Geology topics

J.W. Karl

Publications and source records attributed to J.W. Karl.

4 recordsLinked to original sources

USGS2012

Revolutionary land use change in the 21st century: Is (rangeland) science relevant?

Rapidly increasing demand for food, fiber, and fuel together with new technologies and the mobility of global capital are driving revolutionary changes in land use throughout the world. Efforts to increase land productivity include conversion of millions of hectares of rangelands to crop production, including many marginal lands with low resistance and resilience to degradation. Sustaining the productivity of these lands requires careful land use planning and innovative management systems. Historically, this responsibility has been left to agronomists and others with expertise in crop production. In this article, we argue that the revolutionary land use changes necessary to support national and global food security potentially make rangeland science more relevant now than ever. Maintaining and increasing relevance will require a revolutionary change in range science from a discipline that focuses on a particular land use or land cover to one that addresses the challenge of managing all lands that, at one time, were considered to be marginal for crop production. We propose four strategies to increase the relevance of rangeland science to global land management: 1) expand our awareness and understanding of local to global economic, social, and technological trends in order to anticipate and identify drivers and patterns of conversion; 2) emphasize empirical studies and modeling that anticipate the biophysical (ecosystem services) and societal consequences of large-scale changes in land cover and use; 3) significantly increase communication and collaboration with the disciplines and sectors of society currently responsible for managing the new land uses; and 4) develop and adopt a dynamic and flexible resilience-based land classification system and data-supported conceptual models (e.g., state-and-transition models) that represent all lands, regardless of use and the consequences of land conversion to various uses instead of changes in state or condition that are focused on a single land use.

Rangeland Ecology and Management↗

USGS2005

An assessment of Idaho's wildlife management areas for the protection of wildlife

Since 1940, Idaho Department of Fish and Game has developed a network of 31 Wildlife Management Areas (WMAs) across the state. This program has been focused mostly on conservation of game species and their habitats. We assessed the contribution of Idaho's WMAs to conservation of all Idaho's wildlife and other aspects of ecological diversity. Predicted occurrences of species' breeding habitats and other data were used to evaluate the representation of wildlife habitat and other ecological conditions. We found 33 of 39 natural land cover types were mapped as occurring in WMAs. WMAs occurred in 10 of 15 of Bailey's ecoregion sections, absent only from two sections that occupy greater than 1% of Idaho. Percent area of WMAs by elevation followed a pattern similar to percent area of Idaho; however, mean elevation for WMAs was lower than for the state and other protected areas in Idaho. We predicted breeding habitat for 98.4% of Idaho's wildlife and all federal and state listed threatened, endangered, or candidate terrestrial vertebrates to occur in at least one WMA. We predicted habitat for 39 species to occur on five or fewer WMAs, and predicted no habitat on WMAs for five species. We found that a system of WMAs established mainly to protect game species potentially conserves many other aspects of Idaho's ecological diversity, may provide habitat for more than 98% of Idaho's wildlife, and complements other protected areas in the state.

Idaho↗

USGS2000

Sensitivity of species habitat-relationship model performance to factors of scale

Researchers have come to different conclusions about the usefulness of habitat-relationship models for predicting species presence or absence. This difference frequently stems from a failure to recognize the effects of spatial scales at which the models are applied. We examined the effects of model complexity, spatial data resolution, and scale of application on the performance of bird habitat relationship (BHR) models on the Craig Mountain Wildlife Management Area and on the Idaho portion of the U.S. Forest Service's Northern Region. We constructed and tested BHR models for 60 bird species detected on the study areas. The models varied by three levels of complexity (amount of habitat information) and three spatial data resolutions (0.09 ha, 4 ha, 10 ha). We tested these models at two levels of analysis: the site level (a homogeneous area <0.5 ha) and cover-type level (an aggregation of many similar sites of a similar land-cover type), using correspondence between model predictions and species detections to calculate kappa coefficients of agreement. Model performance initially increased as models became more complex until a point was reached where omission errors increased at a rate greater than the rate at which commission errors were decreasing. Heterogeneity of the study areas appeared to influence the effect of model complexity. Changes in model complexity resulted in a greater decrease in commission error than increase in omission error. The effect of Spatial data resolution on the performance of BHR models was influenced by the variability of the study area. BHR models performed better at cover-type levels of analysis than at the site level for both study areas. Correct-presence estimates (1 - minus percentage omission error) decreased slightly as number of species detections increased on each study area. Correct-absence estimates (1 - percentage commission error) increased as number of species detections increased on each study area. This suggests that a large number of detections may be necessary to achieve reliable estimates of model accuracy.

Idaho↗

USGS1999

Obtaining environmental measures to facilitate vertebrate habitat modeling

Published literature generally lacks habitat information needed to adequately model the habitats of most wildlife species at large scales (>1:100,000). We searched in primary and secondary literature for occurrence of several potentially useful habitat measures for 20 species of interest to the Idaho Department of Fish and Game. We found adequate information for modeling only the habitats of certain game species and species of special interest. We suggest that many more researchers could collect simple habitat information regarding vegetation composition and structure, topographic features, soils, temperature, and distance to special landscape features such that current research expenses would not be increased significantly. We recommend that habitat data be consistently reported in peer-reviewed literature or deposited into a central data repository. This will not only help fill the gaps in our current knowledge of wildlife but also place it in a format that is readily accessible by the scientific community.

Wildlife Society Bulletin↗