Understanding turning points in dryland ecosystem functioning

Covering around 41% of Earth’s surface and supporting more than one-third of human livelihoods, dryland ecosystems are unquestionably important. Considering that these regions foster many livelihoods that are vulnerable due to poverty and food insecurity (issues that should be exacerbated by climate change), understanding changes in dryland ecosystems and their drivers becomes even more important. Changes in dryland ecosystem functioning can take place gradually or abruptly (the so-called turning points, or TP). Better understanding where and how TPs occur, what causes them, and whether or not they can be predicted could support nature conservation and food security in drylands. With that in mind, first we detected where and when TPs in dryland ecosystem functioning mostly occurred, and characterizing them based on the direction and rate of change before/after the TP. This was done by using time series (1982-2015) of vegetation productivity and precipitation data in global drylands. Hotspot regions with high TP occurrence were detected in North America, the Sahel, Central Asia, and Australia. Next, we focused on better understanding the drivers of abrupt changes and ecosystem productivity in drylands, by (i) studying a drought-induced woody plants die-off case that occurred in Senegal in 2014-2015 and (ii) assessing the anthropogenic footprint over drylands. Although anthropogenic pressure did not present a significant impact over the die-off severity and post-disturbance recovery, soil physical characteristics showed to be important for both. The anthropogenic footprint assessment showed that from 1982 to 2015 there was a decrease in over-productive dryland areas due to human activity, while under-productive areas increased. Finally, the predictability of TPs was evaluated in the Sahel. We demonstrated the usefulness of using changes in ecosystems' resilience as an early warning indicator of abrupt changes, and also showed that human activity might hamper the use of such an early warning signal. We hope that our findings can support decision making and a correct allocation of resources, e.g., by supporting policymakers in the decision of whether or not intervention is needed, by helping in determining the necessary measures to be implemented, and by supporting in the delimitation of priority areas for conservation and/or management.