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A global meta-analysis on the ecological drivers of forest restoration success.

ABSTRACT: Two billion ha have been identified globally for forest restoration. Our meta-analysis encompassing 221 study landscapes worldwide reveals forest restoration enhances biodiversity by 15-84% and vegetation structure by 36-77%, compared with degraded ecosystems. For the first time, we identify the main ecological drivers of forest restoration success (defined as a return to a reference condition, that is, old-growth forest) at both the local and landscape scale. These are as follows: the time elapsed since restoration began, disturbance type and landscape context. The time elapsed since restoration began strongly drives restoration success in secondary forests, but not in selectively logged forests (which are more ecologically similar to reference systems). Landscape restoration will be most successful when previous disturbance is less intensive and habitat is less fragmented in the landscape. Restoration does not result in full recovery of biodiversity and vegetation structure, but can complement old-growth forests if there is sufficient time for ecological succession.

SUBMITTER: Crouzeilles R

PROVIDER: S-EPMC4874030 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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A global meta-analysis on the ecological drivers of forest restoration success.

Crouzeilles Renato R Curran Michael M Ferreira Mariana S MS Lindenmayer David B DB Grelle Carlos E V CE Rey Benayas José M JM

Nature communications 20160519

Two billion ha have been identified globally for forest restoration. Our meta-analysis encompassing 221 study landscapes worldwide reveals forest restoration enhances biodiversity by 15-84% and vegetation structure by 36-77%, compared with degraded ecosystems. For the first time, we identify the main ecological drivers of forest restoration success (defined as a return to a reference condition, that is, old-growth forest) at both the local and landscape scale. These are as follows: the time elap ...[more]

PMID: 27193756

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Project description:Meta-analysis of case studies has become an important tool for synthesizing case study findings in land change. Meta-analyses of deforestation, urbanization, desertification and change in shifting cultivation systems have been published. This present study adds to this literature, with an analysis of the proximate causes and underlying forces of wetland conversion at a global scale using two complementary approaches of systematic review. Firstly, a meta-analysis of 105 case-study papers describing wetland conversion was performed, showing that different combinations of multiple-factor proximate causes, and underlying forces, drive wetland conversion. Agricultural development has been the main proximate cause of wetland conversion, and economic growth and population density are the most frequently identified underlying forces. Secondly, to add a more quantitative component to the study, a logistic meta-regression analysis was performed to estimate the likelihood of wetland conversion worldwide, using globally-consistent biophysical and socioeconomic location factor maps. Significant factors explaining wetland conversion, in order of importance, are market influence, total wetland area (lower conversion probability), mean annual temperature and cropland or built-up area. The regression analyses results support the outcomes of the meta-analysis of the processes of conversion mentioned in the individual case studies. In other meta-analyses of land change, similar factors (e.g., agricultural development, population growth, market/economic factors) are also identified as important causes of various types of land change (e.g., deforestation, desertification). Meta-analysis helps to identify commonalities across the various local case studies and identify which variables may lead to individual cases to behave differently. The meta-regression provides maps indicating the likelihood of wetland conversion worldwide based on the location factors that have determined historic conversions.

Project description:BackgroundForest landscape restoration (FLR) has been adopted by governments and practitioners across the globe to mitigate and adapt to climate change and restore ecological functions across degraded landscapes. However, the extent to which these activities capture CO2 with associated climate mitigation impacts are poorly known, especially in geographies where data on biomass growth of restored forests are limited or do not exist. To fill this gap, we developed biomass accumulation rates for a set of FLR activities (natural regeneration, planted forests and woodlots, agroforestry, and mangrove restoration) across the globe and global CO2 removal rates with corresponding confidence intervals, grouped by FLR activity and region/climate.ResultsPlanted forests and woodlots were found to have the highest CO2 removal rates, ranging from 4.5 to 40.7 t CO2 ha-1 year-1 during the first 20 years of growth. Mangrove tree restoration was the second most efficient FLR at removing CO2, with growth rates up to 23.1 t CO2 ha-1 year-1 the first 20 years post restoration. Natural regeneration removal rates were 9.1-18.8 t CO2 ha-1 year-1 during the first 20 years of forest regeneration, followed by agroforestry, the FLR category with the lowest and regionally broad removal rates (10.8-15.6 t CO2 ha-1 year-1). Biomass growth data was most abundant and widely distributed across the world for planted forests and natural regeneration, representing 45% and 32% of all the data points assessed, respectively. Agroforestry studies, were only found in Africa, Asia, and the Latin America and Caribbean regions.ConclusionThis study represents the most comprehensive review of published literature on tree growth and CO2 removals to date, which we operationalized by constructing removal rates for specific FLR activities across the globe. These rates can easily be applied by practitioners and decision-makers seeking to better understand the positive climate mitigation impacts of existing or planned FLR actions, or by countries making restoration pledges under the Bonn Challenge Commitments or fulfilling Nationally Determined Contributions to the UNFCCC, thereby helping boost FLR efforts world-wide.

Project description:Alpine grassland is the main ecosystem on the Qinghai-Tibet Plateau (QTP). Degradation and restoration of alpine grassland are related to ecosystem function and production, livelihood, and wellbeing of local people. Although a large number of studies research degraded alpine grassland, there are debates about degradation patterns of alpine grassland in different areas and widely applicable ecological restoration schemes due to the huge area of the QTP. In this study, we used the meta-analysis method to synthesize 80 individual published studies which were conducted to examine aboveground and underground characteristics in non-degradation (ND), light degradation (LD), moderate degradation (MD), heavy degradation (HD), and extreme degradation (ED) of alpine grassland on the QTP. Results showed that aboveground biomass (AGB), belowground biomass (BGB), Shannon-Wiener index (H'), soil moisture (SM), soil organic carbon (SOC), soil total nitrogen (TN), and available nitrogen (AN) gradually decreased along the degradation gradient, whereas soil bulk density (BD) and soil pH gradually increased. In spite of a tendency to soil desertification, losses of other soil nutrients and reduction of enzymes, there was no linear relationship between the variations with degradation gradient. Moreover, the decreasing extent of TN was smaller in areas with higher precipitation and temperature, and the decreasing extent of AGB, SOC, and TN was larger in areas with a higher extent of corresponding variables in the stage of ND during alpine grassland degradation. These findings suggest that in areas with higher precipitation and temperature, reseeding and sward cleavage can be used for restoration on degraded alpine grassland. Fencing and fertilization can be used for alpine grassland restoration in areas with lower precipitation and temperature. Microbial enzymes should not be used to restore degraded alpine grassland on a large scale on the QTP without detailed investigation and analysis. Future studies should pay more attention to the effects of climate factors on degradation processes and specific ecological restoration strategies in different regions of the QTP.

Dataset Information

A global meta-analysis on the ecological drivers of forest restoration success.

Publications

A global meta-analysis on the ecological drivers of forest restoration success.

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