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At least 487 records · Page 27Linked to original sources
USGS2015

Defining conservation targets on a landscape-scale

Conservation planning, the process of deciding how to protect, conserve, enhance and(or) minimize loss of natural and cultural resources, is a fundamental process to achieve conservation success in a time of rapid environmental change. Conservation targets, the measurable expressions of desired resource conditions, are an important tool in biological planning to achieve effective outcomes. Conservation targets provide a focus for planning, design, conservation action, and collaborative monitoring of environmental trends to guide landscape-scale conservation to improve the quality and quantity of key ecological and cultural resources. It is essential to have an iterative and inclusive method to define conservation targets that is replicable and allows for the evaluation of the effectiveness of conservation targets over time. In this document, we describe a process that can be implemented to achieve landscape-scale conservation, which includes defining conservation targets. We also describe what has been accomplished to date (September 2015) through this process for the Peninsular Florida Landscape Conservation Cooperative (PFLCC).

Florida↗
USGS2016

Modeling the effects of land cover and use on landscape capability for urban ungulate populations

Expanding ungulate populations are causing concerns for wildlife professionals and residents in many urban areas worldwide. Nowhere is the phenomenon more apparent than in the eastern US, where urban white-tailed deer (Odocoileus virginianus) populations are increasing. Most habitat suitability models for deer have been developed in rural areas and across large (>1000 km2) spatial extents. Only recently have we begun to understand the factors that contribute to space use by deer over much smaller spatial extents. In this study, we explore the concepts, terminology, methodology and state-of-the-science in wildlife abundance modeling as applied to overabundant deer populations across heterogeneous urban landscapes. We used classified, high-resolution digital orthoimagery to extract landscape characteristics in several urban areas of upstate New York. In addition, we assessed deer abundance and distribution in 1-km2 blocks across each study area from either aerial surveys or ground-based distance sampling. We recorded the number of detections in each block and used binomial mixture models to explore important relationships between abundance and key landscape features. Finally, we cross-validated statistical models of abundance and compared covariate relationships across study sites. Study areas were characterized along a gradient of urbanization based on the proportions of impervious surfaces and natural vegetation which, based on the best-supported models, also distinguished blocks potentially occupied by deer. Models performed better at identifying occurrence of deer and worse at predicting abundance in cross-validation comparisons. We attribute poor predictive performance to differences in deer population trajectories over time. The proportion of impervious surfaces often yielded better predictions of abundance and occurrence than did the proportion of natural vegetation, which we attribute to a lack of certain land cover classes during cold and snowy winters. Merits and limitations of our approach to habitat suitability modeling are discussed in detail.

Book chapter↗
USGS2017

The Conservation Efforts Database: Improving our knowledge of landscape conservation actions

The Conservation Efforts Database (CED) is a secure, cloud-based tool that can be used to document and track conservation actions across landscapes. A recently released factsheet describes this tool ahead of the rollout of CED version 2.0. The CED was developed by the U.S. Fish and Wildlife Service, the USGS, and the Great Northern Landscape Conservation Cooperative to support the 2015 Endangered Species Act status review for greater sage-grouse. Currently, the CED accepts policy-level data, such as Land Use Plans, and treatment level data, such as conifer removals and post-fire recovery efforts, as custom spatial and non-spatial records. In addition to a species assessment tool, the CED can also be used to summarize the extent of restoration efforts within a specific area or to strategically site conservation actions based on the location of other implemented actions. The CED can be an important tool, along with post-conservation monitoring, for implementing landscape-scale adaptive management.

Report↗
USGS2017

Dynamic optimization of landscape connectivity embedding spatial-capture-recapture information

Maintaining landscape connectivity is increasingly important in wildlife conservation, especially for species experiencing the effects of habitat loss and fragmentation. We propose a novel approach to dynamically optimize landscape connectivity. Our approach is based on a mixed integer program formulation, embedding a spatial capture-recapture model that estimates the density, space usage, and landscape connectivity for a given species. Our method takes into account the fact that local animal density and connectivity change dynamically and non-linearly with different habitat protection plans. In order to scale up our encoding, we propose a sampling scheme via random partitioning of the search space using parity functions. We show that our method scales to realworld size problems and dramatically outperforms the solution quality of an expectation maximization approach and a sample average approximation approach.

Conference Paper↗
USGS2014

Making decisions in complex landscapes: Headwater stream management across multiple federal agencies

Headwater stream ecosystems are vulnerable to numerous threats associated with climate and land use change. In the northeastern US, many headwater stream species (e.g., brook trout and stream salamanders) are of special conservation concern and may be vulnerable to climate change influences, such as changes in stream temperature and streamflow. Federal land management agencies (e.g., US Fish and Wildlife Service, National Park Service, USDA Forest Service, Bureau of Land Management and Department of Defense) are required to adopt policies that respond to climate change and may have longer-term institutional support to enforce such policies compared to state, local, non-governmental, or private land managers. However, federal agencies largely make management decisions in regards to headwater stream ecosystems independently. This fragmentation of management resources and responsibilities across the landscape may significantly impede the efficiency and effectiveness of conservation actions, and higher degrees of collaboration may be required to achieve conservation goals. This project seeks to provide an example of cooperative landscape decision-making to address the conservation of headwater stream ecosystems. We identified shared and contrasting objectives of each federal agency and potential collaboration opportunities that may increase efficient and effective management of headwater stream ecosystems in two northeastern US watersheds. These workshops provided useful insights into the adaptive capacity of federal institutions to address threats to headwater stream ecosystems. Our ultimate goal is to provide a decision-making framework and analysis that addresses large-scale conservation threats across multiple stakeholders, as a demonstration of cooperative landscape conservation for aquatic ecosystems. Additionally, we aim to provide new scientific knowledge and a regional perspective to resource managers to help inform local management decisions.

Maine, New Hampshire, Virginia, West Virginia↗
USGS2008

Late Pleistocene through Holocene landscape evolution of the White River Badlands, South Dakota

Badlands are common arid and semiarid landscapes long recognized in slope development and erosion rate studies by preeminent geomorphologists including Gilbert, Davis, and Schumm. The trip described here will examine in detail Quaternarystrata and landscape evolution in arguably the most famous badlands, the White River Badlands of South Dakota, which were pivotal during development of vertebrate paleontology in North America. Geologists have collected fossils from the White River Group there nearly every field season since the mid-1800s; however, until recently, little work was reported on the extensively exposed Quaternary strata. The White River Badlands are also a proposed dust source for the widespread PeoriaLoess of the Central Great Plains. The research highlighted on this trip includes (1) luminescence and radiocarbon ages from late Pleistocene through Holocene eolian sand, (2) radiocarbon ages from Holocene eolian cliff-top deposits, (3) luminescenceages from late Pleistocene fluvial silts, (4) radiocarbon ages of late Holocene fluvial silts, and (5) cosmogenic ages on ventifacts from the adjoining upper prairie. These new studies will facilitate discussions, including (1) late Quaternary paleoenvironments,(2) late Quaternary fluvial incision rates and episodes, (3) up-wind sediment supply of late Quaternary nonglaciogenic loess, (4) landscape evolution spanning late Pleistocene tableland through late Holocene sod table development, and (5) modern erosion-pedimentation rates.

South Dakota↗
USGS2020

Using biodiversity metrics to guide conservation planning in altered tropical landscapes

Biodiversity metrics are frequently used to guide conservation planning because they can summarize biogeographical attributes of plant and animal communities quickly and at multiple scales. Attributes include habitat features of high conservation value, representativeness, and redundancy of biological communities. We conducted a rapid ecological assessment of resident avian species in the west-central mountainous region of Puerto Rico in 2015, a landscape dominated by coffee cultivation. We focused on this landscape because shade-grown and restored shade-grown coffee plantations offer an opportunity to complement protected habitat (e.g., reserves) to enhance species persistence. We used species richness, which tallies the number of unique species, and a quadratic entropy index of diversity, which incorporates interspecific taxonomic differentiation to evaluate species representativeness and redundancy across sun- and shade-grown coffee plantations and secondary forest. We surveyed 120 sites, calculating both metrics using species-specific occupancy probabilities estimated from community-level occupancy models. Species representativeness and redundancy were high as neither metric was able to discriminate among habitat types, possibly because plant communities were redundant, and the avian community was dominated by species adept at exploiting altered habitats. Similarly, we could not discriminate among avian communities modeling each biodiversity metric as a function of site-specific habitat covariates. Our findings and available knowledge on avian community demographics suggest that conservation strategies could couple protected habitat (e.g., reserves) and restored habitat (e.g., coffee plantations) to enhance species diversity and persistence across human-modified landscapes.

Caribbean Naturalist↗
USGS2005

Landscape characteristics of Rhizophora mangle forests and propagule deposition in coastal environments of Florida (USA)

Field dispersal studies are seldom conducted at regional scales even though reliable information on mid-range dispersal distance is essential for models of colonization. The purpose of this study was to examine the potential distance of dispersal of Rhizophora mangle propagules by comparing deposition density with landscape characteristics of mangrove forests. Propagule density was estimated at various distances to mangrove sources (R. mangle) on beaches in southwestern Florida in both high-and low-energy environments, either facing open gulf waters vs. sheltered, respectively. Remote sensing and Geographic Information Systems were used to identify source forests and to determine their landscape characteristics (forest size and distance to deposition area) for the regression analyses. Our results indicated that increasing density of propagules stranded on beaches was related negatively to the distance of the deposition sites from the nearest stands of R. mangle and that deposition was greatly diminished 2 km or more from the source. Measures of fragmentation such as the area of the R. mangle forests were related to propagule deposition but only in low-energy environments. Our results suggest that geographic models involving the colonization of coastal mangrove systems should include dispersal dynamics at mid-range scales, i.e., for our purposes here, beyond the local scale of the forest and up to 5 km distant. Studies of mangrove propagule deposition at various spatial scales are key to understanding regeneration limitations in natural gaps and restoration areas. Therefore, our study of mid-range propagule dispersal has broad application to plant ecology, restoration, and modeling. ?? Springer 2005.

Landscape Ecology↗
USGS2005

Drainage ditches facilitate frog movements in a hostile landscape

Ditches are common in landscapes influenced by agricultural, forestry, and peat mining activities, and their value as corridors remains unassessed. Pond-breeding amphibians can encounter hostile environments when moving between breeding, summering, or hibernation sites, and are likely to benefit from the presence of ditches in the landscape. Within a system consisting of ditch networks in bogs mined for peat in eastern New Brunswick, Canada, I quantified the breeding, survival, and movements of green frogs (Rana clamitans melanota) in drainage ditches and also surveyed peat fields. Frogs rarely ventured on peat fields and most individuals frequented drainage ditches containing water, particularly in late summer. Though frogs did not breed in ditches, their survival rate in ditches was high (88%). Ditches did not hinder frog movements, as frogs moved independently of the current. Results indicate that drainage ditches containing water enable some movements between habitats isolated by peat mining, in contrast to peat surfaces, and suggest they function as amphibian movement corridors. Thus, such drainage ditches may mitigate the effects of peat extraction on amphibian populations. At the very least, these structures provide an alternative to hostile peat surfaces. This study highlights that small-scale corridors are potentially valuable in population dynamics. ?? Springer 2005.

Landscape Ecology↗
USGS2008

Importance of agricultural landscapes to nesting burrowing owls in the Northern Great Plains, USA

Anthropogenic habitat loss and fragmentation are the principle factors causing declines of grassland birds. Declines in burrowing owl (Athene cunicularia) populations have been extensive and have been linked to habitat loss, primarily the decline of black-tailed prairie dog (Cynomys ludovicianus) colonies. Development of habitat use models is a research priority and will aid conservation of owls inhabiting human-altered landscapes. From 2001 to 2004 we located 160 burrowing owl nests on prairie dog colonies on the Little Missouri National Grassland in North Dakota. We used multiple linear regression and Akaike's Information Criterion to estimate the relationship between cover type characteristics surrounding prairie dog colonies and (1) number of owl pairs per colony and (2) reproductive success. Models were developed for two spatial scales, within 600 m and 2,000 m radii of nests for cropland, crested wheatgrass (Agropyron cristatum), grassland, and prairie dog colonies. We also included number of patches as a metric of landscape fragmentation. Annually, fewer than 30% of prairie dog colonies were occupied by owls. None of the models at the 600 m scale explained variation in number of owl pairs or reproductive success. However, models at the 2,000 m scale did explain number of owl pairs and reproductive success. Models included cropland, crested wheatgrass, and prairie dog colonies. Grasslands were not included in any of the models and had low importance values, although percentage grassland surrounding colonies was high. Management that protects prairie dog colonies bordering cropland and crested wheatgrass should be implemented to maintain nesting habitat of burrowing owls. ?? 2008 Springer Science+Business Media B.V.

Landscape Ecology↗
USGS2009

Conservation of northern bobwhite on private lands in Georgia, USA under uncertainty about landscape-level habitat effects

Large-scale habitat enhancement programs for birds are becoming more widespread, however, most lack monitoring to resolve uncertainties and enhance program impact over time. Georgia?s Bobwhite Quail Initiative (BQI) is a competitive, proposal-based system that provides incentives to landowners to establish habitat for northern bobwhites (Colinus virginianus). Using data from monitoring conducted in the program?s first years (1999?2001), we developed alternative hierarchical models to predict bobwhite abundance in response to program habitat modifications on local and regional scales. Effects of habitat and habitat management on bobwhite population response varied among geographical scales, but high measurement variability rendered the specific nature of these scaled effects equivocal. Under some models, BQI had positive impact at both local farm scales (1, 9 km2), particularly when practice acres were clustered, whereas other credible models indicated that bird response did not depend on spatial arrangement of practices. Thus, uncertainty about landscape-level effects of management presents a challenge to program managers who must decide which proposals to accept. We demonstrate that optimal selection decisions can be made despite this uncertainty and that uncertainty can be reduced over time, with consequent improvement in management efficacy. However, such an adaptive approach to BQI program implementation would require the reestablishment of monitoring of bobwhite abundance, an effort for which funding was discontinued in 2002. For landscape-level conservation programs generally, our approach demonstrates the value in assessing multiple scales of impact of habitat modification programs, and it reveals the utility of addressing management uncertainty through multiple decision models and system monitoring.

Landscape Ecology↗
USGS2014

Estimating landscape resistance to dispersal

Dispersal is an inherently spatial process that can be affected by habitat conditions in sites encountered by dispersers. Understanding landscape resistance to dispersal is important in connectivity studies and reserve design, but most existing methods use resistance functions with cost parameters that are subjectively chosen by the investigator. We develop an analytic approach allowing for direct estimation of resistance parameters that folds least cost path methods typically used in simulation approaches into a formal statistical model of dispersal distributions. The core of our model is a frequency distribution of dispersal distances expressed as least cost distance rather than Euclidean distance, and which includes terms for feature-specific costs to dispersal and sex (or other traits) of the disperser. The model requires only origin and settlement locations for multiple individuals, such as might be obtained from mark–recapture studies or parentage analyses, and maps of the relevant habitat features. To evaluate whether the model can estimate parameters correctly, we fit our model to data from simulated dispersers in three kinds of landscapes (in which resistance of environmental variables was categorical, continuous with a patchy configuration, or continuous in a trend pattern). We found maximum likelihood estimators of resistance and individual trait parameters to be approximately unbiased with moderate sample sizes. We applied the model to a small grizzly bear dataset to demonstrate how this approach could be used when the primary interest is in the prediction of costs and found that estimates were consistent with expectations based on bear ecology. Our method has important practical applications for testing hypotheses about dispersal ecology and can be used to inform connectivity planning efforts, via the resistance estimates and confidence intervals, which can be used to create a data-driven resistance surface.

Landscape Ecology↗
USGS2020

Estimation of metademographic rates and landscape connectivity for a conservation-reliant anuran

Context Amphibian conservation efforts commonly assume populations are tied to waterbodies that collectively function as a metapopulation. This assumption is rarely evaluated, and there is a need to understand the degree of connectivity among patches to appropriately define, manage, and conserve biological populations. Objectives Our objectives were to quantify local persistence, colonization, and recruitment (metademographic rates) in relation to habitat attributes, evaluate the influence of the spatial arrangement of patches on landscape-scale population dynamics, and estimate the scale at which metapopulation dynamics are occurring for Oregon spotted frog ( Rana pretiosa ). Methods We collected R. pretiosa detection/non-detection data and habitat information from 93 sites spread throughout the species’ extant range in Oregon, USA, 2010–2018. We developed a spatial multistate dynamic occupancy model to analyze these data. Results The proportion of sites occupied by R. pretiosa was relatively stable despite regular turnover in site occupancy. Connectivity was greatest when the distance between sites was within 4.49–7.70 km, and the results suggested that populations within 1 km are at the appropriate spatial scale for effective population management. Rana pretiosa metademographic rates were strongly tied to water availability, vegetation characteristics, and beaver dams. Conclusions Our analysis provides critical information to identify the appropriate spatial scale for effective population management, estimates the distance at which populations are connected, and quantifies the effects of hypothesized threats to species at a landscape scale. We believe this model will prove to be useful to inform conservation and management strategies for multiple species.

Oregon↗
USGS2014

Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin

The distribution of permafrost is important to understand because of permafrost's influence on high-latitude ecosystem structure and functions. Moreover, near-surface (defined here as within 1 m of the Earth's surface) permafrost is particularly susceptible to a warming climate and is generally poorly mapped at regional scales. Subsequently, our objectives were to (1) develop the first-known binary and probabilistic maps of near-surface permafrost distributions at a 30 m resolution in the Alaskan Yukon River Basin by employing decision tree models, field measurements, and remotely sensed and mapped biophysical data; (2) evaluate the relative contribution of 39 biophysical variables used in the models; and (3) assess the landscape-scale factors controlling spatial variations in permafrost extent. Areas estimated to be present and absent of near-surface permafrost occupy approximately 46% and 45% of the Alaskan Yukon River Basin, respectively; masked areas (e.g., water and developed) account for the remaining 9% of the landscape. Strong predictors of near-surface permafrost include climatic indices, land cover, topography, and Landsat 7 Enhanced Thematic Mapper Plus spectral information. Our quantitative modeling approach enabled us to generate regional near-surface permafrost maps and provide essential information for resource managers and modelers to better understand near-surface permafrost distribution and how it relates to environmental factors and conditions.

Alaska↗
USGS2023

The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management

Understanding where, when, and why agroecosystems are changing requires quality information about ecosystems that span land tenure, ecological processes, and spatial scales. Over the past two decades, land management agencies and research groups have adopted a suite of standardized methods for monitoring rangelands, which have been implemented at over 85,000 monitoring locations globally. However, the ability to use these data to understand agroecosystem dynamics and change across scales and across land ownership has been limited because, until now, these data have not been available in a harmonized, accessible format for analyses, modeling, and decision-support tools. We present the Landscape Data Commons, a cyberinfrastructure platform that harmonizes and aggregates standardized agroecosystem data, enables linkages to models, and facilitates analysis and interpretation of data within decision-support tools. The Landscape Data Commons provides a community platform for users to contribute data and develop next-generation tools to support agroecosystem management through the 21st century.

Agricultural & Environmental Letters↗
USGS2017

Landscape genetic approaches to guide native plant restoration in the Mojave Desert

Restoring dryland ecosystems is a global challenge due to synergistic drivers of disturbance coupled with unpredictable environmental conditions. Dryland plant species have evolved complex life-history strategies to cope with fluctuating resources and climatic extremes. Although rarely quantified, local adaptation is likely widespread among these species and potentially influences restoration outcomes. The common practice of reintroducing propagules to restore dryland ecosystems, often across large spatial scales, compels evaluation of adaptive divergence within these species. Such evaluations are critical to understanding the consequences of large-scale manipulation of gene flow and to predicting success of restoration efforts. However, genetic information for species of interest can be difficult and expensive to obtain through traditional common garden experiments. Recent advances in landscape genetics offer marker-based approaches for identifying environmental drivers of adaptive genetic variability in non-model species, but tools are still needed to link these approaches with practical aspects of ecological restoration. Here, we combine spatially-explicit landscape genetics models with flexible visualization tools to demonstrate how cost-effective evaluations of adaptive genetic divergence can facilitate implementation of different seed sourcing strategies in ecological restoration. We apply these methods to Amplified Fragment Length Polymorphism (AFLP) markers genotyped in two Mojave Desert shrub species of high restoration importance: the long-lived, wind-pollinated gymnosperm Ephedra nevadensis , and the short-lived, insect-pollinated angiosperm Sphaeralcea ambigua . Mean annual temperature was identified as an important driver of adaptive genetic divergence for both species. Ephedra showed stronger adaptive divergence with respect to precipitation variability, while temperature variability and precipitation averages explained a larger fraction of adaptive divergence in Sphaeralcea . We describe multivariate statistical approaches for interpolating spatial patterns of adaptive divergence while accounting for potential bias due to neutral genetic structure. Through a spatial bootstrapping procedure, we also visualize patterns in the magnitude of model uncertainty. Finally, we introduce an interactive, distance-based mapping approach that explicitly links marker-based models of adaptive divergence with local or admixture seed sourcing strategies, promoting effective native plant restoration.

Mojave Desert↗
USGS2017

Historical and projected trends in landscape drivers affecting carbon dynamics in Alaska

Modern climate change in Alaska has resulted in widespread thawing of permafrost, increased fire activity, and extensive changes in vegetation characteristics that have significant consequences for socioecological systems. Despite observations of the heightened sensitivity of these systems to change, there has not been a comprehensive assessment of factors that drive ecosystem changes throughout Alaska. Here we present research that improves our understanding of the main drivers of the spatiotemporal patterns of carbon dynamics using in situ observations, remote sensing data, and an array of modeling techniques. In the last 60 yr, Alaska has seen a large increase in mean annual air temperature (1.7°C), with the greatest warming occurring over winter and spring. Warming trends are projected to continue throughout the 21st century and will likely result in landscape-level changes to ecosystem structure and function. Wetlands, mainly bogs and fens, which are currently estimated to cover 12.5% of the landscape, strongly influence exchange of methane between Alaska's ecosystems and the atmosphere and are expected to be affected by thawing permafrost and shifts in hydrology. Simulations suggest the current proportion of near-surface (within 1 m) and deep (within 5 m) permafrost extent will be reduced by 9–74% and 33–55% by the end of the 21st century, respectively. Since 2000, an average of 678 595 ha/yr was burned, more than twice the annual average during 1950–1999. The largest increase in fire activity is projected for the boreal forest, which could result in a reduction in late-successional spruce forest (8–44%) and an increase in early-successional deciduous forest (25–113%) that would mediate future fire activity and weaken permafrost stability in the region. Climate warming will also affect vegetation communities across arctic regions, where the coverage of deciduous forest could increase (223–620%), shrub tundra may increase (4–21%), and graminoid tundra might decrease (10–24%). This study sheds light on the sensitivity of Alaska's ecosystems to change that has the potential to significantly affect local and regional carbon balance, but more research is needed to improve estimates of land-surface and subsurface properties, and to better account for ecosystem dynamics affected by a myriad of biophysical factors and interactions.

Alaska↗
USGS2023

Combining local, landscape, and regional geographies to assess plant community vulnerability to invasion impact

Invasive species science has focused heavily on the invasive agent. However, management to protect native species also requires a proactive approach focused on resident communities and the features affecting their vulnerability to invasion impacts. Vulnerability is likely the result of factors acting across spatial scales, from local to regional, and it is the combined effects of these factors that will determine the magnitude of vulnerability. Here, we introduce an analytical framework that quantifies the scale-dependent impact of biological invasions on native richness from the shape of the native species–area relationship (SAR). We leveraged newly available, biogeographically extensive vegetation data from the U.S. National Ecological Observatory Network to assess plant community vulnerability to invasion impact as a function of factors acting across scales. We analyzed more than 1000 SARs widely distributed across the USA along environmental gradients and under different levels of non-native plant cover. Decreases in native richness were consistently associated with non-native species cover, but native richness was compromised only at relatively high levels of non-native cover. After accounting for variation in baseline ecosystem diversity, net primary productivity, and human modification, ecoregions that were colder and wetter were most vulnerable to losses of native plant species at the local level, while warmer and wetter areas were most susceptible at the landscape level. We also document how the combined effects of cross-scale factors result in a heterogeneous spatial pattern of vulnerability. This pattern could not be predicted by analyses at any single scale, underscoring the importance of accounting for factors acting across scales. Simultaneously assessing differences in vulnerability between distinct plant communities at local, landscape, and regional scales provided outputs that can be used to inform policy and management aimed at reducing vulnerability to the impact of plant invasions.

Ecological Applications↗