Lab of Landscape Ecology and Conservation Biology’s research projects

Developing a Conservation Science Program and Landscape Assessment for the Kane and Two Mile Ranches on the Kaibab Plateau

We are working to restore and conserve biological diversity and ecosystem function across the Kane and Two Mile Ranches and adjacent public lands on the Arizona Strip and nearby areas of the Colorado Plateau. For this project, we are collaborating closely with:

  • The Grand Canyon Trust
  • Arizona Game and Fish Department
  • The U.S. Forest Service
  • The Bureau of Land Management
  • and a variety of other agencies and organizations

The Kane and Two Mile Ranches, owned and operated by the Grand Canyon Trust, comprise over 850,000 acres on the Kaibab and Paria Plateaus, and include some of the most extensive public wild lands in the Southwest. Recently, large-stand replacing fire events on the Kaibab Plateau, rangeland degradation at lower elevations, and the decline of riparian habitats across the region have heightened concerns about land management, restoration, conservation, and sustainable ranching practices, and stakeholders in the region have organized to develop new, broad-scale lane and resource management strategies. 

We are developing integrative models of fundamental ecological attributes and processes for diverse ecosystems across the vast project area, which will inform restoration, fire management, and sensitive and invasive species management scenarios Our efforts are supporting a science-driven approach to collaborative land and resource management at the landscape level, and facilitating a new management paradigm for ecological restoration and conservation planning in the region.

For more information, check out the Kane and Two Mile Ranches Program website.

Ecology and conservation of arid grasslands

This experimental research program involves groups with divergent interests in the grazing debate including ranchers, environmentalists, public servants, and interested citizens.

Rangelands across the world provide important ecosystem services to society, so developing management strategies that promote ecological and economic sustainability is of key importance. Yet, the application of sustainability to the rangelands of the western United States has been fraught with conflict. In most cases, the management of natural resources has been government-mandated and expert-driven. This has limited the ability of managers and scientists to effectively translate scientific and technical information to the rest of the public, often leading to public resistance and resentment.

We see an immediate need for ecological and social science to disseminate information that will help focus and perhaps resolve the impasse over grazing impacts and other natural resource issues. By organizing "collaborative management teams" that include ranchers, environmentalists, public servants, and interested citizens, we have shaped a promising experimental research program.

Effective area models: modeling edge effects and mobile animals in patchy landscapes

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The Effective Area Model (EAM) links field and remotely sensed data in a landscape model that permits comparison of the impacts of alternative land use strategies on animal populations. Through a GIS-interface, the model predicts changes in animal abundance given changes in landscape pattern.


Terrestrial landscapes are being converted to novel states at increasing rates, due to accelerating human land use and its impacts. Remaining natural habitats are more fragmented and are often embedded in anthropogenic habitat types. Given this degree of dynamism, an approach for estimating changes in population density and viability that explicitly accounts for changes in the spatial patterning of habitats in the landscapes is essential. In addition to simple abundance responses, estimates should account for time lags and unexpected transient dynamics that accompany landscape change. We discuss a spatial modeling approach, developed with support from SERDP (project CS-1100), that incorporates empirical data on how animals respond to habitat edges and predicts changes in animal abundance and distribution under various land management scenarios. In addition to typical patch size, shape, and distribution metrics, this model explicitly incorporates information on patch context. Inputs to the model include habitat maps and animal density response functions, generated from empirical data. 

Each response function describes animal density in terms of a probability distribution along a habitat gradient stretching between the interiors of adjacent habitat types. Preliminary model results show marked differences from the predictions of a null model that does not incorporate edge and matrix effects. Predictions of bird densities in a heterogeneous desert riparian ecosystem differ by factors of 0.6-2.7, and differences between predictions of the effective area model and null model tend to increase with increasing landscape heterogeneity. We examine the predicted effects of landscape change in riparian habitats along the San Pedro River, adjacent to Ft. Huachuca, AZ, and demonstrate how different species are expected to respond in dramatically different ways to changes induced by, for example, groundwater pumping, fire, and habitat restoration efforts.


The detrimental effects of habitat fragmentation on animal populations are widely documented, but the development of practical tools to predict the effects of fragmentation and design appropriate mitigation efforts has progressed only slowly. The Effective Area Model links field and remotely sensed data in a landscape model that permits comparison of the impacts of alternative land use strategies on animal populations. Through a GIS-interface, the model predicts changes in animal abundance given changes in landscape pattern. It is a flexible modeling approach that is empirically based and designed to capture many of the influences that emerge from heterogeneous landscapes and affect animal populations. The model is parameterized by measuring the density response of target organisms as a function of their location in the landscape. The value of a population attribute, such as abundance, is affected by the quality of the patch in which the individuals resides, as well as the context of the patch within the landscape. Our approach is map-based and it assumes that abundance can be characterized as a graded response dependent upon location relative to various habitat patches and patch boundaries.


The EAM requires two classes of input data: characterization of each species density response to habitat type and distance from edges, and a detailed habitat map. The habitat spatial data is incorporated as an Arc/Info® coverage, ArcView® shapefile or Arc/Info® GRID. The habitat map, portrayed at a landscape scale, is developed from remotely sensed and/or field data. Two decisions are made at this point: (1) the resolution of the map in terms of the number of habitat types to recognize; and (2) the grid cell size of the map. The model identifies all contiguous habitat patches and their location, then prompts the user to input species-specific response functions describing how organisms respond to habitat edges. It then projects values from the appropriate density response function across the landscape. Here we model density of yellow warbler, a riparian bird, comparing predictions of the EAM to predictions of a null model that ignores edge effects(see Figure 1; darker shades represent higher densities). The EAM predicts a density of 20 yellow warblers/ha in the modeled landscape, compared with only 7 birds/ha in the null model. Preliminary results from field studies testing these predictions support the EAM approach. For other species, the contrast between predictions of the EAM and null model are less pronounced, but still large enough to suggest that consideration of edge responses in heterogeneous landscapes is important when assessing habitat quality and estimating animal abundance.

An application example and management implications

The San Pedro River in southeastern Arizona is the last free-flowing river in the Southwest. It supports very high species diversity for many taxonomic groups and is an important seasonal habitat for Neotropical migrant birds. It is a threatened river, due to increased demand for water to supply agriculture and rapid urban growth. Groundwater depletion, due to excessive pumping, may have dramatic effects on riparian vegetation, leading to a decline in riparian habitats. We used the Effective Area Model to examine avian responses to habitat heterogeneity and landscape change along a 1.5 km x 3 km section of the upper San Pedro River. Given a hypothetical draw-down scenario, we assumed a simple type conversion from more mesic to more xeric habitat types following a drop in the level of the water table. We created a habitat map for the drawdown scenario and generated new density grids for the yellow warbler (Figure 2). Model results for this hypothetical scenario demonstrate possible applications of the Effective Area Model for predicting the outcomes of alternative management scenarios. The EAM provides an rapid, automated means of assessing the effects of shifts in patch size, shape, and edge characteristics, given a relatively small set of clearly stated assumptions regarding species responses and the spatial relationship of their habitats. The EAM provides decision-makers with a practical and useful tool for comparing the impacts if alternative land management plans.

ForestERA Project: Forest Ecosystem Restoration Analysis for the Southwest

The Forest Ecosystem Restoration Analysis (ForestERA) Project is a collaborative process that views forest ecosystems from a landscape perspective to discover better ways to restore their health and protect our communities. Stakeholders representing diverse backgrounds, priorities, needs, and points of view work together in small groups using the best scientific information and tools available. Participants view maps of spatial data to weigh factors such as fire, community, wildlife, and watershed, important in landscape-scale prioritization against one another. This process results in a detailed, integrated action plan that reflects multiple inputs, value and points of view.

A new approach to forest restoration in the American Southwest

Many scientists, forest managers, political leaders, and concerned citizens agree that there is urgent need to protect human communities from severe wildfire events and to restore natural fire regimes and ecosystem function in forests of the American Southwest. However, given the high cost of using selective thinning and prescribed fire to restore even a few hundred acres, it is appropriate to question whether any given site-specific project is really the best use of the limited resources available. Forest Ecosystem Restoration Analysis (ForestERA) is a set of powerful tools that enables the public and professionals to work productively together to bring sound science and a landscape perspective to the management and conservation of forested ecosystems and the protection of human communities from the threat of wildfire.

Learn more about ForestERA Projects at: 

Integrated spatial models of plant communities, fuels, fire, wildlife habitat, and climate change in the Sonoran Desert

Our new research programs—which encompass more than 30,000 square kilometers of the Sonoran Desert—seek to support the conservation and recovery of military and adjacent lands in southwestern Arizona, including areas managed by:

  • The Barry M. Goldwater Air Force Range
  • U.S. Army Yuma Proving Ground
  • Cabeza Prieta and Kofa National Wildlife Refuges
  • Organ Pipe Cactus National Monument
  • The Bureau of Land Management

We are developing cutting-edge techniques to generate new models and maps of fundamental ecological processes that are needed to reduce the impact of non-native invasive plants and fire, while improving habitat for threatened, endangered, and at-risk species, in the context of global change.

Working with colleagues from multiple federal and state agencies and the University of Massachusetts, Amherst, we are developing unique methods and tools which will integrate models of plant invasion, fire, wildlife habitat, and climate change to provide practical management recommendations for sustainable military testing and training activities. Our research will increase the ability of the Department of Defense and regional stakeholders to identify and implement spatially explicit, cross-jurisdictional planning and management strategies that are needed to reduce the impact of non-native invasive plants and fire, while improving habitat for threatened, endangered, and at-risk species, in the context of global change.

Specifically, our research involves extensive field sampling efforts to train and test regional- and landscape-scale models of native non-native invasive plant distribution, biomass, and fine-fuels production. Species-specific models will incorporate novel remote sensing techniques that identify species based on both phenological and spectral differences using satellite platforms of differing spatial, temporal, and spectral resolutions. Species distribution maps at landscape and regional scales will be used to assess biogeographical relationships of invasive plants to land use and climate, and to model changing invasion risk with global change. Biomass maps will be used to model fuel loads and to predict areas of high fire risk, hazard, and behavior. Scenario-based invasion and fire risk predictions will be integrated with models of resource use and habitat connectivity for sensitive wildlife species, including the Sonoran pronghorn. Results will be embedded into a highly flexible, spatial decision-support package to guide management on Department of Defense (DoD) and surrounding lands.

Landscape-scale models of wildlife-habitat relationships


  • the Arizona Game and Fish Department
  • U.S. Forest Service
  • National Park Service
  • Bureau of Land Management
  • other agencies and NGOs in Arizona, Nevada, and California

Our lab is working to develop spatially explicit predictive models of wildlife response to habitat and landscape change across extensive spatial scales. We use novel spatial and statistical techniques to estimate occupancy, abundance, or connectivity parameters for multiple species of sensitive wildlife, including, but not limited to:

  • American pronghorn
  • Merriam’s Turkey
  • Northern Goshawk
  • Songbirds
  • Puma
  • desert bighorn sheep
  • kit fox
  • and numerous other species

Land Use History and land cover change

The Land Use History of North America project (LUHNA) is a national effort sponsored by the U.S. Geological Survey and the National Aeronautics and Space Administration (NASA). Our lab has been involved in the development of the program since its inception in 1995. Principal products of the project are two web sites, one continental in scope, containing case studies from across North America, and another developed in our lab, focusing on our biogeographic region, the Colorado Plateau.

For more information about LUNHA visit one of the following sites.

LUHNA’s concept: 

LUHNA-Colorado Plateau: