Search

Novel approaches to quantifying density and distributions could help biologists adaptively manage wildlife populations, particularly if methods are accurate, consistent, cost-effective, rapid, and sensitive to change. Such approaches may also improve research on interactions between density and processes of interest, such as disease transmission across multiple populations. We assess how satellite imagery, unmanned aerial system (UAS) imagery, and Global Positioning System (GPS) collar data vary in characterizing elk density, distribution, and count patterns across times with and without supplemental feeding at the National Elk Refuge (NER) in the US state of Wyoming. We also present the first comparison of satellite imagery data with traditional counts for ungulates in a temperate system. We further evaluate seven different aggregation metrics to identify the most consistent and sensitive metrics for comparing density and distribution across time and populations. All three data sources detected higher densities and aggregation locations of elk during supplemental feeding than non-feeding at the NER. Kernel density estimates (KDEs), KDE polygon areas, and the first quantile of interelk distances detected differences with the highest sensitivity and were most highly correlated across data sources. Both UAS and satellite imagery provide snapshots of density and distribution patterns of most animals in the area at lower cost than GPS collars. While satellite-based counts were lower than traditional counts, aggregation metrics matched those from UAS and GPS data sources when animals appeared in high contrast to the landscape, including brown elk against new snow in open areas. UAS counts of elk were similar to traditional ground-based counts on feed grounds and are the best data source for assessing changes in small spatial extents. Satellite, UAS, or GPS data can provide appropriate data for assessing density and changes in density from adaptive management actions. For the NER, where high elk densities are beneath controlled airspace, GPS collar data will be most useful for evaluating how management actions, including changes in the dates of supplemental feeding, influence elk density and aggregation across large spatial extents. Using consistent and sensitive measures of density may improve research on the drivers and effects of density within and across a wide range of species.

Fire regimes in many dry forests of western North America are substantially different from historical conditions, and there is concern about the ability of these forests to recover following severe wildfire. Fire refugia, unburned or low-severity burned patches where trees survived fire, may serve as essential propagule sources that enable forest regeneration. To quantify the influence of fire refugia spatial pattern and other biophysical factors on the process of post-fire tree regeneration; in particular examining both the proximity and density of surrounding refugia to characterize the landscape of refugial seed sources. We surveyed regeneration at 135 sites in stand-replacement patches across a gradient of fire refugia density in eastern Oregon, USA. We characterized the influence of refugial seed source pattern and other environmental factors on the abundance of regenerating seedlings, and examined the relationship between post-fire climate and the temporal pattern of ponderosa pine seedling establishment. Tree seedlings were present in 83% of plots 12–17 years post-fire, and densities varied substantially (0–67800 stems ha−1, median = 1100). Variation in seedling abundance was driven by the spatial patterns of refugial seed sources. Despite widespread post-fire shrub cover, high-severity burned forests have not undergone a persistent type conversion to shrublands. Ponderosa pine seedling establishment peaked 5–11 years after fire and was not closely associated with post-fire climate. Fire refugia and the seed sources they contain fostered tree regeneration in severely burned patches. Management practices that reduce refugia within post-fire landscapes may negatively influence essential forest recovery processes.

Time series of vegetative indices derived from satellite imagery constitute tools to measure ecological effects of natural and management-induced disturbances to ecosystems. Over the past century, sagebrush-reduction treatments have been applied widely throughout western North America to increase herbaceous vegetation for livestock and wildlife. We used indices from satellite imagery to 1) quantify effects of prescribed-fire, herbicide, and mechanical treatments on vegetative cover, productivity, and phenology, and 2) describe how vegetation changed over time following these treatments. We hypothesized that treatments would increase herbaceous cover and accordingly shift phenologies towards those typical of grass-dominated systems. We expected prescribed burns would lead to the greatest and most-prolonged effects on vegetative cover and phenology, followed by herbicide and mechanical treatments. Treatments appeared to increase herbaceous cover and productivity, which coincided with signs of earlier senescence − signals expected of grass-dominated systems, relative to sagebrush-dominated systems. Spatial heterogeneity for most phenometrics was lower in treated areas relative to controls, which suggested treatment-induced homogenization of vegetative communities. Phenometrics that explain spring migrations of ungulates mostly were unaffected by sagebrush treatments. Fire had the strongest effect on vegetative cover, and yielded the least evidence for sagebrush recovery. Overall, treatment effects were small relative to those reported from field-based studies for reasons most likely related to sagebrush recovery, treatment specification, and untreated patches within mosaicked treatment applications. Treatment effects were also small relative to inter-annual variation in phenology and productivity that was explained by temperature, snowpack, and growing-season precipitation. Our results indicated that cumulative NDVI, late-season phenometrics, and spatial heterogeneity of several phenometrics may serve as useful indicators of vegetative change in sagebrush ecosystems.

Aim Studies of fire activity along environmental gradients have been undertaken, but the results of such studies have yet to be integrated with fire-regime analysis. We characterize fire-regime components along climate gradients and a gradient of human influence. Location We focus on a climatically diverse region of north-western North America extending from northern British Columbia, Canada, to northern Utah and Colorado, USA. Methods We used a multivariate framework to collapse 12 climatic variables into two major climate gradients and binned them into 73 discrete climate domains. We examined variation in fire-regime components (frequency, size, severity, seasonality and cause) across climate domains. Fire-regime attributes were compiled from existing databases and Landsat imagery for 1897 large fires. Relationships among the fire-regime components, climate gradients and human influence were examined through bivariate regressions. The unique contribution of human influence was also assessed. Results A primary climate gradient of temperature and summer precipitation and a secondary gradient of continentality and winter precipitation in the study area were identified. Fire occupied a distinct central region of such climate space, within which fire-regime components varied considerably. We identified significant interrelations between fire-regime components of fire size, frequency, burn severity and cause. The influence of humans was apparent in patterns of burn severity and ignition cause. Main conclusions Wildfire activity is highest where thermal and moisture gradients converge to promote fuel production, flammability and ignitions. Having linked fire-regime components to large-scale climate gradients, we show that fire regimes – like the climate that controls them – are a part of a continuum, expanding on models of varying constraints on fire activity. The observed relationships between fire-regime components, together with the distinct role of climatic and human influences, generate variation in biotic communities. Thus, future changes to climate may lead to ecological changes through altered fire regimes.

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass (Bromus tectorum) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

Salt and sediment contributions to the Colorado River and its tributaries pose economic and environmental concerns for the United States and Mexico. Land use decisions promoting the aggregation of Mancos Shale derived soils are one way to reduce the transportation of salts and sediments to water resources. We used a simple field test of soil aggregate stability to determine the site characteristics influencing the soil stability of sedimentary marine shale in the Gunnison Gorge National Conservation Area in Southwestern Colorado. Ninety-six 1 m 2 plots were intensively sampled to explore relationships between soil stability and the biological, chemical and physical site characteristics. Analysis of variance showed decreased soil stability when erosion features were present at a sample location suggesting the applicability of stability test results to the erosion potential of Mancos Shale derived soils ( p = 0.02). Analysis using generalized linear models with a negative binomial distribution and non-parametric regression tree models determined that the best predictor variable for soil stability was the percent cover of visible biological soil crust. Identifying the importance of biological soil crust in the stabilization of Mancos Shale soils is important for land use planning because biological soil crusts respond to changes in land use. The results of this study lead to improved interpretation of the field soil stability test and may assist in the definition of important ecological or functional thresholds in many arid and semiarid environments.

We examined species–area curves, species composition and similarity (Jaccard's coefficients), and species richness in 17 vegetation types to develop a composite index of a vegetation type's contribution to regional species richness. We collected data from 1 to 1000 m 2 scales in 147 nested plots in Rocky Mountain National Park, Colorado, USA to compare three species–area curve models’ abilities to estimate the number of species observed in each vegetation type. The log(species)–log(area) curve had the largest adjusted coefficients of determination ( r 2 values) in 12 of the 17 types, followed by the species–log(area) curve with five of the highest values. When the slopes of the curves were corrected for species overlap among plots with Jaccard's coefficients, the species–log(area) curves estimated values closest to those observed. We combined information from species–area curves and measures of heterogeneity with information on the area covered by each vegetation type and found that the types making the greatest contributions to regional biodiversity covered the smallest areas. This approach may provide an accurate and relatively rapid way to rank hotspots of plant diversity within regions of interest.

Land managers need cost-effective and informative tools for non-native plant species management. Many local, state, and federal agencies adopted mapping systems designed to collect comparable data for the early detection and monitoring of non-native species. We compared mapping information to statistically rigorous, plot-based methods to better understand the benefits and compatibility of the two techniques. Mapping non-native species locations provided a species list, associated species distributions, and infested area for subjectively selected survey sites. The value of this information may be compromised by crude estimates of cover and incomplete or biased estimations of species distributions. Incorporating plot-based assessments guided by a stratified-random sample design provided a less biased description of non-native species distributions and increased the comparability of data over time and across regions for the inventory, monitoring, and management of non-native and native plant species.

Spatial heterogeneity may have differential effects on the distribution of native and nonnative plant species richness. We examined the effects of spatial heterogeneity on native and nonnative plant species richness distributions in the central part of Rocky Mountain National Park, Colorado, USA. Spatial heterogeneity around vegetation plots was characterized using landscape metrics, environmental/topographic variables (slope, aspect, elevation, and distance from stream or river), and soil variables (nitrogen, clay, and sand). The landscape metrics represented five components of landscape heterogeneity and were measured at four spatial extents (within varying radii of 120, 240, 480, and 960 m) using the FRAGSTATS landscape pattern analysis program. Akaike's Information Criterion adjusted for small sample size (AICc) was used to select the best models from a set of multiple linear regression models developed for native and nonnative plant species richness at four spatial extents and three levels of ecological hierarchy (i.e., landscape, land cover, and community). Both native and nonnative plant species richness were positively correlated with edge density, Simpson's diversity index and interspersion/juxtaposition index, and were negatively correlated with mean patch size. The amount of variation explained at four spatial extents and three hierarchical levels ranged from 30% to 70%. At the landscape level, the best models explained 43% of the variation in native plant species richness and 70% of the variation in nonnative plant species richness (240-m extent). In general, the amount of variation explained was always higher for nonnative plant species richness, and the inclusion of landscape metrics always significantly improved the models. The best models explained 66% of the variation in nonnative plant species richness for both the conifer land cover type and lodgepole pine community. The relative influence of the components of spatial heterogeneity differed for native and nonnative plant species richness and varied with the spatial extent of analysis and levels of ecological hierarchy. The study offers an approach to quantify spatial heterogeneity to improve models of plant biodiversity. The results demonstrate that ecologists must recognize the importance of spatial heterogeneity in managing native and nonnative plant species.

We present an approach to quantitatively assess nonnative plant invasions at landscape scales from both habitat and species perspectives. Our case study included 34 nonnative species found in 142 plots (0.1 ha) in 14 vegeta- tion types within the Grand Staircase-Escalante National Monument, Utah. A plot invasion index, based on nonnative species richness and cover, showed that only 16 of 142 plots were heavily invaded. A species invasive index, based on frequency, cover, and number of vegetation types invaded, showed that only 7 of 34 plant species were highly invasive. Multiple regressions using habitat characteristics (moisture index, elevation, soil P, native species richness, maximum crust development class, bare ground, and rock) explained 60% of variation in nonnative species richness and 46% of variation in nonnative species cover. Three mesic habitats (aspen, wet meadow, and perennial riparian types) were par- ticularly invaded (31 of 34 nonnative species studied were found in these types). Species-specific logistic regression models for the 7 most invasive species correctly predicted occurrence 89% of the time on average (from 80% for Bromus tectorum, a habitat generalist, to 93% for Tamarix spp., a habitat specialist). Even with such a modest sampling intensity (

We briefly reviewed the literature on habitat matching in invading non-native plant species. Then we hypothesized that the richness and cover of native annual and perennial plant species integrate complex local information of vegetation and soils that would help to predict invasion success by similarly adapted non-native plant species. We tested these ‘life-history habitat matching’ relationships in 603 0.1-ha plots, including 294 plots in Colorado, which were relatively high for the cover of native perennial plant species, and for 309 0.1-ha plots in southern Utah, which were relatively high in the cover of native annual plant species. We found strong positive relationships between the richness and foliar cover for both native and non-native species, whether they were annual or perennial species (0.34 > r 2

Basic information on where nonnative plant spe- cies have successfully invaded is lacking. We assessed the vulnerability of 22 vegetation types (25 sets of four plots in nine study areas) to nonnative plant invasions in the north- central United States. In general, habitats with high native species richness were more heavily invaded than species- poor habitats, low-elevation areas were more invaded than high-elevation areas, and riparian zones were more invaded than nearby upland sites. For the 100 1000-m 2 plots (across all vegetation types), 50% of the variation in nonnative species richness was explained by longitude, latitude, native plant species richness, soil total percentage nitrogen, and mean maximum July temperature (n 100 plots; P 0.001). At the vegetation-type scale (n 25 sets of four 1000-m 2 plots/ type), 64% of the variation in nonnative species richness was explained by native plant species richness, elevation, and Oc- tober to June precipitation (P 0.001). The foliar cover of nonnative species (log) was strongly positively correlated with the nonnative species richness at the plot scale (r 0.77, P 0.001) and vegetation-type scale (r 0.83, P 0.001). We concluded that, at the vegetation-type and re- gional scales in the north- central United States, (1) vegetation types rich in native species are often highly vulnerable to inva- sion by nonnative plant species; (2) where several nonnative species become established, nonnative species cover can substantially increase; (3) the attributes that maintain high na- tive plant species richness (high light, water, nitrogen, and temperatures) also help maintain nonnative plant species rich- ness; and (4) more care must be taken to preserve native spe- cies diversity in highly vulnerable habitats. Invasive nonnative plant species are a growing con- cern in the north- central United States and elsewhere because some of them can poison livestock, clog water- ways, compete with cash crops, and degrade rangelands (Westbrooks 1999). In this paper, we operationally de- fine nonnative species as species from other continents. Managers of national parks, wildlife refuges, and other natural areas are also concerned because of the poten- tial negative effects of nonnative plant species on native

Some theories and experimental studies suggest that areas of low plant spe- cies richness may be invaded more easily than areas of high plant species richness. We gathered nested-scale vegetation data on plant species richness, foliar cover, and frequency from 200 1-m 2 subplots (20 1000-m 2 modified-Whittaker plots) in the Colorado Rockies (USA), and 160 1-m 2 subplots (16 1000-m 2 plots) in the Central Grasslands in Colorado, Wyoming, South Dakota, and Minnesota (USA) to test the generality of this paradigm. At the 1-m 2 scale, the paradigm was supported in four prairie types in the Central Grasslands, where exotic species richness declined with increasing plant species richness and cover. At the 1-m 2 scale, five forest and meadow vegetation types in the Colorado Rockies contradicted the paradigm; exotic species richness increased with native-plant species richness and foliar cover. At the 1000-m 2 plot scale (among vegetation types), 83% of the variance in exotic species richness in the Central Grasslands was explained by the total percentage of nitrogen in the soil and the cover of native plant species. In the Colorado Rockies, 69% of the variance in exotic species richness in 1000-m 2 plots was explained by the number of native plant species and the total percentage of soil carbon. At landscape and biome scales, exotic species primarily invaded areas of high species richness in the four Central Grasslands sites and in the five Colorado Rockies vegetation types. For the nine vegetation types in both biomes, exotic species cover was positively correlated with mean foliar cover, mean soil percentage N, and the total number of exotic species. These patterns of invasibility depend on spatial scale, biome and vegetation type, spatial autocorrelation effects, availability of resources, and species-specific responses to grazing and other disturbances. We conclude that: (1) sites high in herbaceous foliar cover and soil fertility, and hot spots of plant diversity (and biodiversity), are invasible in many landscapes; and (2) this pattern may be more closely related to the degree resources are available in native plant communities, independent of species richness. Exotic plant in- vasions in rare habitats and distinctive plant communities pose a significant challenge to land managers and conservation biologists.

Only a small portion of any landscape can be sampled for vascular plant diversity because of constraints of cost (salaries, travel time between sites, etc.). Often, the investigator decides to reduce the cost of creating a vegetation map by increasing the minimum mapping unit (MMU), and/or by reducing the number of vegetation classes to be considered. Questions arise about what information is sacrificed when map resolution is decreased. We compared plant diversity patterns from vegetation maps made with 100-ha, 50-ha, 2-ha, and 0.02-ha MMUs in a 754-ha study area in Rocky Mountain National Park, Colorado, United States, using four 0.025-ha and 21 0.1-ha multiscale vegetation plots. We developed and tested species–log(area) curves, correcting the curves for within-vegetation type heterogeneity with Jaccard’s coefficients. Total species richness in the study area was estimated from vegetation maps at each resolution (MMU), based on the corrected species–area curves, total area of the vegetation type, and sp...

We present a rapid, cost-efficient methodology to link plantdiversity surveys from plots to landscapes using: (1) unbiasedsite selection based on remotely sensed information; (2) multi-scale field techniques to assess plant diversity; (3)mathematical models (species-area curves) to estimate thenumber of species in larger areas corrected for within-typeheterogeneity; and (4) mathematical techniques to estimatetotal species richness and patterns of plant diversity in alandscape. We demonstrate the methodology in a 754 ha studyarea in Rocky Mountain National Park, Colorado, U.S.A.,using four 0.025 ha and twenty-one 0.1 ha multi-scalevegetation plots. We recorded 330 plant species (∼1/3 thenumber of plants recorded in the 1074 km2 Park) in the2.2 ha area within the plots: this represents a samplingintensity of 0.29% of the 754 ha study site. We estimated 552plant species, about half the plant species recorded in the Park,in just 0.7% of the Park‘s area. We show how this rapid,cost-efficient methodology: (1) produces a rich informationbase on the patterns of native plant diversity and thedistribution of non-native plant species and keystoneecosystems; and (2) can be easily adapted for other nationaland state parks, national forests, wildlife refuges, and nature reserves.

Studies to identify gaps in the protection of habitat for speciesof concern have been inconclusive and hampered by single-scale orpoor multi-scale sampling methods, large minimum mapping units(MMU's of 2 ha to 100 ha), limited and subjectively selected fieldobservations, and poor mathematical and ecological models. Weovercome these obstacles with improved multi-scale samplingtechniques, smaller MMU's (< 0.02 ha), an unbiased sampling designbased on double sampling, improved mathematical models includingspecies-area curves corrected for habitat heterogeneity, andgeographic information system-based ecological models. We applythis landscape analysis approach to address resource issues inRocky Mountain National Park, Colorado. Specifically, we quantifythe effects of elk grazing on plant diversity, identify areas ofhigh or unique plant diversity needing increased protection, andevaluate the patterns of non-native plant species on thelandscape. Double sampling techniques use satellite imagery,aerial photography, and field data to stratify homogeneous andheterogeneous units and “keystone ecosystems” (ecosystems thatcontain or support a high number of species or have distinctivespecies compositions). We show how a multi-scale vegetationsampling design, species-area curves, analyses of within- andbetween-vegetation type species overlap, and geographic informationsystem (GIS) models can be used to quantify landscape-scalepatterns of vascular plant diversity in the Park. The new multi-scale vegetation plot techniques quickly differentiated plantspecies differences in paired study sites. Three plots in the OuzelBurn area (burned in 1978) contained 75 plant species, while only17 plant species were found in paired plots outside the burn.Riparian areas contained 109 plant species, compared to just 55species in paired plots in adjacent forests. However, plant speciesrichness patterns inside and outside elk exclosures were morecomplex. One elk exclosure contained more species than its adjacentopen range (52 species inside and 48 species outside). Two elkexclosures contained fewer species inside than outside (105 and 41species inside and 112 and 74 species outside, respectively).However, there was only 26% to 48% overlap (using Jaccard'sCoefficient) of plant species composition inside and outside theexclosures. One elk exclosure had 13% cover of non-indigenousspecies inside the exclosure compared to 4% outside, butnon-indigenous species cover varied by location. We compared plantdiversity patterns from vegetation maps made with 100 ha, 50 ha, 2ha, and 0.02 ha MMU's in the 754 ha Beaver Meadows study area usingfour 0.025 ha and twenty-one 0.1 ha multi-scale vegetation plots.Preliminary data suggested that the 2 ha MMU provided an accurateestimate of the number of plant species (–14%) for a study area,but the number of habitats (polygons) was reduced by 67%, andaspen, a unique and important habitat type, was missed entirely. Wedescribe a hypothesis-driven approach to the design andimplementation of geospatial databases for local resourcemonitoring and ecosystem management.

Fire is a natural part of most forest ecosystems in the western United States, but its effects on nonnative plant invasion have only recently been studied. Also, forest managers are engaging in fuel reduction projects to lessen fire severity, often without considering potential negative ecological consequences such as nonnative plant species introductions. Increased availability of light, nutrients, and bare ground have all been associated with high- severity fires and fuel treatments and are known to aid in the establishment of nonnative plant species. We use vegetation and environmental data collected after wildfires at seven sites in coniferous forests in the western United States to study responses of nonnative plants to wildfire. We compared burned vs. unburned plots and plots treated with mechanical thinning and/or prescribed burning vs. untreated plots for nonnative plant species richness and cover and used correlation analyses to infer the effect of abiotic site conditions on invasibility. Wildfire was responsible for significant increases in nonnative species richness and cover, and a significant decrease in native cover. Mechanical thinning and prescribed fire fuel treatments were associated with significant changes in plant species composition at some sites. Treatment effects across sites were minimal and inconclusive due to significant site and site 3 treatment interaction effects caused by variation between sites including differences in treatment and fire severities and initial conditions (e.g., nonnative species sources). We used canonical correspondence analysis (CCA) to determine what combinations of environmental variables best explained patterns of nonnative plant species richness and cover. Variables related to fire severity, soil nutrients, and elevation explained most of the variation in species composition. Nonnative species were generally associated with sites with higher fire severity, elevation, percentage of bare ground, and lower soil nutrient levels and lower canopy cover. Early assessments of postfire stand conditions can guide rapid responses to nonnative plant invasions.

Establishment and spread of non-native species following wildfires can pose threats to long-term native plant recovery. Factors such as disturbance severity, resource availability, and propagule pressure may influence where non-native species establish in burned areas. In addition, pre- and post-fire management activities may influence the likelihood of non-native species establishment. In the present study we examine the establishment of non-native species after wildfires in relation to native species richness, fire severity, dominant native plant cover, resource availability, and pre- and post-fire management actions (fuel treatments and post-fire rehabilitation treatments). We used an information-theoretic approach to compare alternative hypotheses. We analysed post-fire effects at multiple scales at three wildfires in Colorado and New Mexico. For large and small spatial scales at all fires, fire severity was the most consistent predictor of non-native species cover. Non-native species cover was also correlated with high native species richness, low native dominant species cover, and high seeded grass cover. There was a positive, but non-significant, association of non-native species with fuel-treated areas at one wildfire. While there may be some potential for fuels treatments to promote non-native species establishment, wildfire and post-fire seeding treatments seem to have a larger impact on non-native species.