Temporal baselines are needed for biodiversity, in order for the change in biodiversity to be measured over time, the targets for biodiversity conservation to be defined and conservation progress to ...be evaluated. Limited biodiversity information is widely recognized as a major barrier for identifying temporal baselines, although a comprehensive quantitative assessment of this is lacking. Here, we report on the temporal baselines that could be drawn from biodiversity monitoring schemes in Europe and compare those with the rise of important anthropogenic pressures. Most biodiversity monitoring schemes were initiated late in the 20
century, well after anthropogenic pressures had already reached half of their current magnitude. Setting temporal baselines from biodiversity monitoring data would therefore underestimate the full range of impacts of major anthropogenic pressures. In addition, biases among taxa and organization levels provide a truncated picture of biodiversity over time. These limitations need to be explicitly acknowledged when designing management strategies and policies as they seriously constrain our ability to identify relevant conservation targets aimed at restoring or reversing biodiversity losses. We discuss the need for additional research efforts beyond standard biodiversity monitoring to reconstruct the impacts of major anthropogenic pressures and to identify meaningful temporal baselines for biodiversity.
•We develop a new method to estimate IUCN species extent of occurrence (EOO) from distribution model predictions (SDMs).•Our method relies on maximising geographical similarity between the SDM and ...empirical EOOs.•We assessed the method using 50 plant species from Costa Rica and Panama, 20 with well sampled and known distributions.•SDMs predicted the true EOO better than empirical estimates around sampled localities, especially for small sample sizes.•Our findings illustrate how SDMs can provide useful information to complement the IUCN Red Listing process.
Characterising a species’ geographical extent is central to many conservation assessments, including those of the IUCN Red List of threatened species. The IUCN recommends that extent of occurrence (EOO) to be quantified by drawing a minimum convex polygon (MCP) around known or inferred presence localities. EOO calculated from verified specimens is commonly used in Red List assessments when other data are scarce, as is the case for many threatened plant species. Yet rarely do these estimates incorporate inferred localities from species distribution models (SDMs). A key impediment stems from uncertainty about how SDM predictions relate to EOO. Here we address this issue by comparing the EOOs estimated from specimen localities with EOOs derived from SDMs for plant species occurring in Costa Rica and Panama. We first analyse 20 plant species, with well-known and well-sampled distributions, and train SDMs to subsamples of the data and assess how well the SDM-derived MCPs predict both the MCPs of the subsamples and the MCPs of the complete dataset. We find that when sample sizes are small (5 or 10 samples) the SDM-derived MCPs are actually closer to the complete dataset than to the MCPs of the subsamples, both in terms of EOO and geographically. This occurs when using a probability threshold based on maximum geographical similarity between the SDM-derived MCP and the subsample MCP; other threshold methods performed less well. For the species with less well-known distributions, the SDM-derived EOOs correlate strongly with, but tend to be larger than, EOOs estimated by point data. This implies that a SDM-derived EOO may be more representative of the full EOO than that drawn around known localities. Our findings reveal situations in which SDMs provide useful information that complements the IUCN Red Listing process.
Gymnosperms on the EDGE Forest, Félix; Moat, Justin; Baloch, Elisabeth ...
Scientific reports,
04/2018, Letnik:
8, Številka:
1
Journal Article
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Driven by limited resources and a sense of urgency, the prioritization of species for conservation has been a persistent concern in conservation science. Gymnosperms (comprising ginkgo, conifers, ...cycads, and gnetophytes) are one of the most threatened groups of living organisms, with 40% of the species at high risk of extinction, about twice as many as the most recent estimates for all plants (i.e. 21.4%). This high proportion of species facing extinction highlights the urgent action required to secure their future through an objective prioritization approach. The Evolutionary Distinct and Globally Endangered (EDGE) method rapidly ranks species based on their evolutionary distinctiveness and the extinction risks they face. EDGE is applied to gymnosperms using a phylogenetic tree comprising DNA sequence data for 85% of gymnosperm species (923 out of 1090 species), to which the 167 missing species were added, and IUCN Red List assessments available for 92% of species. The effect of different extinction probability transformations and the handling of IUCN data deficient species on the resulting rankings is investigated. Although top entries in our ranking comprise species that were expected to score well (e.g. Wollemia nobilis, Ginkgo biloba), many were unexpected (e.g. Araucaria araucana). These results highlight the necessity of using approaches that integrate evolutionary information in conservation science.
Essential Biodiversity Variables (EBVs) consolidate information from varied biodiversity observation sources. Here we demonstrate the links between data sources, EBVs and indicators and discuss how ...different sources of biodiversity observations can be harnessed to inform EBVs. We classify sources of primary observations into four types: extensive and intensive monitoring schemes, ecological field studies and satellite remote sensing. We characterize their geographic, taxonomic and temporal coverage. Ecological field studies and intensive monitoring schemes inform a wide range of EBVs, but the former tend to deliver short-term data, while the geographic coverage of the latter is limited. In contrast, extensive monitoring schemes mostly inform the population abundance EBV, but deliver long-term data across an extensive network of sites. Satellite remote sensing is particularly suited to providing information on ecosystem function and structure EBVs. Biases behind data sources may affect the representativeness of global biodiversity datasets. To improve them, researchers must assess data sources and then develop strategies to compensate for identified gaps. We draw on the population abundance dataset informing the Living Planet Index (LPI) to illustrate the effects of data sources on EBV representativeness. We find that long-term monitoring schemes informing the LPI are still scarce outside of Europe and North America and that ecological field studies play a key role in covering that gap. Achieving representative EBV datasets will depend both on the ability to integrate available data, through data harmonization and modeling efforts, and on the establishment of new monitoring programs to address critical data gaps.
•Terrestrial biodiversity observations can be organized into four types.•These types differ in taxonomic, geographic, and temporal coverage.•The representativeness of EBV datasets is affected by the underlying types of data.•Global datasets of population abundance are affected by the lack of long-term data.•New monitoring programs must address critical data gaps.
Areas of plant diversity—What do we know? Brummitt, Neil; Araújo, Ana Claudia; Harris, Timothy
Plants, people, planet,
January 2021, Letnik:
3, Številka:
1
Journal Article
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Societal Impact Statement
Identifying regions of the world that are rich in plant species will enable conservation efforts to be more effectively targeted. We present a review of global studies of ...plant diversity, including novel analyses from our own work, and highlight areas of the world that are consistently identified by multiple studies utilizing varied data sets as being particularly rich in plant species. This will be of interest to botanical professionals and conservationists seeking to identify and conserve priority species‐rich environments, including those working to progress international conservation targets, and to all those interested in the global distribution of biodiversity and its conservation.
Summary
Areas of high diversity for vascular plants, both for numbers of species and of endemic species, are by now well established and in agreement across a variety of studies using a wide range of data from different sources. Here we review the current state of knowledge of geographical patterns of plant diversity around the world, compare this with our knowledge of vertebrate taxonomic groups, and reflect on next steps for better characterizing patterns of diversity in order to achieve effective conservation prioritization. We illustrate this with analyses of geographical patterns of plant diversity from three different data types with differing degrees of geographical and ecological resolution. At broad spatial scales these analyses are largely congruent with each other and with areas of high diversity and endemism for species of terrestrial vertebrates.
Identifying regions of the world that are rich in plant species will enable conservation efforts to be more effectively targeted. We present a review of global studies of plant diversity, including novel analyses from our own work, and highlight areas of the world that are consistently identified by multiple studies utilizing varied data sets as being particularly rich in plant species. This will be of interest to botanical professionals and conservationists seeking to identify and conserve priority species‐rich environments, including those working to progress international conservation targets, and to all those interested in the global distribution of biodiversity and its conservation.
ABSTRACT
Key global indicators of biodiversity decline, such as the IUCN Red List Index and the Living Planet Index, have relatively long assessment intervals. This means they, due to their inherent ...structure, function as late‐warning indicators that are retrospective, rather than prospective. These indicators are unquestionably important in providing information for biodiversity conservation, but the detection of early‐warning signs of critical biodiversity change is also needed so that proactive management responses can be enacted promptly where required. Generally, biodiversity conservation has dealt poorly with the scattered distribution of necessary detailed information, and needs to find a solution to assemble, harmonize and standardize the data. The prospect of monitoring essential biodiversity variables (EBVs) has been suggested in response to this challenge. The concept has generated much attention, but the EBVs themselves are still in development due to the complexity of the task, the limited resources available, and a lack of long‐term commitment to maintain EBV data sets. As a first step, the scientific community and the policy sphere should agree on a set of priority candidate EBVs to be developed within the coming years to advance both large‐scale ecological research as well as global and regional biodiversity conservation. Critical ecological transitions are of high importance from both a scientific as well as from a conservation policy point of view, as they can lead to long‐lasting biodiversity change with a high potential for deleterious effects on whole ecosystems and therefore also on human well‐being. We evaluated candidate EBVs using six criteria: relevance, sensitivity to change, generalizability, scalability, feasibility, and data availability and provide a literature‐based review for eight EBVs with high sensitivity to change. The proposed suite of EBVs comprises abundance, allelic diversity, body mass index, ecosystem heterogeneity, phenology, range dynamics, size at first reproduction, and survival rates. The eight candidate EBVs provide for the early detection of critical and potentially long‐lasting biodiversity change and should be operationalized as a priority. Only with such an approach can science predict the future status of global biodiversity with high certainty and set up the appropriate conservation measures early and efficiently. Importantly, the selected EBVs would address a large range of conservation issues and contribute to a total of 15 of the 20 Aichi targets and are, hence, of high biological relevance.
Societal Impact Statement
Proposals to increase protected area networks to 30% of land area globally will, given habitat conversion, require ecosystem restoration. Trait‐based approaches provide ...tools for this and highlight priorities for protected area expansion—both where functional diversity has the highest values and where it is higher than expected given species richness. Maps of sampled angiosperm species from across Africa show where these diversity metrics deviate. These maps also show the 30% of land with greatest potential to support functional diversity at national and continental scales, of which less than a quarter is protected, demonstrating the need for coordinated trans‐national plant conservation efforts.
Proposals to increase protected area networks to 30% of land area globally will, given habitat conversion, require ecosystem restoration. Trait‐based approaches provide tools for this and highlight priorities for protected area expansion—both where functional diversity has the highest values and where it is higher than expected given species richness. Maps of sampled angiosperm species from across Africa show where these diversity metrics deviate. These maps also show the 30% of land with greatest potential to support functional diversity at national and continental scales, of which less than a quarter is protected, demonstrating the need for coordinated trans‐national plant conservation efforts.
Human-driven global change is causing ongoing declines in biodiversity worldwide. In order to address these declines, decision-makers need accurate assessments of the status of and pressures on ...biodiversity. However, these are heavily constrained by incomplete and uneven spatial, temporal and taxonomic coverage. For instance, data from regions such as Europe and North America are currently used overwhelmingly for large-scale biodiversity assessments due to lesser availability of suitable data from other, more biodiversity-rich, regions. These data-poor regions are often those experiencing the strongest threats to biodiversity, however. There is therefore an urgent need to fill the existing gaps in global biodiversity monitoring. Here, we review current knowledge on best practice in capacity building for biodiversity monitoring and provide an overview of existing means to improve biodiversity data collection considering the different types of biodiversity monitoring data. Our review comprises insights from work in Africa, South America, Polar Regions and Europe; in government-funded, volunteer and citizen-based monitoring in terrestrial, freshwater and marine ecosystems. The key steps to effectively building capacity in biodiversity monitoring are: identifying monitoring questions and aims; identifying the key components, functions, and processes to monitor; identifying the most suitable monitoring methods for these elements, carrying out monitoring activities; managing the resultant data; and interpreting monitoring data. Additionally, biodiversity monitoring should use multiple approaches including extensive and intensive monitoring through volunteers and professional scientists but also harnessing new technologies. Finally, we call on the scientific community to share biodiversity monitoring data, knowledge and tools to ensure the accessibility, interoperability, and reporting of biodiversity data at a global scale.
Mind the gap Marsh, Charles J.; Gavish, Yoni; Kunin, William E. ...
Diversity & distributions,
12/2019, Letnik:
25, Številka:
12
Journal Article
Recenzirano
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Aim
The Area of Occupancy (AOO) of a species is often utilized to assess extinction risk for determining IUCN Red List status. However, the recommended raw‐counts method of summing occupied grid ...cells likely reflects only sampling effort, as the majority of species have not been sampled across their entire range at the fine grains required by IUCN. More accurate measurements can be generated at coarser grains (so‐called atlas data) as false absences are reduced. If we fit the occupancy‐area relationship to these data, we can extrapolate the relationship down to estimate occupancy at finer grains. Numerous models have been proposed to carry out such occupancy downscaling, but have only been tested on a limited range of species.
Methods
We test the ability of downscaling models to recover fine grain AOO against the raw‐counts method for 28,900 virtual species with a wide range of prevalence and aggregation characteristics, subsampled to reflect common spatial biases in sampling effort. We address several questions for ensuring accurate downscaling: How to generate accurate atlas data? How far can we accurately extrapolate the occupancy‐area relationship given perfect data? Can occupancy downscaling overcome false absences at fine grain sizes? And how does sampling bias and coverage affect accuracy?
Results
Downscaling was more accurate than the raw‐counts method in all scenarios except where sampling coverage was very high and/or the sampling bias was positively related to the species distribution. However, if atlas data contained many false absences, then even downscaling under‐estimated actual occupancy.
Main conclusions
Occupancy downscaling has the potential to be a useful tool for estimating AOO for IUCN Red List assessments, especially when sampling coverage is low and the currently recommended method is ineffective. However, its application should be tailored to the species’ characteristics, as well as the sampling coverage and bias of the species’ records.
Plant-diversity hotspots on a global scale are well established, but smaller local hotspots within these must be identified for effective conservation of plants at the global and local scales. We ...used the distributions of endemic and endemic-threatened species of Myrtaceae to indicate areas of plant diversity and conservation importance within the Atlantic coastal forests (Mata Atlântica) of Brazil. We applied 3 simple, inexpensive geographic information system (GIS) techniques to a herbarium specimen database: predictive species-distribution modeling (Maxent); complementarity analysis (DIVA-GIS); and mapping of herbarium specimen collection locations. We also considered collecting intensity, which is an inherent limitation of use of natural history records for biodiversity studies. Two separate areas of endemism were evident: the Serra do Mar mountain range from Paraná to Rio de Janeiro and the coastal forests of northern Espírito Santo and southern Bahia. We identified 12 areas of approximately 35 km² each as priority areas for conservation. These areas had the highest species richness and were highly threatened by urban and agricultural expansion. Observed species occurrences, species occurrences predicted from the model, and results of our complementarity analysis were congruent in identifying those areas with the most endemic species. These areas were then prioritized for conservation importance by comparing ecological data for each.
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