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At least 1,225 records · Page 68Linked to original sources

USGS2022

Defining biologically relevant and hierarchically nested population units to inform wildlife management

Wildlife populations are increasingly affected by natural and anthropogenic changes that negatively alter biotic and abiotic processes at multiple spatiotemporal scales and therefore require increased wildlife management and conservation efforts. However, wildlife management boundaries frequently lack biological context and mechanisms to assess demographic data across the multiple spatiotemporal scales influencing populations. To address these limitations, we developed a novel approach to define biologically relevant subpopulations of hierarchically nested population levels that could facilitate managing and conserving wildlife populations and habitats. Our approach relied on the Spatial “K”luster Analysis by Tree Edge Removal clustering algorithm, which we applied in an agglomerative manner (bottom-to-top). We modified the clustering algorithm using a workflow and population structure tiers from least-cost paths, which captured biological inferences of habitat conditions (functional connectivity), dispersal capabilities (potential connectivity), genetic information, and functional processes affecting movements. The approach uniquely included context of habitat resources (biotic and abiotic) summarized at multiple spatial scales surrounding locations with breeding site fidelity and constraint-based rules (number of sites grouped and population structure tiers). We applied our approach to greater sage-grouse ( Centrocercus urophasianus ), a species of conservation concern, across their range within the western United States. This case study produced 13 hierarchically nested population levels (akin to cluster levels, each representing a collection of subpopulations of an increasing number of breeding sites). These closely approximated population closure at finer ecological scales (smaller subpopulation extents with fewer breeding sites; cluster levels ≥2), where >92% of individual sage-grouse's time occurred within their home cluster. With available population monitoring data, our approaches can support the investigation of factors affecting population dynamics at multiple scales and assist managers with making informed, targeted, and cost-effective decisions within an adaptive management framework. Importantly, our approach provides the flexibility of including species-relevant context, thereby supporting other wildlife characterized by site fidelity.

Ecology and Evolution↗

USGS2001

Corticosterone facilitates begging and affects resource allocation in the black-legged kittiwake

Parent black-legged kittiwakes ( Rissa tridactyla ) and their dependent chicks respond to food shortages by increasing circulating levels of corticosterone. To examine the behavioral significance of corticosterone release, we experimentally increased levels of circulating corticosterone in parents and chicks up to the levels observed during food shortages. We found that corticosterone-implanted chicks begged more frequently than sham-implanted controls. Corticosterone-implanted chicks in broods of two begged more frequently than singletons. Parent kittiwakes then responded to the increase in corticosterone levels in their chicks by increasing chick-feeding rates. However, feeding rates were not different among corticosterone-implanted chicks in broods of two and singletons. We also found that corticosterone-implanted parents spent more time away from the nest—perhaps foraging—and less time brooding/guarding chicks than sham-implanted controls. Untreated mates of the corticosterone-implanted bird did not compensate for the change in their partner's behavior; consequently, chicks were left unattended about 20% of the time compared to 1% at the control nests. However, corticosterone-implanted parents did not decrease their chick-feeding rates. Our findings suggest two functional implications of the increased corticosterone secretion during food shortages in the black-legged kittiwake: it facilitates begging in chicks, and it affects time allocated by parents to guarding young at the nest. Thus, release of corticosterone might provide a mechanistic link between physiological condition and behavioral interactions among adults and their young.

Behavioral Ecology↗

USGS2021

Abundance of Gulf Coast Waterdogs (Necturus beyeri) along Bayou Lacombe, Saint Tammany Parish, Louisiana

Few ecological studies have been conducted on Gulf Coast Waterdogs (Necturus beyeri), and published studies have focused on relatively small stream sections of 125 m to 1.75 km. In 2015, we sampled 25 sites along a 13.4-km stretch of Bayou Lacombe (Saint Tammany Parish, Louisiana, USA) to better understand factors that may influence the distribution of Gulf Coast Waterdogs within streams. We checked 250 unbaited traps once per week for 3 weeks, capturing 170 Gulf Coast Waterdogs at 18 of 25 sites. We used hierarchical models of abundance to estimate abundance at each site, as a function of site covariates including pH, turbidity, and distance from headwaters. The abundance of Gulf Coast Waterdogs within Bayou Lacombe was highest toward the center of the sampled stream segment, but we found no evidence that pH or turbidity affected abundance within our study area. Site-level abundance estimates of Gulf Coast Waterdogs ranged from 0 to 82, and we estimated there were 767 (95% Bayesian credible interval [CRI]: 266–983) Gulf Coast Waterdogs summed across all 25 sampling sites. We derived an estimate of 6,321 (95% CRI: 2,139–15,922) Gulf Coast Waterdogs for the entire 13.4-km stream section, which includes our 25 sites and the adjoining stream reaches between sites. Our results suggest that Gulf Coast Waterdogs may be uncommon or absent in the headwaters, possibly because of shallow water and swift currents with limited preferred habitats. Gulf Coast Waterdogs favor the middle stream reaches with adequate depth and abundant preferred microhabitats.

Louisiana↗

USGS2001

Forest fragmentation and bird community dynamics: Inference at regional scales

With increasing fragmentation of natural areas and a dramatic reduction of forest cover in several parts of the world, quantifying the impact of such changes on species richness and community dynamics has been a subject of much concern. Here, we tested whether in more fragmented landscapes there was a lower number of area-sensitive species and higher local extinction and turnover rates, which could explain higher temporal variability in species richness. To investigate such potential landscape effects at a regional scale, we merged two independent, large-scale monitoring efforts: the North American Breeding Bird Survey (BBS) and the Land Use and Land Cover Classification data from the U.S. Geological Survey. We used methods that accounted for heterogeneity in the probability of detecting species to estimate species richness and temporal changes in the bird communities for BBS routes in three mid-Atlantic U.S. states. Forest breeding bird species were grouped prior to the analyses into area-sensitive and non-area-sensitive species according to previous studies. We tested predictions relating measures of forest structure at one point in time (1974) to species richness at that time and to parameters of forest bird community change over the following 22-yr-period (1975–1996). We used the mean size of forest patches to characterize landscape structure, as high correlations among landscape variables did not allow us to disentangle the relative roles of habitat fragmentation per se and habitat loss. As predicted, together with lower species richness for area-sensitive species on routes surrounded by landscapes with lower mean forest-patch size, we found higher mean year-to-year rates of local extinction. Moreover, the mean year-to-year rates of local turnover (proportion of locally new species) for area-sensitive species were also higher in landscapes with lower mean forest-patch size. These associations were not observed for the non-area-sensitive species group. These results suggest that landscape structure may influence forest bird communities at regional scales through its effects on the total number of species but also on the temporal rates of change in community composition. Evidence for higher rates of local extinction and turnover in more fragmented landscapes suggests that bird communities function as metapopulations at a regional scale, and points out the importance of colonizations and recolonizations from surrounding landscapes to local community dynamics. Further, our results illustrate that the methods used to estimate the community parameters can be a powerful statistical tool in addressing questions relative to the dynamics of communities.

Ecology↗

USGS2006

A review of methods to estimate cause-specific mortality in presence of competing risks

Estimating cause-specific mortality is often of central importance for understanding the dynamics of wildlife populations. Despite such importance, methodology for estimating and analyzing cause-specific mortality has received little attention in wildlife ecology during the past 20 years. The issue of analyzing cause-specific, mutually exclusive events in time is not unique to wildlife. In fact, this general problem has received substantial attention in human biomedical applications within the context of biostatistical survival analysis. Here, we consider cause-specific mortality from a modern biostatistical perspective. This requires carefully defining what we mean by cause-specific mortality and then providing an appropriate hazard-based representation as a competing risks problem. This leads to the general solution of cause-specific mortality as the cumulative incidence function (CIF). We describe the appropriate generalization of the fully nonparametric staggered-entry Kaplan–Meier survival estimator to cause-specific mortality via the nonparametric CIF estimator (NPCIFE), which in many situations offers an attractive alternative to the Heisey–Fuller estimator. An advantage of the NPCIFE is that it lends itself readily to risk factors analysis with standard software for Cox proportional hazards model. The competing risks–based approach also clarifies issues regarding another intuitive but erroneous “cause-specific mortality” estimator based on the Kaplan–Meier survival estimator and commonly seen in the life sciences literature.

Journal of Wildlife Management↗

USGS2007

Beach morphology monitoring in the Columbia River Littoral Cell: 1997-2005

This report describes methods used, data collected, and results of the Beach Morphology Monitoring Program in the Columbia River Littoral Cell (CRLC) from 1997 to 2005. A collaborative group primarily consisting of the US Geological Survey and the Washington State Department of Ecology performed this work. Beach Monitoring efforts consisted of collecting topographic and bathymetric horizontal and vertical position data using a Real Time Kinematic Differential Global Positioning System (RTK-DGPS). Sediment size distribution data was also collected as part of this effort. The monitoring program was designed to: 1) quantify the short- to medium-term (seasonal to interannual) beach change rates and morphological variability along the CRLC and assess the processes responsible for these changes; 2) collect beach state data (i.e., grain size, beach slope, and dune/sandbar height/position) to enhance the conceptual understanding of CRLC functioning and refine predictions of future coastal change and hazards; 3) compare and contrast the scales of environmental forcing and beach morphodynamics in the CRLC to other coastlines of the world; and 4) provide beach change data in a useful format to land use managers.

Oregon, Washington↗

USGS2022

Balancing future renewable energy infrastructure siting and associated habitat loss for migrating whooping cranes

The expansion of human infrastructure has contributed to novel risks and disturbance regimes in most ecosystems, leading to considerable uncertainty about how species will respond to altered landscapes. A recent assessment revealed that whooping cranes ( Grus americana ), an endangered migratory waterbird species, avoid wind-energy infrastructure during migration. However, uncertainties regarding collective impacts of other types of human infrastructure, such as power lines on migration, variable drought conditions, and continued construction of wind energy infrastructure may compromise ongoing recovery efforts for whooping cranes. Droughts are increasing in frequency and severity throughout the whooping crane migration corridor, and the impacts of drought on stopover habitat use are largely unknown. Moreover, decision-based analyses are increasingly advocated to guide recovery planning for endangered species, yet applications remain rare. Using GPS locations from 57 whooping cranes from 2010 through 2016 in the United States Great Plains, we assessed habitat selection and avoidance of potential disturbances during migration relative to drought conditions, and we used these results in an optimization analysis to select potential sites for new wind energy developments that minimize relative habitat loss for whooping cranes and maximize wind energy potential. Drought occurrence and severity varied spatially and temporally across the migration corridor during our study period. Whooping cranes rarely used areas <5 km from human settlements and wind energy infrastructure under both drought and non-drought conditions, and <2 km from power lines during non-drought conditions, with the lowest likelihood of use near wind energy infrastructure. Whooping cranes differed in their selection of wetland and cropland land cover types depending on drought or non-drought conditions. We identified scenarios for wind energy expansion across the migration corridor and in select states, which are robust to uncertain drought conditions, where future loss of highly selected stopover habitats could be minimized under a common strategy. Our approach was to estimate functional habitat loss while integrating current disturbances, potential future disturbances, and uncertainty in drought conditions. Therefore, dynamic models describing potential costs associated with risk-averse behaviors resulting from future developments can inform proactive conservation before population impacts occur.

Kansas, Montana, Nebraska, North Dakota, South Dak↗

USGS1980

Ecology of a Maryland population of black rat snakes (Elaphe o. obsoleta)

Behavior, growth and age of black rat snakes under natural conditions were investigated by mark-recapture methods at the Patuxent Wildlife Research Center for 22 years (1942-1963), with limited observations for 13 more years (1964-1976). Over the 35-year period, 330 snakes were recorded a total of 704 times. Individual home ranges remained stable for many years; male ranges averaged at least 600 m in diam and female ranges at least 500 m, each including a diversity of habitats, evidenced also in records of foods. Population density was low, probably less than 0.5 snake/ha. Peak activity of both sexes was in May and June, with a secondary peak in September. Large trees in the midst of open areas appeared to serve a significant functional role in the behavioral life pattern of the snake population. Male combat was observed three times in the field. Male snakes grew more rapidly than females, attained larger sizes and lived longer. Some individuals of both sexes probably lived 20 years or more. Weight-length relationships changed as the snakes grew and developed heavier bodies in proportion to length. Growth apparently continued throughout life. Some individuals, however, both male and female, stopped growing for periods of I or 2 years and then resumed, a condition probably related to poor health, suggested by skin ailments.

Maryland↗

USGS2011

Microbial ecology of deep-water mid-Atlantic canyons

The research described in this fact sheet will be conducted from 2012 to 2014 as part of the U.S. Geological Survey's DISCOVRE (DIversity, Systematics, and COnnectivity of Vulnerable Reef Ecosystems) Program. This integrated, multidisciplinary effort will be investigating a variety of topics related to unique and fragile deep-sea ecosystems from the microscopic level to the ecosystem level. One goal is to improve understanding, at the microbiological scale, of the benthic communities (including corals) that reside in and around mid-Atlantic canyon habitats and their associated environments. Specific objectives include identifying and characterizing the microbial associates of deep-sea corals, characterizing the microbial biofilms on hard substrates to better determine their role in engineering the ecosystem, and adding a microbial dimension to benthic community structure and function assessments by characterizing micro-eukaryotes, bacteria, and archaea in deep-sea sediments.

Fact Sheet↗

USGS2008

Modeling mechanisms of vegetation change due to fire in a semi-arid ecosystem

Vegetation growth and community composition in semi-arid environments is determined by water availability and carbon assimilation mechanisms specific to different plant types. Disturbance also impacts vegetation productivity and composition dependent on area affected, intensity, and frequency factors. In this study, a new spatially explicit ecosystem model is presented for the purpose of simulating vegetation cover type changes associated with fire disturbance in the northern Chihuahuan Desert region. The model is called the Landscape and Fire Simulator (LAFS) and represents physiological activity of six functional plant types incorporating site climate, fire, and seed dispersal routines for individual grid cells. We applied this model for Big Bend National Park, Texas, by assessing the impact of wildfire on the trajectory of vegetation communities over time. The model was initialized and calibrated based on landcover maps derived from Landsat-5 Thematic Mapper data acquired in 1986 and 1999 coupled with plant biomass measurements collected in the field during 2000. Initial vegetation cover change analysis from satellite data showed shrub encroachment during this time period that was captured in the simulated results. A synthetic 50-year climate record was derived from historical meteorological data to assess system response based on initial landcover conditions. This simulation showed that shrublands increased to the detriment of grass and yucca-ocotillo vegetation cover types indicating an ecosystem-level trajectory for shrub encroachment. Our analysis of simulated fires also showed that fires significantly reduced site biomass components including leaf area, stem, and seed biomass in this semi-arid ecosystem. In contrast to other landscape simulation models, this new model incorporates detailed physiological responses of functional plant types that will allow us to simulated the impact of increased atmospheric CO2 occurring with climate change coupled with fire disturbance. Simulations generated from this model are expected to be the subject of subsequent studies on landscape dynamics with specific regard to prediction of wildlife distributions associated with fire management and climate change.

Ecological Modelling↗

USGS2002

Using simple environmental variables to estimate below-ground productivity in grasslands

In many temperate and annual grasslands, above-ground net primary productivity (NPP) can be estimated by measuring peak above-ground biomass. Estimates of below-ground net primary productivity and, consequently, total net primary productivity, are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems to develop simple models or algorithms to estimate missing components of total system NPP. Any estimate of below-ground NPP (BNPP) requires an accounting of total root biomass, the percentage of living biomass and annual turnover of live roots. We derived a relationship using above-ground peak biomass and mean annual temperature as predictors of below-ground biomass (r2 = 0.54; P = 0.01). The percentage of live material was 0.6, based on published values. We used three different functions to describe root turnover: constant, a direct function of above-ground biomass, or as a positive exponential relationship with mean annual temperature. We tested the various models against a large database of global grassland NPP and the constant turnover and direct function models were approximately equally descriptive (r2 = 0.31 and 0.37), while the exponential function had a stronger correlation with the measured values (r2 = 0.40) and had a better fit than the other two models at the productive end of the BNPP gradient. When applied to extensive data we assembled from two grassland sites with reliable estimates of total NPP, the direct function was most effective, especially at lower productivity sites. We provide some caveats for its use in systems that lie at the extremes of the grassland gradient and stress that there are large uncertainties associated with measured and modelled estimates of BNPP.

Global Ecology and Biogeography↗

USGS2011

Environmental conditions constrain the distribution and diversity of archaeal merA in Yellowstone National Park, Wyoming, U.S.A.

The distribution and phylogeny of extant protein-encoding genes recovered from geochemically diverse environments can provide insight into the physical and chemical parameters that led to the origin and which constrained the evolution of a functional process. Mercuric reductase (MerA) plays an integral role in mercury (Hg) biogeochemistry by catalyzing the transformation of Hg(II) to Hg(0). Putative merA sequences were amplified from DNA extracts of microbial communities associated with mats and sulfur precipitates from physicochemically diverse Hg-containing springs in Yellowstone National Park, Wyoming, using four PCR primer sets that were designed to capture the known diversity of merA. The recovery of novel and deeply rooted MerA lineages from these habitats supports previous evidence that indicates merA originated in a thermophilic environment. Generalized linear models indicate that the distribution of putative archaeal merA lineages was constrained by a combination of pH, dissolved organic carbon, dissolved total mercury and sulfide. The models failed to identify statistically well supported trends for the distribution of putative bacterial merA lineages as a function of these or other measured environmental variables, suggesting that these lineages were either influenced by environmental parameters not considered in the present study, or the bacterial primer sets were designed to target too broad of a class of genes which may have responded differently to environmental stimuli. The widespread occurrence of merA in the geothermal environments implies a prominent role for Hg detoxification in these environments. Moreover, the differences in the distribution of the merA genes amplified with the four merA primer sets suggests that the organisms putatively engaged in this activity have evolved to occupy different ecological niches within the geothermal gradient.

Yellowstone National Park↗

USGS2019

An analysis of autocorrelation and bias in home range estimation

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

Ecological Monographs↗

USGS2015

Functional response of ungulate browsers in disturbed eastern hemlock forests

Ungulate browsing in predator depleted North American landscapes is believed to be causing widespread tree recruitment failures. However, canopy disturbances and variations in ungulate densities are sources of heterogeneity that can buffer ecosystems against herbivory. Relatively little is known about the functional response (the rate of consumption in relation to food availability) of ungulates in eastern temperate forests, and therefore how “top down” control of vegetation may vary with disturbance type, intensity, and timing. This knowledge gap is relevant in the Northeastern United States today with the recent arrival of hemlock woolly adelgid (HWA; Adelges tsugae ) that is killing eastern hemlocks ( Tsuga canadensis ) and initiating salvage logging as a management response. We used an existing experiment in central New England begun in 2005, which simulated severe adelgid infestation and intensive logging of intact hemlock forest, to examine the functional response of combined moose ( Alces americanus ) and white-tailed deer ( Odocoileus virginianus ) foraging in two different time periods after disturbance (3 and 7 years). We predicted that browsing impacts would be linear or accelerating (Type I or Type III response) in year 3 when regenerating stem densities were relatively low and decelerating (Type II response) in year 7 when stem densities increased. We sampled and compared woody regeneration and browsing among logged and simulated insect attack treatments and two intact controls (hemlock and hardwood forest) in 2008 and again in 2012. We then used AIC model selection to compare the three major functional response models (Types I, II, and III) of ungulate browsing in relation to forage density. We also examined relative use of the different stand types by comparing pellet group density and remote camera images. In 2008, total and proportional browse consumption increased with stem density, and peaked in logged plots, revealing a Type I response. In 2012, stem densities were greatest in girdled plots, but proportional browse consumption was highest at intermediate stem densities in logged plots, exhibiting a Type III (rather than a Type II) functional response. Our results revealed shifting top–down control by herbivores at different stages of stand recovery after disturbance and in different understory conditions resulting from logging vs. simulated adelgid attack. If forest managers wish to promote tree regeneration in hemlock stands that is more resistant to ungulate browsers, leaving HWA-infested stands unmanaged may be a better option than preemptively logging them.

Massachusetts↗

USGS2002

On the estimation of species richness based on the accumulation of previously unrecorded species

Estimation of species richness of local communities has become an important topic in community ecology and monitoring. Investigators can seldom enumerate all the species present in the area of interest during sampling sessions. If the location of interest is sampled repeatedly within a short time period, the number of new species recorded is typically largest in the initial sample and decreases as sampling proceeds, but new species may be detected if sampling sessions are added. The question is how to estimate the total number of species. The data collected by sampling the area of interest repeatedly can be used to build species-accumulation curves: the cumulative number of species recorded as a function of the number of sampling sessions (which we refer to as ?species-accumulation data?). A classic approach used to compute total species richness is to fit curves to the data on species accumulation with sampling effort. This approach does not rest on direct estimation of the probability of detecting species during sampling sessions and has no underlying basis regarding the sampling process that gave rise to the data. Here we recommend a probabilistic, nonparametric estimator for species richness for use with species-accumulation data. We use estimators of population size that were developed for capture-recapture data, but that can be used to estimate the size of species assemblages using species-accumulation data. Models of detection probability account for the underlying sampling process. They permit variation in detection probability among species. We illustrate this approach using data from the North American Breeding Bird Survey (BBS). We describe other situations where species accumulation data are collected under different designs (e.g., over longer periods of time, or over spatial replicates) and that lend themselves to use of capture-recapture models for estimating the size of the community of interest. We discuss the assumptions and interpretations corresponding to each situation.

Alabama, Louisiana, Maine, Maryland, New Hampshire↗

USGS2021

Does restoration of plant diversity trigger concomitant soil microbiome changes in dryland ecosystems?

Drylands are highly vulnerable to land degradation, and despite increasing efforts, restoration success remains low. Although often ignored in the design and deployment of management strategies, soil microbial communities might be critical for dryland restoration due to their central role in promoting soil stability, nutrient cycling and plant establishment. We collected soil samples from eight dryland restoration sites within RestoreNet, a restoration field trial network, and determined their soil microbiome using 16S rRNA (bacteria and archaea) and ITS (fungi) amplicon sequencing. Each previously degraded site was treated with monoculture (single species) and polyculture (multiple species) seedling plantings. Contrary to our initial expectations, we found that these different revegetation interventions did not trigger changes in microbial diversity, composition or relative abundance of functional groups across sites after 1 year of revegetation. Synthesis and applications . Considering the crucial role of soil micro-organisms in dryland ecosystem functions, our results suggest that site-specific targeted microbiome restoration should be considered to accelerate the establishment of desired microbial communities. Plant community-based restoration practices such as revegetation have a limited impact on soil micro-organisms in the short term.

Journal of Applied Ecology↗

USGS2016

Baseline glucocorticoids are drivers of body mass gain in a diving seabird

Life-history trade-offs are influenced by variation in individual state, with individuals in better condition often completing life-history stages with greater success. Although resource accrual significantly impacts key life-history decisions such as the timing of reproduction, little is known about the underlying mechanisms driving resource accumulation. Baseline corticosterone (CORT, the primary avian glucocorticoid) mediates daily and seasonal energetics, responds to changes in food availability, and has been linked to foraging behavior, making it a strong potential driver of individual variation in resource accrual and deposition. Working with a captive colony of white-winged scoters ( Melanitta fusca deglandi ), we aimed to causally determine whether variation in baseline CORT drives individual body mass gains mediated through fattening rate (plasma triglycerides corrected for body mass). We implanted individuals with each of three treatment pellets to elevate CORT within a baseline range in a randomized order: control, low dose of CORT, high dose of CORT, then blood sampled and recorded body mass over a two-week period to track changes in baseline CORT, body mass, and fattening rates. The high CORT treatment significantly elevated levels of plasma hormone for a short period of time within the biologically relevant, baseline range for this species, but importantly did not inhibit the function of the HPA (hypothalamic–pituitary–adrenal) axis. Furthermore, an elevation in baseline CORT resulted in a consistent increase in body mass throughout the trial period compared to controls. This is some of the first empirical evidence demonstrating that elevations of baseline CORT within a biologically relevant range have a causal, direct, and positive influence on changes in body mass.

Ecology and Evolution↗

USGS2016

Effects of diffusion on total biomass in heterogeneous continuous and discrete-patch systems

Theoretical models of populations on a system of two connected patches previously have shown that when the two patches differ in maximum growth rate and carrying capacity, and in the limit of high diffusion, conditions exist for which the total population size at equilibrium exceeds that of the ideal free distribution, which predicts that the total population would equal the total carrying capacity of the two patches. However, this result has only been shown for the Pearl-Verhulst growth function on two patches and for a single-parameter growth function in continuous space. Here, we provide a general criterion for total population size to exceed total carrying capacity for three commonly used population growth rates for both heterogeneous continuous and multi-patch heterogeneous landscapes with high population diffusion. We show that a sufficient condition for this situation is that there is a convex positive relationship between the maximum growth rate and the parameter that, by itself or together with the maximum growth rate, determines the carrying capacity, as both vary across a spatial region. This relationship occurs in some biological populations, though not in others, so the result has ecological implications.

Theoretical Ecology↗