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.     

National Red Listing Beyond the 2010 Target

Abstract: Following creation of the 2010 Biodiversity Target under the Convention on Biological Diversity and adoption of the United Nations Millennium Development Goals, information on status and trends of biodiversity at the national level has become increasingly important to both science and policy. National red lists (NRLs) of threatened species may provide suitable data for reporting on progress toward these goals and for informing national conservation priority setting. This information will also become increasingly important for developing species‐ and ecosystem‐based strategies for climate change adaptation. We conducted a thorough global review of NRLs in 109 countries and analyzed gaps in NRL coverage in terms of geography and taxonomy to determine priority regions and taxonomic groups for further investment. We then examined correlations between the NRL data set and gross domestic product (GDP) and vertebrate species richness. The largest geographic gap was in Oceania, followed by middle Africa, the Caribbean, and western Africa, whereas the largest taxonomic gaps were for invertebrates, fungi, and lichens. The comprehensiveness of NRL coverage within a given country was positively correlated with GDP and negatively correlated with total vertebrate richness and threatened vertebrate richness. This supports the assertion that regions with the greatest and most vulnerable biodiversity receive the least conservation attention and indicates that financial resources may be an integral limitation. To improve coverage of NRLs, we propose a combination of projects that target underrepresented taxa or regions and projects that provide the means for countries to create or update NRLs on their own. We recommend improvements in knowledge transfer within and across regions as a priority for future investment.     

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.     

Monitoring of Biological Diversity: a Common-Ground Approach

Abstract:  Practical approaches to monitoring biological diversity vary widely among countries, and the accumulating data are frequently not generalizable at the international scale. Although many present monitoring schemes, especially in developed countries, produce highly complex data, there is often a lack of basic data about the level and spatial distribution of biodiversity. We augmented the general framework for improving biomonitoring, proposed by Green et al. (2005) , and identified its core tasks and attributes. The first priority for a more unified biodiversity monitoring is to agree on a minimum set of core tasks and attributes, which will make it possible to build a standardized biomonitoring system even in countries with few resources. Our scheme has two main organizational levels—taxa and ecosystems. The basic elements of the biomonitoring system proposed are recording of presence and absence of taxa and ecosystems in a target area, mapping of their distribution in space, and assessment of their status. All the elements have to be repeated over time. Although these tasks are fundamental, they are frequently not considered in currently functioning biomonitoring programs. The whole system has to be hierarchical and additive: if more resources are available, new activities may be added to the basic routine. Agreeing on a common standard will facilitate aggregating measures of biodiversity status and trends into regional and global indices. This information will relate directly to several Convention on Biological Diversity indicators for assessing progress toward the 2010 Biodiversity Target.     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

A strategy for the next decade to address data deficiency in neglected biodiversity

Measuring progress toward international biodiversity targets requires robust information on the conservation status of species, which the International Union for Conservation of Nature (IUCN) Red List of Threatened Species provides. However, data and capacity are lacking for most hyperdiverse groups, such as invertebrates, plants, and fungi, particularly in megadiverse or high-endemism regions. Conservation policies and biodiversity strategies aimed at halting biodiversity loss by 2020 need to be adapted to tackle these information shortfalls after 2020. We devised an 8-point strategy to close existing data gaps by reviving explorative field research on the distribution, abundance, and ecology of species; linking taxonomic research more closely with conservation; improving global biodiversity databases by making the submission of spatially explicit data mandatory for scientific publications; developing a global spatial database on threats to biodiversity to facilitate IUCN Red List assessments; automating preassessments by integrating distribution data and spatial threat data; building capacity in taxonomy, ecology, and biodiversity monitoring in countries with high species richness or endemism; creating species monitoring programs for lesser-known taxa; and developing sufficient funding mechanisms to reduce reliance on voluntary efforts. Implementing these strategies in the post-2020 biodiversity framework will help to overcome the lack of capacity and data regarding the conservation status of biodiversity. This will require a collaborative effort among scientists, policy makers, and conservation practitioners.     

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.     

Current Constraints and Future Directions in Estimating Coextinction

Abstract: Coextinction is a poorly quantified phenomenon, but results of recent modeling suggest high losses to global biodiversity through the loss of dependent species when hosts go extinct. There are critical gaps in coextinction theory, and we outline these in a framework to direct future research toward more accurate estimates of coextinction rates. Specifically, the most critical priorities include acquisition of more accurate host data, including the threat status of host species; acquisition of data on the use of hosts by dependent species across a wide array of localities, habitats, and breadth of both hosts and dependents; development of models that incorporate correlates of nonrandom host and dependent extinctions, such as phylogeny and traits that increase extinction‐proneness; and determination of whether dependents are being lost before their hosts and adjusting models accordingly. Without synergistic development of better empirical data and more realistic models to estimate the number of cothreatened species and coextinction rates, the contribution of coextinction to global declines in biodiversity will remain unknown and unmanaged.     

A guide to representing variability and uncertainty in biodiversity indicators

Biodiversity indicators are used to inform decisions and measure progress toward global targets, such as the United Nations Sustainable Development Goals. Indicators aggregate and simplify complex information, so underlying information influencing its reliability and interpretation (e.g., variability in data and uncertainty in indicator values) can be lost. Communicating uncertainty is necessary to ensure robust decisions and limit misinterpretations of trends, yet variability and uncertainty are rarely quantified in biodiversity indicators. We developed a guide to representing uncertainty and variability in biodiversity indicators. We considered the key purposes of biodiversity indicators and commonly used methods for representing uncertainty (standard error, bootstrap resampling, and jackknife resampling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high-profile biodiversity indicators (Red List Index, Living Planet Index, and Ocean Health Index), we tested the use, suitability, and interpretation of each interval method based on the formulation and data types underpinning the indicators. The methods revealed vastly different information; indicator formula and data distribution affected the suitability of each interval method. Because the data underpinning each indicator were not normally distributed, methods relying on normality or symmetrical spread were unsuitable. Quantiles, bootstrapping, and jackknifing provided useful information about the underlying variability and uncertainty. We built a decision tree to inform selection of the appropriate interval method to represent uncertainty or variation in biodiversity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of biodiversity indicator trends to facilitate accurate interpretation by decision makers.     

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.