Relative importance of habitat area and isolation for bird occurrence patterns in a naturally patchy landscape

There is debate among ecologists about whether total habitat area or patch arrangement contributes most to population and/or community responses to fragmented or patchy landscapes. We tested the relative effects of patch area and isolation for predicting bird occurrence in a naturally patchy landscape in the Bear River Mountains of Northern Utah, USA. We selected focal patches (mountain meadows) ranging in elevation from 1,920 to 2,860 m and in size from 0.6 to 182 ha. Breeding birds were sampled in each focal meadow during the summers of 2003 and 2004 using variable-distance point transects. Logistic regression and likelihood-based model selection were used to determine the relationship between likelihood of occurrence of three bird species (Brewer’s sparrow, vesper sparrow, and white-crowned sparrow) and area, isolation, and proximity metrics. We used model weights and model-averaged confidence intervals to assess the importance of each predictor variable. Plots of area versus isolation were used to evaluate complex relationships between the variables. We found that meadow area was the most important variable for explaining occurrence for two species, and that isolation was the most important for the other. We also found that the absolute distance was more appropriate for evaluating isolation responses than was the species-specific proximity metric. Our findings add clarity to the debate between ecologists regarding the relative importance of area and isolation in species responses to patchy landscapes.     

Summer spatial patterning of chukars in relation to free water in western Utah

Free water is considered important to wildlife in arid regions. In the western United States, thousands of water developments have been built to benefit wildlife in arid landscapes. Agencies and researchers have yet to clearly demonstrate their effectiveness. We combined a spatial analysis of summer chukar (Alectoris chukar) covey locations with dietary composition analysis in western Utah. Our specific objectives were to determine if chukars showed a spatial pattern that suggested association with free water in four study areas and to document summer dietary moisture content in relation to average distance from water. The observed data for the Cedar Mountains study area fell within the middle of the random mean distance to water distribution suggesting no association with free water. The observed mean distance to water for the other three areas was much closer than expected compared to a random spatial process, suggesting the importance of free water to these populations. Dietary moisture content of chukar food items from the Cedar Mountains (59%) was significantly greater (P < 0.05) than that of birds from Box Elder (44%) and Keg-Dugway (44%). Water developments on the Cedar Mountains are likely ineffective for chukars. Spatial patterns on the other areas, however, suggest association with free water and our results demonstrate the need for site-specific considerations. Researchers should be aware of the potential to satisfy water demand with pre-formed and metabolic water for a variety of species in studies that address the effects of wildlife water developments. We encourage incorporation of spatial structure in model error components in future ecological research.     

The behavior of landscape metrics commonly used in the study of habitat fragmentation

A meaningful interpretation of landscape metrics is possible only when the limitations of each measure are fully understood, the range of attainable values is known, and the user is aware of potential shifts in the range of values due to characteristics of landscape patches. To examine the behavior of landscape metrics, we generated artificial landscapes that mimicked fragmentation processes while controlling the size and shape of patches in the landscape and the mode of disturbance growth. We developed nine series of increasingly fragmented landscapes and used these to investigate the behavior of edge density, contagion, mean nearest neighbor distance, mean proximity index, perimeter-area fractal dimension, and mass fractal dimension. We found that most of the measures were highly correlated, especially contagion and edge density, which had a near-perfect inverse correspondence. Many of the measures were linearly-associated with increasing disturbance until the proportion of disturbance on the landscape was approximately 0.40, with non-linear associations at higher proportions. None of the measures was able to differentiate between landscape patterns characterized by dispersed versus aggregated patches. The highest attainable value of each measure was altered by either patch size or shape, and in some cases, by both attributes. We summarize our findings by discussing the utility of each metric.     

Restoring habitat permeability to roaded landscapes with isometrically-scaled wildlife crossings

Globally, human activities impact from one-third to one-half of the earth’s land surface; a major component of development involves the construction of roads. In the US and Europe, road networks fragment normal animal movement patterns, reduce landscape permeability, and increase wildlife-vehicle collisions, often with serious wildlife population and human health consequences. Critically, the placement of wildlife crossing structures to restore landscape connectivity and reduce the number of wildlife-vehicle collisions has been a hit-or-miss proposition with little ecological underpinning, however recent important developments in allometric scaling laws can be used to guide their placement. In this paper, we used cluster analysis to develop domains of scale for mammalian species groups having similar vagility and developed metrics that reflect realistic species movement dynamics. We identified six home range area domains; three quarters of 102 species clustered in the three smallest domains. We used HR^0.5 to represent a daily movement metric; when individual species movements were plotted against road mile markers, 71.2% of 72 species found in North America were included at distances of ?1 mi. The placement of wildlife crossings based on the HR^0.5 metric, along with appropriate auxiliary mitigation, will re-establish landscape permeability by facilitating wildlife movement across the roaded landscape and significantly improve road safety by reducing wildlife vehicle collisions.     

Advancing landscape ecology as a science: the need for consistent reporting guidelines

Context

In the face of global change, evidence-based information for policy development and political action is needed. Research syntheses have the potential to produce more reliable and generalizable results than are possible from small and regional extent primary studies. Data-sharing and detailed reporting are indispensable prerequisites for syntheses, however syntheses often are seriously hindered by insufficient reporting of primary data.

Objectives

Since many ecological processes are strongly influenced by spatial pattern, we suggest reporting guidelines for landscape-ecological studies. Better data reporting will not only benefit the quality of primary research studies, and allow replication, but also facilitate research syntheses.

Methods

We evaluated how landscape context information was reported in primary research articles including recently published articles in the journal Landscape Ecology. We further looked at the author guidelines for several journals to check what authors are expected to report.

Results

Specifically, we found that the existing reporting of landscape context information was insufficient to evaluate the effects of tropical forest edges on bird nest predation risk. More generally, exact study locations were not provided in any evaluated article. No journal gave detailed instructions to authors on how to report study characteristics.

Conclusions

We argue that consideration of the following reporting guidelines could substantially facilitate research syntheses: (1.1) detailed map of study area, (1.2) spatial location of sampling points; (2.1) land-use types; (2.2) vegetation, key resources, soil, geology, and disturbance history; (2.3) additional site parameters; (3) results for each sampling point.