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Geology topics

Jay E. Diffendorfer

Publications and source records attributed to Jay E. Diffendorfer.

At least 55 records · Page 3Linked to original sources
USGS2020

A continuously updated, geospatially rectified database of utility-scale wind turbines in the United States

Nearly 60,000 utility-scale wind turbines are installed in the United States as of July, 2019, representing over 97 gigawatts of electric power capacity; US wind turbine installations continue to grow at a rapid pace. Yet, until April 2018, no publicly-available, regularly updated data source existed to describe those turbines and their locations. Under a cooperative research and development agreement, analysts from three organizations collaborated to develop and release the United States Wind Turbine Database (USWTDB) - a publicly available, continuously updated, spatially rectified data source of locations and attributes of utility-scale wind turbines in the United States. Technical specifications and wind facility data, incorporated from five sources, undergo rigorous quality control. The location of each turbine is visually verified using high-resolution aerial imagery. The quarterly-updated data are available in a variety of formats, including an interactive web application, comma-separated values (CSV), shapefile, and application programming interface (API). The data are used widely by academic researchers, engineers and developers from wind energy companies, government agencies, planners, educators, and the general public.

Scientific Data↗
USGS2020

Challenges for leveraging citizen science to support statistically robust monitoring programs

Large samples and long time series are often needed for effective broad-scale monitoring of status and trends in wild populations. Obtaining those sample sizes can be more feasible when volunteers contribute to the dataset, but volunteer-selected sites are not always representative of a population. Previous work to account for biased site selection has relied on knowledge of covariates to explain differences between site types, but such knowledge is often unavailable. For cases where relevant covariates have not been defined, we used a simulation study to identify the consequences of including non-probabilistically selected sites (NP sites) in addition to sites selected from a probability-based design (P sites), test modeling frameworks that might correct for biases, and evaluate whether those frameworks could allow NP sites to reduce the sampling requirement for P sites and potentially reduce costs of monitoring. We informed the simulation with pilot data from surveys of monarch butterflies and their obligate larval host plant, milkweed. We found strong biases in NP sites versus P sites in density and trends of monarchs and milkweed. Modeling frameworks that accounted for site type with a group effect or that strongly downweighted NP sites successfully produced unbiased estimates. However, sampling more NP sites typically did not improve accuracy or precision, and adding NP sites sometimes required also adding P sites to prevent biases. Further work on novel modeling frameworks would be useful to allow citizen-science data to contribute useful information to conservation.

Biological Conservation↗
USGS2020

Quantifying the contribution of habitats and pathways to a spatially structured population facing environmental change

The consequences of environmental disturbance and management are difficult to quantify for spatially structured populations because changes in one location carry through to other areas as a result of species movement. We develop a metric, G , for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different from other contribution metrics, as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences the ordering of node contribution. We find that habitats within which all individuals reside during one season are the most important to short-term network growth under complete removal scenarios, whereas the central breeding region contributes most to population growth over all but the strongest disturbances. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations. use changes in one location carry through to other areas due to species movement. We develop a metric, G, for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different than other contribution metrics as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences ordering of node contribution. We find that habitats through which all migrants flow are the most important to short-term network growth under complete-removal scenarios. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations.

American Naturalist↗
USGS2020

Learning from real-world experience to understand renewable energy impacts to wildlife

The project team sought to use real-world data to understand adverse effects to wildlife of renewable energy production that is critical to meeting California’s climate and clean energy goals. The project had three main components. First, a systematic literature review studied 20 peer-reviewed publications and 612 reports from other nonreviewed sources from 231 wind and solar facilities in North America. Within California, 50 percent of facilities collected pre- and post-construction data, 30 percent had experimental study designs, and fewer than 7 percent estimated detection probability during habitat use surveys. Mitigation at wind power plants focused on repowering to reduce risk to soaring birds and at solar facilities emphasized wildlife deterrence and compensatory mitigation. Second, the authors developed a best-practices approach to employ environmental isotopes (for example, hydrogen obtained from animal tissue) and rescaling functions (a statistical approach to modeling the relationship between variables) to assign individual birds or bats to their place of origin. The team applied this approach to feathers from 411 individuals of 12 species killed at wind facilities and 515 individuals of 19 species killed at solar facilities. From 24 percent to 100 percent (mean +/- SD = 49 percent +/- 33 percent) and 25 percent to 100 percent (73 percent +/- 25 percent) of birds grew feathers at a location outside the collection site at wind and solar facilities, respectively. Third, the authors constructed Bayesian integrated population models (probability models) for 29 focal species affected by wind or solar energy generation in California. Species predominantly local in origin generally had lower population growth rates than did species that were predominantly nonlocal in origin. These patterns illustrate the complex linkages between behavioral ecology, vulnerability to mortality, and population-level impacts to wildlife from fatalities at renewable energy facilities. This project benefits the renewable energy sector by providing a framework and specific tools for understanding environmental impacts of renewable energy generation.

California↗
USGS2019

Is the timing, pace and success of the monarch migration associated with sun angle?

A basic question concerning the monarch butterfly’s fall migration is which monarchs succeed in reaching overwintering sites in Mexico, which fail—and why. We document the timing and pace of the fall migration, ask whether the sun’s position in the sky is associated with the pace of the migration, and whether timing affects success in completing the migration. Using data from the Monarch Watch tagging program, we explore whether the fall monarch migration is associated with the daily maximum vertical angle of the sun above the horizon (Sun Angle at Solar Noon, SASN) or whether other processes are more likely to explain the pace of the migration. From 1998 to 2015, more than 1.38 million monarchs were tagged and 13,824 (1%) were recovered in Mexico. The pace of migration was relatively slow early in the migration but increased in late September and declined again later in October as the migrating monarchs approached lower latitudes. This slow-fast-slow pacing in the fall migration is consistent with monarchs reaching latitudes with the same SASN, day after day, as they move south to their overwintering sites. The observed pacing pattern and overall movement rates are also consistent with monarchs migrating at a pace determined by interactions among SASN, temperature, and daylength. The results suggest monarchs successfully reaching the Monarch Butterfly Biosphere Reserve (MBBR) migrate within a “migration window” with an SASN of about 57° at the leading edge of the migration and 46° at the trailing edge. Migrants reaching locations along the migration route with SASN outside this migration window may be considered early or late migrants. We noted several years with low overwintering abundance of monarchs, 2004 and 2011–2014, with high percentages of late migrants. This observation suggests a possible effect of migration timing on population size. The migration window defined by SASN might serve as a framework against which to establish the influence of environmental factors on the size, geographic distribution, and timing of past and future fall migrations.

Frontiers in Ecology and Evolution↗
USGS2019

Challenges for monitoring the extent and land use/cover changes in monarch butterflies’ migratory habitat across the United States and Mexico

This paper presents a synopsis of the challenges and limitations presented by existing and emerging land use/ land cover (LULC) digital data sets when used to analyze the extent, habitat quality, and LULC changes of the monarch (Danaus plexippus) migratory habitat across the United States of America (US) and Mexico. First, the characteristics, state of the knowledge, and issues related to this habitat are presented. Then, the characteristics of the existing and emerging LULC digital data sets with global or cross-border coverage are listed, followed by the data sets that cover only the US or Mexico. Later, we discuss the challenges for determining the extent, habitat quality, and LULC changes in the monarchs’ migratory habitat when using these LULC data sets in conjunction with the current state of the knowledge of the monarchs’ ecology, behavior, and foraging/roosting plants used during their migration. We point to approaches to address some of these challenges, which can be categorized into: (a) LULC data set characteristics and availability; (b) availability of ancillary land management information; (c) ability to construct accurate forage suitability indices for their migration habitat; and (d) level of knowledge of the ecological and behavioral patterns of the monarchs during their journey.

Land↗
USGS2019

Review of indicators for comparing environmental effects across energy sources

Robust, quantitative comparisons of environmental effects across energy sources can support development of energy planning strategies that meet growing demand while managing and minimizing undesirable effects on environmental resources. Multicriteria analyses of energy systems often use a suite of indicators to make such comparisons, but those indicators and their units of measure vary among studies. We reviewed 179 papers that described or applied energy indicators to compare environmental effects of different primary energy sources to answer four questions: (1) what environmental indicators have been used in multicriteria energy-source comparisons? (2) across studies, how consistently are these indicators used to quantify effects? (3) to what degree are different effects accounted for across energy sources and locations? and (4) how comprehensive are indicators in terms of assessing known environmental effects? For reviewed studies, we quantified the number of unique indicators and the diversity of indicators used to measure different effects. We also recorded the specific measurement units applied to quantify each indicator, the energy sources evaluated, and the continent where each study was conducted. While we found that many environmental effects of energy development have been analyzed across multiple sources, indicators were frequently measured, interpreted, and applied in ways that are not directly comparable, and some known environmental effects were infrequently assessed. We also found an emphasis on applying indicators to renewable energy sources; assessing current and potential energy sources, both renewable and nonrenewable, would greatly clarify the full suite of tradeoffs among sources and can inform energy development strategies that minimize adverse environmental effects. Overall, our review indicated that making comprehensive comparisons of the effects of energy development across sources may require efforts to standardize how effects are measured, synthesize effects literature into an open-source database, expand the range of environmental effects analyzed, and establish consistent frameworks for comparison.

Environmental Research Letters↗
USGS2019

Balancing sampling intensity against spatial coverage for a community science monitoring programme

Community science is an increasingly integral part of biodiversity research and monitoring, often achieving broad spatial and temporal coverage but lower sampling intensity than studies conducted by professional scientists. When designing a community‐science monitoring programme, careful assessment of sampling designs that could be both feasible and successful at meeting programme goals is essential. Monarch butterflies ( Danaus plexippus ) are the focus of several successful community‐science projects in the U.S., but broader coverage is needed to monitor breeding areas and explain population declines observed in overwintering areas. The U.S. Monarch Conservation Science Partnership's Integrated Monarch Monitoring Program (IMMP) will representatively monitor monarchs and milkweed across North America. We performed a simulation‐based power analysis to predict trade‐offs between sampling breadth (number of sites and years) and sampling intensity (number of visits or subplots per site and year) for the IMMP. We evaluated whether each sampling design would produce sufficient statistical power to detect population trends and differences among land‐use sectors in densities of milkweed, monarch eggs, and adult monarchs. Sampling breadth had much stronger effects than sampling intensity on statistical power for all three monitoring targets. Depending on land‐use sector, monitoring 400–800 sites over 10–15 years would detect trends in densities of milkweed and adult monarchs, but no scenarios were successful for monarch eggs. Sampling 400–800 sites would also detect small (for adult monarchs) to large (for milkweed) differences among land‐use sectors in density of all three monitoring targets within the first 2–5 years. As more data become available from the IMMP, the sampling goals can be updated. Synthesis and applications . Careful sample design is an essential step in developing a successful monitoring programme. For monarchs and milkweed, we found that sampling breadth (number of sites and years) had a much stronger effect on statistical power than sampling intensity (number of visits or subsamples per site), suggesting field protocols could be tailored to maximize recruitment and retention of volunteers by minimizing the effort required to monitor each site. Many long‐term monitoring programmes might similarly benefit from evaluating the statistical trade‐offs between sampling breadth and intensity in their sampling designs.

Journal of Applied Ecology↗
USGS2019

A Methodology to Assess the National and Regional Impacts of U.S. Wind Energy Development on Birds and Bats

This scientific investigations report describes an effort by the U.S. Geological Survey (USGS) that used research, monitoring data, and modeling to develop a methodology to assess both the current and future population-level consequences of wind energy development on species of birds and bats that are present in the United States during any part of their life cycle. The methodology is currently applicable to birds and bats, focuses primarily on the effects of collisions with turbines, and can be applied to any species that breeds in, migrates through, or otherwise uses any part of the United States. The methodology assesses species at the national and regional scales and identifies those species potentially in need of more detailed study, as well as those species that are likely at low risk from wind energy development. This approach is fundamentally different from existing methods focusing on impacts at individual facilities. This report supersedes USGS Scientific Investigations Report 2015–5066 by the same authors, which described a preliminary version of the methodology. Following reviews of the preliminary methodology by a panel of external experts, public comments, and additional internal review, the methodology was revised and finalized. The three components of the refined methodology described in this new report rely on publicly available fatality information, population estimates, species range maps, turbine location data, biological characteristics of species, and population models. First, three metrics are combined to determine direct and indirect relative effects from wind energy facilities to generate a list of species scores. Second, a generic population model estimates the expected change in population trend caused by the additive mortality from collisions with wind turbines. Third, the methodology combines an estimate of observed fatalities and an estimate of potential biological removal to assess the possibility of a decrease in population size. The latter two components are quantitative. In a test case, the methodology was used to analyze data for six bird species and three bat species. Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable or may require further study. These assumptions should be carefully considered when using outputs from the methodology. Increases in the quality of data for fatalities from collisions with wind turbines, species distributions, abundance, and demography will likely improve results for uses of the methodology. The methodology’s design identifies and prioritizes a subset of the bird and bat species that may experience population-level impacts from collisions with wind turbines, both currently and from future wind energy development in the United States. Results of an assessment using this methodology could focus future research to improve our understanding of those impacts and to guide avoidance and minimization strategies. In addition, this methodology can be used to identify species for more intensive demographic modeling or to highlight those species that may not require any additional research because effects of wind energy development on their populations are projected to be small. The effects of wind energy facilities on nine unidentified species used in the test case described in this report have not been assessed. Their data were simply used to show the application of the methodology to real-world data and the types of outputs it would produce.

Scientific Investigations Report↗
USGS2019

Geographic context affects the landscape change and fragmentation caused by wind energy facilities

Wind energy generation causes transformation of landscapes as new roads, pads, and transmission lines are constructed. Limiting the landscape change and fragmentation caused by these facilities likely minimizes impacts to biodiversity and sensitive wildlife species. We examined the effects of wind energy facilities’ geographic context on changes in landscape patterns. We digitized the footprints of 39 wind facilities and the surrounding land cover using high-resolution imagery. We then measured landscape pattern before and after facility construction using 3 metrics associated with species responses to habitat loss and fragmentation (amount, core area, and connectivity of undeveloped land) within 1km around newly constructed turbines and roads. New facilities decreased the amount of undeveloped land, on average, by just 1.8% while changes in metrics of landscape pattern were relatively much larger (50 to 140%). Statistical models indicated levels of pre-construction development were a key factor explaining the impact of new wind facilities on landscape metrics, with pre-construction road networks, turbine spacing, and topography having smaller influences. As the proportion of developed land around facilities increased, a higher proportion of the facility utilized pre-construction developed land and a lower density of new roads were built, resulting in smaller impacts to undeveloped landscapes. Building of new road networks was also a predictor of landscape fragmentation. Density of new roads was higher in places with little pre-existing development and may be influenced by facility design. Utilizing existing development and carefully placing turbines may provide opportunities to minimize the impacts of new wind energy facilities.

PeerJ↗
USGS2019

Biases in the literature on direct wildlife mortality from energy development

Comparing environmental impacts of different energy sources can inform energy investments and environmental conservation. Direct wildlife mortality from energy development receives substantial public and scientific attention, but it is unclear whether rigorous comparisons of mortality among energy sources are possible. To address this question, we compared availability of mortality studies among energy sources, wildlife groups, and regions, and assessed comparability of mortality indicators measured. Whereas wind and hydropower have received substantial mortality research exceeding their proportional contributions to global energy production, coal, oil and gas, and bioenergy have received fewer studies and are underrepresented relative to their contributions. Furthermore, research is biased toward birds and fish and North America and Europe, and there are inconsistencies among energy sources and limited replication of most indicators measured. These results indicate that rigorous comparisons of direct wildlife mortality among energy sources are not currently possible and highlight research needs for improving understanding of energy's environmental impacts.

BioScience↗
USGS2019

Historical land use and land cover for assessing the northern Colorado Front Range urban landscape

We describe historical land-use and land-cover (LULC) maps for the northern Colorado urban Front Range. The Front Range urban landscape is diverse and interspersed with highly productive agriculture as well as natural land cover types including evergreen forest in the Rocky Mountain foothills and Great Plains grassland. To understand the dynamics of urban growth, raster maps were created at a 1 meter resolution for each of four time steps, nominally 1937, 1957, 1977, and 1997. In total, 38 detailed LULC classes were identified using manual interpretation techniques, aerial photographs, historical maps, and other available information. The maps provide high resolution spatial data for understanding the historical progression of urbanization and will allow further analysis of the effects of urban growth on social and ecological systems.

Colorado↗
USGS2019

Multi-country willingness to pay for transborder migratory species conservation: A case study of Northern Pintails

Using contingent valuation, we estimated willingness to pay (WTP) in Canada, Mexico, and the United States to protect habitat for Northern Pintails (hereafter pintails), a migratory waterfowl species that provides benefits to and requires habitat in the three countries. Our study contributes to research on spatial subsidies by measuring the value of migratory species habitat. While WTP to protect pintail habitat is highest in the household's own country, there also is substantial WTP to protect pintail habitat in the other two countries. Canadian households' annual WTP is US$12 (all dollar values are in 2016 US dollars) to stabilize the pintail population in Canada, US$4 in Mexico, and US$5 in the U.S. Mexican households would pay US$8 in Mexico, US$5 in the U.S., and US$5 in Canada. U.S. households would pay US$28 in the U.S., US$18 in Canada, and US$16 in Mexico. WTP is statistically significantly higher in all three countries to increase the pintail population. WTP as a percentage of household income is statistically significantly higher for respondents in Mexico. WTP is logically related to explanatory variables such as respondent income, interest in hunting waterfowl, and financial support of wildlife conservation organizations. This study has important implications for conducting economic analyses of habitat issues of transboundary migratory species' conservation and to more effectively and equitably achieve conservation goals.

Ecological Economics↗
USGS2019

Quantifying source and sink habitats and pathways in spatially structured populations: A generalized modelling approach

The ability to classify habitats and movement pathways as sources or sinks is an important part of the decision making process for the conservation of spatially structured populations. Diverse approaches have been used to quantify the importance of habitats and pathways in a spatial network, however these approaches have been limited by a lack of general applicability across life histories and movement strategies. In this paper we develop a generalized per-capita contribution metric, the C-metric, for quantifying habitat and pathway quality. This metric is novel in that it can be applied broadly to both metapopulations and migratory species. It allows for any number of age and sex classes, unlimited number of seasons or time intervals within the annual cycle, and for density-dependent parameters. We demonstrate the flexibility of the metric with four case studies: a hypothetical metapopulation, elk of the Greater Yellowstone Ecosystem, northern pintail ducks in North America, and the eastern population of the monarch butterfly. General computer code to calculate the per-capita contribution metric is provided. We demonstrate that the C-metric is useful for identifying source and sink habitats in a network and suggest that the C-metric could be supplemented by some measure of network structure for a more robust description of habitat or pathway importance.

Ecological Modelling↗
USGS2019

Impacts to wildlife of wind energy siting and operation in the United States

Electricity from wind energy is a major contributor to the strategy to reduce greenhouse gas emissions from fossil fuel use and thus reduce the negative impacts of climate change. Wind energy, like all power sources, can have adverse impacts on wildlife. After nearly 25 years of focused research, these impacts are much better understood, although uncertainty remains. In this report, we summarize positive impacts of replacing fossil fuels with wind energy, while describing what we have learned and what remains uncertain about negative ecological impacts of the construction and operation of land-based and offshore wind energy on wildlife and wildlife habitat in the U.S. Finally, we propose research on ways to minimize these impacts. TO SUMMARIZE: 1 Environmental and other benefits of wind energy include near-zero greenhouse gas emissions, reductions of other common air pollutants, and little or no water use associated with producing electricity from wind energy. Various scenarios for meeting U.S. carbon emission reduction goals indicate that a four- to five-fold expansion of land-based wind energy from the current 97 gigawatts (GW) by the year 2050 is needed to minimize temperature increases and reduce the risk of climate change to people and wildlife. 2 Collision fatalities of birds and bats are the most visible and measurable impacts of wind energy production. Current estimates suggest most bird species, especially songbirds, are at low risk of population-level impacts. Raptors as a group appear more vulnerable to collisions. Population-level impacts on migratory tree bats are a concern, and better information on population sizes is needed to evaluate potential impacts to these species. Although recorded fatalities of cave-dwelling bat species are typically low at most wind energy facilities, additional mortality from collisions is a concern given major declines in these species due to white-nose syndrome (WNS). Assessments of regional and cumulative fatality impacts for birds and bats have been hampered by the lack of data from areas with a high proportion of the nation’s installed wind energy capacity. Efforts to expand data accessibility from all regions are underway, and this greater access to data along with improvements in statistical estimators should lead to improved impact assessments. 3 Habitat impacts of wind energy development are difficult to assess. An individual wind energy facility may encompass thousands of acres, but only a small percentage of the landscape within the project area is directly transformed. If a project is sited in previously undisturbed habitat, there is concern for indirect impacts, such as displacement of sensitive species. Studies to date indicate displacement of some species, but the long-term population impacts are unknown. 4 Offshore wind energy development in the U.S. is just beginning. Studies at offshore wind facilities in Europe indicate some bird and marine mammal species are displaced from project areas, but substantial uncertainty exists regarding the individual or population-level impacts of this displacement. Bird and bat collisions with offshore turbines are thought to be less common than at terrestrial facilities, but currently the tools to measure fatalities at offshore wind energy facilities are not available. The wind energy industry, state and federal agencies, conservation groups, academia, and scientific organizations have collaborated for nearly 25 years to conduct the research needed to improve our understanding of risk to wildlife and to avoid and minimize that risk. Efforts to reduce the uncertainty about wildlife risk must keep up withthe pace and scale of the need to reduce carbon emissions. This will require focusing our research priorities and increasing the rate at which we incorporate research results into the development and validation of best practices for siting and operating wind energy facilities.

Issues in Ecology↗
USGS2018

Consequences of ignoring spatial variation in population trend when conducting a power analysis

Long-term, large-scale monitoring programs are becoming increasingly common to document status and trends of wild populations. A successful program for monitoring population trend hinges on the ability to detect the trend of interest. Power analyses are useful for quantifying the sample size needed for trend detection, given expected variation in the population. Four components of variation (within-year variation at a given site, interannual variation within a site, variation among sites in the interannual variation, and variation among sites in mean abundance or density) are commonly considered in power analyses for population trend, but a fifth is not: variation among sites in the local trend. Spatial variation in trend is expected to reduce statistical power, but the magnitude of this reduction has not been fully explored. We used computer simulations to evaluate the consequences of ignoring spatial variation in trend under a variety of sampling designs and wide ranges of other components of variation. The effect of spatial variation in trend on power was minor when other input parameters took extreme values that made the trend either very difficult or very easy to detect. However, at moderate values of the other parameters, spatial variation in trend had a strong effect, reducing statistical power by up to 60%. In some cases, ignoring spatial variation in trend resulted in an 80% probability of a Type I error (falsely detecting a trend in a stable population). Spatial variation in trend is therefore an important consideration when designing a long-term monitoring program for many species, especially those affected by local conditions at sites that are repeatedly surveyed. If variation in trend is ignored, as in most previous power analyses, the recommended sampling design will likely be insufficient to detect the trend of interest and lead to potentially false conclusions of a stable population.

Ecography↗
USGS2018

Prioritizing conserved areas threatened by wildfire and fragmentation for monitoring and management

In many parts of the world, the combined effects of habitat fragmentation and altered disturbance regimes pose a significant threat to biodiversity. This is particularly true in Mediterranean-type ecosystems (MTEs), which tend to be fire-prone, species rich, and heavily impacted by human land use. Given the spatial complexity of overlapping threats and species’ vulnerability along with limited conservation budgets, methods are needed for prioritizing areas for monitoring and management in these regions. We developed a multi-criteria Pareto ranking methodology for prioritizing spatial units for conservation and applied it to fire threat, habitat fragmentation threat, species richness, and genetic biodiversity criteria in San Diego County, California, USA. We summarized the criteria and Pareto ranking results (from west to east) within the maritime, coastal, transitional, inland climate zones within San Diego County. Fire threat increased from the maritime zone eastward to the transitional zone, then decreased in the mountainous inland climate zone. Number of fires and fire return interval departure were strongly negatively correlated. Fragmentation threats, particularly road density and development density, were highest in the maritime climate zone, declined towards the east, and were positively correlated. Species richness criteria showed distributions among climate zones similar to those of the fire threat variables. When using species richness and fire threat criteria, most lower-ranked (higher conservation priority) units occurred in the coastal and transitional zones. When considering genetic biodiversity, lower-ranked units occurred more often in the mountainous inland zone. With Pareto ranking, there is no need to select criteria weights as part of the decision-making process. However, negative correlations and larger numbers of criteria can result in more units assigned to the same rank. Pareto ranking is broadly applicable and can be used as a standalone decision analysis method or in conjunction with other methods.

California↗