Geology topics

Kathi L. Borgmann

Publications and source records attributed to Kathi L. Borgmann.

4 recordsLinked to original sources

USGS2017

Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection

Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail ( Rallus obsoletus yumanensis ), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

Arizona, California, Nevada↗

USGS2015

Range-wide wetland associations of the King Rail: A multi-scale approach

King Rail populations have declined and identifying wetland features that influence King Rail occupancy can help prevent further population declines. We integrated continent-wide marsh bird survey data with spatial wetland data from the National Wetland Inventory (NWI) to examine wetland features that influenced King Rail occupancy throughout the species’ range. We analyzed wetland data at 7 spatial scales to examine the scale(s) at which 68 wetland features were most strongly related to King Rail occupancy. Occupancy was most strongly associated with estuarine features and brackish and tidal saltwater regimes. King Rail occupancy was positively associated with emergent and scrub-shrub wetlands and negatively associated with forested wetlands. The best spatial scale for assessing King Rail occupancy differed among wetland features; we could not identify one spatial scale (among all wetland features) that best explained variation in occupancy. Future research on King Rail habitat that includes multiple spatial scales is more likely to identify the suite of features that influence occupancy. Our results indicate that NWI data may be useful for predicting occupancy based on broad habitat features across the King Rail’s range, which may help inform management decisions for this and other wetland-dependent birds.

Wetlands↗

USGS2015

The nest-concealment hypothesis: New insights from a comparative analysis

Selection of a breeding site is critical for many animals, especially for birds whose offspring are stationary during development. Thus, birds are often assumed to prefer concealed nest sites. However, 74% of studies ( n = 106) that have evaluated this relationship for open-cup nesting songbirds in North America failed to support the nest-concealment hypothesis. We conducted a comparative analysis to identify factors that contribute to variation in the ability of researchers to find support for the nest-concealment hypothesis. We found that some of the discrepancy among studies can be explained by interspecific differences in morphological and extrinsic factors that affect nest predation. Moreover, methods that investigators used to estimate concealment affected whether studies found support for the nest-concealment hypothesis; 33% of the studies that used quantitative estimates found support for the nest-concealment hypothesis whereas only 10% of the studies that used qualitative estimates found support. The timing of measurements also explained some of the ambiguity; studies that provided little information regarding the timing of their foliage density estimates were less likely to support the nest-concealment hypothesis. Species with more conspicuous male plumage were less likely to support the nest-concealment hypothesis when we analyzed studies that used visual estimates. Whereas species with more conspicuous female plumage were more likely to support the nest-concealment hypothesis when we analyzed studies that used quantitative measures. Our results demonstrate that support for the nest-concealment hypothesis has been equivocal, but that some of the ambiguity can be explained by morphological traits and methods used to measure concealment.

Wilson Journal of Ornithology↗

USGS2015

Wildlife Habitat Restoration: Chapter 12

As the preceding chapters point out, many wildlife species and the habitat they depend on are in peril. However, opportunities exist to restore habitat for many imperiled wildlife species. But what is wildlife habitat restoration? We begin this chapter by defining habitat restoration and then provide recommendations on how to maximize success of future habitat restoration efforts for wildlife. Finally, we evaluate whether we have been successful in restoring wildlife habitat and supply recommendations to advance habitat restoration. Successful restoration requires clear and explicit goals that are based on our best understanding of what the habitat was like prior to the disturbing event. Ideally, a restoration project would include: (1) a summary of prerestoration conditions that define the existing status of wildlife populations and their habitat; (2) a description of habitat features required by the focal or indicator species for persistence; (3) an a priori description of measurable, quantitative metrics that define restoration goals and measures of success; (4) a monitoring plan; (5) postrestoration comparisons of habitat features and wildlife populations with adjacent unmodified areas that are similar to the restoration site; and (6) expert review of the entire restoration plan (i.e., the five aforementioned components).

Book chapter↗