Back

A large-scale and long-term experiment to identify effectiveness of ecosystem restoration

Elo, M.; Kareksela, S.; Ovaskainen, O.; Abrego, N.; Niku, J.; Taskinen, S.; Aapala, K.; Kotiaho, J. S.

2024-04-03 ecology
10.1101/2024.04.02.587693 bioRxiv
Show abstract

Ecosystem restoration will increase following the ambitious international targets, which calls for a rigorous evaluation of restoration effectiveness. Studies addressing restoration effectiveness across ecosystems have thus far shown varying and unpredictable patterns. A rigorous assessment of the factors influencing restoration effectiveness is best done with large-scale and long-term experimental data. Here, we present results from a well replicated long-term before-after control-impact experiment on restoration of forestry-drained boreal peatland ecosystems. Our data comprise 151 sites, representing six ecosystem types. Vegetation sampling has been conducted to the species level before restoration and two, five and ten years after restoration. We show that, on average, restoration stops and reverses the trend of further degradation. The variation in restoration outcomes largely arises from ecosystem types: restoration of nutrient-poor ecosystems has higher probability of failure. Our experiment provides clear evidence that restoration can be effective in halting the biodiversity loss of degraded ecosystems, although ecosystem attributes can affect the restoration outcome. These findings underlie the need for evidence-based prioritization of restoration efforts across ecosystems.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.