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At least 1,549 records · Page 86Linked to original sources
USGS2018

Running on empty: Recharge dynamics from animal movement data

Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population-level characteristics are tied with individual-level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous-time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion ( Puma concolor ; in Colorado, USA) and African buffalo ( Syncerus caffer ; in Kruger National Park, South Africa) recharge dynamics.

Ecology Letters↗
USGS2014

Natural flow regimes of the Ozark-Ouachita Interior Highlands region

Natural flow regimes represent the hydrologic conditions to which native aquatic organisms are best adapted. We completed a regional river classification and quantitative descriptions of each natural flow regime for the Ozark–Ouachita Interior Highlands region of Arkansas, Missouri and Oklahoma. On the basis of daily flow records from 64 reference streams, seven natural flow regimes were identified with mixture model cluster analysis: Groundwater Stable, Groundwater, Groundwater Flashy, Perennial Runoff, Runoff Flashy, Intermittent Runoff and Intermittent Flashy. Sets of flow metrics were selected that best quantified nine ecologically important components of these natural flow regimes. An uncertainty analysis was performed to avoid selecting metrics strongly affected by measurement uncertainty that can result from short periods of record. Measurement uncertainties (bias, precision and accuracy) were assessed for 170 commonly used flow metrics. The ranges of variability expected for select flow metrics under natural conditions were quantified for each flow regime to provide a reference for future assessments of hydrologic alteration. A random forest model was used to predict the natural flow regimes of all stream segments in the study area based on climate and catchment characteristics, and a map was produced. The geographic distribution of flow regimes suggested distinct ecohydrological regions that may be useful for conservation planning. This project provides a hydrologic foundation for future examination of flow–ecology relationships in the region. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Arkansas, Missouri, Oklahoma↗
USGS2018

Population ecology of Roosevelt elk: Conservation and management in Redwood National and State Parks. Butch Weckerly. 2017. University of Nevada Press, Reno, Nevada, USA. 224 pp. $54.95 hardback. ISBN 978- 1943859504.

Long-term research on large ungulate populations typically conjures perceptions of extensive (and expensive) animal capture and telemetry work, and subsequent advanced modeling of resource selection and population dynamics that inform management decisions. In contrast, studies lacking a telemetry component are often limited to animal behavior or natural history. Although compelling from a standpoint of advancing understanding of ecological and evolutionary processes, results from the latter can be unfairly labeled as esoteric because they are not easily transferable to resource managers or may not provide exceptional interest to a general public drawn to these charismatic megafuana. Such dichotomies are not predetermined, however, because study conditions exist where dedicated academic researchers on tight budgets can achieve results relevant to ecology and management.

Journal of Wildlife Management↗
USGS2008

Mapping "old" versus "young" piñon-juniper stands with a predictive topo-climatic model in north-central New Mexico, USA

Piñon pine and juniper woodlands in the southwestern United States are often represented as an expanding and even invasive vegetation type, a legacy of historic grazing, and culpable in the degradation of western rangelands. A long-standing emphasis on forage production, in combination with recent hazard fuel concerns, has prompted a new era of woodland management with stated restoration objectives. Yet the extent and dynamics of piñon–juniper communities that predate intensive Euro-American settlement activities are poorly known or understood, while the intrinsic ecological, aesthetic, and economic values of old-growth woodlands are often overlooked. Historical changes in piñon–juniper stands include two related, but poorly differentiated processes: recent tree expansion into grass- or shrub-dominated (i.e., non-woodland) vegetation and thickening or infilling of savanna or mosaic woodlands predating settlement. Our work addresses the expansion pattern, modeling the occurrence of “older” savanna and woodland stands extant prior to 1850 in contrast to “younger” piñon–juniper growth of more recent, postsettlement origin. We present criteria in the form of a diagnostic key for distinguishing “older,” pre-Euro-American settlement piñon–juniper from “younger” (post-1850) stands and report results of predictive modeling and mapping efforts within a north-central New Mexico study area. Selected models suggest a primary role for soil moisture in the current distribution of “old” vs. “young” piñon–juniper stands. Presettlement era woodlands are shown to occupy a discrete ecological space, defined by the interaction of effective (seasonal) moisture with landform setting and fine-scale (soil/water) depositional patterns. “Older” stands are generally found at higher elevations or on skeletal soils in upland settings, while “younger” stands (often dominated by one-seed juniper, Juniperus monosperma ) are most common at lower elevations or in productive, depositional settings. Modeling at broad regional scales can enhance our general understanding of piñon–juniper ecology, while predictive mapping of local areas has potential to provide products useful for land management. Areas of the southwestern United States with strong monsoonal (summer moisture) patterns appear to have been the most susceptible to historical woodland expansion, but even here the great majority of extant piñon–juniper has presettlement origins (although widely thickened and infilled historically), and old-growth structure is not uncommon in appropriate upland settings.

Ecological Applications↗
USGS2022

Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density

Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata . We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.

New Hampshire↗
USGS2008

An annual plant growth proxy in the Mojave Desert using MODIS-EVI data

In the arid Mojave Desert, the phenological response of vegetation is largely dependent upon the timing and amount of rainfall, and maps of annual plant cover at any one point in time can vary widely. Our study developed relative annual plant growth models as proxies for annual plant cover using metrics that captured phenological variability in Moderate-Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) satellite images. We used landscape phenologies revealed in MODIS data together with ecological knowledge of annual plant seasonality to develop a suite of metrics to describe annual growth on a yearly basis. Each of these metrics was applied to temporally-composited MODIS-EVI images to develop a relative model of annual growth. Each model was evaluated by testing how well it predicted field estimates of annual cover collected during 2003 and 2005 at the Mojave National Preserve. The best performing metric was the spring difference metric, which compared the average of three spring MODIS-EVI composites of a given year to that of 2002, a year of record drought. The spring difference metric showed correlations with annual plant cover of R2 = 0.61 for 2005 and R 2 = 0.47 for 2003. Although the correlation is moderate, we consider it supportive given the characteristics of the field data, which were collected for a different study in a localized area and are not ideal for calibration to MODIS pixels. A proxy for annual growth potential was developed from the spring difference metric of 2005 for use as an environmental data layer in desert tortoise habitat modeling. The application of the spring difference metric to other imagery years presents potential for other applications such as fuels, invasive species, and dust-emission monitoring in the Mojave Desert.

Sensors↗
USGS2022

Temporal mismatch in space use by a sagebrush obligate species after large-scale wildfire

The increase in size and frequency of wildfires in sagebrush steppe ecosystems has significant impacts on sagebrush obligate species. We modeled seasonal habitat use by female greater sage-grouse ( Centrocercus urophasianus ) in the Trout Creek Mountains of Oregon and Nevada, USA, to identify landscape characteristics that influenced sage-grouse habitat selection and to create predictive surfaces of seasonal use 1 and 7 years postfire. We developed three resource selection function models using GPS location data from 2013 to 2019 for three biologically distinct seasons (breeding, n = 149 individuals: 8 March–12 June; summer, n = 140 individuals: 13 June–20 October; and winter, n = 94 individuals: 21 October–7 March). For all seasons, by the fourth or fifth year postfire, sage-grouse selected for unburned patches more than all other burn severity patches and the use of unburned areas in comparison with burned areas increased through time. During the breeding season, sage-grouse selected for low-sagebrush ( Artemisia arbuscula )-dominated ecosystems and areas with low biomass (normalized difference vegetation index). During summer, sage-grouse selected for areas with higher annual and perennial grasses and forb cover, and areas that had higher biomass. During winter, sage-grouse selected for areas of intact sagebrush on less rugged terrain. For the winter and breeding season, there was a positive linear relationship between annual grasses and forb cover through time. Seven years postfire (2019), the area predicted to have a high probability of use in each seasonal range decreased (breeding: 16.4%; summer: 12.2%; and winter: 4.2%), while the area predicted to have low or low-medium probability of use increased (breeding: 14.5%; summer: 22.5%; and winter: 22.8%) when compared to the first year following the wildfire (2013). Our results demonstrated a 4- to 5-year time lag before female sage-grouse adapted to a disturbed landscape began avoiding burned areas more than intact, unburned habitats. This mismatch in ecological response may imply declines in habitat availability for sage-grouse and may destabilize population vital rates. Spatially explicit models can aid in identifying priority areas for restoration efforts and conservation actions to mitigate the impacts of future disturbances.

Nevada, Oregon↗
USGS2017

Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission

Agassiz’s desert tortoise (Gopherus agassizii) is a conservation-reliant species with populations north and west of the Colorado River protected as threatened under the Endangered Species Act (Averill-Murray et al. 2012). Since it was listed under this category in 1990, a great deal has been learned about the natural history of the species, and it is now one of the best-studied turtles in the United States (Lovich and Ennen 2013). However, the accumulated body of scientific data available for the species has not yet been translated into recovery or delisting of the species. Successful conservation of any species requires knowledge of their natural history and how vital rates affect their ability to maintain stable populations in the face of natural and anthropogenic stresses. Agassiz’s desert tortoises occur from southwestern Utah to near the Mexican border in California – a distance of over 450 km – but population densities vary greatly across this immense landscape (U.S. Fish and Wildlife Service 2015). Tortoises occur in the Sonoran Desert of California, including the eastern and western ends of the Coachella Valley, where it is one of 27 species covered under the Coachella Valley Multiple Species Habitat Conservation Plan and Natural Community Conservation Plan (CVMSHCP/NCCP). The southern portion of Joshua Tree National Park (JTNP) lies within this 1.1 million acre planning area, and was predicted to be an area of low-density tortoise populations using habitat suitability modeling (Barrows 2011). JTNP is near the southern distributional limit of G. agassizii, yet very little has been published regarding the ecology of tortoises in the Sonoran Desert of California. Reproductive output is an important gross measure of the ability of a population to persist. When integrated with data on fertility and survivorship, this information forms a foundation for assessing population status and formulating effective management strategies (e.g., Congdon et al. 1993, 1994), especially for imperiled species. One aspect of the biology of G. agassizii that has been particularly well-studied is reproductive output. However, most of what we know about this topic comes from research in the Mojave Desert portion of the species’ range (Ernst and Lovich 2009). Comparatively little has been published on the reproductive ecology of populations living in the Sonoran Desert ecosystem of California. Publications by Lovich et al. (1999, 2011, 2012, 2014, 2015) constitute the main body of literature on desert tortoise reproductive ecology in the Sonoran Desert of California, with one study population located at the western end of the CVMSHCP/NCCP area. Collecting data on Agassiz’s desert tortoise ecology in the Sonoran Desert ecosystem is important due to significant differences between the two adjacent desert ecosystems, especially the timing and amounts of annual precipitation, and their potential effects on reproductive output (e.g., Lovich et al. 5 2015). There are also differences in the vulnerability of tortoises to the effects of a warming, drying climate between the two deserts (Barrows 2011; Zylstra et al. 2012). The overall goal of this study was to collect data on demography, reproductive output, and genetic affinities at a study site in the Sonoran Desert portion of JTNP in the eastern end of the CVMSHCP/NCCP area. Specific objectives included: 1) Collect data to establish baselines on tortoise populations and/or their habitat suitability in core habitat within the CVNCCP area, including biotic and abiotic variables affecting persistence of tortoise populations; 2) Compare and contrast with data collected on desert tortoises at USGS/BLM study site near Palm Springs over 16 years; 3) Support long-term modeling efforts needed to determine tortoise population viability; 4) Refine modeled relationships with identified threats such as fire, invasive species and climate change; and 5) Prioritize adaptive management needs for the desert tortoise in and beyond the CVNCCP area. The data from this study will aid in determining baseline estimates of the desert tortoise population size within the planning area as well as establish a marked population of Agassiz’s desert tortoises for future monitoring. Data will be integrated with habitat modeling in order to refine model output. Genetic data will be collected on both the north and south sides of Interstate 10 to determine the potential effects of habitat fragmentation and genetic mixing. Analyses are ongoing and results beyond those presented in this report will be published in peer-reviewed scientific journals following inclusion of additional data collected on the south side of Shavers Valley in 2017-2018.

Report↗
USGS2013

Has the time come for big science in wildlife health?

The consequences of wildlife emerging diseases are global and profound with increased burden on the public health system, negative impacts on the global economy, declines and extinctions of wildlife species, and subsequent loss of ecological integrity. Examples of health threats to wildlife include Batrachochytrium dendrobatidis , which causes a cutaneous fungal infection of amphibians and is linked to declines of amphibians globally; and the recently discovered Pseudogymnoascus (Geomyces) destructans , the etiologic agent of white nose syndrome which has caused precipitous declines of North American bat species. Of particular concern are the novel pathogens that have emerged as they are particularly devastating and challenging to manage. A big science approach to wildlife health research is needed if we are to make significant and enduring progress in managing these diseases. The advent of new analytical models and bench assays will provide us with the mathematical and molecular tools to identify and anticipate threats to wildlife, and understand the ecology and epidemiology of these diseases. Specifically, new molecular diagnostic techniques have opened up avenues for pathogen discovery, and the application of spatially referenced databases allows for risk assessments that can assist in targeting surveillance. Long-term, systematic collection of data for wildlife health and integration with other datasets is also essential. Multidisciplinary research programs should be expanded to increase our understanding of the drivers of emerging diseases and allow for the development of better disease prevention and management tools, such as vaccines. Finally, we need to create a National Fish and Wildlife Health Network that provides the operational framework (governance, policies, procedures, etc.) by which entities with a stake in wildlife health cooperate and collaborate to achieve optimal outcomes for human, animal, and ecosystem health.

EcoHealth↗
USGS2025

Meta-analysis of a megafish: Assessing patterns and predictors of Alligator Gar movement across multiple populations

Background Freshwater megafishes are among some of the most commercially and ecologically important aquatic organisms yet are disproportionately threatened with range and population reduction. Anthropogenic alterations of rivers influencing migrations are among the most significant causes for these declines. However, migratory fishes do not always respond similarly to movement barriers and thus it is necessary to develop models to predict movements of freshwater migratory fishes in the face of anthropogenic alteration. Predicting movement of freshwater fishes is often investigated using statistical packages. However, empirical studies assessing these packages have led to mixed results, questioning its applicability to all taxa. We argue that spatial, temporal, and environmental attributes are more influential for movement of a migratory megafish, the Alligator Gar ( Atractosteus spatula ), than the current parameters explored in a globally relevant fish movement model. Methods This study explored two independent mobile telemetry datasets investigating Alligator Gar movement on the Brazos and Trinity rivers. Environmental associations were investigated to predict Alligator Gar displacement and dispersal using generalized additive models, generalized linear models, and model selection. Leptokurtosis of Alligator Gar populations was also assessed. Predictability of the movement model was tested by comparing observed to model derived stationary and mobile components making up a leptokurtic movement distribution. Results Our study suggests that current and antecedent measures of discharge and water temperature are positively correlated with Alligator Gar displacement and dispersal. However, these patterns are only detectable when monthly relocation intervals are explored rather than seasonal scales. Leptokurtosis was observed in both Alligator Gar populations. However, movement was normally distributed (i.e., mesokurtic) under tracking events following high flood pulses. Additionally, predicted Alligator Gar movement was significantly farther under modeled values compared to observed values, in part because the species undergoes cyclical migrations for reproduction that are sensitive to water temperature and discharge. Discussion In conclusion, this study provides an alternative framework to assess the movement patterns of migratory fishes, which could be tested on additional freshwater fishes, and suggests that assessing spatial, environmental, and temporal processes simultaneously are necessary to capture the complexities of fish movement which currently are unavailable for the movement model we investigated.

Texas↗
USGS2020

Development of a novel framework for modeling field-scale conservation effects of depressional wetlands in agricultural landscapes

The intermixed cropland, grassland, and wetland ecosystems of the upper mid-western United States combine to provide a suite of valuable ecological services. Grassland and wetland losses in the upper midwestern United States have been extensive, but government-funded conservation programs have protected and restored hundreds of thousands of acres of wetland and grassland habitat in the region. The value of restored wetlands in agricultural fields is complex, and the USDA Natural Resource Conservation Service, Conservation Effects Assessment Project (CEAP) has been lacking the methodology to include these conservation practices in their analyses. Our aim is to develop a reproducible methodology for simulating wetlands within the CEAP cropland modeling framework used to evaluate other agricultural conservation practices. Furthermore, we evaluate the effect of using upland conservation practices on the functioning of restored wetlands. By simulating the addition of a depressional wetland that effectively removes 6% of the field from crop production, we obtained a 15% reduction in annual runoff and a 29% and 28% reduction in mean annual nitrogen (N) and phosphorus (P) losses, respectively. The presence of the depressional wetland in the field is estimated to also reduce edge-of-field losses of sediments by 20% and sediment-bound N and P by 19% and 23%, respectively. Additionally, adding a grass filter strip around the wetland greatly decreased sediment inputs to the wetland, increasing the effective life of the wetland, in terms of its ability to perform valued services, by decades to centuries. Our method for modeling depressional wetlands embedded in cropped fields provides a means to quantify the effects of wetland conservation practices on field-level losses for regional assessments, such as the CEAP.

Journal of Soil and Water Conservation↗
USGS2023

PopEquus: a predictive modeling tool to support management decisions for free-roaming horse populations

Feral horse ( Equus caballus ) population management is a challenging problem around the world because populations often exhibit density-independent growth, can exert negative ecological effects on ecosystems, and require great cost to be managed. However, strong value-based connections between people and horses cause contention around management decisions. To help make informed decisions, natural resource managers might benefit from more detailed understanding of how horse management alternatives, including combinations of removals and fertility control methods, could achieve objectives of sustainable, multiple-use ecosystems while minimizing overall horse handling and fiscal costs. Here, we describe a modeling tool that simulates horse management alternatives and estimates trade-offs in predicted metrics related to population size, animal handling, and direct costs of management. The model considers six management actions for populations (removals for adoption or long-term holding; fertility control treatment with three vaccines, intrauterine devices, and mare sterilization), used alone or in combination. We simulated 19 alternative management scenarios at 2-, 3-, and 4-year management return intervals and identified efficiency frontiers among alternatives for trade-offs between predicted population size and six management metrics. Our analysis identified multiple alternatives that could maintain populations within target population size ranges, but some alternatives (e.g., removal and mare sterilization, removal and GonaCon treatment) performed better at minimizing overall animal handling requirements and management costs. Cost savings increased under alternatives with more effective, longer lasting fertility control techniques over longer management intervals compared with alternatives with less-effective, shorter lasting fertility control techniques. We built a user-friendly website application, PopEquus , that decision makers and interested individuals can use to simulate management alternatives and evaluate trade-offs among management and cost metrics. Our results and website application provide quantitative trade-off tools for horse population management decisions and can help support value-based management decisions for wild or feral horse populations and ecosystems at local and regional scales around the world.

Ecosphere↗
USGS2018

Social–ecological landscape patterns predict woody encroachment from native tree plantings in a temperate grassland

Afforestation is often viewed as the purposeful planting of trees in historically nonforested grasslands, but an unintended consequence is woody encroachment, which should be considered part of the afforestation process. In North America's temperate grassland biome, Eastern redcedar ( Juniperus virginiana L.) is a native species used in tree plantings that aggressively invades in the absence of controlling processes. Cedar is a well-studied woody encroacher, but little is known about the degree to which cedar windbreaks, which are advocated for in agroforestry programs, are contributing to woody encroachment, what factors are associated with cedar spread from windbreaks, nor where encroachment from windbreaks is occurring in contemporary social–ecological landscapes. We used remotely sensed imagery to identify the presence and pattern of woody encroachment from windbreaks in the Nebraska Sandhills. We used multimodel inference to compare three classes of models representing three hypotheses about factors that could influence cedar spread: (a) windbreak models based on windbreak structure and design elements; (b) abiotic models focused on local environmental conditions; and (c) landscape models characterizing coupled human-natural features within the broader matrix. Woody encroachment was evident for 23% of sampled windbreaks in the Nebraska Sandhills. Of our candidate models, our inclusive landscape model carried 92% of the model weight. This model indicated that encroachment from windbreaks was more likely near roadways and less likely near farmsteads, other cedar plantings, and waterbodies, highlighting strong social ties to the distribution of woody encroachment from tree plantings across contemporary landscapes. Our model findings indicate where additional investments into cedar control can be prioritized to prevent cedar spread from windbreaks. This approach can serve as a model in other temperate regions to identify where woody encroachment resulting from temperate agroforestry programs is emerging.

Nebraska↗
USGS2010

Landscape genetics of high mountain frog metapopulations

Explaining functional connectivity among occupied habitats is crucial for understanding metapopulation dynamics and species ecology. Landscape genetics has primarily focused on elucidating how ecological features between observations influence gene flow. Functional connectivity, however, may be the result of both these between‐site (landscape resistance) landscape characteristics and at‐site (patch quality) landscape processes that can be captured using network based models. We test hypotheses of functional connectivity that include both between‐site and at‐site landscape processes in metapopulations of Columbia spotted frogs ( Rana luteiventris ) by employing a novel justification of gravity models for landscape genetics (eight microsatellite loci, 37 sites, n = 441). Primarily used in transportation and economic geography, gravity models are a unique approach as flow (e.g. gene flow) is explained as a function of three basic components: distance between sites, production/attraction (e.g. at‐site landscape process) and resistance (e.g. between‐site landscape process). The study system contains a network of nutrient poor high mountain lakes where we hypothesized a short growing season and complex topography between sites limit R. luteiventris gene flow. In addition, we hypothesized production of offspring is limited by breeding site characteristics such as the introduction of predatory fish and inherent site productivity. We found that R. luteiventris connectivity was negatively correlated with distance between sites, presence of predatory fish (at‐site) and topographic complexity (between‐site). Conversely, site productivity (as measured by heat load index, at‐site) and growing season (as measured by frost‐free period between‐sites) were positively correlated with gene flow. The negative effect of predation and positive effect of site productivity, in concert with bottleneck tests, support the presence of source–sink dynamics. In conclusion, gravity models provide a powerful new modelling approach for examining a wide range of both basic and applied questions in landscape genetics.

Idaho↗
USGS2020

Effects of climate change on plague exposure pathways and resulting disease dynamics

Introduction and Objectives: Sylvatic plague, a zoonotic flea-borne disease, caused by the bacterium Yersinia pestis , is relevant to the Department of Defense (DOD), because prairie dogs and other susceptible rodents are present on military installations in several western states. Arthropod-borne diseases, like plague, are thought to be particularly sensitive to local climate conditions. Expected changes in temperature and humidity over the next several decades will likely increase the geographical expansion of plague outbreaks in wildlife. Through a combination of field and laboratory work, along with data-driven modeling, we evaluated the potential effects of climate change on plague exposure pathways in prairie dogs and associated rodents to provide guidance to DOD partners regarding the potential for future outbreaks. Briefly, our specific objectives were to determine the relation between local climate conditions and the prevalence of plague and other pathogens while assessing the ecological roles of specific rodent hosts and vector species in plague dynamics, evaluate flea intensity on rodent hosts and in burrows in relation to local climate conditions, and develop models to predict the effects of climate change on plague dynamics. Technical Approach: Using data and samples collected during a large field study on the effectiveness of vaccination to manage plague in prairie dogs, we assessed rodent/flea assemblages, pathogen prevalence in fleas, and determined how local climate conditions influence flea development rates and relative abundance. Live animals (prairie dogs and some small rodents) were trapped to collect fleas and other samples on 46 prairie dog plots in 6 western states, many sites near DOD lands. At seven additional locations on a latitudinal gradient, fleas were collected from burrows several times per year to assess seasonality and effects of local climate conditions on flea abundance. These data were then used to develop predictive models that could be used to test specific hypotheses. Results: We determined that flea developmental rates, on-host flea abundance, species composition of the flea community, and burrow temperatures varied across a latitudinal gradient. Rodent and flea community composition and abundance differed geographically and were highly specialized. Flea-switching between prairie dogs and short-lived rodents was rare. Flea development rates, on-host flea abundance, and burrow temperatures increased with increasing ambient temperature. Although relative humidity can affect flea development, burrow humidity was uniformly high (~85%) across sampling sites and seasons. A large increase in the number of fleas found on a prairie dog colony, coupled with a greater number of infested burrows, could have substantial effects on plague dynamics in the western United States as the climate warms. In addition to affecting flea load, climate change may also influence body condition of prairie dogs by reducing the amount of forage. This may result in animals being more tolerant of high flea loads (less engaged in grooming behavior) and more vulnerable to disease.

Arizona, Montana, South Dakota, Texas, Utah, Wyomi↗
USGS2015

Species richness and distributions of boreal waterbirds in relation to nesting and brood-rearing habitats

Identification of ecological factors that drive animal distributions allows us to understand why distributions vary temporally and spatially, and to develop models to predict future changes to populations–vital tools for effective wildlife management and conservation. For waterbird broods in the boreal forest, distributions are likely driven by factors affecting quality of nesting and brood-rearing habitats, and the influence of these factors may extend beyond singles species, affecting the entire waterbird community. We used occupancy models to assess factors influencing species richness of waterbird broods on 72 boreal lakes, along with brood distributions of 3 species of conservation concern: lesser scaup ( Aythya affinis ), white-winged scoters ( Melanitta fusca ), and horned grebe ( Podiceps auritus ). Factors examined included abundance of invertebrate foods (Amphipoda, Diptera, Gastropoda, Hemiptera, Odonata), physical lake attributes (lake area, emergent vegetation), water chemistry (nitrogen, phosphorus, chlorophyll a concentrations), and nesting habitats (water edge, non-forest cover). Of the 5 invertebrates, only amphipod density was related to richness and occupancy, consistently having a large and positive relationship. Despite this importance to waterbirds, amphipods were the most patchily distributed invertebrate, with 17% of the study lakes containing 70% of collected amphipods. Lake area was the only other covariate that strongly and positively influenced species richness and occupancy of scaup, scoters, and grebes. All 3 water chemistry covariates, which provided alternative measures of lake productivity, were positively related to species richness but had little effect on scaup, scoter, and grebe occupancy. Conversely, emergent vegetation was negatively related to richness, reflecting avoidance of overgrown lakes by broods. Finally, nesting habitats had no influence on richness and occupancy, indicating that, at a broad spatial scale, brood distributions are largely driven by the presence of quality brood-rearing lakes, not nesting habitats. Our findings are relevant to generating conservation plans or management goals; specifically, boreal lakes with abundant amphipods and surface areas >25 ha are important habitat for waterbird broods and merit conservation, especially given the patchy distribution of amphipods. Moreover, these high quality brood-rearing lakes are much rarer, and thus more constraining, than are quality nesting habitats, which are likely abundant in the boreal.

Alaska↗
USGS2020

Synthesis: A framework for predicting the dark side of ecological subsidies

In this chapter, we synthesize the state of the science regarding ecological subsidies and contaminants at the land-water interface and suggest research and management approaches for linked freshwater-terrestrial ecosystems. Specifically, we focus on movements of animals with complex life histories and the detrital inputs associated with animal and plant matter delivered to freshwaters. We present a framework based on the physicochemical parameters of contaminants and how they shape the relationship between contaminant persistence within resource subsidies (“dark side” of subsidies) and movement of resource subsidies (“bright side” of subsidies) across ecosystem boundaries. This relationship between the “dark side” and “bright side” of subsidies defines an important parameter space that allows researchers and practitioners to predict the potential impacts of aquatic contaminants on resource subsidies and their interaction with other stressors on consumers. Ecological factors such as ecosystem productivity, community composition, and consumer prey preference shape the ecotoxicological outcomes of aquatic contamination on subsidies. Landscape factors such as lithology, hydrogeomorphology, hydroperiod, and land use underlie chemical, toxicological, and ecological patterns and provide the context within which effects of contaminants play out. Finally, effects of contaminants combine with effects of other global stressors on timing, quality, and quantity of subsidies that drive responses to contaminants at the land-water interface. Understanding the “dark side” of ecological subsidies requires expertise from multiple disciplines. We attempt to synthesize current knowledge from those disciplines and generate conceptual models that ecologists can use to guide future research in understanding cross-ecosystem subsidies and contaminant fate and effects.

Book chapter↗
USGS2024

Partitioning of chemicals in aquatic organisms

Human populations have utilized heavy metals and persistent organic pollutants for their physiochemical properties in industrial, agricultural, and consumer goods for decades. Limited knowledge on their persistence and toxicological effects has resulted in organisms being exposed to some of the most problematic compounds ever generated by humans. Although overlap in exposure paradigms exists for historical and emerging contaminants, the different physiochemical properties, sources into the environment, and bioactivity of contaminants of emerging concern (CECs) have highlighted the importance of characterizing their risk to aquatic wildlife under chronic low-dose exposure scenarios. This chapter defines the fundamental terminology associated with characterizing the exposure paradigm in ecological risk assessment. The different sources and fate, routes of exposure, and biotransformation of common contaminants are covered using model chemicals to emphasize important factors that affect their partitioning among different environmental matrices. Finally, this chapter concludes with a discussion about bioaccumulation models and an example of how two similar CECs demonstrate different clearance rates and bioaccumulation potentials in fish.

Book chapter↗