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Considering the global intensification of aridity in tropical biomes due to climate change, we need to understand what shapes the distribution of drought sensitivity in tropical plants. We conducted a pantropical data synthesis representing 1117 species to test whether xylem-specific hydraulic conductivity (KS), water potential at leaf turgor loss (ΨTLP) and water potential at 50% loss of KS (ΨP50) varied along climate gradients. The ΨTLP and ΨP50 increased with climatic moisture only for evergreen species, but KS did not. Species with high ΨTLP and ΨP50 values were associated with both dry and wet environments. However, drought-deciduous species showed high ΨTLP and ΨP50 values regardless of water availability, whereas evergreen species only in wet environments. All three traits showed a weak phylogenetic signal and a short half-life. These results suggest strong environmental controls on trait variance, which in turn is modulated by leaf habit along climatic moisture gradients in the tropics., Ecology Letters, 25 (12), ISSN:1461-023X, ISSN:1461-0248

The distribution of different vegetation types is important information for landscape management, especially in the context of tackling global environmental change. Vegetation types can be mapped using satellite and airborne passive remote sensing. However, spectrally similar yet structurally different vegetation types, like different tree-dominated land covers, are often challenging to map using spectral information alone. We examined the potential of vertical vegetation structure acquired in the global ecosystem dynamics investigation (GEDI) mission that harnesses a space-borne waveform lidar sensor in vegetation mapping across a heterogeneous tropical landscape in Cambodia. We extracted 121 waveform metrics from Level-1B and Level-2A data products at 1062 locations across five key vegetation types. After reducing the relative height variables’ dimensionality through simple linear regressions, we developed a Random Forest classifier to predict vegetation classes based on 23 GEDI metrics. We then used this model to classify the vegetation types across more than 77 000 GEDI footprints in the study area. GEDI metrics alone were useful in identifying vegetation types with 81% accuracy. Cropland/grassland class had the highest prediction accuracy (user’s accuracy [UA] = 89%; producer’s accuracy [PA] = 91%), while dry deciduous forest had the lowest accuracy (UA = 73%; PA = 69%). By comparing the GEDI-only classification with an optical-radar map, we found that structural and topographic information from GEDI Level-1B and Level-2A can complement the spectral information in assessing natural habitats that neighbor other vegetation types in a heterogeneous landscape. The highest classification accuracy at the footprint scale was obtained from the combination of GEDI, Sentinel-1, and Sentinel-2 (88.3%). We also demonstrated how wall-to-wall vegetation mapping is possible by combining the three data sources. These findings expand the potential use of GEDI waveform lidar data in supporting the development of policy-relevant maps that depict the distribution of forests together with other vegetation types.

Although deforestation remains widespread in the tropics, many places are now experiencing significant forest recovery (i.e., forest transition), offering an optimistic outlook for natural ecosystem recovery and carbon sequestration. Naturally regenerated forests, however, may not persist so a more nuanced understanding of the drivers of forest change in the tropics is critical to ensure the success of reforestation efforts and carbon sequestration targets. Here we use 35 years of detailed land cover data to investigate forest trajectories in 3,014 municipalities in the Brazilian Atlantic Forest, a biodiversity and conservation hotspot. Although deforestation was evident in some regions, deforestation reversals, the typical forest transition trajectory, were the prevalent trend in the Atlantic Forest, accounting for 38% of municipalities. However, simultaneous reforestation reversals in the region (13% of municipalities) suggest that these short-term increases in native forest cover do not necessarily translate into persistent trends. In the absence of reversals in reforestation, forests in the region could have sequestered 1.75 Pg C, over three times the actual estimated carbon sequestration (0.52 Pg C). We also showed that failure to distinguish native and planted forests would have masked native forest cover loss in the region and overestimated reforestation by 3.2Mha and carbon sequestration from natural forest regeneration by 0.37 Pg C. Deforestation reversals were prevalent in urbanized municipalities with limited forest cover and high agricultural productivity, highlighting the importance of favorable socio-economic conditions in promoting reforestation. Successful forest restoration efforts will require development and enforcement of environmental policies that promote forest regeneration and ensure the permanence of regrowing forests. This is crucial not only for the fate and conservation of the Atlantic Forest, but also for other tropical nations to achieve their restoration and carbon sequestration commitments.

Tropical forests are converted at an alarming rate for agricultural use and pastureland, but also regrow naturally through secondary succession. For successful forest restoration, it is essential to understand the mechanisms of secondary succession. These mechanisms may vary across forest types, but analyses across broad spatial scales are lacking. Here, we analyse forest recovery using 1,403 plots that differ in age since agricultural abandonment from 50 sites across the Neotropics. We analyse changes in community composition using species-specific stem wood density (WD), which is a key trait for plant growth, survival and forest carbon storage. In wet forest, succession proceeds from low towards high community WD (acquisitive towards conservative trait values), in line with standard successional theory. However, in dry forest, succession proceeds from high towards low community WD (conservative towards acquisitive trait values), probably because high WD reflects drought tolerance in harsh early successional environments. Dry season intensity drives WD recovery by influencing the start and trajectory of succession, resulting in convergence of the community WD over time as vegetation cover builds up. These ecological insights can be used to improve species selection for reforestation. Reforestation species selected to establish a first protective canopy layer should, among other criteria, ideally have a similar WD to the early successional communities that dominate under the prevailing macroclimatic conditions.

Leaf habit has been hypothesized to define a linkage between the slow-fast plant economic spectrum and the drought resistance-avoidance trade-off in tropical forests ('slow-safe vs fast-risky'). However, variation in hydraulic traits as a function of leaf habit has rarely been explored for a large number of species. We sampled leaf and branch functional traits of 97 tropical dry forest tree species from four sites to investigate whether patterns of trait variation varied consistently in relation to leaf habit along the 'slow-safe vs fast-risky' trade-off. Leaf habit explained from 0% to 43.69% of individual trait variation. We found that evergreen and semi-deciduous species differed in their location along the multivariate trait ordination when compared to deciduous species. While deciduous species showed consistent trait values, evergreen species trait values varied as a function of the site. Last, trait values varied in relation to the proportion of deciduous species in the plant community. We found that leaf habit describes the strategies that define drought avoidance and plant economics in tropical trees. However, leaf habit alone does not explain patterns of trait variation, which suggests quantifying site-specific or species-specific uncertainty in trait variation as the way forward.

Predicting drought responses of individual trees in tropical forests remains challenging, in part because trees experience drought differently depending on their position in spatially heterogeneous environments. Specifically, topography and the competitive environment can influence the severity of water stress experienced by individual trees, leading to individual-level variation in drought impacts. A drought in 2015 in Puerto Rico provided the opportunity to assess how drought response varies with topography and neighborhood crowding in a tropical forest. In this study, we integrated 3 years of annual census data from the El Yunque Chronosequence plots with measurements of functional traits and LiDAR-derived metrics of microsite topography. We fit hierarchical Bayesian models to examine how drought, microtopography, and neighborhood crowding influence individual tree growth and survival, and the role functional traits play in mediating species’ responses to these drivers. We found that while growth was lower during the drought year, drought had no effect on survival, suggesting that these forests are fairly resilient to a single-year drought. However, growth response to drought, as well as average growth and survival, varied with topography: tree growth in valley-like microsites was more negatively affected by drought, and survival was lower on steeper slopes while growth was higher in valleys. Neighborhood crowding reduced growth and increased survival, but these effects did not vary between drought/non-drought years. Functional traits provided some insight into mechanisms by which drought and topography affected growth and survival. For example, trees with high specific leaf area grew more slowly on steeper slopes, and high wood density trees were less sensitive to drought. However, the relationships between functional traits and response to drought and topography were weak overall. Species sorting across microtopography may drive observed relationships between average performance, drought response, and topography. Our results suggest that understanding species’ responses to drought requires consideration of the microenvironments in which they grow. Complex interactions between regional climate, topography, and traits underlie individual and species variation in drought response.

Fishers’ response to temperature change reveals the importance of integrating human behavior in climate change analysis., Climate change will reshape ecological dynamics. Yet, how temperature increases alter the behavior and resource use of people reliant on natural resources remains underexplored. Consequent behavior shifts have the potential to mitigate or accelerate climate impacts on livelihoods and food security. Particularly within the small-scale inland fisheries that support approximately 10% of the global population, temperature changes likely affect both fish and fishers. To analyze how changing temperatures alter households’ fishing behavior, we examined fishing effort and fish catch in a major inland fishery. We used longitudinal observational data from households in Cambodia, which has the highest per-capita consumption of inland fish in the world. Higher temperatures caused households to reduce their participation in fishing but had limited net effects on fish catch. Incorporating human behavioral responses to changing environmental conditions will be fundamental to determining how climate change affects rural livelihoods, food production, and food access.

Scientific communication relies on clear presentation of data. Logarithmic scales are used frequently for data presentation in many scientific disciplines, including ecology, but the degree to which they are correctly interpreted by readers is unclear. Analysing the extent of log scales in the literature, we show that 22% of papers published in the journal Ecology in 2015 included at least one log-scaled axis, of which 21% were log–log displays. We conducted a survey that asked members of the Ecological Society of America (988 responses, and 623 completed surveys) to interpret graphs that were randomly displayed with linear–linear or log–log axes. Many more respondents interpreted graphs correctly when the graphs had linear–linear axes than when they had log–log axes: 93% versus 56% for our all-around metric, although some of the individual item comparisons were even more skewed (for example, 86% versus 9% and 88% versus 12%). These results suggest that misconceptions about log-scaled data are rampant. We recommend that ecology curricula include explicit instruction on how to interpret log-scaled axes and equations, and we also recommend that authors take the potential for misconceptions into account when deciding how to visualize data. Logarithmic scales are frequently used in ecological data display, but the degree to which they are understood is not clear. Here, the authors survey members of the Ecological Society of America and find that only 56% of respondents correctly interpreted data presented on log–log axes.

As global climatic changes increase plant susceptibility to large-scale disturbances such as drought and pathogens, understory responses to these disturbances will become increasingly important to long-term forest dynamics. To better understand understory responses to canopy disturbance, we measured changes in the growth and physiology of the dominant understory shrub, American witch-hazel (Hamamelis virginiana L.), in response to girdling of canopy oaks in a temperate hardwood forest of the northeastern United States. Changes in the growth and physiology of H. virginiana may be important to the regeneration of northeastern temperate forests, as this common shrub largely shapes the microenvironment for seedlings on the forest floor where it occurs. Canopy disturbance by girdling resulted in significant increases in light and soil nitrogen availability. In response to these environmental changes, basal-area growth of H. virginiana increased by an average 334%. This growth increase corresponded to significant increases in foliar nitrogen, respiration, and leaf chlorophyll and carotenoid concentrations. These findings indicate improved environmental conditions and increased growth for this understory shrub following the loss of dominant canopy trees. This study suggests that following large-scale canopy disturbance, H. virginiana and shrubs like it may play an important role in competing for soil N and shading seedlings of regenerating canopy species.

Naturally regenerating and restored second growth forests account for over 70% of tropical forest cover and provide key ecosystem services. Understanding climate change impacts on successional trajectories of these ecosystems is critical for developing effective large-scale forest landscape restoration (FLR) programs. Differences in environmental conditions, species composition, dynamics, and landscape context from old growth forests may exacerbate climate impacts on second growth stands. We compile data from 112 studies on the effects of natural climate variability, including warming, droughts, fires, and cyclonic storms, on demography and dynamics of second growth forest trees and identify variation in forest responses across biomes, regions, and landscapes. Across studies, drought decreases tree growth, survival, and recruitment, particularly during early succession, but the effects of temperature remain unexplored. Shifts in the frequency and severity of disturbance alter successional trajectories and increase the extent of second growth forests. Vulnerability to climate extremes is generally inversely related to long-term exposure, which varies with historical climate and biogeography. The majority of studies, however, have been conducted in the Neotropics hindering generalization. Effects of fire and cyclonic storms often lead to positive feedbacks, increasing vulnerability to climate extremes and subsequent disturbance. Fragmentation increases forests’ vulnerability to fires, wind, and drought, while land use and other human activities influence the frequency and intensity of fire, potentially retarding succession. Comparative studies of climate effects on tropical forest succession across biogeographic regions are required to forecast the response of tropical forest landscapes to future climates and to implement effective FLR policies and programs in these landscapes.

Drought-related tree mortality is now a widespread phenomenon predicted to increase in magnitude with climate change. However, the patterns of which species and trees are most vulnerable to drought, and the underlying mechanisms have remained elusive, in part due to the lack of relevant data and difficulty of predicting the location of catastrophic drought years in advance. We used long-term demographic records and extensive databases of functional traits and distribution patterns to understand the responses of 20 to 53 species to an extreme drought in a seasonally dry tropical forest in Costa Rica, which occurred during the 2015 El Niño Southern Oscillation event. Overall, species-specific mortality rates during the drought ranged from 0% to 34%, and varied little as a function of tree size. By contrast, hydraulic safety margins correlated well with probability of mortality among species, while morphological or leaf economics spectrum traits did not. This firmly suggests hydraulic traits as targets for future research.

Tropical secondary forests recover quickly (decades) in tree species richness but slowly (centuries) in species composition., Old-growth tropical forests harbor an immense diversity of tree species but are rapidly being cleared, while secondary forests that regrow on abandoned agricultural lands increase in extent. We assess how tree species richness and composition recover during secondary succession across gradients in environmental conditions and anthropogenic disturbance in an unprecedented multisite analysis for the Neotropics. Secondary forests recover remarkably fast in species richness but slowly in species composition. Secondary forests take a median time of five decades to recover the species richness of old-growth forest (80% recovery after 20 years) based on rarefaction analysis. Full recovery of species composition takes centuries (only 34% recovery after 20 years). A dual strategy that maintains both old-growth forests and species-rich secondary forests is therefore crucial for biodiversity conservation in human-modified tropical landscapes.

In tropical dry forests, deciduousness (i.e., leaf shedding during the dry season) is an important adaptation of plants to cope with water limitation, which helps trees adjust to seasonal drought. Deciduousness is also a critical factor determining the timing and duration of carbon fixation rates, and affecting energy, water, and carbon balance. Therefore, quantifying deciduousness is vital to understand important ecosystem processes in tropical dry forests. The aim of this study was to map tree species deciduousness in three types of tropical dry forests along a precipitation gradient in the Yucatan Peninsula using Sentinel-2 imagery. We propose an approach that combines reflectance of visible and near-infrared bands, normalized difference vegetation index (NDVI), spectral unmixing deciduous fraction, and several texture metrics to estimate the spatial distribution of tree species deciduousness. Deciduousness in the study area was highly variable and decreased along the precipitation gradient, while the spatial variation in deciduousness among sites followed an inverse pattern, ranging from 91.5 to 43.3% and from 3.4 to 9.4% respectively from the northwest to the southeast of the peninsula. Most of the variation in deciduousness was predicted jointly by spectral variables and texture metrics, but texture metrics had a higher exclusive contribution. Moreover, including texture metrics as independent variables increased the variance of deciduousness explained by the models from R2 = 0.56 to R2 = 0.60 and the root mean square error (RMSE) was reduced from 16.9% to 16.2%. We present the first spatially continuous deciduousness map of the three most important vegetation types in the Yucatan Peninsula using high-resolution imagery.

Fire exclusion in the United States over the last century has had major impacts on forest ecosystems and landscapes. Out of a desire to reverse or mitigate the impacts of fire exclusion, some managers conduct prescribed fires meant to mimic the historic ecological role of fire and restore ecosystem properties. In the Southern Appalachians, fire exclusion in pine- and oak-dominated xeric ridge forests has allowed fire-sensitive hardwood species to establish, filling in the canopy and creating shady, moist conditions that are unfavorable for reproduction of fire-dependent pines and oaks. Managers of natural areas use prescribed fire to restore pine and oak dominance, promote pine and oak regeneration, and reduce stand densities. Here, we use multivariate analysis of monitoring data collected before and after 21 fires over 16 years in fire-suppressed xeric pine-oak forests in the Great Smoky Mountains National Park to assess how community composition and structure change after prescribed fire, to what degree changes after fire persist over time, and how the impacts of prescribed fire vary with fire severity and site environment. Fire consistently reduces stand density and shifts plots towards lower shrub cover and higher herbaceous cover. On the other hand, compositional shifts, i.e. changes in relative abundances of species, were highly variable in both magnitude and direction. Fire severity, measured as total fuel reduction and litter and duff reduction, was important for predicting the magnitude of change after fire. The magnitude of fire effects also varied with elevation, likely reflecting variation in local moisture conditions. Our results indicate that while fires do reduce stand density, they have not yet been successful in consistently restoring pine and oak dominance in the canopy. Restoring pine- and oak-dominance in xeric ridge forests in the Southern Appalachians will thus require extended management focus with flexible, adaptive, long-term planning and continued monitoring and research.

Land-use change occurs nowhere more rapidly than in the tropics, where the imbalance between deforestation and forest regrowth has large consequences for the global carbon cycle(1). However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates are influenced by climate, landscape, and prior land use(2-4). Here we analyse aboveground biomass recovery during secondary succession in 45 forest sites and about 1,500 forest plots covering the major environmental gradients in the Neotropics. The studied secondary forests are highly productive and resilient. Aboveground biomass recovery after 20 years was on average 122 megagrams per hectare (Mg ha(-1)), corresponding to a net carbon uptake of 3.05 Mg C ha(-1) yr(-1), 11 times the uptake rate of old-growth forests. Aboveground biomass stocks took a median time of 66 years to recover to 90% of old-growth values. Aboveground biomass recovery after 20 years varied 11.3-fold ( from 20 to 225 Mg ha(-1)) across sites, and this recovery increased with water availability (higher local rainfall and lower climatic water deficit). We present a biomass recovery map of Latin America, which illustrates geographical and climatic variation in carbon sequestration potential during forest regrowth. The map will support policies to minimize forest loss in areas where biomass resilience is naturally low (such as seasonally dry forest regions) and promote forest regeneration and restoration in humid tropical lowland areas with high biomass resilience.

Climate models predict increases in drought conditions in many parts of the tropics. Yet the response of tropical forests to drought remains highly uncertain, especially with regards to the factors that generate spatial heterogeneity in drought response across landscapes. In this study, we used Landsat imagery to assess the impacts of a severe drought in 2015 across an ~80,000-ha landscape in Puerto Rico. Specifically, we asked whether drought effects varied systematically with topography and with forest age, height, and fragmentation. We quantified drought impacts using anomalies of two vegetation indices, the enhanced vegetation index (EVI) and normalized difference water index (NDWI), and fit random forest models of these metrics including slope, aspect, forest age, canopy height, and two indices of fragmentation as predictors. Drought effects were more severe on drier topographic positions, that is, steeper slopes and southwest-facing aspects, and in second-growth forests. Shorter and more fragmented forests were also more strongly affected by drought. We also assessed which factors were associated with stronger recovery from drought. Factors associated with more negative drought anomalies were also associated with more positive postdrought anomalies, suggesting that increased light availability as a result of drought led to high rates of recovery in forests more severely affected by drought. In general, recovery from drought was rapid across the landscape, with postdrought anomalies at or above average across the study area. This suggests that forests in Puerto Rico might be resilient to a single-year drought, though vulnerability to drought varies depending on forest characteristics and landscape position.

© 2018 The Author(s). The nutrient demands of regrowing tropical forests are partly satisfied by nitrogen-fixing legume trees, but our understanding of the abundance of those species is biased towards wet tropical regions. Here we show how the abundance of Leguminosae is affected by both recovery from disturbance and large-scale rainfall gradients through a synthesis of forest inventory plots from a network of 42 Neotropical forest chronosequences. During the first three decades of natural forest regeneration, legume basal area is twice as high in dry compared with wet secondary forests. The tremendous ecological success of legumes in recently disturbed, water-limited forests is likely to be related to both their reduced leaflet size and ability to fix N2, which together enhance legume drought tolerance and water-use efficiency. Earth system models should incorporate these large-scale successional and climatic patterns of legume dominance to provide more accurate estimates of the maximum potential for natural nitrogen fixation across tropical forests.

Identifying the processes that maintain highly diverse plant communities remains a central goal in ecology. Species variation in growth and survival rates across ontogeny, represented by tree size classes and life history stage-specific niche partitioning, are potentially important mechanisms for promoting forest diversity. However, the role of ontogeny in mediating competitive dynamics and promoting functional diversity is not well understood, particular in high-diversity systems such as tropical forests. The interaction between interspecific functional trait variation and ontogenetic shifts in competitive dynamics may yield insights into the ecophysiological mechanisms promoting community diversity. We investigated how functional trait (seed size, maximum height, SLA, leaf N, and wood density) associations with growth, survival, and response to competing neighbors differ among seedlings and two size classes of trees in a subtropical rain forest in Puerto Rico. We used a hierarchical Bayes model of diameter growth and survival to infer trait relationships with ontogenetic change in competitive dynamics. Traits were more strongly associated with average growth and survival than with neighborhood interactions, and were highly consistent across ontogeny for most traits. The associations between trait values and tree responses to crowding by neighbors showed significant shifts as trees grew. Large trees exhibited greater growth as the difference in species trait values among neighbors increased, suggesting trait-associated niche partitioning was important for the largest size class. Our results identify potential axes of niche partitioning and performance-equalizing functional trade-offs across ontogeny, promoting species coexistence in this diverse forest community.

The incidence of escaped agricultural fire has recently been increasing in the Western Amazon, driven by climate variability, land use change, and changes in patterns of residency and land occupation. Preventing and mitigating the negative impacts of fire in the Amazon require a comprehensive understanding not only of what the drivers of fire activity are, but also how these drivers interact and vary across scales. Here, we combine multi-scalar data on land use, climate, and landowner residency to disentangle the drivers of fire activity over 10 years (2001–2010) on individual landholdings in a fire-prone region of the Peruvian Amazon. We examined the relative importance of and interactions between climate variability (drought intensity), land occupation (in particular, landowner absenteeism), and land cover variables (cover of fallow and pasture) for predicting both fire occurrence (whether or not fire was detected on a farm in a given year) and fire size. Drought intensity was the most important predictor of fire occurrence, but land-cover type and degree of landowner absenteeism increased fire probability when conditions were dry enough. On the other hand, drought intensity did not stand out relative to other significant predictors in the fire size model, where degree of landowner absenteeism in a village and percent cover of fallow in a village were also strongly associated with fire size. We also investigated to what extent these variables measured at the individual landholding versus the village scale influenced fire activity. While the predictors measured at the landholding and village scales were approximately of equal importance for modeling fire occurrence, only village scale predictors were important in the model of fire size. These results demonstrate that the relative importance of various drivers of fire activity can vary depending on the scale at which they are measured and the scale of analysis. Additionally, we highlight how a full understanding of the drivers of fire activity should go beyond fire occurrence to consider other metrics of fire activity such as fire size, as implications for fire prevention and mitigation can be different depending on the model considered. Drought early warning systems may be most effective for preventing fire in dry years, but management to address the impacts of landowner absenteeism, such as bolstering community fire control efforts in high-risk areas, could help minimize the size of fires when they do occur. Thus, interventions should focus on minimizing fire size as well as preventing fires altogether, especially because fire is an inexpensive and effective management tool that has been in use for millennia.

Tropical second-growth forests could help mitigate climate change, but the degree to which their carbon potential is achieved will depend on exposure to disturbance. Wind disturbance is common in tropical forests, shaping structure, composition, and function, and influencing successional trajectories. However, little is known about the impacts of extreme winds on second-growth forests in fragmented landscapes, though these ecosystems are often located in mosaics of forest, pasture, cropland, and other land cover types. Indirect evidence suggests that fragmentation increases risk of wind damage in tropical forests, but no studies have found such impacts following severe storms. In this study, we ask whether fragmentation and forest type (old vs. second growth) were associated with variation in wind damage after a severe convective storm in a fragmented production landscape in western Amazonia. We applied linear spectral unmixing to Landsat 8 imagery from before and after the storm, and combined it with field observations of damage to map wind effects on forest structure and biomass. We also used Landsat 8 imagery to map land cover with the goals of identifying old- and second-growth forest and characterizing fragmentation. We used these data to assess variation in wind disturbance across 95,596 hectares of forest, distributed over 6,110 patches. We find that fragmentation is significantly associated with wind damage, with damage severity higher at forest edges and in edgier, more isolated patches. Damage was also more severe in old-growth than in second-growth forests, but this effect was weaker than that of fragmentation. These results illustrate the importance of considering landscape context in planning tropical forest restoration and natural regeneration projects. Assessments of long-term carbon sequestration potential need to consider spatial variation in disturbance exposure. Where risk of extreme winds is high, minimizing fragmentation and isolation could increase carbon sequestration potential. This article is protected by copyright. All rights reserved.

Models reveal the high carbon mitigation potential of tropical forest regeneration., Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We estimate the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades. Our model shows that, in 2008, second-growth forests (1 to 60 years old) covered 2.4 million km2 of land (28.1% of the total study area). Over 40 years, these lands can potentially accumulate a total aboveground carbon stock of 8.48 Pg C (petagrams of carbon) in aboveground biomass via low-cost natural regeneration or assisted regeneration, corresponding to a total CO2 sequestration of 31.09 Pg CO2. This total is equivalent to carbon emissions from fossil fuel use and industrial processes in all of Latin America and the Caribbean from 1993 to 2014. Ten countries account for 95% of this carbon storage potential, led by Brazil, Colombia, Mexico, and Venezuela. We model future land-use scenarios to guide national carbon mitigation policies. Permitting natural regeneration on 40% of lowland pastures potentially stores an additional 2.0 Pg C over 40 years. Our study provides information and maps to guide national-level forest-based carbon mitigation plans on the basis of estimated rates of natural regeneration and pasture abandonment. Coupled with avoided deforestation and sustainable forest management, natural regeneration of second-growth forests provides a low-cost mechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity and ecosystem services.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes; International audience; Tropical reforestation (TR) has been highlighted as an important intervention for climate change mitigation because of its carbon storage potential. TR can also play other frequently overlooked, but significant, roles in helping society and ecosystems adapt to climate variability and change. For example, reforestation can ameliorate climate-associated impacts of altered hydrological cycles in watersheds, protect coastal areas from increased storms, and provide habitat to reduce the probability of species' extinctions under a changing climate. Consequently, reforestation should be managed with both adaptation and mitigation objectives in mind, so as to maximize synergies among these diverse roles, and to avoid trade-offs in which the achievement of one goal is detrimental to another. Management of increased forest cover must also incorporate measures for reducing the direct and indirect impacts of changing climate on reforestation itself. Here we advocate a focus on " climate-smart reforestation, " defined as reforesting for climate change mitigation and adaptation, while ensuring that the direct and indirect impacts of climate change on reforestation are anticipated and minimized. Implications for Practice • Tropical reforestation has a clearly recognized potential for mitigating climate change, but its role in reducing vulnerability to climate change should also be acknowledged. • Climate-smart reforestation should be promoted, that is, reforesting for climate change mitigation and adaptation , while ensuring that the direct and indirect impacts of climate change on reforestation are anticipated and minimized. • Reforestation practices should be designed to avoid the implementation of one strategy (mitigation or adaptation) to the detriment of the other. • Adequate climate policy or institutional arrangements and appropriate technical assistance and information are needed if managers are to pursue the objectives of climate-smart reforestation. • Climate-smart reforestation should be integrated into broader disaster risk reduction programs, adaptation strategies, and landscape management plans.

Many countries have made major commitments to carbon sequestration through reforestation under the Paris Climate Agreement, and recent studies have illustrated the potential for large amounts of carbon sequestration in tropical second-growth forests. However, carbon gains in second-growth forests are threatened by non-permanence, i.e. release of carbon into the atmosphere from clearing or disturbance. The benefits of second-growth forests require long-term persistence on the landscape, but estimates of carbon potential rarely consider the spatio-temporal landscape dynamics of second-growth forests. In this study, we used remotely sensed imagery from a landscape in the Peruvian Amazon to examine patterns of second-growth forest regrowth and permanence over 28 years (1985-2013). By 2013, 44% of all forest cover in the study area was second growth and more than 50% of second-growth forest pixels were less than 5 years old. We modeled probabilities of forest regrowth and clearing as a function of landscape factors. The amount of neighboring forest and variables related to pixel position (i.e. distance to edge) were important for predicting both clearing and regrowth. Forest age was the strongest predictor of clearing probability and suggests a threshold response of clearing probability to age. Finally, we simulated future trajectories of carbon sequestration using the parameters from our models. We compared this with the amount of biomass that would accumulate under the assumption of second-growth permanence. Estimates differed by 900,000 tonnes, equivalent to over 80% of Peru's commitment to carbon sequestration through community reforestation under the Paris Agreement. Though the study area has more than 40,000 hectares of second-growth forest, only a small proportion is likely to accumulate significant carbon. Instead, cycles between forest and non-forest are common. Our results illustrate the importance of considering landscape dynamics when assessing the carbon sequestration potential of second-growth forests.