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At least 1,441 records · Page 80Linked to original sources
USGS2011

Ecoregional-scale monitoring within conservation areas, in a rapidly changing climate

Long-term monitoring of ecological systems can prove invaluable for resource management and conservation. Such monitoring can: (1) detect instances of long-term trend (either improvement or deterioration) in monitored resources, thus providing an early-warning indication of system change to resource managers; (2) inform management decisions and help assess the effects of management actions, as well as anthropogenic and natural disturbances; and (3) provide the grist for supplemental research on mechanisms of system dynamics and cause-effect relationships (Fancy et al., 2009). Such monitoring additionally provides a snapshot of the status of monitored resources during each sampling cycle, and helps assess whether legal standards and regulations are being met. Until the last 1-2 decades, tracking and understanding changes in condition of natural resources across broad spatial extents have been infrequently attempted. Several factors, however, are facilitating the achievement of such broad-scale investigation and monitoring. These include increasing awareness of the importance of landscape context, greater prevalence of regional and global environmental stressors, and the rise of landscape-scale programs designed to manage and monitor biological systems. Such programs include the US Forest Service's Forest Inventory and Analysis (FIA) Program (Moser et al., 2008), Canada's National Forest Inventory, the 3Q Programme for monitoring agricultural landscapes of Norway (Dramstad et al., 2002), and the emerging (US) Landscape Conservation Cooperatives (USDOI Secretarial Order 3289, 2009; Anonymous, 2011). This Special Section explores the underlying design considerations, as well as many pragmatic aspects associated with program implementation and interpretation of results from broad-scale monitoring systems, particularly within the constraints of high-latitude contexts (e.g., low road density, short field season, dramatic fluctuations in temperature). Although Alaska is the focus of most papers in this Special Section, we posit that many of the issues that characterize the remote, relatively undisturbed ecosystems of high northern latitudes are widespread and thus applicable to natural-resource management and conservation across northern portions of the Holarctic ecozone and indeed anywhere broad-scale monitoring is contemplated.

Biological Conservation↗
USGS2011

Quantifying home range habitat requirements for bobcats (Lynx rufus) in Vermont, USA

We demonstrate how home range and habitat use analysis can inform landscape-scale conservation planning for the bobcat, Lynx rufus , in Vermont USA. From 2005 to 2008, we outfitted fourteen bobcats with GPS collars that collected spatially explicit locations from individuals every 4 h for 3–4 months. Kernel home range techniques were used to estimate home range size and boundaries, and to quantify the utilization distribution (UD), which is a spatially explicit, topographic mapping of how different areas within the home range are used. We then used GIS methods to quantify both biotic (e.g. habitat types, stream density) and abiotic (e.g. slope) resources within each bobcat’s home range. Across bobcats, upper 20th UD percentiles (core areas) had 18% less agriculture, 42% less development, 26% more bobcat habitat (shrub, deciduous, coniferous forest, and wetland cover types), and 33% lower road density than lower UD percentiles (UD valleys). For each bobcat, we used Akaike’s Information Criterion (AIC) to evaluate and compare 24 alternative Resource Utilization Functions (hypotheses) that could explain the topology of the individual’s UD. A model-averaged population-level Resource Utilization Function suggested positive responses to shrub, deciduous, coniferous forest, and wetland cover types within 1 km of a location, and negative responses to roads and mixed forest cover types within 1 km of a location. Applying this model-averaged function to each pixel in the study area revealed habitat suitability for bobcats across the entire study area, with suitability scores ranging between −1.69 and 1.44, where higher values were assumed to represent higher quality habitat. The southern Champlain Valley, which contained ample wetland and shrub habitat, was a concentrated area of highly suitable habitat, while areas at higher elevation areas were less suitable. Female bobcat home ranges, on average, had an average habitat suitability score of near 0, indicating that home ranges consisted of both beneficial and detrimental habitat types. We discuss the application of habitat suitability mapping and home range requirements for bobcat conservation and landscape scale management.

Vermont↗
USGS2014

Prioritizing bird conservation actions in the Prairie Hardwood transition of the Midwestern United States

Large-scale planning for the conservation of species is often hindered by a poor understanding of factors limiting populations. In regions with declining wildlife populations, it is critical that objective metrics of conservation success are developed to ensure that conservation actions achieve desired results. Using spatially explicit estimates of bird abundance, we evaluated several management alternatives for conserving bird populations in the Prairie Hardwood Transition of the United States. We designed landscapes conserving species at 50% of their current predicted abundance as well as landscapes attempting to achieve species population targets (which often required the doubling of current abundance). Conserving species at reduced (half of current) abundance led to few conservation conflicts. However, because of extensive modification of the landscape to suit human use, strategies for achieving regional population targets for forest bird species would be difficult under even ideal circumstances, and even more so if maintenance of grassland bird populations is also desired. Our results indicated that large-scale restoration of agricultural lands to native grassland and forest habitats may be the most productive conservation action for increasing bird population sizes but the level of landscape transition required to approach target bird population sizes may be societally unacceptable.

Illinois;Indiana;Iowa;Michigan;Minnesota;Wisconsin↗
USGS2020

Using remote sensing products to predict recovery of vegetation across space and time following energy development

Using localized studies to understand how ecosystems recover can create uncertainty in recovery predictions across landscapes. Large archives of remote sensing data offer opportunities for quantifying the spatial and temporal factors influencing recovery at broad scales and predicting recovery. For example, energy production is a widespread and expanding land use among many semi-arid ecosystems of the Western United States dominated by sagebrush ( Artemisia spp.), a keystone species providing a variety of ecological services. With remotely-sensed (Landsat) estimates of vegetation cover collected every 2–5 years from southwestern Wyoming, USA, over nearly three decades (1985–2015), we modeled changes in sagebrush cover on 375 former oil and gas well pads in response to weather and site-level conditions. We then used modeled relationships to predict recovery time across the landscape as an indicator of resilience for vegetation after well pad disturbances, where faster recovery indicates a greater capacity to recover when similarly disturbed. We found the rate of change in sagebrush cover generally increased with moisture and temperature, particularly at higher elevations. Rate of change in sagebrush cover also increased and decreased with greater percent sand and larger well pads, respectively. We predicted 21% of the landscape would recover to pre-disturbance conditions within 60 years, whereas other areas may require >100 years for recovery. These predictions and maps could inform future restoration efforts as they reflect resilience. This approach also is applicable to other disturbance types (e.g., fires and vegetation removal treatments) across landscapes, which can further improve conservation efforts by characterizing past conditions and monitoring trends in subsequent years.

Wyoming↗
USGS2010

Modeling the impacts of hunting on the population dynamics of red howler monkeys ( Alouatta seniculus )

Overexploitation of wildlife populations occurs across the humid tropics and is a significant threat to the long-term survival of large-bodied primates. To investigate the impacts of hunting on primates and ways to mitigate them, we developed a spatially explicit, individual-based model for a landscape that included hunted and un-hunted areas. We used the large-bodied neotropical red howler monkey ( Alouatta seniculus ) as our case study species because its life history characteristics make it vulnerable to hunting. We modeled the influence of different rates of harvest and proportions of landscape dedicated to un-hunted reserves on population persistence, population size, social dynamics, and hunting yields of red howler monkeys. In most scenarios, the un-hunted populations maintained a constant density regardless of hunting pressure elsewhere, and allowed the overall population to persist. Therefore, the overall population was quite resilient to extinction; only in scenarios without any un-hunted areas did the population go extinct. However, the total and hunted populations did experience large declines over 100 years under moderate and high hunting pressure. In addition, when reserve area decreased, population losses and losses per unit area increased disproportionately. Furthermore, hunting disrupted the social structure of troops. The number of male turnovers and infanticides increased in hunted populations, while birth rates decreased and exacerbated population losses due to hunting. Finally, our results indicated that when more than 55% of the landscape was harvested at high (30%) rates, hunting yields, as measured by kilograms of biomass, were less than those obtained from moderate harvest rates. Additionally, hunting yields, expressed as the number of individuals hunted/year/km 2 , increased in proximity to un-hunted areas, and suggested that dispersal from un-hunted areas may have contributed to hunting sustainability. These results indicate that un-hunted areas serve to enhance hunting yields, population size, and population persistence in hunted landscapes. Therefore, spatial regulation of hunting via a reserve system may be an effective management strategy for sustainable hunting, and we recommend it because it may also be more feasible to implement than harvest quotas or restrictions on season length.

Guárico↗
USGS2024

Visualizing wading bird optimal foraging decisions with aggregation behaviors using individual-based modeling

Foragers on patchy landscapes must efficiently balance time between searching for and consuming resources to meet their daily energetic requirements. Spatial aggregation foraging behaviors may improve foraging efficiency by sharing information on locations of resource hotspots. Wading birds are an example of patch foragers that form colonial aggregations during the breeding season to obtain sufficient prey energy to sustain themselves and their offspring each day. Here, we describe a spatially-explicit simulation model of wading bird optimal foraging that represents information sharing through visual cues. The overall purpose of the model is to describe how wading bird daily foraging and reproductive success may change with alternative water control management practices that determine spatial availability of prey for wading birds on the landscape, throughout their breeding seasons. Wading birds are simulated as individuals that operate independently, sampling and selecting among patches based on a prey density tolerance threshold, but also use information from other birds to inform their selection decisions. Foraging success is evaluated against the fundamental objectives of (a) fulfilling daily energetic demands and (b) minimizing predation exposure, by tracking individual daily energetic intake and time spent foraging. In this way, the model approximates population level dynamics of wading bird aggregations that emerge through collective decision making of birds simulated at the lower individual level. Key results of this study suggest that aggregation behaviors may improve population-level foraging success rates, and the optimal settling threshold may modulate when resources become more scarce or difficult to find. Thus, the model addresses ecological theory on the advantages of foraging in groups versus independently. This technique is appropriate for evaluating wading bird populations that forage on patchy landscapes, such as seasonally-pulsed wetlands, wherever sufficient information is available to describe (1) foraging behavior (e.g., feeding rate, flight speeds, patch selection decisions), (2) key landscape characteristics, (3) spatial distributions of prey densities among foraging patches, and (4) changes in prey densities through time. The model was designed to predict qualitative, testable spatial patterns of wading bird foraging movements which can be compared with empirical observations and empirically-derived habitat suitability models. These techniques can also be applied to other bird species, such as shorebirds, or more generally to any species that transits between discrete foraging patches.

Ecological Modelling↗
USGS2009

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

The rapid growth of housing in and near the wildland–urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60,000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions.

Wisconsin↗
USGS2019

Space use, forays, and habitat selection in California Spotted Owls (Strix occidentalis occidentalis): New insights from high resolution GPS tracking

Our current understanding of the relationship between imperiled species and forest management can benefit from global positioning system (GPS) technologies. Fauna of lateseral stage forests have historically been difficult to detect and track in rugged terrain, leading to challenges in movement characterization and conservation. We investigated movement of California Spotted Owls ( Strix occidentalis occidentalis ) using automated GPS loggers affixed to 15 owls in the northern Sierra Nevada, California. We used >17,000 locations from individual owls to characterize homerange size, movement distances, and roosting and foraging habitat selection at four spatio-temporal scales (landscape, home range, foray, nightly) during the breeding season (April–August). Additionally, we assessed owl use of Protected Activity Centers (PACs), which are designated by the U.S.D.A. Forest Service to protect nesting and roosting habitat. Our results corroborated some previous findings about habitat requirements of California Spotted Owls, while also revealing new nuances in space use and habitat selection. Roosting and foraging owls selected stands with high canopy cover and large trees at multiple spatio-temporal scales, with foraging owls showing strongest selection at the largest (landscape) scale investigated. Although owls selected for PACs while foraging and roosting, PACs protected less than one quarter of foraging space use (volume of use) and fewer than half of observed roosts during the breeding season. Female owl home ranges were double the size of male home ranges, and distances travelled from the nest by females were 1.3 times greater than distances travelled by males, with non-breeding females travelling farthest and visiting up to six PACs during a single breeding season. Foraying behavior of this sort has not been documented previously in California Spotted Owls. Our findings support protection of later seral stage forest attributes for roosting and foraging California Spotted Owls. Given their selection for later seral forest attributes, strongest evidence of foraging habitat selection at the landscape scale, long distances travelled by owls and limited habitat protection afforded by PACs, habitat connectivity across the landscape is likely an important component for owl conservation, and distribution of current protected areas may be inadequate for this wide-ranging species.

California↗
USGS2015

Floodplain complexity and surface metrics: influences of scale and geomorphology

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Geomorphology↗
USGS2017

Excursions in fluvial (dis)continuity

Lurking below the twin concepts of connectivity and disconnectivity are their first, and in some ways, richer cousins: continuity and discontinuity. In this paper we explore how continuity and discontinuity represent fundamental and complementary perspectives in fluvial geomorphology, and how these perspectives inform and underlie our conceptions of connectivity in landscapes and rivers. We examine the historical roots of continuum and discontinuum thinking, and how much of our understanding of geomorphology rests on contrasting views of continuity and discontinuity. By continuum thinking we refer to a conception of geomorphic processes as well as geomorphic features that are expressed along continuous gradients without abrupt changes, transitions, or thresholds. Balance of forces, graded streams, and hydraulic geometry are all examples of this perspective. The continuum view has played a prominent role in diverse disciplinary fields, including ecology, paleontology, and evolutionary biology, in large part because it allows us to treat complex phenomena as orderly progressions and invoke or assume equilibrium processes that introduce order and prediction into our sciences. In contrast the discontinuous view is a distinct though complementary conceptual framework that incorporates non-uniform, non-progressive, and non-equilibrium thinking into understanding geomorphic processes and landscapes. We distinguish and discuss examples of three different ways in which discontinuous thinking can be expressed: 1) discontinuous spatial arrangements or singular events; 2) specific process domains generally associated with thresholds, either intrinsic or extrinsic; and 3) physical dynamics or changes in state, again often threshold-linked. In moving beyond the continuous perspective, a fertile set of ideas comes into focus: thresholds, non-equilibrium states, heterogeneity, catastrophe. The range of phenomena that is thereby opened up to scientific exploration similarly expands: punctuated episodes of cutting and filling, discretization of landscapes into hierarchies of structure and control, the work of extreme events. Orderly and progressive evolution towards a steady or ideal state is replaced by chaotic episodes of disturbance and recovery. Recent developments in the field of geomorphology suggest that we may be on the cusp of a new paradigm that recognizes that both continuous and discontinuous processes and mechanisms play a role in fluvial processes and landscape evolution with neither holding sway over the other and both needed to see rivers as they are.

Geomorphology↗
USGS2022

Tracking geomorphic changes after suburban development with a high density of green stormwater infrastructure practices in Montgomery County, Maryland

Stream morphology is affected by changes on the surrounding landscape. Understanding the effects of urbanization on stream morphology is a critical factor for land managers to maintain and improve vulnerable stream corridors in urbanizing landscapes. Stormwater practices are used in urban landscapes to manage runoff volumes and peak flows, potentially mitigating alterations to the flow regime that drive changes in channel morphology. However, there remains a paucity of long-term studies assessing watershed-scale relationships between urbanization and effects on stream morphology where green stormwater infrastructure exists in high densities. This paper evaluates the geomorphic changes across four headwater catchments in the Chesapeake Bay Watershed over the course of >10 yr and relates these changes to urban development. Annual cross-sectional surveys conducted from 2002 to 2019 in one forested catchment, one agricultural catchment, and two treatment catchments were used to understand the relationship between urbanization and changes in stream morphology. Six cross-sectional geomorphic metrics were calculated and compared with development timelines and high flow events. A channel evolution model was then used to understand the status of morphologic stability at sites within the study. Results suggest downstream environments in developing areas are more impacted during early phases of suburban construction. Channel change during construction could be a result of sediment and erosion control efforts' limitations on preventing and controlling overland sediment mobilization or of increased discharge causing widening and thus bank-derived sediment to move to the streambed. Results demonstrate that geomorphic metrics are highly variable within a small area and are not always accurate representations of broader landscape changes but rather of the more localized environment at a specific stream segment. Despite a high density of stormwater management facilities in urban catchments, substantial alterations to cross sections were found at multiple locations in each catchment including the controls.

Maryland↗
USGS2012

A remote sensing approach for estimating the location and rate of urban irrigation in semi-arid climates

Urban irrigation is an important component of the hydrologic cycle in many areas of the arid and semiarid western United States. This paper describes a new approach that uses readily available datasets to estimate the location and rate of urban irrigation. The approach provides a repeatable methodology at 1/3 km 2 resolution across a large urbanized area (500 km 2 ). For this study, Landsat Thematic Mapper satellite imagery, air photos, climatic records, and a land-use map were used to: (1) identify the fraction of irrigated landscaping in urban areas, and (2) estimate the monthly rate of irrigation being applied to those areas. The area chosen for this study was the San Fernando Valley in Southern California. Identifying irrigated areas involved the use of 29 satellite images, air photos, and a land-use map. The fraction of a pixel that consists of irrigated landscaping (F irr ) was estimated using a linear-mixture model of two land-cover endmembers (selected pixels within a satellite image that represent a targeted land-cover). The two endmembers were impervious and fully-irrigated landscaping. In the San Fernando Valley, we used airport buildings, runways, and pavement to represent the impervious endmember; golf courses and parks were used to represent the fully irrigated endmember. The average F irr using all 29 satellite scenes was 44%. F irr calculated from hand-digitizing using air photos for 13 randomly selected single-family-residential neighborhoods showed similar results (42%). Estimating the rate of irrigation required identification of a third endmember: areas that consisted of urban vegetation but were not irrigated. This "nonirrigated" endmember was used to compute a Normalized Difference Vegetation Index (NDVI) surplus, defined as the difference between the NDVI signals of the irrigated and nonirrigated endmembers. The NDVI signals from irrigated areas remains relatively constant throughout the year, whereas the signal from nonirrigated areas rises and falls seasonally due to precipitation. The areas between airport runways were chosen to represent the nonirrigated endmember. Water-delivery records from 65 spatially-distributed single-family neighborhoods, consisting of nearly 1800 homes, were correlated with the NDVI surplus. The results show a strong exponential correlation ( r 2 = 0.94). In the absence of water-delivery records, which can be difficult to obtain, a surrogate was identified: the landscape evapotranspiration rate (ET L ). ET L was used to scale NDVI surplus (which is dimensionless) to irrigation rates using an exponential scaling function. The monthly irrigation rates calculated from satellite and climatic data compared well with irrigation rates calculated from actual water-delivery data using a paired Wilcoxan signed-rank test ( p = 0.0063). Identification of F irr at the pixel scale, along with identification of the irrigation rate for a fully-irrigated pixel, allows for mapping of urban irrigation over large areas. Maps showing the location and rate of monthly irrigation for the San Fernando study area were computed for January and August 1997.

California↗
USGS2023

Regional variability in peatland burning at mid-to high-latitudes during the Holocene

Northern peatlands store globally-important amounts of carbon in the form of partly decomposed plant detritus. Drying associated with climate and land-use change may lead to increased fire frequency and severity in peatlands and the rapid loss of carbon to the atmosphere. However, our understanding of the patterns and drivers of peatland burning on an appropriate decadal to millennial timescale relies heavily on individual site-based reconstructions. For the first time, we synthesise peatland macrocharcoal records from across North America, Europe, and Patagonia to reveal regional variation in peatland burning during the Holocene. We used an existing database of proximal sedimentary charcoal to represent regional burning trends in the wider landscape for each region. Long-term trends in peatland burning appear to be largely climate driven, with human activities likely having an increasing influence in the late Holocene. Warmer conditions during the Holocene Thermal Maximum (∼9–6 cal. ka BP) were associated with greater peatland burning in North America's Atlantic coast, southern Scandinavia and the Baltics, and Patagonia. Since the Little Ice Age, peatland burning has declined across North America and in some areas of Europe. This decline is mirrored by a decrease in wider landscape burning in some, but not all sub-regions, linked to fire-suppression policies, and landscape fragmentation caused by agricultural expansion. Peatlands demonstrate lower susceptibility to burning than the wider landscape in several instances, probably because of autogenic processes that maintain high levels of near-surface wetness even during drought. Nonetheless, widespread drying and degradation of peatlands, particularly in Europe, has likely increased their vulnerability to burning in recent centuries. Consequently, peatland restoration efforts are important to mitigate the risk of peatland fire under a changing climate. Finally, we make recommendations for future research to improve our understanding of the controls on peatland fires.

Quaternary Science Reviews↗
USGS2014

Modeling a historical mountain pine beetle outbreak using Landsat MSS and multiple lines of evidence

Mountain pine beetles are significant forest disturbance agents, capable of inducing widespread mortality in coniferous forests in western North America. Various remote sensing approaches have assessed the impacts of beetle outbreaks over the last two decades. However, few studies have addressed the impacts of historical mountain pine beetle outbreaks, including the 1970s event that impacted Glacier National Park. The lack of spatially explicit data on this disturbance represents both a major data gap and a critical research challenge in that wildfire has removed some of the evidence from the landscape. We utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We incorporate historical aerial and landscape photos, aerial detection survey data, a nine-year collection of satellite imagery and abiotic data. This study presents a remote sensing based framework to (1) relate measurements of canopy mortality from fine-scale aerial photography to coarse-scale multispectral imagery and (2) classify the severity of mountain pine beetle affected areas using a temporal sequence of Landsat data and other landscape variables. We sampled canopy mortality in 261 plots from aerial photos and found that insect effects on mortality were evident in changes to the Normalized Difference Vegetation Index (NDVI) over time. We tested multiple spectral indices and found that a combination of NDVI and the green band resulted in the strongest model. We report a two-step process where we utilize a generalized least squares model to account for the large-scale variability in the data and a binary regression tree to describe the small-scale variability. The final model had a root mean square error estimate of 9.8% canopy mortality, a mean absolute error of 7.6% and an R 2 of 0.82. The results demonstrate that a model of percent canopy mortality as a continuous variable can be developed to identify a gradient of mountain pine beetle severity on the landscape.

Montana↗
USGS2015

Pesticide concentrations in frog tissue and wetland habitats in alandscape dominated by agriculture

Habitat loss and exposure to pesticides are likely primary factors contributing to amphibian decline in agricultural landscapes. Conservation efforts have attempted to restore wetlands lost through landscape modifications to reduce contaminant loads in surface waters and providing quality habitat to wildlife. The benefits of this increased wetland area, perhaps especially for amphibians, may be negated if habitat quality is insufficient to support persistent populations. We examined the presence of pesticides and nutrients in water and sediment as indicators of habitat quality and assessed the bioaccumulation of pesticides in the tissue of two native amphibian species Pseudacris maculata (chorus frogs) and Lithobates pipiens (leopard frogs) at six wetlands (3 restored and 3 reference) in Iowa, USA. Restored wetlands are positioned on the landscape to receive subsurface tile drainage water while reference wetlands receive water from overland run-off and shallow groundwater sources. Concentrations of the pesticides frequently detected in water and sediment samples were not different between wetland types. The median concentration of atrazine in surface water was 0.2 μg/L. Reproductive abnormalities in leopard frogs have been observed in other studies at these concentrations. Nutrient concentrations were higher in the restored wetlands but lower than concentrations thought lethal to frogs. Complex mixtures of pesticides including up to 8 fungicides, some previously unreported in tissue, were detected with concentrations ranging from 0.08 to 1500 μg/kg wet weight. No significant differences in pesticide concentrations were observed between species, although concentrations tended to be higher in leopard frogs compared to chorus frogs, possibly because of differences in life histories. Our results provide information on habitat quality in restored wetlands that will assist state and federal agencies, landowners, and resource managers in identifying and implementing conservation and management actions for these and similar wetlands in agriculturally dominated landscapes.

Iowa↗
USGS2021

Environmental and anthropogenic drivers of contaminants in agricultural watersheds with implications for land management

If not managed properly, modern agricultural practices can alter surface and groundwater quality and drinking water resources resulting in potential negative effects on aquatic and terrestrial ecosystems. Exposure to agriculturally derived contaminant mixtures has the potential to alter habitat quality and negatively affect fish and other aquatic organisms. Implementation of conservation practices focused on improving water quality continues to increase particularly in agricultural landscapes throughout the United States. The goal of this study was to determine the consequences of land management actions on the primary drivers of contaminant mixtures in five agricultural watersheds in the Chesapeake Bay, the largest watershed of the Atlantic Seaboard in North America where fish health issues have been documented for two decades. Surface water was collected and analyzed for 301 organic contaminants to determine the benefits of implemented best management practices (BMPs) designed to reduce nutrients and sediment to streams in also reducing contaminants in surface waters. Of the contaminants measured, herbicides (atrazine, metolachlor), phytoestrogens (formononetin, genistein, equol), cholesterol and total estrogenicity (indicator of estrogenic response) were detected frequently enough to statistically compare to seasonal flow effects, landscape variables and BMP intensity. Contaminant concentrations were often positively correlated with seasonal stream flow, although the magnitude of this effect varied by contaminant across seasons and sites. Land-use and other less utilized landscape variables including biosolids, manure and pesticide application and percent phytoestrogen producing crops were inversely related with site-average contaminant concentrations. Increased BMP intensity was negatively related to contaminant concentrations indicating potential co-benefits of BMPs for contaminant reduction in the studied watersheds. The information gained from this study will help prioritize ecologically relevant contaminant mixtures for monitoring and contributes to understanding the benefits of BMPs on improving surface water quality to better manage living resources in agricultural landscapes inside and outside the Chesapeake Bay watershed.

Delaware, Maryland, New Jersey, New York, Pennsylv↗
USGS2023

Model-based assessment and mapping of total phosphorus enrichment in rivers with sparse reference data

Water nutrient management efforts are frequently coordinated across thousands of water bodies, leading to a need for spatially extensive information to facilitate decision making. Here we explore potential applications of a machine learning model of river low-flow total phosphorus (TP) concentrations to support landscape nutrient management. The model was trained, validated, and then applied for all rivers of Michigan, USA to identify potential drivers of nutrient variation, predict alteration in nutrient concentrations from minimally disturbed conditions, and explore reach specific sensitivity to riparian agricultural change. A boosted regression tree model of low-flow TP concentrations trained on natural and anthropogenic landscape predictors accounted for 53 % of variation in cross-validation data, had good accuracy, little bias, and plausible relationships between predictors and response. Percent riparian agricultural cover accounted for the greatest root mean square error reduction in the modeled response (33.2 %), followed by riparian soil permeability (12.9 %), watershed slope (9.6 %), and percent urban cover (9.6 %). An apparent non-linear relationship between TP concentrations and percent riparian agricultural cover suggested steep positive increases in stream TP concentrations between 10 and 30 % upstream riparian agricultural cover. Predicted minimally disturbed TP concentrations were spatially variable and ranged from 7.0 to 48.5 μg l −1 , with the highest concentrations in watersheds draining low-permeability lake plain soils. Comparison of minimally disturbed predictions to those from the early 2000s suggested that much of northern Michigan existed close to the reference condition, while lower Michigan streams were often substantially enriched. Our predicted values of minimally disturbed condition generally agree with previous studies but offer greater geographic specificity. Expanded application of machine learning modeling with landscape predictor data have great potential to inform large scale strategy development in landscapes with sparse reference data.

Michigan↗
USGS1998

Species-environment relationships and vegetation patterns: Effects of spatial scale and tree life-stage

Do relationships between species and environmental gradients strengthen or weaken with tree life-stage (i.e., small seedlings, large seedlings, saplings, and mature trees)? Strengthened relationships may lead to distinct forest type boundaries, or weakening connections could lead to gradual ecotones and heterogeneous forest landscapes. We quantified the changes in forest dominance (basal area of tree species by life-stage) and environmental factors (elevation, slope, aspect, intercepted photosynthetically active radiation (PAR), summer soil moisture, and soil depth and texture) across 14 forest ecotones (n = 584, 10 m x 10 m plots) in Rocky Mountain National Park, Colorado, U.S.A. Local, ecotone-specific species-environment relationships, based on multiple regression techniques, generally strengthened from the small seedling stage (multiple R2 ranged from 0.00 to 0.26) to the tree stage (multiple R2 ranged from 0.20 to 0.61). At the landscape scale, combined canonical correspondence analysis (CCA) among species and for all tree life-stages suggested that the seedlings of most species became established in lower-elevation, drier sites than where mature trees of the same species dominated. However, conflicting evidence showed that species-environment relationships may weaken with tree life-stage. Seedlings were only found in a subset of plots (habitats) occupied by mature trees of the same species. At the landscape scale, CCA results showed that species-environment relationships weakened somewhat from the small seedling stage (86.4% of the variance explained by the first two axes) to the tree stage (76.6% of variance explained). The basal area of tree species co-occurring with Pinus contorta Doug. ex. Loud declined more gradually than P. contorta basal area declined across ecotones, resulting in less-distinct forest type boundaries. We conclude that broad, gradual ecotones and heterogeneous forest landscapes are created and maintained by: (1) sporadic establishment of seedlings in sub-optimal habitats; (2) survivorship of saplings and mature trees in a wider range of environmental conditions than seedlings presently endure; and (3) the longevity of trees and persistence of tree species in a broad range of soils, climates, and disturbance regimes.

Plant Ecology↗