Final Report Summary - PRESERVATION (Predictive ecology of global species extinction risk for conservation)
There is now a broad consensus that biodiversity and ecosystem services are seriously at risk throughout the planet. Nevertheless, the resources available for biodiversity conservation are limited in terms of finance, space and time and, therefore, should be distributed effectively across regions identified as priorities for biodiversity conservation. Assessing extinction risks of species is one of the most commonly found and effective approaches that have been adopted by international organisations to prioritise conservation efforts. However, the limiting factor in these assessments is the availability of sufficient data on individual species’ abundance. Focusing on waterbird communities, for which long-term population count data are available globally, this project aimed to estimate extinction risks in different regions and for over 400 different species, and test the effects of different predictors on the estimated extinction risks across the globe.
During the first half of this project, I collected the required data on waterbird population counts. For the African-Eurasian region, Dr. Szabolcs Nagy (Wetlands International) provided population count records for 108 species in 90 countries (16,137 survey sites) for the period of 1983 – 2007. For the Asian-Australasian region, Dr. Taej Mundkur (Wetlands International) prepared population count records for 439 species in 30 countries (8,053 survey sites) for the period of 1973 - 2013. For South America, Dr. Daniel Blanco (Wetlands International) provided population count records for 367 species in 10 countries (2,284 survey sites) for the period of 1990 - 2012. For North America, I decided to use data based on the Christmas Bird Count and launched collaborative work with Dr. Justin Schuetz and Dr. Candan Soykan (The National Audubon Society), who provided data for 174 species in the US and Canada (3,412 survey sites) for the period of 1966 - 2012. As a total, I compiled 3,126,254 population count records since 1982 on 487 waterbird species at 29,599 non-breeding sites in 132 countries throughout the globe, which cover most of the non-breeding grounds for global waterbird species, except for several countries (e.g. Mexico).
During the second half of the project, I analysed these population count data to estimate the global distribution of waterbird population changes. To this end, I developed a novel hierarchical Bayesian model to account for variations in population changes among sites as well as temporal and spatial autocorrelation in each species’ population size. Using this model, I quantified the population change (1990 – present) in each of the 461 species with sufficient data at a resolution of 1º×1º.
In many species the estimated population growth rates varied greatly within their geographical ranges. Most notably, my analysis revealed that many common species that show an increasing trend in Europe and North America have severely declined since 1990 in other regions, such as the Middle East, Central Asia, sub-Saharan Africa and South America (e.g. Northern Pintail, Common Teal, Mallard, Great White Egret, Black-winged Stilt and Northern Shoveler). There are also species that have declined globally (e.g. Common Pochard), only in Europe (e.g. Greater Scaup and Dunlin) only in North America (e.g. Sanderling), and have increased globally (e.g. Common Goldeneye, Common Moorhen and Common Greenshank). These findings show the importance of considering within-species variations in population changes, which have been ignored so far, when assessing the distribution of threats to species. The analysis of this project also provided crucial information on the population status of highly threatened species, such as Baer’s Pochard and Siberian Crane (Critically Endangered based on the International Union for Conservation of Nature (IUCN)’s Red List) as well as 14 Endangered and 22 Vulnerable species.
By calculating the mean population growth rate across all species observed within each grid cell, I identified the Middle East, Central Asia, sab-Saharan Africa, South America, and Australasia as the hotspots of waterbird population losses. South America has experienced severe population declines in both migratory and resident species, while declines in South Africa and Australasia were severer in migrants, most likely due to the impact of habitat loss and hunting pressure in their stopover and/or breeding sites (e.g. the Middle East/Central Asia for species in South Africa, and the Yellow Sea for those in Australasia). In contrast, waterbird populations have generally increased in most European and North American countries, which presumably shows the effect of successful conservation efforts in these regions.
Most areas identified as the hotspots of waterbird population losses in this project (e.g. South America, sab-Saharan Africa, the Middle East and Central Asia) have been overlooked in earlier similar assessments (e.g. Williamson et al. 2013 Biodiversity and Conservation 22: 1501-1512) and thus, the findings of this project directly inform conservation policies and practice at both global (e.g. Aichi Biodiversity Targets) and local (e.g. management of each protected area) scales. For example, two-thirds of reports recently submitted by Parties to the Convention on Biological Diversity lacked evidence-based information on biodiversity change, and the outcome of this project addresses this knowledge gap. Similarly, my collaborators at the Wetlands International are already trying to inform the IUCN Red List using the results of this project. Another potential beneficiary of this project’s outcome is the Intergovernmental Platform on Biodiversity & Ecosystem Services, which is now conducting regional assessments on biodiversity and ecosystem services. These assessments are most likely to face spatial gaps in the availability of information on biodiversity status, particularly in data-poor regions, such as sab-Saharan Africa, the Middle East and Southeast Asia, and the results of this project, once published, provide an important knowledge base for these assessments.
Finally, to identify the drivers of the estimated population changes in waterbirds, I have developed a novel statistical model that estimates the effect of different predictors on each of the within- and among-species variations in population growth rates while accounting for spatial and phylogenetic autocorrelation in data.
During the first half of this project, I collected the required data on waterbird population counts. For the African-Eurasian region, Dr. Szabolcs Nagy (Wetlands International) provided population count records for 108 species in 90 countries (16,137 survey sites) for the period of 1983 – 2007. For the Asian-Australasian region, Dr. Taej Mundkur (Wetlands International) prepared population count records for 439 species in 30 countries (8,053 survey sites) for the period of 1973 - 2013. For South America, Dr. Daniel Blanco (Wetlands International) provided population count records for 367 species in 10 countries (2,284 survey sites) for the period of 1990 - 2012. For North America, I decided to use data based on the Christmas Bird Count and launched collaborative work with Dr. Justin Schuetz and Dr. Candan Soykan (The National Audubon Society), who provided data for 174 species in the US and Canada (3,412 survey sites) for the period of 1966 - 2012. As a total, I compiled 3,126,254 population count records since 1982 on 487 waterbird species at 29,599 non-breeding sites in 132 countries throughout the globe, which cover most of the non-breeding grounds for global waterbird species, except for several countries (e.g. Mexico).
During the second half of the project, I analysed these population count data to estimate the global distribution of waterbird population changes. To this end, I developed a novel hierarchical Bayesian model to account for variations in population changes among sites as well as temporal and spatial autocorrelation in each species’ population size. Using this model, I quantified the population change (1990 – present) in each of the 461 species with sufficient data at a resolution of 1º×1º.
In many species the estimated population growth rates varied greatly within their geographical ranges. Most notably, my analysis revealed that many common species that show an increasing trend in Europe and North America have severely declined since 1990 in other regions, such as the Middle East, Central Asia, sub-Saharan Africa and South America (e.g. Northern Pintail, Common Teal, Mallard, Great White Egret, Black-winged Stilt and Northern Shoveler). There are also species that have declined globally (e.g. Common Pochard), only in Europe (e.g. Greater Scaup and Dunlin) only in North America (e.g. Sanderling), and have increased globally (e.g. Common Goldeneye, Common Moorhen and Common Greenshank). These findings show the importance of considering within-species variations in population changes, which have been ignored so far, when assessing the distribution of threats to species. The analysis of this project also provided crucial information on the population status of highly threatened species, such as Baer’s Pochard and Siberian Crane (Critically Endangered based on the International Union for Conservation of Nature (IUCN)’s Red List) as well as 14 Endangered and 22 Vulnerable species.
By calculating the mean population growth rate across all species observed within each grid cell, I identified the Middle East, Central Asia, sab-Saharan Africa, South America, and Australasia as the hotspots of waterbird population losses. South America has experienced severe population declines in both migratory and resident species, while declines in South Africa and Australasia were severer in migrants, most likely due to the impact of habitat loss and hunting pressure in their stopover and/or breeding sites (e.g. the Middle East/Central Asia for species in South Africa, and the Yellow Sea for those in Australasia). In contrast, waterbird populations have generally increased in most European and North American countries, which presumably shows the effect of successful conservation efforts in these regions.
Most areas identified as the hotspots of waterbird population losses in this project (e.g. South America, sab-Saharan Africa, the Middle East and Central Asia) have been overlooked in earlier similar assessments (e.g. Williamson et al. 2013 Biodiversity and Conservation 22: 1501-1512) and thus, the findings of this project directly inform conservation policies and practice at both global (e.g. Aichi Biodiversity Targets) and local (e.g. management of each protected area) scales. For example, two-thirds of reports recently submitted by Parties to the Convention on Biological Diversity lacked evidence-based information on biodiversity change, and the outcome of this project addresses this knowledge gap. Similarly, my collaborators at the Wetlands International are already trying to inform the IUCN Red List using the results of this project. Another potential beneficiary of this project’s outcome is the Intergovernmental Platform on Biodiversity & Ecosystem Services, which is now conducting regional assessments on biodiversity and ecosystem services. These assessments are most likely to face spatial gaps in the availability of information on biodiversity status, particularly in data-poor regions, such as sab-Saharan Africa, the Middle East and Southeast Asia, and the results of this project, once published, provide an important knowledge base for these assessments.
Finally, to identify the drivers of the estimated population changes in waterbirds, I have developed a novel statistical model that estimates the effect of different predictors on each of the within- and among-species variations in population growth rates while accounting for spatial and phylogenetic autocorrelation in data.