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At least 1,189 records · Page 66Linked to original sources
USGS2013

Odor-conditioned rheotaxis of the sea lamprey: Modeling, analysis and validation

Mechanisms for orienting toward and locating an odor source are sought in both biology and engineering. Chemical ecology studies have demonstrated that adult female sea lamprey show rheotaxis in response to a male pheromone with dichotomous outcomes: sexually mature females locate the source of the pheromone whereas immature females swim by the source and continue moving upstream. Here we introduce a simple switching mechanism modeled after odor-conditioned rheotaxis for the sea lamprey as they search for the source of a pheromone in a one-dimensional riverine environment. In this strategy, the females move upstream only if they detect that the pheromone concentration is higher than a threshold value and drifts down (by turning off control action to save energy) otherwise. In addition, we propose various uncertainty models such as measurement noise, actuator disturbance, and a probabilistic model of a concentration field in turbulent flow. Based on the proposed model with uncertainties, a convergence analysis showed that with this simplistic switching mechanism, the lamprey converges to the source location on average in spite of all such uncertainties. Furthermore, a slightly modified model and its extensive simulation results explain the behaviors of immature female lamprey near the source location.

Bioinspiration and Biomimetics↗
USGS1983

Habitat suitability index models: redhead (wintering)

The redhead is a North American waterfowl species with economic as well as ecological importance. It is highly desired by hunters. Retrieved redhead kill in the United States averaged 143,000 birds during the three waterfowl seasons from 1975 to 1977 (U.S. Department of the Interior 1981a, 1981b). Populations on the principal breeding grounds of the redhead--the prairie and parkland region of south-central Canada and north-central United States--averaged 710,000 birds from 1955 to 1981 (Bellrose 1976; A. Novara, U.S. Fish and Wildlife Service [USFWS], Jamestown, North Dakota; pers. comm.). Redhead numbers began to decline in the 1960's. Killing redheads became illegal from 1960 to 1963, and strict bag limits were imposed after that (Bellrose 1976). A breeding population low of 387,000 birds occurred in 1963, but prairie populations began to recover after that time. Their numbers peaked in 1980 when 1,146,000 birds were recorded (A. Novara, pers. comm.). During the fall, over a third of the total redhead population uses the migration corridor that extends from the prairie breeding area to the Texas gulf coast. Another migration corridor extends from the second most important breeding area--the Great Salt Basin--to the Texas coast (Bellrose 1976). During the fall, over a third of the total redhead population uses the migration corridor that extends from the prairie breeding area to the Texas gulf coast. Another migration corridor extends from the second most important breeding area--the Great Salt Basin--to the Texas coast (Bellrose 1976).

FWS/OBS↗
USGS2018

A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language

Recent studies hypothesize various causes of species‐level trait covariation, namely size (e.g., metabolic theory of ecology and leaf economics spectrum), pace‐of‐life (e.g., slow‐to‐fast continuum; lifestyle continuum), evolutionary history (e.g., phylogenetic conservatism), and ecological conditions (e.g., stabilizing selection). Various methods have been used in attempts to partition trait correlation among these influences (e.g., univariate analysis, principal components analysis, and factor analysis). However, it is not clear that the implied causal structure assumed by these methods matches the hypothesized causal structure driving trait correlations, a situation that can potentially lead to biased estimates and incorrect partitioning among mechanisms. Here, we propose the application of graphical causal models (GCM) for across‐kingdom synthesis and to aid researchers in their selection of correct analytical strategies. Graphical causal models use causal diagrams (i.e., box‐and‐arrow graphs) to represent expert knowledge of the data‐generating processes to analytically investigate the possibility of identifying hypothesized causal associations. We developed a causal diagram that synthesizes prominent hypotheses of trait covariation. Using the causal diagram, we (1) derived a quantitative expression to partition trait covariance among its hypothesized causal elements (i.e., size, pace‐of‐life, evolutionary history, and ecological conditions) and (2) developed analytic strategies to attribute trait covariance among the hypothesized causal elements under real‐world data availability, namely unobserved variables (i.e., pace‐of‐life) and confounding variables (i.e., evolutionary history and ecological conditions). Finally, we tested each analytic strategy by simulating trait datasets and, after incorporating the data limitations, tested their ability to correctly partition trait covariance. The analytical strategies were able to correctly partition trait covariance into the hypothesized causal elements of size, pace‐of‐life, and the historical effects of evolutionary history and ecological conditions. We demonstrate the efficacy of these strategies by applying them to a widely used trait dataset. Overall, the application of GCM revealed that researchers have used inappropriate measures to represent their theoretical constructs and have relied on analytical strategies that violated their causal assumptions, likely resulting in biased estimates. We discuss how this mismatch between theoretical language and statistical methods is prevalent in species‐level, trait‐based research and call for future studies to address these limitations.

Ecosphere↗
USGS2024

Predictive understanding of stream salinization in a developed watershed using machine learning

Stream salinization is a global issue, yet few models can provide reliable salinity estimates for unmonitored locations at the time scales required for ecological exposure assessments. Machine learning approaches are presented that use spatially limited high-frequency monitoring and spatially distributed discrete samples to estimate the daily stream-specific conductance across a watershed. We compare the predictive performance of space- and time-unaware Random Forest models and space- and time-aware Recurrent Graph Convolution Neural Network models (KGE: 0.67 and 0.64, respectively) and use explainable artificial intelligence methods to interpret model predictions and understand salinization drivers. These models are applied to the Delaware River Basin, a developed watershed with diverse land uses that experiences anthropogenic salinization from winter deicer applications. These models capture seasonality for the winter first flush of deicers, and the streams with elevated predictions correspond well with indicators of deicer application. This result suggests that these models can be used to identify potential salinity-impaired streams for winter best management practices. Daily salinity predictions are driven primarily by land cover (urbanization) trends that may represent anthropogenic salinization processes and weather at time scales up to three months. Such modeling approaches are likely transferable to other watersheds and can be applied to further understand salinization risks and drivers.

Environmental Science and Technology↗
USGS2023

Estimating fat content in barred owls (Strix varia) with predictive models developed from direct measures of proximate body composition

Body condition indices and related metrics can help assess habitat quality and other ecological processes, and ideally, these metrics are based on measures of lipids directly extracted from the species of interest. In recent decades, barred owls ( Strix varia ) have become a species of conservation concern as they invaded older forests of the US Pacific Northwest, and caused population declines of the closely related and federally threatened northern spotted owl ( Strix occidentalis caurina ). A simple and effective measure of barred owl body condition could help to understand how habitat quality varies within their new range, which in turn can inform their management and other aspects of their ecology. Using 77 barred owl carcasses collected during experimental removals in Washington and Oregon, USA, we measured the amount of lipid in each specimen with proximate body composition analysis. We then fit and compared (with adjusted R 2 values) alternative linear regression models to estimate the percent lipids in dry mass of the owls based on morphometric body condition indices, a qualitative fat score of subcutaneous breast fat, sex and the time of year females were collected (relative to egg production). Adjusted R 2 values for all models ranged from 0.49 to 0.87, with the best model including mass divided by foot-pad length, fat score, sex and the time of year a female was collected. Most models generated comparable estimates of percent lipids at a population level and we provided correction factors to apply these models when used with live barred owls, allowing for site-specific comparisons of body condition among individuals inhabiting a diversity of environmental conditions.

Conservation Physiology↗
USGS2014

Decomposition

A cornerstone of ecosystem ecology, decomposition was recognized as a fundamental process driving the exchange of energy in ecosystems by early ecologists such as Lindeman 1942 and Odum 1960). In the history of ecology, studies of decomposition were incorporated into the International Biological Program in the 1960s to compare the nature of organic matter breakdown in various ecosystem types. Such studies still have an important role in ecological studies of today. More recent refinements have brought debates on the relative role microbes, invertebrates and environment in the breakdown and release of carbon into the atmosphere, as well as how nutrient cycling, production and other ecosystem processes regulated by decomposition may shift with climate change. Therefore, this bibliography examines the primary literature related to organic matter breakdown, but it also explores topics in which decomposition plays a key supporting role including vegetation composition, latitudinal gradients, altered ecosystems, anthropogenic impacts, carbon storage, and climate change models. Knowledge of these topics is relevant to both the study of ecosystem ecology as well projections of future conditions for human societies.

Article↗
USGS2009

The Ozark Highlands

The Ozark Highlands include diverse topographic, geologic, soil, and hydrologic conditions that support a broad range of habitat types. The landscape features rugged uplands - some peaks higher than 2,500 feet above sea level - with exposed rock and varying soil depths and includes extensive areas of karst terrain. The Highlands are characterized by extreme biological diversity and high endemism (uniqueness of species). Vegetation communities are dominated by open oak-hickory and shortleaf pine woodlands and forests. Included in this vegetation matrix is an assemblage of various types of fens, forests, wetlands, fluvial features, and carbonate and siliceous glades. An ever-growing human population in the Ozark Highlands has become very dependent on reservoirs constructed on major rivers in the region and, in some cases, groundwater for household and public water supply. Because of human population growth in the Highlands and increases in industrial and agricultural activities, not only is adequate water quantity an issue, but maintaining good water quality is also a challenge. Point and nonpoint sources of excessive nutrients are an issue. U.S. Geological Survey (USGS) partnership programs to monitor water quality and develop simulation tools to help stakeholders better understand strategies to protect the quality of water and the environment are extremely important. The USGS collects relevant data, conducts interpretive studies, and develops simulation tools to help stakeholders understand resource availability and sustainability issues. Stakeholders dependent on these resources are interested in and benefit greatly from evolving these simulation tools (models) into decision support systems that can be used for adaptive management of water and ecological resources. The interaction of unique and high-quality biological and hydrologic resources and the effects of stresses from human activities can be evaluated best by using a multidisciplinary approach that the USGS can provide. Information varying from defining baseline resource conditions to developing simulation models will help resource managers and users understand the human impact on resource sustainability. Varied expertise and experience in biological and water-resources activities across the entire Highlands make the USGS a valued collaborator in studies of Ozark ecosystems, streams, reservoirs, and groundwater. A large part of future success will depend on the involvement and active participation of key partners.

Fact Sheet↗
USGS2006

Data collection network to support ecosystem forecasting for the Barataria Basin - Mississippi River domain

Ecosystem forecasting is limited by a number of uncertainties including inadequate initialization information, unknown boundary conditions, inaccurate model physics and atmospheric forcing functions, and inadequate algorithm development of geomorphic and ecological responses to hydrodynamic and geophysical processes. Monitoring can help reduce these uncertainties by providing numerical information on those variables that can improve simulation capabilities. A data collection network was designed for the Mississippi River, south of Tarbert Landing, Ms. to Venice, La., and for the inland and nearshore waters of Barataria Basin, La. The network considered existing monitoring efforts that effectively link oceanographic and water quality observations to system drivers to support ecosystem hindcasting, nowcasting, and forecasting capabilities. The design was driven by the diverse needs of the modeling community and utilized questionnaire surveys, workshops, and web- based applications to inventory past and present modeling applications, domains, and attributes. The use of existing monitoring stations, including variables measured and frequency of data collection, were also considered, as well as recommendations on where new monitoring stations should be located, what types of data should be collected, and at what temporal frequency. Compiled databases are presented as a series of GIS layers to represent overlap between existing and requested stations, and priorities are established for either maintaining or augmenting existing stations or deploying new stations. An optimization plan will be prepared from the results of this study that will provide a rationale for the ecosystem forecasting data collection network that includes a description of existing monitoring programs to support ecosystem forecasting and a set of justifiable locations for "megastations" that meet the needs of the modeling and assessment communities.

Louisiana↗
USGS2017

Complex networks of functional connectivity in a wetland reconnected to its floodplain

Disturbances such as fire or flood, in addition to changing the local magnitude of ecological, hydrological, or biogeochemical processes, can also change their functional connectivity—how those processes interact in space. Complex networks offer promise for quantifying functional connectivity in watersheds. The approach resolves connections between nodes in space based on statistical similarities in perturbation signals (derived from solute time series) and is sensitive to a wider range of timescales than traditional mass-balance modeling. We use this approach to test hypotheses about how fire and flood impact ecological and biogeochemical dynamics in a wetland (Everglades, FL, USA) that was reconnected to its floodplain. Reintroduction of flow pulses after decades of separation by levees fundamentally reconfigured functional connectivity networks. The most pronounced expansion was that of the calcium network, which reflects periphyton dynamics and may represent an indirect influence of elevated nutrients, despite the comparatively smaller observed expansion of phosphorus networks. With respect to several solutes, periphyton acted as a “biotic filter,” shifting perturbations in water-quality signals to different timescales through slow but persistent transformations of the biotic community. The complex-networks approach also revealed portions of the landscape that operate in fundamentally different regimes with respect to dissolved oxygen, separated by a threshold in flow velocity of 1.2 cm/s, and suggested that complete removal of canals may be needed to restore connectivity with respect to biogeochemical processes. Fire reconfigured functional connectivity networks in a manner that reflected localized burn severity, but had a larger effect on the magnitude of solute concentrations.

Florida↗
USGS2007

A conceptual life-history model for pallid and shovelnose sturgeon

Intensive management of the Missouri and Mississippi Rivers has resulted in dramatic physical changes to these rivers. These changes have been implicated as causative agents in the decline of pallid sturgeon. The pallid sturgeon, federally listed as endangered, is endemic to the turbid waters of the Missouri River and the Lower Mississippi River. The sympatric shovelnose sturgeon historically was more common and widespread than the pallid sturgeon. Habitat alteration, river regulation, pollution, and over-harvest have resulted in the now predictable patterns of decline and localized extirpation of sturgeon across species and geographic areas. Symptomatic of this generalized pattern of decline is poor reproductive success, and low or no recruitment of wild juveniles to the adult population. The purpose of this report is to introduce a conceptual life-history model of the factors that affect reproduction, growth, and survival of shovelnose and pallid sturgeons. The conceptual model provided here was developed to organize the understanding about the complex life history of Scaphirhynchus sturgeons. It was designed to be used for communication, planning, and to provide the structure for a population-forecasting model. These models are intended to be dynamic and responsive to new information and changes in river management, thereby providing scientists, stakeholders, and managers with ways to improve understanding of the effects of management actions on the ecological requirements of Scaphirhynchus sturgeons. As new scientific knowledge becomes available, it could be included in the model in many ways at various integration levels.

Circular↗
USGS2021

Ecological potential fractional component cover based on Long-Term satellite observations across the western United States

Rangelands have immense inherent spatial and temporal variability, yet land condition and trends are often assessed at a limited number of spatially “representative” points. Spatially comprehensive, and quantitative, Ecological Potential (EP) data provide a baseline for comparison to current rangeland vegetation conditions and trends. Here, we define EP as potential fractional cover (bare ground, herbaceous, litter, shrub, and sagebrush) represented in the least disturbed areas and most productive years of the Landsat satellite archive (1985-present) for each 30-m pixel. We produce EP maps across rangelands in the western United States by training regression tree models using Rangeland Condition Monitoring Assessment and Projection (RCMAP) time-series fractional cover maps in ecologically intact sites (with limited annual herbaceous cover, no recent disturbance or vegetation treatment, and less bare ground cover than expected). As independent predictor variables in these models, we use digital soils and topography data and six bimonthly composites of the 90th percentile of Normalized Difference Vegetation Index (NDVI) and associated spectral bands from the 1985–2020 Landsat archive. EP predictions were successful in capturing biophysical gradients present in the independent variables and depicting potential cover in the absence of disturbance; we found no influence of fires or land treatments in the data. Next, we compared EP to contemporary (2018) cover, to create departure maps that can be used as a screening tool indicating degradation and providing an early warning of vegetation state change. Finally, we used a dichotomous key to convert the 1985 and 2018 RCMAP cover and EP cover into vegetation states important to land management decisions (invaded sagebrush steppe , annual grasslands, etc.). We found that in 1985, 21.2% of the study area had a different vegetation state than EP, and this percentage increased to 24.2% by 2018. More than 50% of the EP native sagebrush steppe was converted to an annual grassland, perennial grassland, or non-sagebrush shrub by 2018, and an additional 7% was classified as invaded sagebrush steppe, at risk of transition to another state. EP products provide a spatio-temporal reference of vegetation conditions from the last three decades across rangelands in the western United States. Use of the EP reference can improve adaptive management practice by providing monitoring and control data, which are often lacking, and assist in differentiating treatment effect from confounding factors.

western United States↗
USGS2023

Reconstructing missing data by comparing interpolation techniques: Applications for long-term water quality data

Missing data are typical yet must be addressed for proper inferences or expanding datasets to guide our limnological understanding and management of aquatic systems. Interpolation methods (i.e., estimating missing values using known values within the dataset) can alleviate data gaps and common problems. We compared seven popular interpolation methods for predicting substantial missingness in a long-term water quality dataset from the Upper Mississippi River, U.S.A. The dataset included 80,000 sampling sites collected over 30 yr that had substantial missingness for total nitrogen (TN), total phosphorus (TP), and water velocity. For all three interpolated water quality variables, random forests had very high prediction accuracy and outperformed the methods of ordinary kriging, polynomial regressions, regression trees, and inverse distance weighting. TP had a mean absolute error (MAE) of 0.03 mg (L-TP) −1 , TN had a MAE of 0.39 mg (L-TN) −1 , and water velocity had a MAE of 0.10 m s −1 . The random forests' error rates were mapped and showed low spatiotemporal variability across the riverscape, indicating high model performance across many habitat types and large spatial scales. In the current era of “big data,” interpolation becomes an imperative step prior to ecological analyses yet remains unfamiliar and underutilized. Our research briefly describes the importance of addressing missingness and provides a roadmap to conduct model intercomparisons of other big datasets. We also share adaptable data analysis scripts, which allows others to readily conduct interpolation comparisons for many limnology applications and contexts.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2020

Depth-dependent soil mixing persists across climate zones

Soil mixing over long (>10 2 y) timescales enhances nutrient fluxes that support soil ecology, contributes to dispersion of sediment and contaminated material, and modulates fluxes of carbon through Earth’s largest terrestrial carbon reservoir. Despite its foundational importance, we lack robust understanding of the rates and patterns of soil mixing, largely due to a lack of long-timescale data. Here we demonstrate that luminescence, a light-sensitive property of minerals used for geologic dating, can be used as a long-timescale sediment tracer in soils to reveal the structure of soil mixing. We develop a probabilistic model of transport and mixing of tracer particles and associated luminescence in soils and compare with a global compilation of luminescence versus depth in various locations. The model–data comparison reveals that soil mixing rate varies over the soil depth, with this depth dependency persisting across climate and ecological zones. The depth dependency is consistent with a model in which mixing intensity decreases linearly or exponentially with depth, although our data do not resolve between these cases. Our findings support the long-suspected idea that depth-dependent mixing is a spatially and temporally persistent feature of soils. Evidence for a climate control on the patterns and intensities of soil mixing with depth remains elusive and requires the further study of soil mixing processes.

PNAS↗
USGS2019

Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture-recapture data from camera traps

Camera-trapping data analyzed with spatially explicit capture–recapture (SCR) models can provide a rigorous method for estimating density of small populations of elusive carnivore species. We sought to develop and evaluate the efficacy of SCR models for estimating density of a presumed low-density bobcat ( Lynx rufus ) population in fragmented landscapes of west-central Illinois, USA. We analyzed camera-trapping data from 49 camera stations in a 1,458-km 2 area deployed over a 77-day period from 1 February to 18 April 2017. Mean operational time of cameras was 52 days (range = 32–67 days). We captured 23 uniquely identifiable bobcats 113 times and recaptured these same individuals 90 times; 15 of 23 (65.2%) individuals were recaptured at ≥2 camera traps. Total number of bobcat capture events was 139, of which 26 (18.7%) were discarded from analyses because of poor image quality or capture of only a part of an animal in photographs. Of 113 capture events used in analyses, 106 (93.8%) and 7 (6.2%) were classified as positive and tentative identifications, respectively; agreement on tentative identifications of bobcats was high (71.4%) among 3 observers. We photographed bobcats at 36 of 49 (73.5%) camera stations, of which 34 stations were used in analyses. We estimated bobcat density at 1.40 individuals (range = 1.00–2.02)/100 km 2 . Our modeled bobcat density estimates are considerably below previously reported densities (30.5 individuals/100 km 2 ) within the state, and among the lowest yet recorded for the species. Nevertheless, use of remote cameras and SCR models was a viable technique for reliably estimating bobcat density across west-central Illinois. Our research establishes ecological benchmarks for understanding potential effects of colonization, habitat fragmentation, and exploitation on future assessments of bobcat density using standardized methodologies that can be compared directly over time. Further application of SCR models that quantify specific costs of animal movements (i.e., least-cost path models) while accounting for landscape connectivity has great utility and relevance for conservation and management of bobcat populations across fragmented Midwestern landscapes.

Illinois↗
USGS2026

Space-based monitoring of penguin diet links sea ice, food webs, and population change

Rapid environmental change is reshaping Antarctic ecosystems through shifts in temperature and sea ice dynamics, with implications for species such as the iconic Adélie penguin ( Pygoscelis adeliae ). Because Antarctic predators rely on a relatively small number of key prey resources in the region 1 whose life histories are intrinsically linked to sea ice, 2 , 3 these abiotic changes are expected to cascade through food webs. However, the scale and remoteness of Antarctica have limited efforts to link environmental change to ecological responses across the continent. Combining tools from imaging spectroscopy, stable isotope analysis, and hierarchical statistical modeling, we reconstructed Adélie penguin diet across the entirety of the species’ global range over a three-decade period (1984–2013) using satellite imagery from the Landsat program. This approach leveraged the distinct spectral properties (a generalized measure of color) of penguin guano as observed by satellites, 4 , 5 which vary according to penguin diet. 6 , 7 We found pronounced differences in diet across the continent and that year-to-year dietary shifts were strongly associated with sea ice dynamics. Higher sea ice corresponded to more fish-based diets, whereas lower sea ice was associated with a greater reliance on krill. Additionally, spatial differences in penguin diet were associated with long-term trends in penguin abundance, linking food web processes to large-scale population dynamics. This study represents the first use of satellite observations to capture trophic dynamics at continental and decadal scales and highlights how environmental change might restructure Antarctic food webs and influence the future of a key sentinel species.

Current Biology↗
USGS2011

Quantifying seascape structure: Extending terrestrial spatial pattern metrics to the marine realm

Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change.

Marine Ecology Progress Series↗
USGS2019

Energy intake rate influences survival of Black Oystercatcher Haematopus bachmani broods

Black Oystercatchers Haematopus bachmani, a species of conservation concern, depend on marine intertidal prey resources. We examined diet, feeding rates, growth, and survival of Black Oystercatcher broods in southcentral Alaska, 2013-2014. To determine the importance of diet on brood survival, we modeled daily survival rates of broods as a function of energy intake rate and other ecological factors. We hypothesized that broods fed at higher energy intake rates would grow faster and fly earlier, thereby being less vulnerable to predators and having higher rates of survival. Consistent with our prediction, broods with higher energy intake rates had higher rates of growth and daily survival. The best-supported model indicated that brood survival varied by energy intake rate and brood age. To understand how adults meet the increasing nutritional needs of developing chicks, we examined delivery rates and prey type and size as a function of brood age. Delivery rates differed by age, but composition and size classes of prey items did not, indicating that adults respond to the rising energetic needs of broods by increasing parental effort rather than switching prey. These findings demonstrate the importance of diet and provisioning to broods and given the consequences of reduced energy intake on survival, indicate that shifts in intertidal invertebrates as a result of climate change could have significant impacts on Black Oystercatcher populations.

Alaska↗
USGS2020

The distribution of woody species in relation to climate and fire in Yosemite National Park, California, USA

Background The effects of climate on plant species ranges are well appreciated, but the effects of other processes, such as fire, on plant species distribution are less well understood. We used a dataset of 561 plots 0.1 ha in size located throughout Yosemite National Park, in the Sierra Nevada of California, USA, to determine the joint effects of fire and climate on woody plant species. We analyzed the effect of climate (annual actual evapotranspiration [AET], climatic water deficit [Deficit]) and fire characteristics (occurrence [BURN] for all plots, fire return interval departure [FRID] for unburned plots, and severity of the most severe fire [dNBR]) on the distribution of woody plant species. Results Of 43 species that were present on at least two plots, 38 species occurred on five or more plots. Of those 38 species, models for the distribution of 13 species (34%) were significantly improved by including the variable for fire occurrence (BURN). Models for the distribution of 10 species (26%) were significantly improved by including FRID, and two species (5%) were improved by including dNBR. Species for which distribution models were improved by inclusion of fire variables included some of the most areally extensive woody plants. Species and ecological zones were aligned along an AET-Deficit gradient from cool and moist to hot and dry conditions. Conclusions In fire-frequent ecosystems, such as those in most of western North America, species distribution models were improved by including variables related to fire. Models for changing species distributions would also be improved by considering potential changes to the fire regime.

California↗