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At least 721 records · Page 40Linked to original sources

USGS2024

Response of corvid nest predators to thinning: implications for balancing short- and long-term goals for restoration of forest habitat

Forest thinning on public lands in the Pacific Northwest USA is an important tool for restoring diversity in forest stands with a legacy of simplified structure from decades of intensive management for timber production. A primary application of thinning in young (< 50-year-old) stands is to accelerate forest development to mitigate loss of late-seral habitat to decades of logging. However, thinning may have short-term negative effects for some species associated with mature forest that are expected to benefit from the practice over the long term. An increased risk of nest predation is a primary concern to managers charged with stewardship of habitat for the federally threatened Marbled Murrelet ( Brachyramphus marmoratus ), a species that nests in older forests. Predation by corvids is the greatest cause of nest failure for the Marbled Murrelet, and corvids are known to respond positively to forest disturbance, but quantitative information is lacking on the potential impacts of thinning on risk of nest predation. We investigated the response of two common corvid nest predators, Steller’s Jay ( Cyanocitta stelleri ) and Canada Jay ( Perisoreus canadensis ), to variation in thinning intensity in young forest (< 50 years old) using data from a long-term silviculture experiment. We used a Before-After-Control-Impact (BACI) design, linear mixed modeling, and occupancy modeling to quantify differences in corvid observation rates among varying levels of thinning intensity, and to assess changes in jay response over more than a decade following thinning. We found an increase in observation rates of both species in the heavily thinned treatment during the first 5 to 7 years following thinning, and some evidence of a short-term increase in Steller’s Jay activity in the thinning-with-gaps treatment. Neither jay species responded to the least intensive thinning treatment, which reduced average canopy cover by < 30%. By approximately a decade after thinning, observation rates of jays did not differ between unthinned controls and any of the thinning treatments. Incorporating our quantitative information into landscape-level planning can help managers balance short- and long-term conservation goals.

Oregon↗

USGS2021

Annual winter water-level drawdowns influence physical habitat structure and macrophytes in Massachusetts, USA, lakes

Annual wintertime water-level drawdowns are a common management strategy in recreational lakes; however, few studies have estimated their relative impact on lake littoral habitat among a set of typically co-occurring anthropogenic stressors including lakeshore development and herbicide application. Within 21 Massachusetts, USA lakes that represented a drawdown magnitude gradient (0.07–2.26 m), we assessed depth-specific littoral habitat (coarse wood, sediment, macrophytes) at two sites adjacent to forested or developed shorelines. Using generalized linear mixed models, we found coarse wood abundance and branching complexity was not correlated with drawdown magnitude but was primarily explained by the presence of lakeshore development. Drawdown magnitude was negatively correlated with silt cover and positively correlated with coarse substrate cover, with effects further varying by depth (0.5 m vs. 1 m). Macrophyte biomass and biovolume were negatively correlated with drawdown magnitude with effects also varying by depth for biomass. Macrophyte taxa with annual longevity strategies (e.g., Najas flexilis ) and amphibious growth forms increased in biomass proportions with drawdown magnitude. Distance-based redundancy analyses suggested macrophyte taxa composition was driven by drawdown magnitude, coarse substrate, alkalinity, water transparency, and herbicide use. These results suggest the importance of water quality and depth on macrophyte assemblage responses to winter drawdowns and the potential to develop drawdown-tolerant macrophyte assemblages. Altogether, understanding the unique impacts of anthropogenic stressors on littoral zone habitat across heterogeneous environmental lake conditions can help minimize impacts to lake ecological integrity while maintaining recreational value.

Massachusetts↗

USGS2026

Bird guilds exhibit varied responses to floodplain forest restoration in the Colorado River delta, Mexico

Grouping species into guilds can be useful to inform management decisions locally and at broader scales because guilds lack species-specificity. We investigated the response of five breeding bird guilds to riparian habitat restoration in the arid Colorado River delta, based on two decades of bird detections (2002–2021) at 230 bird count stations across 7 routes in actively revegetated (“restored”) sites, and 20 routes in non-actively revegetated (“control”) sites. We used guilds based on habitat associations. We also described changes in vegetation and explored their influence on bird species detections and guild dynamics. Riparian forest bird specialists responded positively to active revegetation, but this positive response was delayed and weaker in a river reach where restoration began later and featured less typical riparian vegetation. Birds associated with wetland habitat showed a positive response to restoration in the wettest reach, which had a baseline of high abundance of wetland birds in control sites and relatively abundant macrophyte cover. Conversely, the abundance of desert scrub bird specialists was highest in the driest and least vegetated restored reach. Generalists only exhibited decreased detections in the wettest restored reach. All this occurred while declines of riparian forest, wetland, desert scrub, and generalist bird species observed over a decade prior to restoration had stabilized in control sites. Detections of birds associated with agricultural fields increased in the study area, irrespective of restoration efforts. Our study demonstrates that the choice of bird guilds as ecological indicators can significantly influence the interpretation of restoration outcomes.

Arizona↗

USGS2014

Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data

LiDAR (Light Detection And Ranging) is an emerging remote-sensing tool that can provide fine-scale data describing vertical complexity of vegetation relevant to species that are responsive to forest structure. We used LiDAR data to estimate occupancy probability for the federally threatened marbled murrelet ( Brachyramphus marmoratus ) in the Oregon Coast Range of the United States. Our goal was to address the need identified in the Recovery Plan for a more accurate estimate of the availability of nesting habitat by developing occupancy maps based on refined measures of nest-strand structure. We used murrelet occupancy data collected by the Bureau of Land Management Coos Bay District, and canopy metrics calculated from discrete return airborne LiDAR data, to fit a logistic regression model predicting the probability of occupancy. Our final model for stand-level occupancy included distance to coast, and 5 LiDAR-derived variables describing canopy structure. With an area under the curve value (AUC) of 0.74, this model had acceptable discrimination and fair agreement (Cohen's κ = 0.24), especially considering that all sites in our sample were regarded by managers as potential habitat. The LiDAR model provided better discrimination between occupied and unoccupied sites than did a model using variables derived from Gradient Nearest Neighbor maps that were previously reported as important predictors of murrelet occupancy (AUC = 0.64, κ = 0.12). We also evaluated LiDAR metrics at 11 known murrelet nest sites. Two LiDAR-derived variables accurately discriminated nest sites from random sites (average AUC = 0.91). LiDAR provided a means of quantifying 3-dimensional canopy structure with variables that are ecologically relevant to murrelet nesting habitat, and have not been as accurately quantified by other mensuration methods.

Oregon↗

USGS2021

Predicted spatial distribution of the Eastern Spotted Skunk (Spilogale putorius) in Virginia using detection and non-detection records

The geographic distribution of a species is a fundamental component in understanding its ecology and is necessary for forming effective conservation plans. For rare and elusive species of conservation concern, accurate maps of predicted occurrence are particularly problematic and often highly subjective. Spilogale putorius (Eastern Spotted Skunk) populations have experienced large declines since the 1940s. Their elusive behavior and perceived rarity result in low detection probability when using conventional methods for sampling small mammals. Low detection probability often causes uncertainty as to where Eastern Spotted Skunks could be a management concern. We modeled the distribution of predicted occurrence of Eastern Spotted Skunks using verifiable occurrence and non-detection records obtained throughout Virginia from 2010 to 2020. Occurrence data consisted of trapping records reported to the Virginia Department of Wildlife Resources, incidental photo-verified reports of sightings and road-killed animals, and remote-camera detections. Non-detections were presumed at baited remote-camera locations following intense survey efforts. We fit predicted occurrence models using generalized linear modeling in an information-theoretic framework using the package ‘stats’ in Program R. Our results incidated a greater probability of presence from the Blue Ridge westward, increasing with slope steepness along northeastern- to southeastern-facing slopes and decreasing with slope steepness along southeastern- to southwestern-facing slopes. Emergent rock outcrops prominent along northeastern slopes offer ample protective rocky cover, whereas mixed Quercus spp. (oak), Kalmia latifolia (Mountain Laurel), and Rhododendron maximum (Rosebay Rhododendron) forest communities along southern-facing slopes provide suitable areas of cover, both of which are critical for spotted skunk survival and reproductive success. Our analysis provides insight into the relationships between landscape features and Eastern Spotted Skunk distributions across Virginia. Understanding these relationships is critical for the effective management and conservation of this vulnerable species.

Virginia↗

USGS2016

Spatial and temporal patterns of mercury concentrations in freshwater fish across the Western United States and Canada

Methylmercury contamination of fish is a global threat to environmental health. Mercury (Hg) monitoring programs are valuable for generating data that can be compiled for spatially broad syntheses to identify emergent ecosystem properties that influence fish Hg bioaccumulation. Fish total Hg (THg) concentrations were evaluated across the Western United States (US) and Canada, a region defined by extreme gradients in habitat structure and water management. A database was compiled with THg concentrations in 96,310 fish that comprised 206 species from 4262 locations, and used to evaluate the spatial distribution of fish THg across the region and effects of species, foraging guilds, habitats, and ecoregions. Areas of elevated THg exposure were identified by developing a relativized estimate of fish mercury concentrations at a watershed scale that accounted for the variability associated with fish species, fish size, and site effects. THg concentrations in fish muscle ranged between 0.001 and 28.4 (μg/g wet weight (ww)) with a geometric mean of 0.17. Overall, 30% of individual fish samples and 17% of means by location exceeded the 0.30 μg/g ww US EPA fish tissue criterion. Fish THg concentrations differed among habitat types, with riverine habitats consistently higher than lacustrine habitats. Importantly, fish THg concentrations were not correlated with sediment THg concentrations at a watershed scale, but were weakly correlated with sediment MeHg concentrations, suggesting that factors influencing MeHg production may be more important than inorganic Hg loading for determining fish MeHg exposure. There was large heterogeneity in fish THg concentrations across the landscape; THg concentrations were generally higher in semi-arid and arid regions such as the Great Basin and Desert Southwest, than in temperate forests. Results suggest that fish mercury exposure is widespread throughout Western US and Canada, and that species, habitat type, and region play an important role in influencing ecological risk of mercury in aquatic ecosystems.

Science of the Total Environment↗

USGS1999

A GIS modeling method applied to predicting forest songbird habitat

We have developed an approach for using “presence” data to construct habitat models. Presence data are those that indicate locations where the target organism is observed to occur, but that cannot be used to define locations where the organism does not occur. Surveys of highly mobile vertebrates often yield these kinds of data. Models developed through our approach yield predictions of the amount and the spatial distribution of good-quality habitat for the target species. This approach was developed primarily for use in a GIS context; thus, the models are spatially explicit and have the potential to be applied over large areas. Our method consists of two primary steps. In the first step, we identify an optimal range of values for each habitat variable to be used as a predictor in the model. To find these ranges, we employ the concept of maximizing the difference between cumulative distribution functions of (1) the values of a habitat variable at the observed presence locations of the target organism, and (2) the values of that habitat variable for all locations across a study area. In the second step, multivariate models of good habitat are constructed by combining these ranges of values, using the Boolean operators “and” and “or.” We use an approach similar to forward stepwise regression to select the best overall model. We demonstrate the use of this method by developing species-specific habitat models for nine forest-breeding songbirds (e.g., Cerulean Warbler, Scarlet Tanager, Wood Thrush) studied in southern Ohio. These models are based on species’ microhabitat preferences for moisture and vegetation characteristics that can be predicted primarily through the use of abiotic variables. We use slope, land surface morphology, land surface curvature, water flow accumulation downhill, and an integrated moisture index, in conjunction with a land-cover classification that identifies forest/nonforest, to develop these models. The performance of these models was evaluated with an independent data set. Our tests showed that the models performed better than random at identifying where the birds occurred and provided useful information for predicting the amount and spatial distribution of good habitat for the birds we studied. In addition, we generally found positive correlations between the amount of habitat, as predicted by the models, and the number of territories within a given area. This added component provides the possibility, ultimately, of being able to estimate population sizes. Our models represent useful tools for resource managers who are interested in assessing the impacts of alternative management plans that could alter or remove habitat for these birds.

Ecological Applications↗

USGS2024

Characterization of change in tree cover state and condition over the conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Forests↗

USGS2000

Fire frequency in the Interior Columbia River Basin: Building regional models from fire history data

Fire frequency affects vegetation composition and successional pathways; thus it is essential to understand fire regimes in order to manage natural resources at broad spatial scales. Fire history data are lacking for many regions for which fire management decisions are being made, so models are needed to estimate past fire frequency where local data are not yet available. We developed multiple regression models and tree-based (classification and regression tree, or CART) models to predict fire return intervals across the interior Columbia River basin at 1-km resolution, using georeferenced fire history, potential vegetation, cover type, and precipitation databases. The models combined semiqualitative methods and rigorous statistics. The fire history data are of uneven quality; some estimates are based on only one tree, and many are not cross-dated. Therefore, we weighted the models based on data quality and performed a sensitivity analysis of the effects on the models of estimation errors that are due to lack of cross-dating. The regression models predict fire return intervals from 1 to 375 yr for forested areas, whereas the tree-based models predict a range of 8 to 150 yr. Both types of models predict latitudinal and elevational gradients of increasing fire return intervals. Examination of regional-scale output suggests that, although the tree-based models explain more of the variation in the original data, the regression models are less likely to produce extrapolation errors. Thus, the models serve complementary purposes in elucidating the relationships among fire frequency, the predictor variables, and spatial scale. The models can provide local managers with quantitative information and provide data to initialize coarse-scale fire-effects models, although predictions for individual sites should be treated with caution because of the varying quality and uneven spatial coverage of the fire history database. The models also demonstrate the integration of qualitative and quantitative methods when requisite data for fully quantitative models are unavailable. They can be tested by comparing new, independent fire history reconstructions against their predictions and can be continually updated, as better fire history data become available.

California, Idaho, Montana, Nevada, Oregon, Utah, ↗

USGS2021

Increased growth rates of stream salamanders following forest harvesting

Timber harvesting can influence headwater streams by altering stream productivity, with cascading effects on the food web and predators within, including stream salamanders. Although studies have examined shifts in salamander occupancy or abundance following timber harvest, few examine sublethal effects such as changes in growth and demography. To examine the effect of upland harvesting on growth of the stream-associated Ouachita dusky salamander ( Desmognathus brimleyorum ), we used capture–mark–recapture over three years at three headwater streams embedded in intensely managed pine forests in west-central Arkansas. The pine stands surrounding two of the streams were harvested, with retention of a 14- and 21-m-wide forested stream buffer on each side of the stream, whereas the third stream was an unharvested control. At the two treatment sites, measurements of newly metamorphosed salamanders were on average 4.0 and 5.7 mm larger post-harvest compared with pre-harvest. We next assessed the influence of timber harvest on growth of post-metamorphic salamanders with a hierarchical von Bertalanffy growth model that included an effect of harvest on growth rate. Using measurements from 839 individual D . brimleyorum recaptured between 1 and 6 times (total captures, n = 1229), we found growth rates to be 40% higher post-harvest. Our study is among the first to examine responses of individual stream salamanders to timber harvesting, and we discuss mechanisms that may be responsible for observed shifts in growth. Our results suggest timber harvest that includes retention of a riparian buffer (i.e., streamside management zone) may have short-term positive effects on juvenile stream salamander growth, potentially offsetting negative sublethal effects associated with harvest.

Arkansas↗

USGS2008

A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance- based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods. ?? 2008 Springer Science+Business Media, LLC.

Environmental and Ecological Statistics↗

USGS2009

Distribution, density, and biomass of introduced small mammals in the southern mariana islands

Although it is generally accepted that introduced small mammals have detrimental effects on island ecology, our understanding of these effects is frequently limited by incomplete knowledge of small mammal distribution, density, and biomass. Such information is especially critical in the Mariana Islands, where small mammal density is inversely related to effectiveness of Brown Tree Snake (Boiga irregularis) control tools, such as mouse-attractant traps. We used mark-recapture sampling to determine introduced small mammal distribution, density, and biomass in the major habitats of Guam, Rota, Saipan, and Tinian, including grassland, Leucaena forest, and native limestone forest. Of the five species captured, Rattus diardii (sensu Robins et al. 2007) was most common across habitats and islands. In contrast, Mus musculus was rarely captured at forested sites, Suncus murinus was not captured on Rota, and R. exulans and R. norvegicus captures were uncommon. Modeling indicated that neophobia, island, sex, reproductive status, and rain amount influenced R. diardii capture probability, whereas time, island, and capture heterogeneity influenced S. murinus and M. musculus capture probability. Density and biomass were much greater on Rota, Saipan, and Tinian than on Guam, most likely a result of Brown Tree Snake predation pressure on the latter island. Rattus diardii and M. musculus density and biomass were greatest in grassland, whereas S. murinus density and biomass were greatest in Leucaena forest. The high densities documented during this research suggest that introduced small mammals (especially R. diardii) are impacting abundance and diversity of the native fauna and flora of the Mariana Islands. Further, Brown Tree Snake control and management tools that rely on mouse attractants will be less effective on Rota, Saipan, and Tinian than on Guam. If the Brown Tree Snake becomes established on these islands, high-density introduced small mammal populations will likely facilitate and support a high-density Brown Tree Snake population, even as native species are reduced or extirpated. ?? 2009 by University of Hawai'i Press All rights reserved.

Pacific Science↗

USGS2017

Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change

To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eBird citizen-science project to model probabilities of occurrence relative to land-use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species-specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long-distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from −0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.

Great Plains Landscape Conservation Cooperative↗

USGS2025

Near real-time indicators of burn severity in the western U.S. from active fire tracking

Background Timely information on wildfire burn severity is critical to assess and mitigate potential post-fire impacts on soils, vegetation, and hillslope stability. Tracking individual fire spread and intensity using satellite active fire data provides a pathway to near real-time (NRT) information. Here, we generated a large database ( n = 2177) of wildfire events in the western United States (U.S.) between 2012 and 2021 using active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Fire Events Data Suite (FEDS) algorithm to track large fire growth every 12 h. We integrated fire tracking data with final fire perimeters and burn severity data from the Monitoring Trends in Burn Severity (MTBS) program to evaluate the relationship between burn severity and fire behavior metrics derived from the fire tracking approach, including the rate of fire spread and average fire radiative power (FRP) of fire detections for each 12-h growth increment. Results When stratified by vegetation type, FRP and rate of spread metrics were positively correlated with classified burn severity for each 12-h growth increment, highlighting the potential to rapidly identify areas of high and low severity burning. In forests, integrated measures of FRP over the fire lifetime captured persistent flaming and smoldering that compensated for initial differences between AM (01:30) and PM (13:30) fire detections. Predictive modeling of these relationships based on multiple fire behavior indicators and vegetation type from the LANDFIRE program yielded an accuracy of 78% for the separation of unburned/low and moderate/high burn severity classes. Conclusions These results demonstrate the ability to capture within-fire differences in burn severity using NRT indicators from fire tracking to assist with emergency management and disaster preparedness for post-fire hazards, such as landslides, debris flows, or changes in stream flow and water quality. As VIIRS data are available within minutes of each satellite overpass in the U.S., rapid estimates of burn severity based on fire tracking can be made days or weeks before a large wildfire is fully contained.

western United States↗

USGS2011

Occupancy and abundance of wintering birds in a dynamic agricultural landscape

Assessing wildlife management action requires monitoring populations, and abundance often is the parameter monitored. Recent methodological advances have enabled estimation of mean abundance within a habitat using presence–absence or count data obtained via repeated visits to a sample of sites. These methods assume populations are closed and intuitively assume habitats within sites change little during a field season. However, many habitats are highly variable over short periods. We developed a variation of existing occupancy and abundance models that allows for extreme spatio‐temporal differences in habitat, and resulting changes in wildlife abundance, among sites and among visits to a site within a field season. We conducted our study in sugarcane habitat within the Everglades Agricultural Area southeast of Lake Okeechobee in south Florida. We counted wintering birds, primarily passerines, within 245 sites usually 5 times at each site during December 2006–March 2007. We estimated occupancy and mean abundance of birds in 6 vegetation states during the sugarcane harvest and allowed these parameters to vary temporally or spatially within a vegetation state. Occupancy and mean abundance of the common yellowthroat ( Geothlypis trichas ) was affected by structure of sugarcane and uncultivated edge vegetation (occupancy = 1.00 [ = 0.96–1.00] and mean abundance = 7.9 [ = 3.2–19.5] in tall sugarcane with tall edge vegetation versus 0.20 [ = 0.04–0.71] and 0.22 [ = 0.04–1.2], respectively, in short sugarcane with short edge vegetation in one half of the study area). Occupancy and mean abundance of palm warblers ( Dendroica palmarum ) were constant (occupancy = 1.00, = 0.69–1.00; mean abundance = 18, = 1–270). Our model may enable wildlife managers to assess rigorously effects of future edge habitat management on avian distribution and abundance within agricultural landscapes during winter or the breeding season. The model may also help wildlife managers make similar management decisions involving other dynamic habitats such as wetlands, prairies, and even forested areas if forest management or fires occur during the field season.

Florida↗

USGS2023

Visitor use and activities detected using trail cameras at forest restoration sites

We used trail cameras to monitor human visits and activities at two sites in northeast Indiana being restored to bottomland hardwood forests. These sites, managed as nature preserves, are close to cities, where trails and parking lots have been added for ease of access. In this study, trail cameras were successfully used to capture visitation rates and activity types. The two sites had median visitor use rates of 1 and 13 visitors per day. Across both sites, “parking lot use only” (62%), hikers (30.2%), and bicyclists (5%) accounted for more than 97% of site visits. Overall, most weekday visitor-time occurred during daylight hours, peaking at lunch and evening. Mean total number of daily visitors was higher during weekends; however, total daily visitor-time did not vary between days of the week. Michaelis-Menten rarefaction models of sampling efficiency across the study’s four camera stations suggest sampling duration of 27 to 55 days to accurately estimate mean daily visitor counts and 3 to 40 days to detect half the maximal numbers of observed activities. Study estimates of visitation provide land managers with information for accommodating visitor use activities on the restored sites and offer inputs for cultural ecosystem services assessments and associated economic analyses.

Ecological Restoration↗

USGS2011

Survival of white-tailed deer neonates in Minnesota and South Dakota

Understanding the influence of intrinsic (e.g., age, birth mass, and sex) and habitat factors on survival of neonate white-tailed deer improves understanding of population ecology. During 2002–2004, we captured and radiocollared 78 neonates in eastern South Dakota and southwestern Minnesota, of which 16 died before 1 September. Predation accounted for 80% of mortality; the remaining 20% was attributed to starvation. Canids (coyotes [ Canis latrans ], domestic dogs) accounted for 100% of predation on neonates. We used known fate analysis in Program MARK to estimate survival rates and investigate the influence of intrinsic and habitat variables on survival. We developed 2 a priori model sets, including intrinsic variables (model set 1) and habitat variables (model set 2; forested cover, wetlands, grasslands, and croplands). For model set 1, model { S age-interval } had the lowest AIC c (Akaike's information criterion for small sample size) value, indicating that age at mortality (3-stage age-interval: 0–2 weeks, 2–8 weeks, and >8 weeks) best explained survival. Model set 2 indicated that habitat variables did not further influence survival in the study area; β-estimates and 95% confidence intervals for habitat variables in competing models encompassed zero; thus, we excluded these models from consideration. Overall survival rate using model { S age-interval } was 0.87 (95% CI = 0.83–0.91); 61% of mortalities occurred at 0–2 weeks of age, 26% at 2–8 weeks of age, and 13% at >8 weeks of age. Our results indicate that variables influencing survival may be area specific. Region-specific data are needed to determine influences of intrinsic and habitat variables on neonate survival before wildlife managers can determine which habitat management activities influence neonate populations.

Journal of Wildlife Management↗

USGS2011

Spatial scaling of core and dominant forest cover in the Upper Mississippi and Illinois River floodplains, USA

Different organisms respond to spatial structure in different terms and across different spatial scales. As a consequence, efforts to reverse habitat loss and fragmentation through strategic habitat restoration ought to account for the different habitat density and scale requirements of various taxonomic groups. Here, we estimated the local density of floodplain forest surrounding each of ~20 million 10-m forested pixels of the Upper Mississippi and Illinois River floodplains by using moving windows of multiple sizes (1–100 ha). We further identified forest pixels that met two local density thresholds: ‘core’ forest pixels were nested in a 100% (unfragmented) forested window and ‘dominant’ forest pixels were those nested in a >60% forested window. Finally, we fit two scaling functions to declines in the proportion of forest cover meeting these criteria with increasing window length for 107 management-relevant focal areas: a power function (i.e. self-similar, fractal-like scaling) and an exponential decay function (fractal dimension depends on scale). The exponential decay function consistently explained more variation in changes to the proportion of forest meeting both the ‘core’ and ‘dominant’ criteria with increasing window length than did the power function, suggesting that elevation, soil type, hydrology, and human land use constrain these forest types to a limited range of scales. To examine these scales, we transformed the decay constants to measures of the distance at which the probability of forest meeting the ‘core’ and ‘dominant’ criteria was cut in half ( S 1/2 , m). S 1/2 for core forest was typically between ~55 and ~95 m depending on location along the river, indicating that core forest cover is restricted to extremely fine scales. In contrast, half of all dominant forest cover was lost at scales that were typically between ~525 and 750 m, but S 1/2 was as long as 1,800 m. S 1/2 is a simple measure that (1) condenses information derived from multi-scale analyses, (2) allows for comparisons of the amount of forest habitat available to species with different habitat density and scale requirements, and (3) can be used as an index of the spatial continuity of habitat types that do not scale fractally.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗