The Why,What, and How of Global Biodiversity Indicators Beyond the 2010 Target

Abstract: The 2010 biodiversity target agreed by signatories to the Convention on Biological Diversity directed the attention of conservation professionals toward the development of indicators with which to measure changes in biological diversity at the global scale. We considered why global biodiversity indicators are needed, what characteristics successful global indicators have, and how existing indicators perform. Because monitoring could absorb a large proportion of funds available for conservation, we believe indicators should be linked explicitly to monitoring objectives and decisions about which monitoring schemes deserve funding should be informed by predictions of the value of such schemes to decision making. We suggest that raising awareness among the public and policy makers, auditing management actions, and informing policy choices are the most important global monitoring objectives. Using four well‐developed indicators of biological diversity (extent of forests, coverage of protected areas, Living Planet Index, Red List Index) as examples, we analyzed the characteristics needed for indicators to meet these objectives. We recommend that conservation professionals improve on existing indicators by eliminating spatial biases in data availability, fill gaps in information about ecosystems other than forests, and improve understanding of the way indicators respond to policy changes. Monitoring is not an end in itself, and we believe it is vital that the ultimate objectives of global monitoring of biological diversity inform development of new indicators.     

Making conservation decisions under uncertainty for the persistence of multiple species.

Population models for multiple species provide one of the few means of assessing the impact of alternative management options on the persistence of biodiversity, but they are inevitably uncertain. Is it possible to use population models in multiple-species conservation planning given the associated uncertainties? We use information-gap decision theory to explore the impact of parameter uncertainty on the conservation decision when planning for the persistence of multiple species. An information-gap approach seeks robust outcomes that are most immune from error. We assess the impact of uncertainty in key model parameters for three species, whose extinction risks under four alternative management scenarios are estimated using a metapopulation model. Three methods are described for making conservation decisions across the species, taking into account uncertainty. We find that decisions based on single species are relatively robust to uncertainty in parameters, although the estimates of extinction risk increase rapidly with uncertainty. When identifying the best conservation decision for the persistence of all species, the methods that rely on the rankings of the management options by each species result in decisions that are similarly robust to uncertainty. Methods that depend on absolute values of extinction risk are sensitive to uncertainty, as small changes in extinction risk can alter the ranking of the alternative scenarios. We discover that it is possible to make robust conservation decisions even when the uncertainties of the multiple-species problem appear overwhelming. However, the decision most robust to uncertainty is likely to differ from the best decision when uncertainty is ignored, illustrating the importance of incorporating uncertainty into the decision-making process.     

Matches and mismatches between conservation investments and biodiversity values in the European Union

Recently, the European Commission adopted a new strategy to halt the loss of biodiversity. Member states are expected to favor a more effective collection and redistribution of European Union (EU) funds under the current Multiannual Financial Framework for 2014–2020. Because of the large spatial variation in the distribution of biodiversity and conservation needs at the continental scale, EU instruments should ensure that countries with higher biodiversity values get more funds and resources for the conservation than other countries. Using linear regressions, we assessed the association between conservation investments and biodiversity values across member states, accounting for a variety of conservation investment indicators, taxonomic groups (including groups of plants, vertebrates, and invertebrates), and indicators of biodiversity value. In general, we found clear overall associations between conservation investments and biodiversity variables. However, some countries received more or less investment than would be expected based on biodiversity values in those countries. We also found that the extensive use of birds as unique indicators of conservation effectiveness may lead to biased decisions. Our results can inform future decisions regarding funding allocation and thus improve distribution of EU conservation funds.     

Mapping social–ecological vulnerability to inform local decision making

An overarching challenge of natural resource management and biodiversity conservation is that relationships between people and nature are difficult to integrate into tools that can effectively guide decision making. Social–ecological vulnerability offers a valuable framework for identifying and understanding important social–ecological linkages, and the implications of dependencies and other feedback loops in the system. Unfortunately, its implementation at local scales has hitherto been limited due at least in part to the lack of operational tools for spatial representation of social–ecological vulnerability. We developed a method to map social–ecological vulnerability based on information on human–nature dependencies and ecosystem services at local scales. We applied our method to the small‐scale fishery of Moorea, French Polynesia, by combining spatially explicit indicators of exposure, sensitivity, and adaptive capacity of both the resource (i.e., vulnerability of reef fish assemblages to fishing) and resource users (i.e., vulnerability of fishing households to the loss of fishing opportunity). Our results revealed that both social and ecological vulnerabilities varied considerably through space and highlighted areas where sources of vulnerability were high for both social and ecological subsystems (i.e., social–ecological vulnerability hotspots) and thus of high priority for management intervention. Our approach can be used to inform decisions about where biodiversity conservation strategies are likely to be more effective and how social impacts from policy decisions can be minimized. It provides a new perspective on human–nature linkages that can help guide sustainability management at local scales; delivers insights distinct from those provided by emphasis on a single vulnerability component (e.g., exposure); and demonstrates the feasibility and value of operationalizing the social–ecological vulnerability framework for policy, planning, and participatory management decisions.     

Evaluating and structuring indicators for wetland assessment

Wetland assessment has been a popular field of research worldwide. However, various indicators have been used in wetland assessment for different purposes and backgrounds and also because of the research limitations. Therefore, a more comprehensive, sound, and efficient indicator system is needed for researchers’ referencing to evaluate wetlands. After an extensive review of wetland assessment literatures, the reported indicators were evaluated using the developed assessment system, based on the Analytical Hierarchy Process (AHP) with three main goals: nature protection, function utilization, and sustainable development. Each indicator was evaluated using two methods. The first method was to study the percentage of the indicator application, and the second was to assess the weighted ratios assigned to the indicators according to principles of comparability, typicality, sensibility, and availability. The results of these two methods were compared to study the commonalities and specialties of the indicators. They also showed that some indicators were widely used, including biodiversity, weather and climate, hydrological change, and the output of wetland. On the other hand, other sustainable indicators were easily ignored, such as environmental carrying capacity and wetland planning. Furthermore, an indicator system for wetland assessment was structured and strategized to discuss how to choose indicators for wetland assessment under different conditions. The proposed approach can be used to guide the process of wetland assessments in the future.     

Identifying Conservation Areas on the Basis of Alternative Distribution Data Sets

Abstract:  Distribution data on biodiversity features is a major component of conservation planning that are often inaccurate; thus, the true distribution of each feature is commonly over- or underrepresented. The selection of distribution data sets may therefore lead to variability in the spatial configuration and size of proposed reserve networks and uncertainty regarding the extent to which these networks actually contain the biodiversity features they were identified to protect. Our goals were to investigate the impact on reserve selection of choosing different distribution data sets and to propose novel methods to minimize uncertainty about target attainment within reserves. To do so, we used common prioritization methods (richness mapping, systematic reserve design, and a novel approach that integrates multiple types of distribution data) and three types of data on the distribution of mammals (predicted distribution models, occurrence records, and a novel combination of the two) to simulate the establishment of regional biodiversity reserves for the state of Arizona (U.S.A.). Using the results of these simulations, we explored variability in reserve placement and size as a function of the distribution data set. Spatial overlap of reserve networks identified with only predicted distribution data or only occurrence distribution data never exceeded 16%. In pairwise comparisons between reserves created with all three types of distribution data, overlap never achieved 50%. The reserve size required to meet conservation targets also varied with the type of distribution data used and the conservation goal; the largest reserve system was 10 times the smallest. Our results highlight the impact of employing different types of distribution data and identify novel tools for application to existing distribution data sets that can minimize uncertainty about target attainment.     

Putting People on the Map through an Approach That Integrates Social Data in Conservation Planning

Conservation planning is integral to strategic and effective operations of conservation organizations. Drawing upon biological sciences, conservation planning has historically made limited use of social data. We offer an approach for integrating data on social well‐being into conservation planning that captures and places into context the spatial patterns and trends in human needs and capacities. This hierarchical approach provides a nested framework for characterizing and mapping data on social well‐being in 5 domains: economic well‐being, health, political empowerment, education, and culture. These 5 domains each have multiple attributes; each attribute may be characterized by one or more indicators. Through existing or novel data that display spatial and temporal heterogeneity in social well‐being, conservation scientists, planners, and decision makers may measure, benchmark, map, and integrate these data within conservation planning processes. Selecting indicators and integrating these data into conservation planning is an iterative, participatory process tailored to the local context and planning goals. Social well‐being data complement biophysical and threat‐oriented social data within conservation planning processes to inform decisions regarding where and how to conserve biodiversity, provide a structure for exploring socioecological relationships, and to foster adaptive management. Building upon existing conservation planning methods and insights from multiple disciplines, this approach to putting people on the map can readily merge with current planning practices to facilitate more rigorous decision making. Poner a la Gente en el Mapa por Medio de una Estrategia que Integra Información Social en la Planeación de la Conservación     

Matching biodiversity indicators to policy needs

At the global scale, biodiversity indicators are typically used to monitor general trends, but are rarely implemented with specific purpose or linked directly to decision making. Some indicators are better suited to predicting future change, others are more appropriate for evaluating past actions, but this is seldom made explicit. We developed a conceptual model for assigning biodiversity indicators to appropriate functions based on a common approach used in economics. Using the model, indicators can be classified as leading (indicators that change before the subject of interest, informing preventative actions), coincident (indicators that measure the subject of interest), or lagging (indicators that change after the subject of interest has changed and thus can be used to evaluate past actions). We classified indicators based on ecological theory on biodiversity response times and management objectives in 2 case studies: global species extinction and marine ecosystem collapse. For global species extinctions, indicators of abundance (e.g., the Living Planet Index or biodiversity intactness index) were most likely to respond first, as leading indicators that inform preventative action, while extinction indicators were expected to respond slowly, acting as lagging indicators flagging the need for evaluation. For marine ecosystem collapse, indicators of direct responses to fishing were expected to be leading, while those measuring ecosystem collapse could be lagging. Classification defines an active role for indicators within the policy cycle, creates an explicit link to preventative decision-making, and supports preventative action.     

Testing the Value of Six Taxonomic Groups as Biodiversity Indicators at a Local Scale

Abstract:  We examined six groups of taxa—woody plants, aquatic and terrestrial herpetofauna, small terrestrial birds, orchids, and Orthoptera—to determine their efficiency as biodiversity indicators in the Dadia Reserve in northern Greece. We investigated the indicator value of each group by examining the degree of congruence of its species-richness pattern with that of the other groups and the efficiency of its complementary network in conserving the other groups and biodiversity. The two techniques differed in many respects in their outputs, but they both showed woody plants as the best biodiversity indicator. There was in general low congruence in the species richness patterns across the different groups. Significant relationships were found between woody plants and birds, Orthoptera and terrestrial herpetofauna, and birds and aquatic herpetofauna. None of the optimal complementary networks of the groups we examined protected all species of the other groups. Nevertheless, the complementary network of woody plants adequately conserved all groups except orchids. We conclude that the principle of complementarity must be integrated into the methodology of evaluating an indicator. In an applied context, our results provide a scientific background on which to base a biomonitoring program for the Dadia Reserve. In a wider scope, if the group of woody plants prove an adequate biodiversity indicator for other Mediterranean areas as well, this will be important because it will facilitate conservation-related decisions for the entire Mediterranean region.     

Adaptive resource management and the value of information

The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time.     

A Global Indicator for Biological Invasion

Abstract:  "Trends in invasive alien species" is one of only two indicators of threat to biodiversity that form part of the Convention on Biological Diversity's (CBD) framework for monitoring progress toward its "2010 target" (i.e., the commitment to achieve by 2010 a significant reduction in the current rate of biodiversity loss). To date, however, there is no fully developed indicator for invasive alien species (IAS) that combines trends, derived from a standard set of methods, across species groups, ecosystems, and regions. Here we provide a rationale for the form and characteristics of an indicator of trends in IAS that will meet the 2010 framework goal and targets for this indicator. We suggest single and composite indicators that include problem-status and management-status measures that are designed to be flexible, readily disaggregated, and as far as possible draw on existing data. The single indicators at national and global scales are number of IAS and numbers of operational management plans for IAS. Global trends in IAS are measured as the progress of nations toward the targets of stabilizing IAS numbers and the implementation of IAS management plans. The proposed global indicator thus represents a minimum information set that most directly addresses the indicator objective and simultaneously aims to maximize national participation. This global indicator now requires testing to assess its accuracy, sensitivity, and tractability. Although it may not be possible to achieve the desired objective for a global indicator of biological invasion by 2010 as comprehensively as desired, it seems possible to obtain trend estimates for a component of the taxa, ecosystems, and regions involved. Importantly, current indicator development initiatives will also contribute to developing the mechanisms necessary for monitoring global trends in IAS beyond 2010.     

Ecosystem network analysis indicators are generally robust to parameter uncertainty in a phosphorus model of Lake Sidney Lanier, USA

Understanding how data uncertainty influences ecosystem analysis is critical as we move toward ecosystem-based management. Here, we investigate how 18 Ecological Network Analysis (ENA) indicators that characterize ecosystem growth, development, and condition are affected by uncertainty in an ecosystem model of Lake Sidney Lanier (USA). We applied ENA to 122 plausible parameterizations of the ecosystem developed by Borrett and Osidele (2007, Ecological Modelling 200, 371-387), and then used the coefficient of variation (CV) to compare system indicator variability. We considered Total System Throughput (TST) as a measure of the underlying model uncertainty and tested three hypotheses. First, we hypothesized that non-ratio indicators whose calculation includes the TST would be at least as variable as TST if not more variable. Second, we postulated that indicators calculated as ratios, with TST in the numerator and denominator would tend to be less variable than TST because its influence will cancel. Last, we expected the Average Mutual Information (AMI) to be less variable than TST because it is a bounded function. Our work shows that the 18 indicators grouped into four categories. The first group has significantly larger CVs than the CV for TST. In this group, model uncertainty is amplified rendering these three indicators less useful. The second group of four indicators shows no significant difference in variability with respect to TST. Finally, there are two groups whose CV values are significantly lower than that for TST. The least variable group includes the ratio-based indicators and Average Mutual Information. Due to their low variability, we conclude that these indicators are the most robust to the parameter uncertainty and most useful for ecosystem assessment and comparative ecosystem analysis. In summary, this work suggests that we can be as certain, or more certain, in most of the selected ENA indicators as we are in the parameters of the model analyzed.     

Ecological Ethics: Building a New Tool Kit for Ecologists and Biodiversity Managers

Abstract:  Ecological research and biodiversity management often raise ethical questions in areas that include responsibilities and duties to the scientific community, public welfare, research animals, species, and ecosystems. Answering these questions is challenging because ecologists and biodiversity managers do not have the equivalent of bioethics, an established field with a support network focused mainly on biomedicine, to guide them in making decisions. Environmental ethics provides some insight into environmental values and the duties these may impose on humans. But for the most part those in the field have not considered many of the common responsibilities and obligations that ecologists and managers have to the scientific profession or to public welfare. There is a need to bring ethicists, scientists, and biodiversity managers together in a collaborative effort to study and inform the methods of ethical analysis and problem solving in ecological research and biodiversity management. We present a series of cases that illustrate the kinds of ethical questions faced by researchers and biodiversity managers in practice. We argue for the creation of an extensive case database and a pluralistic and integrated ethical framework, one that draws from the theoretical (normative), research, animal, and environmental ethics traditions. These tools form the foundations of a new area of inquiry and practical ethical problem solving, that we call "ecological ethics."     

Sensitivity of Systematic Reserve Selection to Decisions about Scale, Biological Data, and Targets: Case Study from Southern British Columbia

Abstract:  The identification of conservation areas based on systematic reserve-selection algorithms requires decisions related to both spatial and ecological scale. These decisions may affect the distribution and number of sites considered priorities for conservation within a region. We explored the sensitivity of systematic reserve selection by altering values of three essential variables. We used a 1:20,000–scale terrestrial ecosystem map and habitat suitability data for 29 threatened vertebrate species in the Okanagan region of British Columbia, Canada. To these data we applied a reserve-selection algorithm to select conservation sites while altering selection unit size and shape, features of biodiversity (i.e., vertebrate species), and area conservation targets for each biodiversity feature. The spatial similarity, or percentage overlap, of selected sets of conservation sites identified (1) with different selection units was ≤40%, (2) with different biodiversity features was 59%, and (3) with different conservation targets was ≥94%. Because any selected set of sites is only one of many possible sets, we also compared the conservation value (irreplaceability) of all sites in the region for each variation of the data. The correlations of irreplaceability were weak for different selection units (0.23 ≤ r ≤ 0.67), strong for different biodiversity features ( r = 0.84), and mixed for different conservation targets ( r = 0.16; 0.16; 1.00). Because of the low congruence of selected sites and weak correlations of irreplaceability for different selection units, recommendations from studies that have been applied at only one spatial scale must be considered cautiously.     

Future distribution modelling: A stitch in time is not enough

The last two decades have seen an increasing number of studies assessing the impact of climate change upon biodiversity. A central assumption underpinning research into the potential future habitat of terrestrial biota is that species are presently in equilibrium with their environments and that quantitative climate models adequately represent the distribution of species. Recently, many alarming predictions have emerged concerning the extinction and redistribution of species. Here, we show that even large-scale models of the climatic niche dimensions of species are temporally variable. Distributional models were developed for Salix (willow) species occurring in the province of Ontario, Canada, using three historical climate data sets. Although historical data very accurately represented the distributions of willows, the inherent variability within the models of species based on different periods greatly influenced the direction and magnitude of projected distributional change. We expose a fundamental uncertainty with respect to predicting the responses of species to climate change.     

The 2010 Biodiversity Indicators: Challenges for Science and Policy

Abstract:  The 2010 biodiversity target adopted globally and in Europe is an important political commitment for improved biodiversity conservation and management. Whether or not it is achieved will be judged by a set of biodiversity indicators now under development. We reviewed the development of these indicators in Europe and globally, paying particular attention to the need to make the indicators relevant to the purpose; to distinguish between measures of pressure, state, and response; to design and validate the indicators in context; to ensure effective communication with relevant audiences; to turn lists of measures into simple or composite indicators; and to maximize the cost-effectiveness of the indicator process. We conclude that urgent steps are needed to complete the indicator set, reduce and refine the agreed measures, ensure that work is started soon so that reliable reporting occurs in 2010, and start soon on planning for subsequent assessments.     

Prediction of potential areas of species distributions based on presence-only data

We introduce a methodology to infer zones of high potential for the habitat of a species, useful for management of biodiversity, conservation, biogeography, ecology, or sustainable use. Inference is based on a set of sites where the presence of the species has been reported. Each site is associated with covariate values, measured on discrete scales. We compute the predictive probability that the species is present at each node of a regular grid. Possible spatial bias for sites of presence is accounted for. Since the resulting posterior distribution does not have a closed form, a Markov chain Monte Carlo (MCMC) algorithm is implemented. However, we also describe an approximation to the posterior distribution, which avoids MCMC. Relevant features of the approach are that specific notions of data acquisition such as sampling intensity and detectability are accounted for, and that available a priori information regarding areas of distribution of the species is incorporated in a clear-cut way. These concepts, arising in the presence-only context, are not addressed in alternative methods. We also consider an uncertainty map, which measures the variability for the predictive probability at each node on the grid. A simulation study is carried out to test and compare our approach with other standard methods. Two case studies are also presented.     

Efficacy of Land-Cover Models in Predicting Isolation of Marbled Salamander Populations in a Fragmented Landscape

Abstract:  Amphibians worldwide are facing rapid declines due to habitat loss and fragmentation, disease, and other causes. Where habitat alteration is implicated, there is a need for spatially explicit conservation plans. Models built with geographic information systems (GIS) are frequently used to inform such planning. We explored the potential for using GIS models of functional landscape connectivity as a reliable proxy for genetically derived measures of population isolation. We used genetic assignment tests to characterize isolation of marbled salamander populations and evaluated whether the relative amount of modified habitat around breeding ponds was a reliable indicator of population isolation. Using a resampling analysis, we determined whether certain land-cover variables consistently described population isolation. We randomly drew half the data for model building and tested the performance of the best models on the other half 100 times. Deciduous forest was consistently associated with lower levels of population isolation, whereas salamander populations in regions of agriculture and anthropogenic development were more isolated. Models that included these variables and pond size explained 65–70% of variation in genetically inferred isolation across sites. The resampling analysis confirmed that these habitat variables were consistently good predictors of isolation. Used judiciously, simple GIS models with key land-cover variables can be used to estimate population isolation if field sampling and genetic analysis are not possible.     

Indicators for Monitoring Biodiversity: A Hierarchical Approach

Abstract: Biodiversity is presently a minor consideration in environmental policy. It has been regarded as too broad and vague a concept to be applied to real-world regulatory and management problems. This problem can be corrected if biodiversity is recognized as an end in itself, and if measurable indicators can be selected to assess the status of biodiversity over time. Biodiversity, as presently understood, encompasses multiple levels of biological organization. In this paper, I expand the three primary attributes of biodiversity recognized by Jerry Franklin — composition, structure, and function—into a nested hierarchy that incorporates elements of each attribute at four levels of organization: regional landscape, community-ecosystem, population-species, and genetic. Indicators of each attribute in terrestrial ecosystems, at the four levels of organization, are identified for environmental monitoring purposes. Projects to monitor biodiversity will benefit from a direct linkage to long-term ecological research and a commitment to test hypotheses relevant to biodiversity conservation. A general guideline is to proceed from the top down, beginning with a coarse-scale inventory of landscape pattern, vegetation, habitat structure, and species distributions, then overlaying data on stress levels to identify biologically significant areas at high risk of impoverishment. Intensive research and monitoring can be directed to high-risk ecosystems and elements of biodiversity, while less intensive monitoring is directed to the total landscape (or samples thereof). In any monitoring program, particular attention should be paid to specifying the questions that monitoring is intended to answer and validating the relationships between indicators and the components of biodiversity they represent.     

The Threat of Transformation: Quantifying the Vulnerability of Grasslands in South Africa

Abstract:  The ability to predict which areas of conservation importance are most vulnerable to transformation and to rank the relative damage that transforming land uses could cause to biodiversity are important components of an effective and realistic conservation planning process. We used the South African grassland biome as a case study to illustrate the assessment of vulnerability to land-use transformation through the construction of a "threat map." We identified the dominant transforming land uses and created suitability models based on area appropriateness for each. Land uses were scored according to their expected relative impacts on biodiversity, with a framework that included compositional, structural, and functional components. This information, once combined, resulted in a map that highlighted the areas most vulnerable to transformation in terms of the likelihood of their transformation and the impact on their biodiversity. We propose that such an analysis of the threat of transformation, in combination with species-representation approaches, will aid the integration of conservation planning theory and decision making. This approach can be applied at any scale and in any region with a robustness and accuracy dependent on data quality, resultant suitability models, and comprehension of how land uses affect an area's biodiversity.