Governments and the private sector are realizing the manifold benefits of restoring degraded landscapes. How can we make these projects cost-effective and successful? The SESYNC team examined 166 restoration studies to find the answer.
Over the past five years there have been numerous global, regional, and national targets set for forest landscape restoration (FLR). These bold targets are motivated by diverse goals, including conserving biodiversity, sequestering carbon, improving water supply, and sustaining human livelihoods (Chazdon et al. 2017). The overriding challenge is how to implement restoration projects spanning tens to hundreds of hectares, in order to meet the millions of hectares of forest restoration promised by national governments (Holl 2017). A first step in is to synthesise and learn from past work.
How did we go about this?
We identified 166 restoration studies and conducted a meta-analysis to figure out what factors influence the degree of forest recovery across the world. We focused on the recovery of abundance and diversity of plant and animal populations and nutrient cycling functions. We also looked at whether recovery was affected by the type of past land use (was the area mined, logged, or used for agriculture?) and the existing forest type (tropical or temperate, wet or dry). We compared the rate and degree of recovery in former agricultural sites that were left alone until the landscape recovered (passive recovery) and those where trees were planted (active recovery). To learn more about our analytical approach and the types of restoration practices used after different disturbance types, see our earlier blog and our recent open access paper on this study (Meli et al. 2017).
What did we learn?
Our quantitative synthesis of global forest restoration efforts supports a few general conclusions and recommendations.
One, we learned that many forests can recover floral and faunal abundance and diversity relatively quickly, an important result given the growing interest in FLR and the importance of ecosystem services. Plant and animal abundance recovered the most quickly (within 10 years) but the diversity of species and the functions they served took longer to return to reference forest values, taking from 30 to 40 years on average. This does not mean that all species and functions recover in all forests. It typically takes much longer for the full suite of forest-dependent species to recover (Curran et al. 2014).
Two, our results clearly show that different metrics (e.g. plant abundance, nutrient cycling) respond variably to restoration actions. Nonetheless, many of the large-scale forest restoration initiatives set lofty goals to simultaneously restore ecological integrity, biodiversity, climate resilience, and a range of social goals across millions of hectares, despite the fact that specific ecological restoration objectives are often conflicting and variable depending on localised social and ecological constraints. Therefore, it is important that individual restoration projects clearly define measurable objectives from the outset to evaluate the efficacy of active restoration methods in achieving specific desired outcomes.
Three, we found high recovery in many studies where the land use ceased and there was no further human intervention. This tells us that passive recovery is a viable and less expensive restoration option in cases where initial recovery may be rapid and the approach fits with broader project goals (Chazdon & Guariguata 2016). This does not mean all sites will recover quickly without active planting or improvement of abiotic conditions. But, given limited resources for active restoration, passive restoration should be considered as an option and the natural resilience of a given site assessed, prior to selecting a restoration approach.
Four, our study did not show consistent differences overall in the recovery in actively and passively restored sites that were used previously for agriculture. Rather, there was a high degree of variability with some studies and response variables showing positive effects of active restoration interventions and others showing no or negative effects. We hasten to note, however, that few studies compared active and passive restoration in the same site so it is difficult to make robust comparisons. More projects and scientific studies are needed that directly compare passive recovery with a mix of active restoration approaches and monitor the results for multiple years.
Our study highlighted the need to tailor restoration strategies to a) the resilience of the ecosystem you’re trying to restore and b) your specific project goals to most effectively allocate your limited resources. The high variations in the rate of passive recovery across sites and the mixed effects of active restoration show that you need to carefully consider all options and decide which ones are best suited to the site and project goals.
For example, passive recovery should be considered on sites that were logged and in landscapes where there are sufficient sources of colonising plants and animals. Conversely, tree planting may be more appropriate on sites where recovery is slower or where a primary goal of the study it to provide specific high value trees for the local community.
We also suggest that land managers wait a few years to observe the rate and direction of natural recovery, before investing in active restoration efforts. Clearly, selecting restoration strategies requires considering ecological and social goals in addition to institutional and policy factors.
By Karen D. Holl, Paula Meli, José M. Rey Benayas, and the SESYNC/iDIV Restoration Synthesis Working Group
This project is part of a larger study synthesising results of ecosystem recovery and restoration across a range of ecosystem types that is funded by the U.S. National Socio-Environmental Synthesis Center and the German Centre for Integrative Biodiversity Research. This study on forest recovery is supported by UK aid from the UK government through the KNOWFOR project.
Chazdon, RL, PHS Brancalion, D Lamb, L Laestadius, M Calmon & others. 2017. A policy-driven knowledge agenda for global forest and landscape restoration. Conservation Letters125-132.
Chazdon, RL & MR Guariguata. 2016. Natural regeneration as a tool for large-scale forest restoration in the tropics: prospects and challenges. Biotropica 48:716-730.
Curran, M, S Hellweg & J Beck. 2014. Is there any empirical support for biodiversity offset policy? Ecological Applications 24:617-632.
Holl, KD. 2017. Restoring tropical forests from the bottom up. Science 355:455-456.
Meli, P, KD Holl, JMR Benayas, HP Jones, PC Jones & others. 2017. A global review of past land use, climate, and active vs. passive restoration effects on forest recovery. Plos One 12:e0171368.