Reintroductions backfire by destabilising food webs and triggering further extinction cascades
Johnson, T. F.; Danet, A.; Haefling, T.; Beckerman, A. P.
Show abstract
Conservation interventions like reintroduction are considered vital to bending the curve of biodiversity loss1, with the potential for multiplicative benefits that not only reduce extinction pressure on the reintroduced species, but also restore wider community dynamics and ecosystem functions2,3. Its growing popularity reflects these perceived benefits4. Reintroduction success is usually judged only by the survival of the released species4, but there is no guarantee that the wider community will recover. Using simulated food webs, we show that reintroductions can frequently have unintended negative consequences: triggering extinction cascades, reducing biomass, and destabilising communities. These perverse impacts are unlikely to be detected as reintroduction success is often measured solely by the ability for reintroduced species to survive - which our models suggest is likely - introducing a risk that conservation action superficially appears successful but is actually further depleting our ecosystems.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The spatial configuration of biotic interactions shapes coexistence-area relation-ships in an annual plant community 96%
- Landscape heterogeneity buffers biodiversity of meta-food-webs under global change through rescue and drainage effects 96%
- Extinction cascades, community collapse, and recovery across a Mesozoic hyperthermal event 95%
Similar papers in this journal
- Slower, but deeper community change: anthropogenic impacts on species temporal turnover are regulated by intrinsic dynamics 95%
- Co-occurrence history increases ecosystem temporal stability and recovery from a flood in experimental plant communities 94%
- At what spatial scales are alternative stable states relevant in highly interconnected ecosystems? 92%
"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.