Calculating Biologically Accurate Mitigation Credits: Insights from the California Tiger Salamander

Abstract:  Current conservation mitigation plans often fail to ensure full in-kind habitat replacement for endangered species, which suggests the need for improved methods for calculating mitigation credits. A simple, yet biologically meaningful method for calculating mitigation credits would be to let the number of mitigation credits assigned to a parcel of land scale with the reproductive value of the individuals occupying that parcel. This can be accomplished by dividing the population into 2 or more subdivisions with different reproductive values, calculating the densities of these subdivisions as a function of one or more habitat parameters, and then forming a weighted sum of these densities such that each density distribution is weighted by the reproductive value of its respective subdivision of the population. This weighted sum is the density distribution of reproductive value, and by integrating it over a particular parcel, one can determine the mitigation value of that parcel. We carried out this procedure for a population of California tiger salamanders ( Ambystoma californiense ), with distance from breeding site as our habitat parameter and the 3 visually identifiable age classes (adults, juveniles, and metamorphs) as our population subdivisions. This led to a density distribution of reproductive value that decreased exponentially with increasing distance from a breeding site. Mitigation strategies derived from this function will be more likely to ensure the persistence of California tiger salamander populations than current approaches, which assign all land within 1.6 km of a breeding site the same mitigation value. Use of the density distribution of reproductive value as a basis for mitigation plans is a procedure that can be applied to all endangered species, and it should improve the quality of mitigation decisions.     

Habitat Suitability Models and the Shortfall in Conservation Planning for African Vertebrates

Abstract:  Ongoing loss of biodiversity requires identifying large-scale conservation priorities, but the detailed information on the distribution of species required for this purpose is often missing. We present a systematic reserve selection for 1223 African mammals and amphibians in which habitat suitability models are used as estimates of the area occupied by species. In the framework of the World Conservation Union (IUCN) Global Amphibian Assessment and IUCN Global Mammal Assessment, we collected the geographic range (extent of occurrence) and habitat preferences for each species. We used the latter to build species-specific habitat suitability models inside geographic ranges, and for 181 species we verified the models by comparing suitability levels to presence-absence data collected in the field. We then used the suitable areas as estimators of the area of occupancy and compared the results of systematic reserve selection based on geographic ranges to those based on estimated areas of occupancy. Our results showed that the reserve system would need a 30-100% expansion to achieve minimal conservation targets, concentrated in the tropics, where species richness reaches a maximum. Comparative analyses revealed that using geographic ranges, which overestimate the area occupied by species, underestimates the total amount of area that needs to be conserved. The area selected for conservation doubled when we used the estimated area of occupancy in place of the geographic ranges. This happened because the suitable areas potentially occupied by each species overlapped less than their geographic ranges. As a result, any given protected area contained fewer species than predicted by the analysis of ranges. Because species are more specialized than our estimates of distribution based on extent of occurrence suggest, we propose that this is a general effect in systematic conservation planning.     

Assessing Conservation Management's Evidence Base: a Survey of Management-Plan Compilers in the United Kingdom and Australia

Abstract:  Conservation management is becoming increasingly resource intensive as threats to biodiversity grow through habitat destruction, habitat disturbance, and overexploitation. To achieve successful conservation and sustainable use of natural resources, we need to scientifically evaluate the effectiveness of conservation interventions and provide an efficient framework through which scientific evidence can be used to support decision making in policy and practice. We conducted the first formal assessment of the extent to which scientific evidence is used in conservation management through a questionnaire survey and follow-up interviews of compilers of protected-area management plans from major conservation organizations within the United Kingdom and Australia. Our survey results show that scientific information is not being used systematically to support decision making largely because it is not easily accessible to decision makers. This, in combination with limited monitoring and evaluation of effectiveness of management interventions, results in the majority of decisions being based on experience rather than on evidence. To address this problem we propose using an evidence-based framework adapted from that used in the health services and explain how we are currently putting an equivalent framework into practice by establishing review and dissemination units to serve the conservation sector.     

Knowing But Not Doing: Selecting Priority Conservation Areas and the Research–Implementation Gap

Abstract: Conservation assessment is a rapidly evolving discipline whose stated goal is the design of networks of protected areas that represent and ensure the persistence of nature (i.e., species, habitats, and environmental processes) by separating priority areas from the activities that degrade or destroy them. Nevertheless, despite a burgeoning scientific literature that ever refines these techniques for allocating conservation resources, it is widely believed that conservation assessments are rarely translated into actions that actually conserve nature. We reviewed the conservation assessment literature in peer‐reviewed journals and conducted survey questionnaires of the authors of these studies. Two‐thirds of conservation assessments published in the peer‐reviewed scientific literature do not deliver conservation action, primarily because most researchers never plan for implementation. This research–implementation gap between conservation science and real‐world action is a genuine phenomenon and is a specific example of the “knowing–doing gap” that is widely recognized in management science. Given the woefully inadequate resources allocated for conservation, our findings raise questions over the utility of conservation assessment science, as currently practiced, to provide useful, pragmatic solutions to conservation planning problems. A reevaluation of the conceptual and operational basis of conservation planning research is urgently required. We recommend the following actions for beginning a process for bridging the research–implementation gap in conservation planning: (1) acknowledge the research–implementation gap is real, (2) source research questions from practitioners, (3) situate research within a broader conservation planning model, (4) expand the social dimension of conservation assessments, (5) support conservation plans with transdisciplinary social learning institutions, (6) reward academics for societal engagement and implementation, and (7) train students in skills for “doing” conservation.     

Incorporating the Effects of Socioeconomic Uncertainty into Priority Setting for Conservation Investment

Abstract:  Uncertainty in the implementation and outcomes of conservation actions that is not accounted for leaves conservation plans vulnerable to potential changes in future conditions. We used a decision-theoretic approach to investigate the effects of two types of investment uncertainty on the optimal allocation of global conservation resources for land acquisition in the Mediterranean Basin. We considered uncertainty about (1) whether investment will continue and (2) whether the acquired biodiversity assets are secure, which we termed transaction uncertainty and performance uncertainty, respectively. We also developed and tested the robustness of different rules of thumb for guiding the allocation of conservation resources when these sources of uncertainty exist. In the presence of uncertainty in future investment ability (transaction uncertainty), the optimal strategy was opportunistic, meaning the investment priority should be to act where uncertainty is highest while investment remains possible. When there was a probability that investments would fail (performance uncertainty), the optimal solution became a complex trade-off between the immediate biodiversity benefits of acting in a region and the perceived longevity of the investment. In general, regions were prioritized for investment when they had the greatest performance certainty, even if an alternative region was highly threatened or had higher biodiversity value. The improved performance of rules of thumb when accounting for uncertainty highlights the importance of explicitly incorporating sources of investment uncertainty and evaluating potential conservation investments in the context of their likely long-term success.     

Mapping Human and Social Dimensions of Conservation Opportunity for the Scheduling of Conservation Action on Private Land

Abstract Spatial prioritization techniques are applied in conservation‐planning initiatives to allocate conservation resources. Although typically they are based on ecological data (e.g., species, habitats, ecological processes), increasingly they also include nonecological data, mostly on the vulnerability of valued features and economic costs of implementation. Nevertheless, the effectiveness of conservation actions implemented through conservation‐planning initiatives is a function of the human and social dimensions of social‐ecological systems, such as stakeholders’ willingness and capacity to participate. We assessed human and social factors hypothesized to define opportunities for implementing effective conservation action by individual land managers (those responsible for making day‐to‐day decisions on land use) and mapped these to schedule implementation of a private land conservation program. We surveyed 48 land managers who owned 301 land parcels in the Makana Municipality of the Eastern Cape province in South Africa. Psychometric statistical and cluster analyses were applied to the interview data so as to map human and social factors of conservation opportunity across a landscape of regional conservation importance. Four groups of landowners were identified, in rank order, for a phased implementation process. Furthermore, using psychometric statistical techniques, we reduced the number of interview questions from 165 to 45, which is a preliminary step toward developing surrogates for human and social factors that can be developed rapidly and complemented with measures of conservation value, vulnerability, and economic cost to more‐effectively schedule conservation actions. This work provides conservation and land management professionals direction on where and how implementation of local‐scale conservation should be undertaken to ensure it is feasible.     

Conservation Deficits for the Continental United States: an Ecosystem Gap Analysis

Abstract:  Few attempts have been made to analyze the status of conservation efforts at a continental scale, mainly because of the lack of high-quality data sets at this scale. Given that land management agencies want to prioritize conservation efforts and spend limited resources wisely, we recognized the need to undertake a national gap analysis. We developed the most detailed national vegetation cover map feasible to analyze the degree of representation of ecosystem analysis units (an initial representation of ecosystem types) in the network of conservation lands for the continental United States. We combined The Nature Conservancy's ecoregions with the natural land-cover types of the National Land Cover Data Set and examined the conservation status of each combination. The majority of ecosystem analysis units have a small percentage of their total area residing in lands that are managed to support biodiversity. The median percentage of area conserved on status 1 and 2 lands (highest of four levels of protection) as designated by the Gap Analysis Program for the 554 ecosystem analysis units is 4.0% (SD 18.1%). This finding, which highlights our national conservation deficits, points to the need to address the size and diversity of the conservation estate.     

GIS and geostatistics: Essential partners for spatial analysis

Initially, geographical information systems (GIS) concentrated on two issues: automated map making, and facilitating the comparison of data on thematic maps. The first required high quality graphics, vector data models and powerful data bases, the second is based on grid cells that can be manipulated by suites of mathematical operators collectively termed map algebra. Both kinds of GIS are widely available and are taught in many universities and technical colleges. After more than 20 years of development, most standard GIS provide both kinds of functionality and good quality graphic display, but until recently they have not included the methods of statistics and geostatistics as tools for spatial analysis. Recently, standard statistical packages have been linked to GIS for both exploratory data analysis and statistical analysis and hypothesis testing. Standard statistical packages include methods for the analysis of random samples of cases or objects that are not necessarily co-located in space—if the results of statistical analysis display a spatial pattern then that is because the underlying data also share that pattern. Geostatistics addresses the need to make predictions of sampled attributes (i.e., maps) at unsampled locations from sparse, often expensive data. To make up for lack of hard data geostatistics has concentrated on the development of powerful methods based on stochastic theory. Though there have been recent moves to incorporate ancillary data in geostatistical analyses, insufficient attention has been paid to using modern methods of data display for the visualization of results. GIS can serve geostatistics by aiding geo-registration of data, facilitating spatial exploratory data analysis, providing a spatial context for interpolation and conditional simulation, as well as providing easy-to-use and effective tools for data display and visualization. The value of geostatistics for GIS lies in the provision of reliable interpolation methods with known errors, methods of upscaling and generalization, and for supplying multiple realizations of spatial patterns that can be used in environmental modeling. These stochastic methods are improving understanding of how errors in models of spatial processes accrue from errors in data or incompleteness in the structure of the models. New developments in GIS, based on ideas taken from map algebra, cellular automata and image analysis are providing high level programming languages for modeling dynamic processes such as erosion or the development of alluvial fans and deltas. Research has demonstrated that these models need stochastic inputs to yield realistic results. Non-stochastic tools such as fuzzy subsets have been shown to be useful for spatial analysis when probabilistic approaches are inappropriate or impossible. The conclusion is that in spite of differences in history and approach, the linkage of GIS, statistics and geostatistics provides a powerful, and complementary suite of tools for spatial analysis in the agricultural, earth and environmental sciences.     

Incorporating connectivity into conservation planning for the optimal representation of multiple species and ecosystem services

Conservation planning tends to focus on protecting species’ ranges or landscape connectivity but seldom both—particularly in the case of diverse taxonomic assemblages and multiple planning goals. Therefore, information on potential trade-offs between maintaining landscape connectivity and achieving other conservation objectives is lacking. We developed an optimization approach to prioritize the maximal protection of species’ ranges, ecosystem types, and forest carbon stocks, while also including habitat connectivity for range-shifting species and dispersal corridors to link protected area. We applied our approach to Sabah, Malaysia, where the state government mandated an increase in protected-area coverage of approximately 305,000 ha but did not specify where new protected areas should be. Compared with a conservation planning approach that did not incorporate the 2 connectivity features, our approach increased the protection of dispersal corridors and elevational connectivity by 13% and 21%, respectively. Coverage of vertebrate and plant species’ ranges and forest types were the same whether connectivity was included or excluded. Our approach protected 2% less forest carbon and 3% less butterfly range than when connectivity features were not included. Hence, the inclusion of connectivity into conservation planning can generate large increases in the protection of landscape connectivity with minimal loss of representation of other conservation targets.