Ecosystem indices to support global biodiversity conservation

Governments have committed to global targets to slow biodiversity loss and sustain ecosystem services. Biodiversity state indicators that measure progress towards these targets mostly focus on species, while indicators synthesizing ecosystem change are largely lacking. We fill this gap with three indices quantifying past and projected changes in ecosystems using data from the International Union for Conservation of Nature (IUCN) Red List of Ecosystems. Our indices quantify changes in risk of ecosystem collapse, ecosystem area, and ecological processes and capture variation in underlying patterns among ecosystems. We apply the indices to three case studies of regional and national assessments (American/Caribbean forests, terrestrial ecosystems of Colombia, and terrestrial ecosystems of South Africa) to illustrate the indices’ complementarity and versatility in revealing patterns of interest for users across sectors. Our indices have the potential to fill the recognized need for ecosystem indicators to inform conservation targets, guide policy, and prioritize management actions

An indicator-based approach for cross-realm coastal biodiversity assessments

Ecosystem status assessments are generally separated into realm-specific analyses (terrestrial, freshwater, estuarine or marine), but without integrating these into a coherent assessment of coastal biodiversity across the land–sea interface. Trends in assessment indicators in coastal versus non-coastal areas have also rarely been considered. In this study we aimed to compile the first cross-realm national biodiversity assessment for the South African coast using three key indicators. The ecological condition, ecosystem threat status, and ecosystem protection level of coastal ecosystem types (n = 186) were determined and compared with those of non-coastal ecosystem types (n = 444). Nearly half (46.9%) of the South African coastal habitat has been degraded compared with 20% of non-coastal areas. Proportionately, there are three-times (60%) as many threatened coastal ecosystem types (or 55% by area) as there are threatened non-coastal ecosystem types (19%, 6% by area). Despite the impacted state of coastal biodiversity, protection levels are generally higher in the coastal zone (87% of ecosystem types have some protection) compared with non-coastal areas (75%), although fewer coastal ecosystem types have met their biodiversity targets (24%, vs 28% for non-coastal ecosystem types). These results illustrate the importance of using a cross-realm approach for status assessments, management and conservation of coastal biodiversity. The assessment methods described are flexible and widely applicable to other regions

Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands

International audienceThe African continent is facing one of the driest periods in the past three decades as well as continued deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for improved capabilities of monitoring large-scale aboveground carbon stock dynamics. Here we use a satellite dataset based on vegetation optical depth derived from low-frequency passive microwaves (L-VOD) to quantify annual aboveground biomass-carbon changes in sub-Saharan Africa between 2010 and 2016. L-VOD is shown not to saturate over densely vegetated areas. The overall net change in drylands (53% of the land area) was −0.05 petagrams of C per year (Pg C yr$^{−1}$) associated with drying trends, and a net change of −0.02 Pg C yr$^{−1}$ was observed in humid areas. These trends reflect a high inter-annual variability with a very dry year in 2015 (net change, −0.69 Pg C) with about half of the gross losses occurring in drylands. This study demonstrates, first, the applicability of L-VOD to monitor the dynamics of carbon loss and gain due to weather variations, and second, the importance of the highly dynamic and vulnerable carbon pool of dryland savannahs for the global carbon balance, despite the relatively low carbon stock per unit area