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At least 1,639 records · Page 91Linked to original sources
USGS2021

Natural history of a bighorn sheep pneumonia epizootic: Source of infection, course of disease, and pathogen clearance

A respiratory disease epizootic at the National Bison Range (NBR) in Montana in 2016–2017 caused an 85% decline in the bighorn sheep population, documented by observations of its unmarked but individually identifiable members, the subjects of an ongoing long-term study. The index case was likely one of a small group of young bighorn sheep on a short-term exploratory foray in early summer of 2016. Disease subsequently spread through the population, with peak mortality in September and October and continuing signs of respiratory disease and sporadic mortality of all age classes through early July 2017. Body condition scores and clinical signs suggested that the disease affected ewe groups before rams, although by the end of the epizootic, ram mortality (90% of 71) exceeded ewe mortality (79% of 84). Microbiological sampling 10 years to 3 months prior to the epizootic had documented no evidence of infection or exposure to Mycoplasma ovipneumoniae at NBR, but during the epizootic, a single genetic strain of M. ovipneumoniae was detected in affected animals. Retrospective screening of domestic sheep flocks near the NBR identified the same genetic strain in one flock, presumptively the source of the epizootic infection. Evidence of fatal lamb pneumonia was observed during the first two lambing seasons following the epizootic but was absent during the third season following the death of the last identified M. ovipneumoniae carrier ewe. Monitoring of life-history traits prior to the epizootic provided no evidence that environmentally and/or demographically induced nutritional or other stress contributed to the epizootic. Furthermore, the epizootic occurred despite proactive management actions undertaken to reduce risk of disease and increase resilience in this population. This closely observed bighorn sheep epizootic uniquely illustrates the natural history of the disease including the (presumptive) source of spillover, course, severity, and eventual pathogen clearance.

Montana↗
USGS2022

Classifying behavior from short-interval biologging data: An example with GPS tracking of birds

Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets. We apply a framework for using K -means clustering to classify bird behavior using points from short time interval GPS tracks. K -means clustering is a well-known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K -means clustering to six focal variables derived from GPS data collected at 1–11 s intervals from free-flying bald eagles ( Haliaeetus leucocephalus ) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life-stage- and age-related variation in behavior. After filtering for data quality, the K -means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non-moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight. The K -means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short-interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high-dimensional movement data, it provides insight into small-scale variation in behavior that would not be possible with many other analytical approaches.

Ecology and Evolution↗
USGS2021

Life-history attributes of Arctic-breeding birds drive uneven responses to environmental variability across different phases of the reproductive cycle

Animals exhibit varied life-history traits that reflect adaptive responses to their environments. For Arctic-breeding birds, traits related to diet, egg nutrient allocation, clutch size, and chick growth are predicted to be under increasing selection pressure due to rapid climate change and increasing environmental variability across high-latitude regions. We compared four migratory birds (black brant [ Branta bernicla nigricans ], lesser snow geese [ Chen caerulescens caerulescens ], semipalmated sandpipers [ Calidris pusilla ], and Lapland longspurs [ Calcarius lapponicus ]) with varied life histories at an Arctic site in Alaska, USA, to understand how life-history traits help moderate environmental variability across different phases of the reproductive cycle. We monitored aspects of reproductive performance related to the timing of breeding, reproductive investment, and chick growth from 2011 to 2018. In response to early snowmelt and warm temperatures, semipalmated sandpipers advanced their site arrival and bred in higher numbers, while brant and snow geese increased clutch sizes; all four species advanced their nest initiation dates. During chick rearing, longspur nestlings were relatively resilient to environmental variation, whereas warmer temperatures increased the growth rates of sandpiper chicks but reduced growth rates of snow goose goslings. These responses generally aligned with traits along the capital-income spectrum of nutrient acquisition and altricial–precocial modes of chick growth. Under a warming climate, the ability to mobilize endogenous reserves likely provides geese with relative flexibility to adjust the timing of breeding and the size of clutches. Higher temperatures, however, may negatively affect the quality of herbaceous foods and slow gosling growth. Species may possess traits that are beneficial during one phase of the reproductive cycle and others that may be detrimental at another phase, uneven responses that may be amplified with future climate warming. These results underscore the need to consider multiple phases of the reproductive cycle when assessing the effects of environmental variability on Arctic-breeding birds.

Alaska↗
USGS2022

Errors in aerial survey count data: Identifying pitfalls and solutions

Accurate estimates of animal abundance are essential for guiding effective management, and poor survey data can produce misleading inferences. Aerial surveys are an efficient survey platform, capable of collecting wildlife data across large spatial extents in short timeframes. However, these surveys can yield unreliable data if not carefully executed. Despite a long history of aerial survey use in ecological research, problems common to aerial surveys have not yet been adequately resolved. Through an extensive review of the aerial survey literature over the last 50 years, we evaluated how common problems encountered in the data (including nondetection, counting error, and species misidentification) can manifest, the potential difficulties conferred, and the history of how these challenges have been addressed. Additionally, we used a double-observer case study focused on waterbird data collected via aerial surveys and an online group (flock) counting quiz to explore the potential extent of each challenge and possible resolutions. We found that nearly three quarters of the aerial survey methodology literature focused on accounting for nondetection errors, while issues of counting error and misidentification were less commonly addressed. Through our case study, we demonstrated how these challenges can prove problematic by detailing the extent and magnitude of potential errors. Using our online quiz, we showed that aerial observers typically undercount group size and that the magnitude of counting errors increases with group size. Our results illustrate how each issue can act to bias inferences, highlighting the importance of considering individual methods for mitigating potential problems separately during survey design and analysis. We synthesized the information gained from our analyses to evaluate strategies for overcoming the challenges of using aerial survey data to estimate wildlife abundance, such as digital data collection methods, pooling species records by family, and ordinal modeling using binned data. Recognizing conditions that can lead to data collection errors and having reasonable solutions for addressing errors can allow researchers to allocate resources effectively to mitigate the most significant challenges for obtaining reliable aerial survey data.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2014

Inferences about population dynamics from count data using multi-state models: A comparison to capture-recapture approaches

Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers ( Setophaga caerulescens ) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales.

New Hampshire↗
USGS2020

Changes in prey, turbidity, and competition reduce somatic growth and cause the collapse of a fish population

Somatic growth exerts strong control on patterns in the abundance of animal populations via effects on maturation, fecundity, and survival rates of juveniles and adults. In this paper, we quantify abiotic and biotic drivers of rainbow trout growth in the Colorado River, AZ, and the resulting impact on spatial and temporal variation in abundance. Inferences are based on approximately 10,000 observations of individual growth grates obtained through an intensive mark‐recapture effort conducted over five years (2012‐2016) in a 130 km‐long study segment downstream of Glen Canyon Dam. Prey availability, turbidity‐driven feeding efficiency, and intra‐specific competition were the dominant drivers of rainbow trout growth. Discharge, water temperature, and solar insulation were also evaluated but had a smaller influence. Mixed‐effect models explained 79‐82% of the variability in observed growth rates, with fixed covariate effects explaining 79‐87% of the total variation in growth parameters across five reaches and 18 quarterly sampling intervals. Reductions in growth owing in part to a phosphorous‐driven decline in prey availability, led to substantive weight loss and poor fish condition. This in turn lowered survival rates and delayed maturation, which led to a rapid decline in abundance and later recruitments. Reductions in feeding efficiency, due to episodic inputs of fine sediment from tributaries, and warmer water temperatures, contributed to reduced growth in downstream reaches, which led to more severe declines in abundance. Somatic growth rates increased following the population collapse due to reduced competition, and in the absence of substantive increases in prey availability. Our study elucidates important linkages between abiotic and biotic factors, somatic growth, and vital rates, and demonstrates how variation in somatic growth influences temporal and spatial patterns in abundance.

Arizona↗
USGS2021

Sea otter population collapse in southwest Alaska: Assessing ecological covariates, consequences, and causal factors

Sea otter ( Enhydra lutris ) populations in southwest Alaska declined substantially between about 1990 and the most recent set of surveys in 2015. Here we report changes in the distribution and abundance of sea otters, and covarying patterns in reproduction, mortality, body size and condition, diet and foraging behavior, food availability, health profiles, and exposure to environmental contaminants over this 25-yr period. The population decline, which resulted in densities on the order of 5% of environmental carrying capacity, ranged from Attu Island in the west to about Castle Cape (on the south side of the Alaska Peninsula) in the east. Remaining sea otters moved closer to shore and into shallow, protected habitats. Reproductive rates appeared unchanged with the decline. Although the demographic cause of the decline was clearly elevated mortality, stranded carcasses were rare or absent. The net rate of energy gain by foraging sea otters, body length and condition, and prey biomass density, all increased after the decline and varied inversely with sea otter population density beyond the area of decline. Sea otters within the area of decline showed no increases in health anomalies, disease, contaminant exposure, or abnormal gene transcription patterns as compared to animals outside the area of decline. These collective findings are inconsistent with nutritional limitation, disease, or environmental contaminants, and consistent with predation (or possibly some other density-independent factor) as the reason for the sea otter population decline. Our approach and analyses provide a broad conceptual template for thinking about and assessing the causes of wildlife population declines.

Alaska↗
USGS2024

Environmental variation structures reproduction and recruitment in long-lived mega-herbivores: Galapagos giant tortoises

Migratory, long-lived animals are an important focus for life-history theory because they manifest extreme trade-offs in life-history traits: delayed maturity, low fecundity, variable recruitment rates, long generation times, and vital rates that respond to variation across environments. Galapagos tortoises are an iconic example: they are long-lived, migrate seasonally, face multiple anthropogenic threats, and have cryptic early life-history stages for which vital rates are unknown. From 2012 to 2021, we studied the reproductive ecology of two species of Galapagos tortoises ( Chelonoidis porteri and C. donfaustoi ) along elevation gradients that coincided with substantial changes in climate and vegetation productivity. Specifically, we (1) measured the body and reproductive condition of 166 adult females, (2) tracked the movements of 33 adult females using global positioning system telemetry, and monitored their body condition seasonally, (3) recorded nest temperatures, clutch characteristics, and egg survival from 107 nests, and (4) used radiotelemetry to monitor growth, survival, and movements of 104 hatchlings. We also monitored temperature and rainfall from field sites, and remotely sensed primary productivity along the elevation gradient. Our study showed that environmental variability, mediated by elevation, influenced vital rates of giant tortoises, specifically egg production by adult females and juvenile recruitment. Adult females were either elevational migrants or year-round lowland residents. Migrants had higher body condition than residents, and body condition was positively correlated with the probability of being gravid. Nests occurred in the hottest, driest parts of the tortoise's range, between 6 and 165 m elevation. Clutch size increased with elevation, whereas egg survival decreased. Hatchling survival and growth were highest at intermediate elevations. Hatchlings dispersed rapidly to 100–750 m from their nests before becoming sedentary (ranging over <0.2 ha). Predicted future climates may impact the relationships between elevation and vital rates of Galapagos tortoises and other species living across elevation gradients. Resilience will be maximized by ensuring the connectivity of foraging and reproductive areas within the current and possible future elevational ranges of these species.

Galapagos Islands, Santa Cruz Island↗
USGS2024

Using mobile acoustic monitoring and false-positive N-mixture models to estimate bat abundance and population trends

Estimating the abundance of unmarked animal populations from acoustic data is challenging due to the inability to identify individuals and the need to adjust for observation biases including detectability (false negatives), species misclassification (false positives), and sampling exposure. Acoustic surveys conducted along mobile transects were designed to avoid counting individuals more than once, where raw counts are commonly treated as an index of abundance. More recently, false-positive abundance models have been developed to estimate abundance while accounting for imperfect detection and misclassification. We adapted these methods to model summertime abundance and trends of three species of bats at multiple spatial scales using acoustic recordings collected along mobile transects by partners of the North American Bat Monitoring Program (NABat) from 2012 to 2020. This multiscale modeling spanned individual transect routes, larger NABat grid cells (10 km × 10 km), and across the entire extent of modeled species ranges. We estimated relationships between species abundances and a suite of abiotic and biotic predictors (landcover types, climatological variables, physiographic diversity, building density, and the impacts of white-nose syndrome [WNS]) and found varying levels of support between species. We present clear evidence of substantial declines in populations of tricolored bats ( Perimyotis subflavus ) and little brown bats ( Myotis lucifugus ), declines that corresponded in space and time with the progression of WNS, a devastating disease of hibernating bats. In contrast, our analysis revealed that similar population-wide declines probably have not occurred in big brown bats ( Eptesicus fuscus ), a species known to be less affected by WNS. This study provides the first abundance-based species distribution predictions and population trends for bats in their summer ranges in North America. These models will probably be applicable to assessing wildlife populations in other monitoring programs where acoustic data are used or where false-negative and false-positive detections are present. Finally, our abundance framework (as a spatial point pattern process) can serve as a foundation from which more sophisticated integrated species distribution models that incorporate additional streams of monitoring data (e.g., stationary acoustics, captures) can be developed for North American bats.

Ecological Monographs↗
USGS2026

Microclimate mediates the strength and direction of avian biotic interactions

Theory predicts that that the strength and direction of species interactions can shift from being competitive in benign environments toward being facilitative in stressful environments. However, the environmental context dependency of species interactions has rarely been tested in animal communities. We capitalized on a 15-year, landscape-scale dataset, collected annually in a relatively stable old-growth forest environment to test the long-held hypothesis that the strength and direction of species interactions might be mediated by climatic conditions. It is generally accepted that competitive and facilitative interactions drive the distributions of many species. Using multi-species dynamic occupancy models applied to long-term data, we tested whether annual settlement by bird species could affect either the persistence or settlement by other phylogenetically related species, and whether these interactions are mediated by microclimate. We found that species interactions were influenced by microclimate for some, but not all avian species pairs. Related species pairs more often showed settlement dynamics that were indicative of attraction rather than repulsion. In some cases, competitive interactions at warmer microclimates flipped to become facilitative in colder ones. However, the reverse was also true: facilitative interactions amplified for some species under warm conditions. Furthermore, species pairs that were closely related were more likely to exhibit competitive relationships along at least part of the microclimatic gradient. Our results highlight the importance of using long-term data to incorporate competitive and facilitative interactions into species distribution models and support the notion that the strength and direction of species interactions can be dependent on microclimatic environmental conditions.

Oregon↗
USGS2016

Distribution of a climate-sensitive species at an interior range margin

Advances in understanding the factors that limit a species’ range, particularly in the context of climate change, have come disproportionately through investigations at range edges or margins. The margins of a species’ range might often correspond with anomalous microclimates that confer habitat suitability where the species would otherwise fail to persist. We addressed this hypothesis using data from an interior, climatic range margin of the American pika ( Ochotona princeps ), an indicator of relatively cool, mesic climates in rocky habitats of western North America. Pikas in Lava Beds National Monument, northeastern California, USA, occur at elevations much lower than predicted by latitude and longitude. We hypothesized that pika occurrence within Lava Beds would be associated primarily with features such as “ice caves” in which sub-surface ice persists outside the winter months. We used data loggers to monitor sub-surface temperatures at cave entrances and at non-cave sites, confirming that temperatures were cooler and more stable at cave entrances. We surveyed habitat characteristics and evidence of pika occupancy across a random sample of cave and non-cave sites over a 2-yr period. Pika detection probability was high (~0.97), and the combined occupancy of cave and non-cave sites varied across the 2 yr from 27% to 69%. Contrary to our hypothesis, occupancy was not higher at cave sites. Vegetation metrics were the best predictors of site use by pikas, followed by an edge effect and elevation. The importance of vegetation as a predictor of pika distribution at this interior range margin is congruent with recent studies from other portions of the species’ range. However, we caution that vegetation composition depends on microclimate, which might be the proximal driver of pika distribution. The microclimates available in non-cave crevices accessible to small animals have not been characterized adequately for lava landscapes. We advocate innovation in the acquisition and use of microclimatic data for understanding the distributions of many taxa. Appropriately scaled microclimatic data are increasingly available but rarely used in studies of range dynamics.

Ecosphere↗
USGS2016

Plague cycles in two rodent species from China: Dry years might provide context for epizootics in wet years

Plague, a rodent-associated, flea-borne zoonosis, is one of the most notorious diseases in history. Rates of plague transmission can increase when fleas are abundant. Fleas commonly desiccate and die when reared under dry conditions in laboratories, suggesting fleas will be suppressed during droughts in the wild, thus reducing the rate at which plague spreads among hosts. In contrast, fleas might increase in abundance when precipitation is plentiful, producing epizootic outbreaks during wet years. We tested these hypotheses using a 27-yr data set from two rodents in Inner Mongolia, China: Mongolian gerbils ( Meriones unguiculatus ) and Daurian ground squirrels ( Spermophilus dauricus ). For both species of rodents, fleas were most abundant during years preceded by dry growing seasons. For gerbils, the prevalence of plague increased during wet years preceded by dry growing seasons. If precipitation is scarce during the primary growing season, succulent plants decline in abundance and, consequently, herbivorous rodents can suffer declines in body condition. Fleas produce more offspring and better survive when parasitizing food-limited hosts, because starving animals tend to exhibit inefficient behavioral and immunological defenses against fleas. Further, rodent burrows might buffer fleas from xeric conditions aboveground during dry years. After a dry year, fleas might be abundant due to the preceding drought, and if precipitation and succulent plants become more plentiful, rodents could increase in density, thereby creating connectivity that facilitates the spread of plague. Moreover, in wet years, mild temperatures might increase the efficiency at which fleas transmit the plague bacterium, while also helping fleas to survive as they quest among hosts. In this way, dry years could provide context for epizootics of plague in wet years.

Ecosphere↗
USGS2016

Forecasting climate change impacts on plant populations over large spatial extents

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush ( Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

Wyoming↗
USGS2017

Model-based estimators of density and connectivity to inform conservation of spatially structured populations

Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.

Ecosphere↗
USGS2017

Effects of experimentally reduced snowpack and passive warming on montane meadow plant phenology and floral resources

Climate change can have a broad range of effects on ecosystems and organisms, and early responses may include shifts in vegetation phenology and productivity that may not coincide with the energetics and forage timing of higher trophic levels. We evaluated phenology, annual height growth, and foliar frost responses of forbs to a factorial experiment of snow removal (SR) and warming in a high-elevation meadow over two years in the Rocky Mountains, United States. Species included arrowleaf balsamroot ( Balsamorhiza sagittata , early-season emergence and flowering) and buckwheat ( Eriogonum umbellatum, semi-woody and late-season flowering), key forbs for pollinator and nectar-using animal communities that are widely distributed and locally abundant in western North America. Snow removal exerted stronger effects than did warming, and advanced phenology differently for each species. Specifically, SR advanced green-up by a few days for B. sagittata to >2 wk in E. umbellatum , and led to 5- to 11-d advances in flowering of B. sagittata in one year and advances in bud break in 3 of 4 species/yr combinations. Snow removal increased height of E. umbellatum appreciably (~5 cm added to ~22.8 cm in control), but led to substantial increases in frost damage to flowers of B. sagittata . Whereas warming had no effects on E. umbellatum , it increased heights of B. sagittata by >6 cm (compared to 30.7 cm in control plots) and moreover led to appreciable reductions in frost damage to flowers. These data suggest that timing of snowmelt, which is highly variable from year to year but is advancing in recent decades, has a greater impact on these critical phenological, growth, and floral survival traits and floral/nectar resources than warming per se, although warming mitigated early effects of SR on frost kill of flowers. Given the short growing season of these species, the shifts could cause uncoupling in nectar availability and timing of foraging.

Ecosphere↗
USGS2017

The estimation of growth dynamics for Pomacea maculata from hatchling to adult

Pomacea maculata is a relatively new invasive species to the Gulf Coast region and potentially threatens local agriculture (rice) and ecosystems (aquatic vegetation). The population dynamics of P. maculata have largely been unquantified, and therefore, scientists and field-workers are ill-equipped to accurately project population sizes and the resulting impact of this species. We studied the growth of P. maculata ranging in weights from 6 to 105 g, identifying the sex of the animals when possible. Our studied population had a 4:9 male:female sex ratio. We present the findings from initial analysis of the individual growth data of males and females, from which it was apparent that females were generally larger than males and that small snails grew faster than larger snails. Since efforts to characterize the male and female growth rates from individual data do not yield statistically supported estimates, we present the estimation of several parameterized growth rate functions within a population-level mathematical model. We provide a comparison of the results using these various growth functions and discuss which best characterizes the dynamics of our observed population. We conclude that both males and females exhibit biphasic growth rates, and thus, their growth is size-dependent. Further, our results suggest that there are notable differences between males and females that are important to take into consideration in order to accurately model this species' population dynamics. Lastly, we include preliminary analyses of ongoing experiments to provide initial estimates of growth in the earliest life stages (hatchling to ≈6 g).

Ecosphere↗
USGS2017

Simulated juvenile salmon growth and phenology respond to altered thermal regimes and stream network shape

It is generally accepted that climate change will stress coldwater species such as Pacific salmon. However, it is unclear what aspect of altered thermal regimes (e.g., warmer winters, springs, summers, or increased variability) will have the greatest effect, and what role the spatial properties of river networks play. Thermally diverse habitats may afford protection from climate change by providing opportunities for aquatic organisms to find and use habitats with optimal conditions for growth. We hypothesized that climate‐altered thermal regimes will change growth and timing of life history events such as emergence or migration but that changes will be moderated in topologically complex stream networks where opportunities to thermoregulate are more readily available to mobile animals. Because climate change effects on populations are spatially variable and contingent upon physiological optima, assessments of risk must take a spatially explicit approach. We developed a spatially structured individual‐based model for Chinook Salmon ( Oncorhynchus tshawytscha ) in which movement decisions and growth were governed by water temperature and conspecific density. We evaluated growth and phenology (timing of egg emergence and smolting) under a variety of thermal regimes (each having a different minimum, rate of warming, maximum, and variability) and in three network shapes of increasing spatial complexity. Across networks, fish generally grew faster and were capable of smolting earlier in warmer scenarios where water temperatures experienced by fish were closer to optimal; however, growth decreased for some fish. We found that salmon size and smolt date responded more strongly to warmer springs and summers than to warmer winters or increased variability. Fish in the least complex network grew faster and were ready to smolt earlier than fish in the more spatially complex network shapes in the contemporary thermal regime; patterns were similar but less clear in warmer thermal regimes. Our results demonstrate that network topology may influence how fish respond to thermal landscapes, and this information will be useful for incorporating a spatiotemporal context into conservation decisions that promote long‐term viability of salmon in a changing climate.

Ecosphere↗
USGS2018

Mineral constraints on arctic caribou (Rangifer tarandus): a spatial and phenological perspective

Arctic caribou ( Rangifer tarandus ) have the longest terrestrial migration of any ungulate but little is known about the spatial and seasonal variation of minerals in summer forages and the potential impacts of mineral nutrition on the foraging behavior and nutritional condition of arctic caribou. We investigated the phenology, availability, and mechanistic relationships of calcium, phosphorus, magnesium, sodium, potassium, iron, manganese, copper, and zinc in three species of woody browse, three species of graminoids, and one forb preferred by caribou over two transects bisecting the ranges of the Central Arctic (CAH) and Western Arctic (WAH) caribou herds in Alaska. Transects traversed three ecoregions (Coastal Plain, Arctic Foothills and Brooks Range) along known migration paths in the summer ranges of both herds. Concentrations of mineral in forages were compared to estimated dietary requirements of lactating female caribou. Spatial distribution of the abundance of minerals in caribou forage was associated with interactions of soil pH and mineral content, while temporal variation was related to plant maturity, and thus nitrogen and fiber content of forages. Concentrations of sodium were below caribou requirements in all forage species for most of the summer and adequate only on the Coastal Plain during the second half of summer. Phosphorus declined in plants from emergence to senescence and was below requirements in all forages by mid‐summer, while concentrations of copper declined to marginal concentrations at plant senescence. Interactions of sodium with potassium, calcium with phosphorus, and copper with zinc in forages likely exacerbate the constraints of low concentrations sodium, phosphorus, and copper. Forages on the WAH contained significantly more phosphorus and copper than forages collected on the CAH transect. We suspect that migrations of caribou to the Arctic Coastal Plain may allow parturient females to replenish sodium stores depleted by foraging inland through the long arctic winters, while also extending the availability of adequate phosphorus, if animals are able to selectively track emerging waves of forage.

Alaska↗