginal information, we used simulation to examine the effects of mean abundance ( λ ¯ : 0.1, 0.5, 1, 5), detection probability ( p ¯ : 0.1, 0.2, 0.5), and number of sampling sites ( n site : 10, 20, 40) and visits ( n visit : 2, 3, 4) on the bias and precision of species-level parameters (mean abundance and covariate effect) and a community-level parameter (species richness). Bias and imprecision of estimates decreased when any of the four variables ( λ ¯ , p ¯ , n site , n visit ) increased. Detection probability p ¯ was most important for the estimates of mean abundance, while λ ¯ was most influential for covariate effect and species richness estimates. For all parameters, increasing n site was more beneficial than increasing n visit . Minimal conditions for obtaining adequate performance of community abundance models were n site ≥ 20, p¯ ≥ 0.2, and λ ¯ ≥ 0.5. At lower abundance, the performance of community abundance and community occupancy models as species richness estimators were comparable. We then used additive partitioning analysis to reveal that raw species counts can overestimate β diversity both of species richness and the Shannon index, while community abundance models yielded better estimates. Community N -mixture abundance models thus have great potential for use with community ecology or conservation applications provided that replicated counts are available.

Ecological Research↗
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↗
USGS2008

Faunal impact on vegetation structure and ecosystem function in mangrove forests: A review

The last 20 years witnessed a real paradigm shift concerning the impact of biotic factors on ecosystem functions as well as on vegetation structure of mangrove forests. Before this small scientific revolution took place, structural aspects of mangrove forests were viewed to be the result of abiotic processes acting from the bottom-up, while, at ecosystem level, the outwelling hypothesis stated that mangroves primary production was removed via tidal action and carried to adjacent nearshore ecosystems where it fuelled detrital based food-webs. The sesarmid crabs were the first macrofaunal taxon to be considered a main actor in mangrove structuring processes, thanks to a number of studies carried out in the Indo-Pacific forests in the late 1970s and early 1980s. Following these classical papers, a number of studies on Sesarmidae feeding and burrowing ecology were carried out, which leave no doubts about the great importance of these herbivorous crabs in structuring and functioning Old world ecosystems. Although Sesarmidae are still considered very important in shaping mangrove structure and functioning, recent literature emphasizes the significance of other invertebrates. The Ocypodidae have now been shown to have the same role as Sesarmidae in terms of retention of forest products and organic matter processing in New world mangroves. In both New and Old world mangroves, crabs process large amounts of algal primary production, contribute consistently to retention of mangrove production and as ecosystem engineers, change particle size distribution and enhance soil aeration. Our understanding of the strong impact of gastropods, by means of high intake rates of mangrove products and differential consumption of propagules, has changed only recently. The role of insects must also be stressed. It is now clear that older techniques used to assess herbivory rates by insects strongly underestimate their impact, both in case of leaf eating and wood boring species and that herbivorous insects can potentially play a strong role in many aspects of mangrove ecology. Moreover, researchers only recently realized that ant–plant interactions may form an important contribution to our understanding of insect–plant dynamics in these habitats. Ants seem to be able to relieve mangroves from important herbivores such as many insects and sesarmid crabs. It thus seems likely that ants have positive effects on mangrove performance.

Aquatic Botany↗
USGS2015

Caveats for correlative species distribution modeling

Correlative species distribution models are becoming commonplace in the scientific literature and public outreach products, displaying locations, abundance, or suitable environmental conditions for harmful invasive species, threatened and endangered species, or species of special concern. Accurate species distribution models are useful for efficient and adaptive management and conservation, research, and ecological forecasting. Yet, these models are often presented without fully examining or explaining the caveats for their proper use and interpretation and are often implemented without understanding the limitations and assumptions of the model being used. We describe common pitfalls, assumptions, and caveats of correlative species distribution models to help novice users and end users better interpret these models. Four primary caveats corresponding to different phases of the modeling process, each with supporting documentation and examples, include: (1) all sampling data are incomplete and potentially biased; (2) predictor variables must capture distribution constraints; (3) no single model works best for all species, in all areas, at all spatial scales, and over time; and (4) the results of species distribution models should be treated like a hypothesis to be tested and validated with additional sampling and modeling in an iterative process.

Ecological Informatics↗
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↗
USGS2001

Early post-fire succession in California chaparral: Changes in diversity, density, cover and biomass

For four consecutive years, following the fires in November 1993, temporal variations in species richness, cover and biomass of component plant groups in early post-fire chaparral succession were monitored on different aspects at the Stunt Ranch Santa Monica Mountains Reserve, southern California. Plant groups were categorized based on growth form, life form, ability to fix nitrogen, geographic origin and regeneration strategies. North-facing slopes exhibited higher species richness, higher species turnover rate over time and faster vegetation recovery in terms of biomass accumulation and return to pre-fire species composition. This was probably due to higher species richness and biomass of nitrogen-fixing species found on north-facing slopes in comparison to south-facing slopes. On both north- and south-facing slopes, annuals had the highest species turnover rate, followed by herbaceous perennials and shrubs. In the first four post-fire years, annual species were the largest floristic group, but herbaceous perennials and shrubs were the major contributors to community biomass. Nitrogen-fixing species and exotics contributed significantly to early post-fire community structure. Although the general trends in post-fire succession are clear in terms of temporal changes in the relative proportions of different plant groups, environmental variation and the nature of plant life histories of component species, especially dominant species, could alter such trends significantly.

Ecological Research↗
USGS2012

A tale of two land uses in the American West: rural residential growth and energy development

This paper describes a spatiotemporal land use map for a rural county in the western United States. Sublette County, Wyoming has undergone recent land use change in the form of heightened rural residential development on private land and increased energy development on both public and private land. In this study we integrate energy production data, population census data, ownership parcel data, and a series of Landsat Thematic Mapper and Enhanced Thematic Mapper scenes (over a 25-year period) to create a map that illustrates the changing landscape. Spatial change on the landscape is mapped at 30 square meters, congruent with a Landsat pixel. Sublette County has a wealth of wildlife and associated habitat which is affected by both types of growth. While we do not attempt to quantify the effect of disturbance on wildlife species, we believe our results can provide important baseline data that can be incorporated into land use planning and ecological-wildlife research at the landscape scale.

Journal of Maps↗
USGS2025

Sentinel imagery detects the presence of live trees following large wildfires in California

Identifying live tree presence following wildfire is important for burn damage assessments and decision making, as these trees serve as seed sources for recovery. Satellite-based remote sensing offers an efficient means to assess burn severity with products representing vegetation greenness and char/ash presence and their change from pre- to post-fire imagery. While effective at assessing burn severity (e.g. ecosystem change), there remain limitations in identifying fire refugia (surviving trees), due to the difficulty of teasing apart different green vegetation types (e.g. trees, shrubs, grasses). In this paper, we use 10 m Sentinel-2 satellite data to predict live tree presence across three sites impacted by the 2021 California fire season. We used vegetation indices (VIs) from post-fire imagery (normalized difference vegetation index [NDVI], normalized burn ratio [NBR], normalized difference water index [NDWI], visible atmospherically resistant index [VARI], and burn area index [BAI]), differential VIs from pre- and post-fire imagery (dNDVI, dNBR, RdNBR, dNDWI, dVARI), and direct reflectance bands (all bands model; visible, near-infrared, and shortwave infrared; B1–B12) to predict live tree presence via random forest modeling. To calibrate and validate the random forest models, we photointerpreted ∼2300 pixels per fire region using 2022 National Agriculture Imagery Program imagery. We performed additional field-based validation using tree presence/absence data two years post-fire ( n = 296 observations across two sites). At the site level, the all bands model outperformed the vegetation index-based models (80%–85% vs 65%–79% accuracy). Errors were mainly false positives attributed to pixels with green understory vegetation but no live trees. In cross-site inference, which involved pooling two sites for model calibration to test on the third site, the all bands model retained good performance (76%–81% accuracy). Evaluation against field survey data demonstrated a larger range of performance (50%–87% accuracy) that highlights limitations based on tree isolation and crown percent greenness. Relative to differential-based VIs, our results highlight potential advantages of using post-fire Sentinel-2 imagery and random forest modeling for identifying live tree presence and scaling to full fire extents.

California↗
USGS2026

Initial condition uncertainty exerts a large and persistent influence on model simulations of ecosystem carbon dynamics in California

Uncertainties in terrestrial ecosystem models limit their predictive power. Efforts to reduce projection error have rarely focused on constraining uncertainty in the initial state of the ecosystem, however, despite evidence that matching model initial conditions to real-world observations reduces overall model bias. Here we use an integrated land change and carbon gain-loss model to evaluate the influence of initial condition uncertainty on simulations of California wildland ecosystems during the years 1985–2020. We generated 36 initial conditions scenarios by varying the source data used to initialize state variables and then ran simulations based on each of these scenarios under a constant set of historical conditions. We found that discrepancies in initial forest extent and initial forest age among scenarios generated wide uncertainty ranges in model estimates of terrestrial ecosystem carbon stocks and flux rates at the outset of the simulation period, but differences in initial forest composition had no impact. Over time, forest age became more homogeneous across model scenarios leading to exponential rates of decline in the uncertainty ranges of live biomass and dead wood carbon but little to no impact on uncertainties in litter and soil organic carbon. Uncertainties in individual carbon flux rates were consistent with uncertainties in their source pools. In contrast, model estimates of ecosystem carbon balance demonstrated a shift in system behavior not apparent in trends for individual carbon stocks and fluxes. Specifically, estimates of ecosystem carbon balance converged across scenarios for the first 20 years of the simulation period but then began to diverge at an accelerating rate, possibly due to weakened resilience to the increased frequency and severity of climate-driven disturbances. Our results demonstrate that uncertainty in the initial state of the system can have large and persistent impacts on the predictability of ecosystem carbon dynamics, and that ongoing shifts in external forcing by climate and climate-driven disturbances can exacerbate these impacts.

California↗
USGS2026

Bridging ecology and geosciences in riverscapes: Implications for process-based restoration

There has been a growing interest in integrating geological and ecological processes for sustainable river management and restoration. Lotic systems are shaped by diverse physical processes, including geology, geomorphology, hydrology, and interactions with terrestrial processes. However, restoration practices often prioritize specific habitats or river forms without fully considering the underlying physical processes that support biological communities and ecosystem functions. In this paper, we synthesize studies that integrally examine geological and ecological processes across different scales and components of riverscapes, including geohydrological processes, which have been less investigated in riverscape studies. We begin by examining processes at broader spatial scales, including river–watershed and river–riparian interactions, and gradually narrow our focus to the dynamics that occur among habitats within river channels, through which we highlight the significance of conceptualizing rivers as dynamic “networks” rather than linear features. Finally, we identify both scientific and practical challenges that can be addressed to bridge the gap between basic-science implications and their implementation in riverscape restorations.

Ecological Research↗
USGS2006

Resource availability controls fungal diversity across a plant diversity gradient

Despite decades of research, the ecological determinants of microbial diversity remain poorly understood. Here, we test two alternative hypotheses concerning the factors regulating fungal diversity in soil. The first states that higher levels of plant detritus production increase the supply of limiting resources (i.e. organic substrates) thereby increasing fungal diversity. Alternatively, greater plant diversity increases the range of organic substrates entering soil, thereby increasing the number of niches to be filled by a greater array of heterotrophic fungi. These two hypotheses were simultaneously examined in experimental plant communities consisting of one to 16 species that have been maintained for a decade. We used ribosomal intergenic spacer analysis (RISA), in combination with cloning and sequencing, to quantify fungal community composition and diversity within the experimental plant communities. We used soil microbial biomass as a temporally integrated measure of resource supply. Plant diversity was unrelated to fungal diversity, but fungal diversity was a unimodal function of resource supply. Canonical correspondence analysis (CCA) indicated that plant diversity showed a relationship to fungal community composition, although the occurrence of RISA bands and operational taxonomic units (OTUs) did not differ among the treatments. The relationship between fungal diversity and resource availability parallels similar relationships reported for grasslands, tropical forests, coral reefs, and other biotic communities, strongly suggesting that the same underlying mechanisms determine the diversity of organisms at multiple scales. ?? 2006 Blackwell Publishing Ltd/CNRS.

Ecology Letters↗
USGS2014

Nutritional stress affects corticosterone deposition in feathers of Caspian tern chicks

Stressful environmental conditions affect the adrenocortical function of developing animals, which can have consequences for their fitness. Discovery of the avian stress hormone corticosterone (CORT) in feathers has the potential to broaden the application of endocrine research in ecological and evolutionary studies of wild birds by providing a long-term measure of CORT secretion. Mechanisms of CORT deposition in feathers are not well known and few studies have related feather CORT to circulating plasma CORT during feather growth. Our objective was to experimentally test the validity of using feather CORT as a measure of CORT secretion in developing birds experiencing nutritional stress. Caspian tern Hydroprogne caspia chicks were fed ad libitum or restricted (35% less than ad libitum) diets for four weeks. We measured CORT in feathers from these chicks to examine the relationship between feather CORT concentrations and nutritional limitation, circulating plasma CORT, and feather development. We found that feather CORT was higher in controls fed ad libitum than in restricted individuals, despite higher levels of plasma CORT in restricted chicks compared to controls. Feather mass and growth rates were strongly and positively related to feather CORT concentrations in both treatments. This is the first experimental study to show that feather CORT concentrations can be lower in response to nutritional stress, even when plasma CORT concentrations are elevated. Our results indicate that CORT deposition in feathers may be confounded when feather mass and growth rates are compromised by nutritional stress. We conclude that feather CORT can be used for assessing nutritional stress in growing birds, but the direction of response depends on how strongly stress affects feather development.

Journal of Avian Biology↗
USGS2016

Local biotic adaptation of trees and shrubs to plant neighbors

Natural selection as a result of plant–plant interactions can lead to local biotic adaptation. This may occur where species frequently interact and compete intensely for resources limiting growth, survival, and reproduction. Selection is demonstrated by comparing a genotype interacting with con- or hetero-specific sympatric neighbor genotypes with a shared site-level history (derived from the same source location), to the same genotype interacting with foreign neighbor genotypes (from different sources). Better genotype performance in sympatric than allopatric neighborhoods provides evidence of local biotic adaptation. This pattern might be explained by selection to avoid competition by shifting resource niches (differentiation) or by interactions benefitting one or more members (facilitation). We tested for local biotic adaptation among two riparian trees, Populus fremontii and Salix gooddingii , and the shrub Salix exigua by transplanting replicated genotypes from multiple source locations to a 17 000 tree common garden with sympatric and allopatric treatments along the Colorado River in California. Three major patterns were observed: 1) across species, 62 of 88 genotypes grew faster with sympatric neighbors than allopatric neighbors; 2) these growth rates, on an individual tree basis, were 44, 15 and 33% higher in sympatric than allopatric treatments for P. fremontii, S. exigua and S. gooddingii , respectively, and; 3) survivorship was higher in sympatric treatments for P. fremontii and S. exigua . These results support the view that fitness of foundation species supporting diverse communities and dominating ecosystem processes is determined by adaptive interactions among multiple plant species with the outcome that performance depends on the genetic identity of plant neighbors. The occurrence of evolution in a plant-community context for trees and shrubs builds on ecological evolutionary research that has demonstrated co-evolution among herbaceous taxa, and evolution of native species during exotic plants invasion, and taken together, refutes the concept that plant communities are always random associations.

Arizona↗
USGS2014

From hybrid swarms to swarms of hybrids

Science has shown that the introgression or hybridization of modern humans ( Homo sapiens ) with Neanderthals up to 40,000 YBP may have led to the swarm of modern humans on earth. However, there is little doubt that modern trade and transportation in support of the humans has continued to introduce additional species, genotypes, and hybrids to every country on the globe. We assessed the utility of species distributions modeling of genotypes to assess the risk of current and future invaders. We evaluated 93 locations of the genus Tamarix for which genetic data were available. Maxent models of habitat suitability showed that the hybrid, T. ramosissima x T. chinensis , was slightly greater than the parent taxa (AUCs > 0.83). General linear models of Africanized honey bees, a hybrid cross of Tanzanian Apis mellifera scutellata and a variety of European honey bee including A. m. ligustica , showed that the Africanized bees (AUC = 0.81) may be displacing European honey bees (AUC > 0.76) over large areas of the southwestern U.S. More important, Maxent modeling of sub-populations (A1 and A26 mitotypes based on mDNA) could be accurately modeled (AUC > 0.9), and they responded differently to environmental drivers. This suggests that rapid evolutionary change may be underway in the Africanized bees, allowing the bees to spread into new areas and extending their total range. Protecting native species and ecosystems may benefit from risk maps of harmful invasive species, hybrids, and genotypes.

Environment and Ecology Research↗
USGS2018

Geomorphometry in landscape ecology: Issues of scale, physiography, and application

Topographic measures are frequently used in a variety of landscape ecology applications, in their simplest form as elevation, slope, and aspect, but increasingly more complex measures are being employed. We explore terrain metric similarity with changes in scale, both grain and extent, and examine how selecting the best measures is sensitive to changes in application. There are three types of topographic measures: 1) those that relate to orientation for approximating solar input, 2) those that capture variability in terrain configuration, and 3) those that provide metrics about landform features. Many biodiversity hotspots and predators have been found to coincide with areas of complexity, yet most complexity measures cannot differentiate between terrain steepness and uneven and broken terrain. Currently characterizing terrain in landscape-level analyses can be challenging, especially at coarser spatial resolutions but developing methods that improve landscape-level assessments include multivariate approaches and the use of neighborhood statistics. Some measures are sensitive to the spatial grain of calculation, the physiography of the landscape, and the scale of application. We show which measures have the potential to be multi-collinear, and illustrate with a case study how the selection of the best measures can change depending on the question at hand using mountain lion (Puma concolor) occurrence data. The case study showed a combination of infrequently employed metrics, such as view-shed analysis and focal statistics, outperform more commonly employed singular metrics. The use of focal statistics as a measure of topographic complexity shows promise for improving how mountain lions use terrain features.

Environment and Ecology Research↗
USGS2006

Submarine ground-water discharge: nutrient loading and nitrogen transformations

Eutrophication of coastal waters due to nonpoint source land-derived nitrogen (N) loads is a worldwide phenomenon and perhaps the greatest agent of change altering coastal ecology (National Research Council, 2000; Howarth and others, 2000). Within the United States, a majority of estuaries have been determined to be moderately to severely impaired by eutrophication associated with increasing nutrient loads (Bricker and others, 1999). In coastal watersheds with soils of high hydraulic conductivity and permeable coastal sediments, ground water is a major route of transport of freshwater and its solutes from land to sea. Freshwater flowing downgradient from aquifers may either discharge from a seepage face near the intertidal zone, or flow directly into the sea as submarine ground-water discharge (SGD) (fig. 1). In the coastal aquifer, entrainment of saline pore water occurs prior to discharge, producing a gradient in ground-water salinity from land to sea, referred to as a subterranean estuary (Moore, 1999). In addition, processes including density-driven flow and tidal pumping create brackish and saline ground-water circulation. Hence, submarine ground-water discharge often consists of a substantial amount of recirculating seawater. Mixing of fresh and saline ground waters in the context of coastal sediments may alter the chemical composition of the discharging fluid. Depending on the biogeochemical setting, removal of fixed N due to processes leading to N 2 (dinitrogen gas) production in the nearshore aquifer and subterranean estuary may significantly attenuate land-derived N loads; or, processes such as ion exchange and tidal pumping in the subterranean estuary may substantially accelerate the transport of both land-derived and sediment re-mineralized N to estuarine water columns. As emphasized by Burnett and others (2001, 2002), a fundamental problem in evaluating the importance of ground-water discharge in marine geochemical budgets is the difficulty of collecting samples across the salinity gradients of coastal aquifers. In addition, locating and quantifying rates of submarine ground-water discharge remains a challenge due to the diffuse and spatially and temporally heterogeneous nature of discharge. As a result, with regard to the study of biogeochemical cycles and chemical loads to coastal waters, the seepage face and subterranean estuary are relatively new and under-studied zones in the aquatic cascade from watershed to sea. Processes occurring in those zones must be understood and considered for proper modeling and management of coastal water resources.

Fact Sheet↗
USGS2011

Molecular genetics at the Fort Collins Science Center

The Fort Collins Science Center operates a molecular genetic and systematics research facility (FORT Molecular Ecology Laboratory) that uses molecular genetic tools to provide genetic information needed to inform natural resource management decisions. For many wildlife species, the data generated have become increasingly important in the development of their long-term management strategies, leading to a better understanding of species diversity, population dynamics and ecology, and future conservation and management needs. The Molecular Ecology Lab serves Federal research and resource management agencies by developing scientifically rigorous research programs using nuclear, mitochondrial and chloroplast DNA to help address many of today's conservation biology and natural resource management issues.

Fact Sheet↗