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Results for “Landscape Ecology”

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At least 127 records · Page 7Linked to original sources
USGS2011

Spatial pattern formation of coastal vegetation in response to external gradients and positive feedbacks affecting soil porewater salinity: A model study

Coastal vegetation of South Florida typically comprises salinity-tolerant mangroves bordering salinity-intolerant hardwood hammocks and fresh water marshes. Two primary ecological factors appear to influence the maintenance of mangrove/hammock ecotones against changes that might occur due to disturbances. One of these is a gradient in one or more environmental factors. The other is the action of positive feedback mechanisms, in which each vegetation community influences its local environment to favor itself, reinforcing the boundary between communities. The relative contributions of these two factors, however, can be hard to discern. A spatially explicit individual-based model of vegetation, coupled with a model of soil hydrology and salinity dynamics is presented here to simulate mangrove/hammock ecotones in the coastal margin habitats of South Florida. The model simulation results indicate that an environmental gradient of salinity, caused by tidal flux, is the key factor separating vegetation communities, while positive feedback involving the different interaction of each vegetation type with the vadose zone salinity increases the sharpness of boundaries, and maintains the ecological resilience of mangrove/hammock ecotones against small disturbances. Investigation of effects of precipitation on positive feedback indicates that the dry season, with its low precipitation, is the period of strongest positive feedback.

Florida↗
USGS2015

The scaling of geographic ranges: implications for species distribution models

Context The geographic ranges of many species are responding to ongoing environmental change. Processes operating at different levels of biological organization, with corresponding spatial extents and grains and temporal rates, interact with the evolving configuration of environmental conditions to determine range dynamics. Objectives To synthesize understanding of scales and scaling, including relevant biological levels of organization, focusing on the processes that mediate species-environment relationships and the models used to make inferences about species distributions. Methods We review concepts related to the scaling of geographic ranges and implications for the most commonly used analytic methods, using simple simulations to illustrate important issues. Results Many processes lead to species distributions being dependent on environmental conditions within sites and within a neighborhood. Studies with large extents and fine grains can cut across several levels of biological organization (individual, within-population, and metapopulation processes) complicating interpretation. Many geographic ranges are not in dynamic equilibrium, but common models used for inference assume equilibrium. Interspecific interactions shape species distributions at multiple scales, and arguments for ignoring species interactions also assume equilibrium. Conclusions There is a need for timely science to inform policy and management decisions; however, we must also strive to provide predictions that best reflect our understanding of ecological systems. Species distributions evolve through time and reflect responses to environmental conditions that are mediated through individual and population processes. Species distribution models that reflect this understanding, and explicitly model dynamics, are likely to give more accurate predictions.

Landscape Ecology↗
USGS2013

Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges

Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.

Alaska↗
USGS2017

A Bayesian method for assessing multiscalespecies-habitat relationships

Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Nebraska↗
USGS2018

Interior Least Tern sandbar nesting habitat measurements from Landsat Thematic Mapper imagery

Sandbars of large sand-bedded rivers of the central United States serve important ecological functions to many species, including the endangered Interior Least Tern ( Sternula antillarum , ILT). The ILT is a colonial bird that feeds on fish and nests primarily on riverine sandbars during its annual breeding season of around May through July, depending on region. During this time, ILTs require bare sand of sufficient elevation so as not to be inundated between nest initiation and fledging of hatchlings. Partly because of decreases in available sandbar habitat from river channelization and impoundment, ILTs were listed as endangered in 1985. Sandbars used by ILTs in central United States rivers are highly dynamic and undergo substantive changes across a wide range of temporal and spatial scales. River hydrology is the primary driver of sandbar morphodynamics in these systems. Better characterization of sandbar area with time, accounting for varying flow regimes, allows for a better understanding of landscape-scale ecology for sandbar-dependent species such as the ILT. This work uses remote-sensing techniques to quantify sandbar area that may be used by ILTs at the land-scape scale and how it has changed with time. The assessment of landscape-scale trends in sandbar area with time requires datasets with high temporal resolution and long record periods covering large geographic areas. Evaluation of remotely sensed datasets requires consideration of river stage fluctuations. To make this assessment, we developed land-cover classification datasets within active channel masks using all available images from the Landsat Thematic Mapper series of satellites meeting cloud-free (40 percent or less) and ice-free criteria. Landsat imagery was selected because of its long record period, spatial coverage, and regular reimaging cycle, making it well suited to monitor ILT sandbar habitat with time. We also attributed each scene with discharge or stage using a new database integrating U.S. Geological Survey and U.S. Army Corps of Engineers river data with Landsat metadata. This report documents development of these riverine classification datasets with a focus on applicability to the ILT. This framework may be used to continue monitoring the ILT sandbar nesting habitat or to evaluate other aquatic and terrestrial species whose life cycles are related to sandbars and channel complexity.

Data Series↗
USGS2013

Wyoming Basin Rapid Ecoregional Assessment

The overall goal of the Wyoming Basin Rapid Ecoregional Assessment (REA) is to provide information that supports regional planning and analysis for the management of ecological resources. The REA provides an assessment of baseline ecological conditions, an evaluation of current risks from drivers of ecosystem change (including energy development, fire, and invasive species), and a predictive capacity for evaluating future risks (including climate change). Additionally, the REA may be used for identifying priority areas for conservation or restoration and for assessing cumulative effects of multiple land uses. The Wyoming Basin REA will address Management Questions developed by the Bureau of Land Management and other agency partners for 8 major biomes and 19 species or species assemblages. The maps developed for addressing Management Questions will be integrated into overall maps of landscape-level ecological values and risks. The maps can be used to address the goals of the REA at a number of levels: for individual species, species assemblages, aquatic and terrestrial systems, and for the entire ecoregion. This allows flexibility in how the products of the REA are compiled to inform planning and management actions across a broad range of spatial scales.

Colorado;Idaho;Montana;Utah;Wyoming↗
USGS2018

Evaluating anthropogenic landscape alterations as wildlife hazards, with wind farms as an example

Anthropogenic alterations to landscape are indicators of potential compromise of that landscape’s ecology . We describe how alterations can be assessed as ‘hazards’ to wildlife through a sequence of three steps: diagnosing the means by which the hazard acts on individual organisms at risk; estimating the fitness cost of the hazard to those individuals and the rate at which that cost occurs; and translating that cost rate into a demographic cost by identifying the relevant demographically-closed population. We exploit the conservation-oriented literature on wind farms to illustrate this conceptual scheme. For wind farms, the third component has received less attention than the first two, which suggests it is the most challenging of the three components. A wind farm provides an example of a ‘spatially localized hazard’, i.e., a discrete alteration of landscape hazardous to some population but of which there are some individuals that do not interact directly with the hazard themselves but nevertheless suffer a reduction in fitness in terms of their contribution to the next generation. Spatially localized hazards are identified via the third component of the scheme and are of particular conservation concern as, by their nature, their depredations on wildlife may be underestimated without an appropriate population-level estimation of the demographic cost of the hazard.

Ecological Indicators↗
USGS2018

Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km 2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.

Sensors↗
USGS2000

Assessing land-use impacts on biodiversity using an expert systems tool

Habitat alteration, in the form of land-use development, is a leading cause of biodiversity loss in the U.S. and elsewhere. Although statutes in the U.S. may require consideration of biodiversity in local land-use planning and regulation, local governments lack the data, resources, and expertise to routinely consider biotic impacts that result from permitted land uses. We hypothesized that decision support systems could aid solution of this problem. We developed a pilot biodiversity expert systems tool (BEST) to test that hypothesis and learn what additional scientific and technological advancements are required for broad implementation of such a system. BEST uses data from the U.S. Geological Survey's Gap Analysis Program (GAP) and other data in a desktop GIS environment. The system provides predictions of conflict between proposed land uses and biotic elements and is intended for use at the start of the development review process. Key challenges were the development of categorization systems that relate named land-use types to ecological impacts, and relate sensitivities of biota to ecological impact levels. Although the advent of GAP and sophisticated desktop GIS make such a system feasible for broad implementation, considerable ongoing research is required to make the results of such a system scientifically sound, informative, and reliable for the regulatory process. We define a role for local government involvement in biodiversity impact assessment, the need for a biodiversity decision support system, the development of a prototype system, and scientific needs for broad implementation of a robust and reliable system.

Landscape Ecology↗
USGS2008

A Landscape Indicator Approach to the Identification and Articulation of the Ecological Consequences of Land Cover Change in the Chesapeake Bay Watershed, 1970-2000

The advancement of geographic science in the area of land surface status and trends and land cover change is at the core of the current geographic scientific research of the U.S. Geological Survey (USGS) (McMahon and others, 2005). Perhaps the least developed or articulated aspects of USGS land change science have been the identification and analysis of the ecological consequences of land cover change. Changes in land use and land cover significantly affect the ability of ecosystems to provide essential ecological goods and services, which, in turn, affect the economic, public health, and social benefits that these ecosystems provide. One of the great scientific challenges for geographic science is to understand and calibrate the effects of land use and land cover change and the complex interaction between human and biotic systems at a variety of natural, geographic, and political scales. Understanding the dynamics of land surface change requires an increased understanding of the complex nature of human-environmental systems and will require a suite of scientific tools that include traditional geographic data and analysis methods, such as remote sensing and geographic information systems (GIS), as well as innovative approaches to understanding the dynamics of complex systems. One such approach that has gained much recent scientific attention is the landscape indicator, or landscape assessment, approach, which has been developed with the emergence of the science of landscape ecology.

Fact Sheet↗
USGS2023

Low-complexity floodplain inundation model performs well for ecological and management applications in a large river ecosystem

Flooding is a dominant physical process that drives the form and function of river-floodplain ecosystems. Efficiently characterizing flooding dynamics can be challenging, especially over geographically broad areas or at spatial and temporal scales relevant for ecosystem management activities. Here, we empirically evaluated a low-complexity geospatial model of floodplain inundation in six study segments of the Upper Mississippi River System (UMRS) by pairing spatially extensive, temporally limited and spatially limited, temporally extensive sampling designs. We found little evidence of systematic bias in model performance although discrepancies between model predictions and empirical data did occur locally. Assessments of model predictions revealed low segment-wide discrepancies of wetted extent under contrasting flow conditions and agreement for inundation event detection and duration. Model performance for predicting event frequency and duration was similar among sites expected to exhibit contrasting patterns of hydrologic connectivity with the main channel. Our results suggest that low-complexity models can efficiently characterize a critical physical process across geographically broad, complex river-floodplain ecosystems. Such tools have the potential for advancing scientific understanding of landscape-scale ecological patterns and for prioritizing management actions in large, complex river-floodplain ecosystems like the UMRS.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2022

Potential cheatgrass abundance within lightly invaded areas of the Great Basin

Context Anticipating where an invasive species could become abundant can help guide prevention and control efforts aimed at reducing invasion impacts. Information on potential abundance can be combined with information on the current status of an invasion to guide management towards currently uninvaded locations where the threat of invasion is high. Objectives We aimed to support management by developing predictive maps of potential cover for cheatgrass ( Bromus tectorum ), a problematic invader that can transform plant communities. We integrated our predictions of potential abundance with mapped estimates of current cover to quantify invasion potential within lightly invaded areas. Methods We used quantile regression to model cheatgrass abundance as a function of climate, weather, and disturbance, treating outputs as low to high invasion scenarios. We developed a species-specific set of covariates and validated model performance using spatially and temporally independent data. Results Potential cheatgrass abundance was higher in areas that had burned, at low elevations, and when fall germination conditions were more favorable. Our results highlight the extensive areas across the Great Basin where cheatgrass abundance could increase to levels that can alter fire behavior and cause other ecological impacts. Conclusions We predict potential cheatgrass abundance to quantify relative invasion risk. Our model results provide high and low scenarios of cheatgrass abundance to guide resource allocation and planning efforts across shrubland ecosystems of the Great Basin that remain relatively uninvaded. Combining information on an invasive species’ current and potential abundance can yield spatial predictions to guide resource allocation and management action.

California, Idaho, Nevada, Oregon, Utah↗
USGS2005

Hydrologic changes in urban streams and their ecological significance

Urban development modifies the production and delivery of runoff to streams and the resulting rate, volume, and timing of streamflow. Given that streamflow demonstrably influences the structure and composition of lotic communities, we have identified four hydrologic changes resulting from urban development that are potentially significant to stream ecosystems: increased frequency of high flows, redistribution of water from base flow to storm flow, increased daily variation in streamflow, and reduction in low flow. Previous investigations of streamflow patterns and biological assemblages provide a scale of ecological significance for each type of streamflow pattern. The scales establish the magnitude of changes in streamflow patterns that could be expected to produce biological responses in streams. Long-term streamflow records from eight streams in urbanizing areas of the United States and five additional reference streams, where land use has been relatively stable, were analyzed to assess if streamflow patterns were modified by urban development to an extent that a biological response could be expected and whether climate patterns could account for equivalent hydrologic variation in the reference streams. Changes in each type of streamflow pattern were evident in some but not all of the urban streams and were nearly absent in the reference streams. Given these results, hydrologic changes are likely significant to urban stream ecosystems, but the significance depends on the stream's physiographic context and spatial and temporal patterns of urban development. In urban streams with substantially altered hydrology, short-term goals for urban stream rehabilitation may be limited because of the difficulty and expense of restoring hydrologic processes in an urban landscape. The ecological benefits of improving physical habitat and water quality may be tempered by persistent effects of altered streamflow. In the end, the hydrologic effects of urban development must be addressed for restoration of urban streams. ?? 2005 by the American Fisheries Society.

American Fisheries Society Symposium↗
USGS2018

An objective road risk assessment method for multiple species: ranking 166 reptiles and amphibians in California

Context Transportation and wildlife agencies may consider the need for barrier structures and safe wildlife road-crossings to maintain the long-term viability of wildlife populations. In order to prioritize these efforts, it is important to identify species that are most at risk of extirpation from road-related impacts. Purpose Our goal was to identify reptiles and amphibians in California most susceptible to road mortality and fragmentation. With over 160 species and a lack of species-specific research data, we developed an objective risk assessment method based upon road ecology science. Methods Risk scoring was based upon a suite of life history and space-use characteristics associated with negative road effects applied in a hierarchical manner from individuals to species. We evaluated risk to both aquatic and terrestrial connectivity and calculated buffer distances to encompass 95% of population-level movements. We ranked species into five relative categories of road-related risk (very-high to very-low) based upon 20% increments of all species scores. Results All chelonids, 72% of snakes, 50% of anurans, 18% of lizards and 17% of salamander species in California were ranked at high or very-high risk from negative road impacts. Results were largely consistent with local and global scientific literature in identifying high risk species and groups. Conclusions This comparative risk assessment method provides a science-based framework to identify species most susceptible to negative road impacts. The results can inform regional-scale road mitigation planning and prioritization efforts and threat assessments for special-status species. We believe this approach is applicable to numerous landscapes and taxonomic groups.

California↗
USGS2023

Understanding ecological response to physical characteristics in side channels of a large floodplain-river ecosystem

Side channels in large floodplain rivers serve a variety of important ecological roles, particularly in reaches where habitat conditions have been degraded or diminished. We developed hypotheses regarding side channel ecological structure whereby we expected species richness of young-of-year fishes to generally be higher in shallower, more physically heterogeneous side channels with lower velocities, with differences based on reproductive guild. We also hypothesized species richness of adult fishes to be higher in side channels with greater heterogeneity that could support diverse foraging resources and provide refugia during extreme flow conditions. To test these hypotheses, we used a 28-year fish community dataset from the Upper Mississippi and Illinois Rivers. Across six study reaches, we assessed metrics of side channel physical size, heterogeneity, and connectivity that were hypothesized to explain variance of fish community response, while accounting for site-level factors across 52 side channels using multilevel models. We then used these side channel-level characteristics in a K-means cluster analysis to classify 1126 side channels across 32 reaches of the river system. Our results indicated that the relative explanatory contributions of physical metrics varied by response variable, providing varying evidence in support of our hypotheses, and indicating that different forms of heterogeneity matter in different ways. Side channel-level factors were more explanatory of fish community responses in side channels of upstream reaches compared to downstream reaches and percent wet forest was the most explanatory side channel-level factor of fish community responses across all models. Our classification of side channels indicated strong spatial contrasts in the abundance and diversity of side channels across reaches. Scaling up to understand how the diversity and abundance of different types of side channels contributes to landscape-scale ecological functions and processes would be useful for establishing targets for reach-scale physical heterogeneity.

Upper Mississippi River and Illinois River↗
USGS2023

Forecasting natural regeneration of sagebrush after wildfires using population models and spatial matching

Context Addressing ecosystem degradation in the Anthropocene will require ecological restoration across large spatial extents. Identifying areas where natural regeneration will occur without direct resource investment will improve scalability of restoration actions. Objectives An ecoregion in need of large scale restoration is the Great Basin of the Western US, where increasingly large and frequent wildfires threaten ecosystem integrity and its foundational shrub species. We develop a framework to forecast where post-wildfire regeneration of sagebrush cover ( Artemisia spp.) is likely to occur within the burnt areas across the region (> 900,000 km 2 ). Methods First, we parameterized population models using Landsat satellite-derived time series of sagebrush cover. Second, we evaluated the out-of-sample performance by predicting natural regeneration in wildfires not used for model training. This model assessment reproduces a management-oriented scenario: making restoration decisions shortly after wildfires with minimal local information. Third, we asked how accounting for increasingly fine-scale spatial heterogeneity could improve model forecasting accuracy. Results Regional-level models revealed that sagebrush post-fire recovery is slow, estimating > 80-year time horizon to reach an average cover at equilibrium of 16.6% (CI95% 9–25). Accounting for wildfire and within-wildfire spatial heterogeneity improved out-of-sample forecasts, resulting in a mean absolute error of 3.5 ± 4.3% cover, compared to the regional model with an error of 7.2 ± 5.1% cover. Conclusions We demonstrate that combining population models and non-parametric spatial matching provides a flexible framework for forecasting plant population recovery. Models for population recovery applied to Landsat-derived time series will assist restoration decision-making, including identifying priority targets for restoration.

Great Basin↗
USGS2020

Comment on 'Kidron (2018): Biocrust research: A critical view on eight common hydrological‐related paradigms and dubious theses. Ecohydrology, e2061'

Kidron (2018) uses a straw man argument in an attempt to debunk eight putative hydrological‐related paradigms he believes to be “common among hydrologists, ecologists, or microbiologists that investigate biocrusts.” These paradigms relate to the roles of physical crusts and vascular plants in biocrust development, the major drivers (climate, porosity, hydrophobicity, and exopolysaccharides) of hydrology (infiltration and runoff), and the effect of mosses on hydrology and therefore vascular plants. We see two major problems with his arguments. First, they assume that the paradigms in question are generally accepted by biocrust researchers. Second, they are based on Kidron's (2018) world view of biocrusts, which has largely been informed by his own studies from a single, distinctly unique area of sand dunes at the Nizzana Research Site in the Negev Desert, Israel. This narrow focus and the selective use of published material disqualify his arguments. Our collective experience, based on more than 250 person years of biocrust research, and more than 700 scientific publications on biocrusts from all continents including Antarctica, indicates that, far from the straw man arguments proposed by Kidron (2018), there is no evidence to support the existence of a unifying theory that captures the global effects of biocrusts on hydrology. Our collective works demonstrate that, contrary to claims by Kidron (2018), the hydrological effects of biocrusts are strongly nuanced, varying with, but not limited to, differences in ecological context, landscape position, site condition, crust type and composition, climatic zone, soil texture and porosity, surface morphology, and spatial scale (reviewed in Weber, Büdel, & Belnap, 2016). Below, we critically analyse each of Kidron's (2018) paradigms, providing rigorous empirical evidence to show that none represent commonly held views among the biocrust research community.

Ecohydrology↗
USGS2020

From forests to fish: Mercury in mountain lake food webs influenced by factors at multiple scales

Mountain lakes, while seemingly pristine, have been subjected to historical fish stocking practices and exposure to atmospherically deposited contaminants like mercury. Mercury bioaccumulation in these ecosystems varies widely due to strong environmental gradients, and there are complex, hierarchical factors that affect mercury transport and loading, methylmercury production, and food web biomagnification. We sought to assess how representative variables associated with watershed, lake, and food web‐scale processes—specifically, catchment tree cover, lake benthic primary production, and fish diet, respectively—are associated with mercury concentrations in mountain lake fish. Mean fish mercury concentrations varied threefold between lakes, with nearshore tree cover and fish diet accounting for the most variance in fish mercury. Tree cover was likely positively correlated to fish Hg due to its contributions to local deposition and its effect on lake biogeochemistry. Fish with benthic diets tended to have higher mercury concentrations, illustrating that food web processes are an important consideration when investigating drivers of contaminant bioaccumulation. Our results suggest that both landscape and ecological factors are determinants of fish mercury bioaccumulation, and thus variables at multiple scales should be considered when managing mountain lake food webs for mercury exposure risk.

Washington↗