A global review of past land use, climate, and active vs. passive restoration effects on forest recovery

Abstract

Global forest restoration targets have been set, yet policy makers and land managers lack guiding principles on how to invest limited resources to achieve them. We conducted a meta-analysis of 166 studies in naturally regenerating and actively restored forests worldwide to answer: (1) To what extent do floral and faunal abundance and diversity and biogeochemical functions recover? (2) Does recovery vary as a function of past land use, time since restoration, forest region, or precipitation? (3) Does active restoration result in more complete or faster recovery than passive restoration? Overall, forests showed a high level of recovery, but the time to recovery depended on the metric type measured, past land use, and region. Abundance recovered quickly and completely, whereas diversity recovered slower in tropical than in temperate forests. Biogeochemical functions recovered more slowly after agriculture than after logging or mining. Formerly logged sites were mostly passively restored and generally recovered quickly. Mined sites were nearly always actively restored using a combination of planting and either soil amendments or recontouring topography, which resulted in rapid recovery of the metrics evaluated. Actively restoring former agricultural land, primarily by planting trees, did not result in consistently faster or more complete recovery than passively restored sites. Our results suggest that simply ending the land use is sufficient for forests to recover in many cases, but more studies are needed that directly compare the value added of active versus passive restoration strategies in the same system. Investments in active restoration should be evaluated relative to the past land use, the natural resilience of the system, and the specific objectives of each project.

Fig 1. Examples of passive and active forest recovery worldwide.

(a) Three-year-old natural regeneration in a dry forest site in the Yucatan Peninsula, Mexico that was previously used for shifting agriculture; (b) a ~12-year-old natural regeneration in former agricultural land in central Spain; (c) a 300-ha, 6-year-old site in the Atlantic forest of Brazil restored by planting >60 species of trees; (d) a ~7-year-old former coal mine in Queensland Australia restored to a eucalypt woodland by recontouring topography, seeding and planting native species, and fertilizing. Photo credits: (a)–Martha Bonilla-Moheno, (b)—José M. Rey Benayas; (c)–Karen Holl, and (d)–Carl Grant.

Fig 2

(a) Geographic distribution of studies. (b) Number of studies using passive or different active restoration actions as a function of the main past land-use types. Numbers of response variables in each category are indicated in parentheses.

Fig 3. Recovery completeness over time in all forest restoration studies.

(a) Abundance, (b) diversity and (c) biogeochemical functions separated by the explanatory factors that explained the most variation in recovery completeness according to model averaging. Colored lines illustrate means and shaded areas indicate 95% confidence intervals of predicted recovery values based on models. Confidence intervals overlapping the black dashed lines indicate full recovery. Circles at time 0 indicate the mean degraded value before restoration started calculated from raw data. Small dots represent raw data. Note log scale for time since restoration on x-axis. See ‘Materials and methods’ for modeling details.

Fig 4. Recovery completeness of different life forms and biogeochemical functions after the three past land-use types.

(a) Abundance and (b) diversity of different life forms, and (c) biogeochemical functions. Number of response variables and studies in each category are indicated in parentheses.

Fig 5. Recovery completeness in actively and passively restored former agricultural sites over time.

(a) Abundance, (b) diversity, and (c) biogeochemical functions. Colored lines illustrate means and shaded areas indicate 95% confidence intervals of predicted recovery values based on models. Confidence intervals overlapping the black dashed lines indicate full recovery. Circles at time 0 indicate the mean degraded value before restoration started calculated from raw data. Small dots represent raw data. Note log scale for time since restoration on x-axis. See ‘Materials and methods‘ for modeling details.