Project description:Protected areas (PAs) play a pivotal role in maintaining viable populations of species and minimizing their habitat loss. Globally, there are currently over 200,000 PAs that cover approximately 15% of land area. The post-2020 global biodiversity framework aims to expand this coverage to 30% by 2030. However, focusing only on the percentage coverage of PAs without evaluating their effectiveness may fail to achieve conservation goals. Here, we use a multidimensional approach incorporating species, climate and anthropogenic vulnerabilities to assess the threat levels in over 2500 PAs in China. We identify nearly 10% of PAs as the most threatened PAs in China and about one-fifth PAs as hotspots of climate and anthropogenic vulnerabilities. We also find high climate instability in species vulnerability hotspots, suggesting an elevated likelihood of species' extirpation therein. Our framework could be useful in assessing resiliency of global protected lands and also in selecting near optimal areas for their future expansion.
Project description:Changes in individual climate variables have been widely documented over the past century. However, assessments that consider changes in the collective interaction amongst multiple climate variables are relevant for understanding climate impacts on ecological and human systems yet are less well documented than univariate changes. We calculate annual multivariate climate departures during 1958-2017 relative to a baseline 1958-1987 period that account for covariance among four variables important to Earth's biota and associated systems: annual climatic water deficit, annual evapotranspiration, average minimum temperature of the coldest month, and average maximum temperature of the warmest month. Results show positive trends in multivariate climate departures that were nearly three times that of univariate climate departures across global lands. Annual multivariate climate departures exceeded two standard deviations over the past decade for approximately 30% of global lands. Positive trends in climate departures over the last six decades were found to be primarily the result of changes in mean climate conditions consistent with the modeled effects of anthropogenic climate change rather than changes in variability. These results highlight the increasing novelty of annual climatic conditions viewed through a multivariate lens and suggest that changes in multivariate climate departures have generally outpaced univariate departures in recent decades.
Project description:Because habitat loss is the main cause of extinction, where and how much society chooses to protect is vital for saving species. The United States is well positioned economically and politically to pursue habitat conservation should it be a societal goal. We assessed the US protected area portfolio with respect to biodiversity in the country. New synthesis maps for terrestrial vertebrates, freshwater fish, and trees permit comparison with protected areas to identify priorities for future conservation investment. Although the total area protected is substantial, its geographic configuration is nearly the opposite of patterns of endemism within the country. Most protected lands are in the West, whereas the vulnerable species are largely in the Southeast. Private land protections are significant, but they are not concentrated where the priorities are. To adequately protect the nation's unique biodiversity, we recommend specific areas deserving additional protection, some of them including public lands, but many others requiring private investment.
Project description:Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.
Project description:Predicting how species respond to human pressure is essential to anticipate their decline and identify appropriate conservation strategies. Both human pressure and extinction risk change over time, but their inter-relationship is rarely considered in extinction risk modelling. Here we measure the relationship between the change in terrestrial human footprint (HFP)-representing cumulative human pressure on the environment-and the change in extinction risk of the world's terrestrial mammals. We find the values of HFP across space, and its change over time, are significantly correlated to trends in species extinction risk, with higher predictive importance than environmental or life-history variables. The anthropogenic conversion of areas with low pressure values (HFP?<?3 out of 50) is the most significant predictor of change in extinction risk, but there are biogeographical variations. Our framework, calibrated on past extinction risk trends, can be used to predict the impact of increasing human pressure on biodiversity.