Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth.

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9-51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.

Predicción de la Recuperación de la Biodiversidad a Escala de Paisaje según la Regeneración Natural del Bosque Tropical Resumen La regeneración natural del bosque es una solución rentable para la recuperación de la biodiversidad basada en la naturaleza, sin embargo, los diferentes factores socioambientales pueden derivar en resultados variables. Cómo predecir la ubicación en donde la regeneración natural del bosque recuperará los niveles de biodiversidad, los cuales son un indicador del valor de la conservación y un suministro potencial de diferentes servicios ambientales, es un vacío de conocimiento importante en la planeación de la restauración forestal. Buscamos predecir y mapear la recuperación a escala de paisaje de la riqueza de especies y la abundancia total de vertebrados, invertebrados y plantas en bosques tropicales y subtropicales de segundo crecimiento para guiar la planeación de la restauración. Primero, realizamos un metaanálisis mundial para cuantificar la medida a la que se desvió la recuperación de la riqueza y la abundancia total de especies en los bosques de segundo crecimiento de los valores de biodiversidad en los bosques antiguos referenciales en el mismo paisaje. Después, utilizamos un algoritmo de aprendizaje automático y un conjunto integral de factores socioambientales para predecir espacialmente la desviación a escala de paisaje para después mapearla. Los modelos explicaron en promedio el 34% de la varianza observada en la recuperación (rango de 9-51%). La recuperación de la biodiversidad a escala de paisaje en los bosques de segundo crecimiento pudo predecirse espacialmente con base en los factores socioambientales del paisaje (demografía humana, uso y cobertura del suelo, alteraciones naturales y antropogénicas, productividad del ecosistema, tipo de topografía y de suelo); fue significativamente más alta para la riqueza de especies que para la abundancia total de vertebrados (desviación media pronosticada ajustada al rango de 0.09 versus 0.34) e invertebrados (0.2 versus 0.35) pero no para las plantas (las cuales mostraron una recuperación similar para ambas medidas [0.24 versus 0.25]); y tuvo una correlación positiva para la abundancia de especies de plantas y vertebrados (Pearson r =0.45, p=0.001). Nuestra estrategia puede ayudar a identificar los paisajes de bosques tropicales y subtropicales con un potencial alto para la recuperación de la biodiversidad por medio de la regeneración natural del bosque.

The role of land-use history in driving successional pathways and its implications for the restoration of tropical forests.

Secondary forests are increasingly important components of human-modified landscapes in the tropics. Successional pathways, however, can vary enormously across and within landscapes, with divergent regrowth rates, vegetation structure and species composition. While climatic and edaphic conditions drive variations across regions, land-use history plays a central role in driving alternative successional pathways within human-modified landscapes. How land use affects succession depends on its intensity, spatial extent, frequency, duration and management practices, and is mediated by a complex combination of mechanisms acting on different ecosystem components and at different spatial and temporal scales. We review the literature aiming to provide a comprehensive understanding of the mechanisms underlying the long-lasting effects of land use on tropical forest succession and to discuss its implications for forest restoration. We organize it following a framework based on the hierarchical model of succession and ecological filtering theory. This review shows that our knowledge is mostly derived from studies in Neotropical forests regenerating after abandonment of shifting cultivation or pasture systems. Vegetation is the ecological component assessed most often. Little is known regarding how the recovery of belowground processes and microbiota communities is affected by previous land-use history. In published studies, land-use history has been mostly characterized by type, without discrimination of intensity, extent, duration or frequency. We compile and discuss the metrics used to describe land-use history, aiming to facilitate future studies. The literature shows that (i) species availability to succession is affected by transformations in the landscape that affect dispersal, and by management practices and seed predation, which affect the composition and diversity of propagules on site. Once a species successfully reaches an abandoned field, its establishment and performance are dependent on resistance to management practices, tolerance to (modified) soil conditions, herbivory, competition with weeds and invasive species, and facilitation by remnant trees. (ii) Structural and compositional divergences at early stages of succession remain for decades, suggesting that early communities play an important role in governing further ecosystem functioning and processes during succession. Management interventions at early stages could help enhance recovery rates and manipulate successional pathways. (iii) The combination of local and landscape conditions defines the limitations to succession and therefore the potential for natural regeneration to restore ecosystem properties effectively. The knowledge summarized here could enable the identification of conditions in which natural regeneration could efficiently promote forest restoration, and where specific management practices are required to foster succession. Finally, characterization of the landscape context and previous land-use history is essential to understand the limitations to succession and therefore to define cost-effective restoration strategies. Advancing knowledge on these two aspects is key for finding generalizable relations that will increase the predictability of succession and the efficiency of forest restoration under different landscape contexts.

Hidden destruction of older forests threatens Brazil's Atlantic Forest and challenges restoration programs.

Understanding the dynamics of native forest loss and gain is critical for biodiversity conservation and ecosystem services, especially in regions experiencing intense forest transformations. We quantified native forest cover dynamics on an annual basis from 1990 to 2017 in Brazil's Atlantic Forest. Despite the relative stability of native forest cover during this period (~28 Mha), the ongoing loss of older native forests, mostly on flatter terrains, have been hidden by the increasing gain of younger native forest cover, mostly on marginal lands for mechanized agriculture. Changes in native forest cover and its spatial distribution increased forest isolation in 36.4% of the landscapes. The clearance of older forests associated with the recut of 27% of younger forests has resulted in a progressive rejuvenation of the native forest cover. We highlight the need to include native forest spatiotemporal dynamics into restoration programs to better estimate their expected benefits and unexpected problems.

Soil dynamics in forest restoration: a data set for temperate and tropical regions.

Restoring forest ecosystems has become a global priority. Yet, soil dynamics are still poorly assessed among restoration studies and there is a lack of knowledge on how soil is affected by forest restoration process. Here, we compile information on soil dynamics in forest restoration based on soil physical, chemical, and biological attributes in temperate and tropical forest regions. It encompasses 50 scientific papers across 17 different countries and contains 1,469 points of quantitative information of soil attributes between reference (e.g., old-growth forest) and restored ecosystems (e.g., forests in their initial or secondary stage of succession) within the same study. To be selected, studies had to be conducted in forest ecosystems, to include multiple sampling sites (replicates) in both restored and reference ecosystems, and to encompass quantitative data of soil attributes for both reference and restored ecosystems. We recorded in each study the following information: (1) study year, (2) country, (3) forest region (tropical or temperate), (4) latitude, (5) longitude, (6) soil class, (7) past disturbance, (8) restoration strategy (active or passive), (9) restoration age, (10) soil attribute type (physical, chemical, or biological); (11) soil attribute, (12) soil attribute unit, (13) soil sampling (procedures), (14) date of sampling, (15) soil depth sampled, (16) soil analysis, (17) quantitative values of soil attributes for both restored and reference ecosystems, (18) type of variation (standard error of deviation) for both restored and reference ecosystems, and (19) quantitative values of the variation for both restored and reference ecosystems. These were the most common data available in the selected studies. This extensive database on the extent soil physical, chemical, and biological attributes differ between reference and restored ecosystems can fill part of the existing gap on both soil science and forest restoration in terms of (1) which are the critical soil attributes to be monitored during forest restoration? and (2) how do environmental factors affect soil attributes in forest restoration? The data will be made available to the scientific community for further analyses on both soil science and forest restoration. Soil information gaps during the forest restoration process and their general patterns can be addressed using this data set. There are no copyright or proprietary restrictions.

Global priority areas for ecosystem restoration.

Extensive ecosystem restoration is increasingly seen as being central to conserving biodiversity1 and stabilizing the climate of the Earth2. Although ambitious national and global targets have been set, global priority areas that account for spatial variation in benefits and costs have yet to be identified. Here we develop and apply a multicriteria optimization approach that identifies priority areas for restoration across all terrestrial biomes, and estimates their benefits and costs. We find that restoring 15% of converted lands in priority areas could avoid 60% of expected extinctions while sequestering 299 gigatonnes of CO2-30% of the total CO2 increase in the atmosphere since the Industrial Revolution. The inclusion of several biomes is key to achieving multiple benefits. Cost effectiveness can increase up to 13-fold when spatial allocation is optimized using our multicriteria approach, which highlights the importance of spatial planning. Our results confirm the vast potential contributions of restoration to addressing global challenges, while underscoring the necessity of pursuing these goals synergistically.

Emerging threats linking tropical deforestation and the COVID-19 pandemic.

Tropical deforestation drivers are complex and can change rapidly in periods of profound societal transformation, such as those during a pandemic. Evidence suggests that the COVID-19 pandemic has spurred illegal, opportunistic forest clearing in tropical countries, threatening forest ecosystems and their resident human communities. A total of 9583 km2 of deforestation alerts from Global Land Analysis & Discovery (GLAD) were detected across the global tropics during the first month following the implementation of confinement measures of local governments to reduce COVID-19 spread, which is nearly double that of 2019 (4732 km2). We present a conceptual framework linking tropical deforestation and the current pandemic. Zoonotic diseases, public health, economy, agriculture, and forests may all be reciprocally linked in complex positive and negative feedback loops with overarching consequences. We highlight the emerging threats to nature and society resulting from this complex reciprocal interplay and possible policy interventions that could minimize these threats.

Author Correction: Strategic approaches to restoring ecosystems can triple conservation gains and halve costs.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Global restoration opportunities in tropical rainforest landscapes.

Over 140 Mha of restoration commitments have been pledged across the global tropics, yet guidance is needed to identify those landscapes where implementation is likely to provide the greatest potential benefits and cost-effective outcomes. By overlaying seven recent, peer-reviewed spatial datasets as proxies for socioenvironmental benefits and feasibility of restoration, we identified restoration opportunities (areas with higher potential return of benefits and feasibility) in lowland tropical rainforest landscapes. We found restoration opportunities throughout the tropics. Areas scoring in the top 10% (i.e., restoration hotspots) are located largely within conservation hotspots (88%) and in countries committed to the Bonn Challenge (73%), a global effort to restore 350 Mha by 2030. However, restoration hotspots represented only a small portion (19.1%) of the Key Biodiversity Area network. Concentrating restoration investments in landscapes with high benefits and feasibility would maximize the potential to mitigate anthropogenic impacts and improve human well-being.

Strategic approaches to restoring ecosystems can triple conservation gains and halve costs.

International commitments for ecosystem restoration add up to one-quarter of the world's arable land. Fulfilling them would ease global challenges such as climate change and biodiversity decline but could displace food production and impose financial costs on farmers. Here, we present a restoration prioritization approach capable of revealing these synergies and trade-offs, incorporating ecological and economic efficiencies of scale and modelling specific policy options. Using an actual large-scale restoration target of the Atlantic Forest hotspot, we show that our approach can deliver an eightfold increase in cost-effectiveness for biodiversity conservation compared with a baseline of non-systematic restoration. A compromise solution avoids 26% of the biome's current extinction debt of 2,864 plant and animal species (an increase of 257% compared with the baseline). Moreover, this solution sequesters 1 billion tonnes of CO2-equivalent (a 105% increase) while reducing costs by US$28 billion (a 57% decrease). Seizing similar opportunities elsewhere would offer substantial contributions to some of the greatest challenges for humankind.

Planning protected areas network that are relevant today and under future climate change is possible: the case of Atlantic Forest endemic birds.

BACKGROUND: A key strategy in biodiversity conservation is the establishment of protected areas. In the future, however, the redistribution of species in response to ongoing climate change is likely to affect species' representativeness in those areas. Here we quantify the effectiveness of planning protected areas network to represent 151 birds endemic to the Brazilian Atlantic Forest hotspot, under current and future climate change conditions for 2050. METHODS: We combined environmental niche modeling and systematic conservation planning using both a county and a regional level planning strategy. We recognized the conflict between biodiversity conservation and economic development, including socio-economic targets (as opposed to biological only) and using planning units that are meaningful for policy-makers. RESULTS: We estimated an average contraction of 29,500 km2 in environmentally suitable areas for birds, representing 52% of currently suitable areas. Still, the most cost-effective solution represented almost all target species, requiring only ca. 10% of the Atlantic Forest counties to achieve that representativeness, independent of strategy. More than 50% of these counties were selected both in the current and future planned networks, representing >83% of the species. DISCUSSION: Our results indicate that: (i) planning protected areas network currently can be useful to represent species under climate change; (ii) the overlapped planning units in the best solution for both current and future conditions can be considered as "no regret" areas; (iii) priority counties are spread throughout the biome, providing specific guidance wherever the possibility of creating protected area arises; and (iv) decisions can occur at different administrative spheres (Federal, State or County) as we found quite similar numerical solutions using either county or regional level strategies.

Ecological restoration success is higher for natural regeneration than for active restoration in tropical forests.

Is active restoration the best approach to achieve ecological restoration success (the return to a reference condition, that is, old-growth forest) when compared to natural regeneration in tropical forests? Our meta-analysis of 133 studies demonstrated that natural regeneration surpasses active restoration in achieving tropical forest restoration success for all three biodiversity groups (plants, birds, and invertebrates) and five measures of vegetation structure (cover, density, litter, biomass, and height) tested. Restoration success for biodiversity and vegetation structure was 34 to 56% and 19 to 56% higher in natural regeneration than in active restoration systems, respectively, after controlling for key biotic and abiotic factors (forest cover, precipitation, time elapsed since restoration started, and past disturbance). Biodiversity responses were based primarily on ecological metrics of abundance and species richness (74%), both of which take far less time to achieve restoration success than similarity and composition. This finding challenges the widely held notion that natural forest regeneration has limited conservation value and that active restoration should be the default ecological restoration strategy. The proposition that active restoration achieves greater restoration success than natural regeneration may have arisen because previous comparisons lacked controls for biotic and abiotic factors; we also did not find any difference between active restoration and natural regeneration outcomes for vegetation structure when we did not control for these factors. Future policy priorities should align the identified patterns of biophysical and ecological conditions where each or both restoration approaches are more successful, cost-effective, and compatible with socioeconomic incentives for tropical forest restoration.

Forest restoration: a global dataset for biodiversity and vegetation structure.

Restoration initiatives are becoming increasingly applied around the world. Billions of dollars have been spent on ecological restoration research and initiatives, but restoration outcomes differ widely among these initiatives in part due to variable socioeconomic and ecological contexts. Here, we present the most comprehensive dataset gathered to date on forest restoration. It encompasses 269 primary studies across 221 study landscapes in 53 countries and contains 4,645 quantitative comparisons between reference ecosystems (e.g., old-growth forest) and degraded or restored ecosystems for five taxonomic groups (mammals, birds, invertebrates, herpetofauna, and plants) and five measures of vegetation structure reflecting different ecological processes (cover, density, height, biomass, and litter). We selected studies that (1) were conducted in forest ecosystems; (2) had multiple replicate sampling sites to measure indicators of biodiversity and/or vegetation structure in reference and restored and/or degraded ecosystems; and (3) used less-disturbed forests as a reference to the ecosystem under study. We recorded (1) latitude and longitude; (2) study year; (3) country; (4) biogeographic realm; (5) past disturbance type; (6) current disturbance type; (7) forest conversion class; (8) restoration activity; (9) time that a system has been disturbed; (10) time elapsed since restoration started; (11) ecological metric used to assess biodiversity; and (12) quantitative value of the ecological metric of biodiversity and/or vegetation structure for reference and restored and/or degraded ecosystems. These were the most common data available in the selected studies. We also estimated forest cover and configuration in each study landscape using a recently developed 1 km consensus land cover dataset. We measured forest configuration as the (1) mean size of all forest patches; (2) size of the largest forest patch; and (3) edge:area ratio of forest patches. Global analyses of the factors influencing ecological restoration success at both the local and landscape scale are urgently needed to guide restoration initiatives and to further develop restoration knowledge in a topic area of much contemporary interest.

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

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.