Clustered disturbances lead to bias in large-scale estimates based on forest sample plots

Exploring characteristics of national forest inventories for integration with global space-based forest biomass data

National forest inventories (NFIs) are a reliable source for national forest measurements. However, they are usually not developed for linking with remotely sensed (RS) biomass information. There are increasing needs and opportunities to facilitate this link towards better global and national biomass estimation. Thus, it is important to study and understand NFI characteristics relating to their integration with space-based products; in particular for the tropics where NFIs are quite recent, less frequent, and partially incomplete in several countries. Here, we (1) assessed NFIs in terms of their availability, temporal distribution, and extent in 236 countries from FAO's Global Forest Resources Assessment (FRA) 2020; (2) compared national forest biomass estimates in 2018 from FRA and global space-based Climate Change Initiative (CCI) product in 182 countries considering NFI availability and temporality; and (3) analyzed the latest NFI design characteristics in 46 tropical countries relating to their integration with space-based biomass datasets. We observed significant NFI availability globally and multiple NFIs were mostly found in temperate and boreal countries while most of the single NFI countries (94 %) were in the tropics. The latest NFIs were more recent in the tropics and many countries (35) implemented NFIs from 2016 onwards. The increasing availability and update of NFIs create new opportunities for integration with space-based data at the national level. This is supported by the agreement we found between country biomass estimates for 2018 from FRA and CCI product, with a significantly higher correlation in countries with recent NFIs. We observed that NFI designs varied greatly in tropical countries. For example, the size of the plots ranged from 0.01 to 1 ha and more than three-quarters of the countries had smaller plots of ≤0.25 ha. The existing NFI designs could pose specific challenges for statistical integration with RS data in the tropics. Future NFI and space-based efforts should aim towards a more integrated approach taking advantage of both data streams to improve national estimates and help future data harmonization efforts. Regular NFI efforts can be expanded with the inclusion of some super-site plots to enhance data integration with currently available space-based applications. Issues related to cost implications versus improvements in the accuracy, timeliness, and sustainability of national forest biomass estimation should be further explored.

Analysis of Canopy Gaps of Coastal Broadleaf Forest Plantations in Northeast Taiwan Using UAV Lidar and the Weibull Distribution

Canopy gaps are pivotal for monitoring forest ecosystem dynamics. Conventional field methods are time-consuming and labor intensive, making them impractical for regional mapping and systematic monitoring. Gaps may be delineated using airborne lidar or aerial photographs acquired from a manned aircraft. However, high cost in data acquisition and low flexibility in flight logistics significantly reduce the accessibility of the approaches. To address these issues, this study utilized miniature light detection and ranging (lidar) onboard an unmanned aircraft vehicle (UAVlidar) to map forest canopy gaps of young and mature broadleaf forest plantations along the coast of northeastern Taiwan. This study also used UAV photographs (UAVphoto) for the same task for comparison purposes. The canopy height models were derived from UAVlidar and UAVphoto with the availability of a digital terrain model from UAVlidar. Canopy gap distributions of the forests were modeled with the power-law zeta and Weibull distributions. The performance of UAVlidar was found to be superior to UAVphoto in delineating the gap distribution through ground observation, mainly due to lidar’s ability to detect small canopy gaps. There were apparent differences of the power-law zeta distributions for the young and mature forest stands with the exponents λ of 1.36 (1.45) and 1.71 (1.61) for UAVlidar and UAVphoto, respectively, suggesting that larger canopy gaps were present within the younger stands. The canopy layer of mature forest stands was homogeneous, and the size distributions of both sensors and methods were insensitive to the spatial extent of the monitored area. Contrarily, the young forests were heterogeneous, but only UAVlidar with the Weibull distribution responded to the change of spatial extent. This study demonstrates that using the Weibull distribution to analyze canopy gap from high-spatial resolution UAVlidar may provide detailed information of regional forest canopy of coastal broadleaf forests.

Deciphering the fingerprint of disturbance on the three-dimensional structure of the world's forests

Canopy gaps and the processes that generate them play an integral role in shaping the structure and dynamics of forests. However, it is only with recent advances in remote sensing technologies such as airborne laser scanning that studying canopy gaps at scale has become a reality. Consequently, we still lack an understanding of how the size distribution and spatial organization of canopy gaps varies among forests ecosystems, nor have we determined whether these emergent properties can be reconciled with existing theories of forest dynamics. Here, I outline a roadmap for integrating remote sensing with field data and individual-based models to build a comprehensive picture of how environmental constraints and disturbance regimes shape the three-dimensional structure of the world's forests.

Impact of a tropical forest blowdown on aboveground carbon balance

Field measurements demonstrate a carbon sink in the Amazon and Congo basins, but the cause of this sink is uncertain. One possibility is that forest landscapes are experiencing transient recovery from previous disturbance. Attributing the carbon sink to transient recovery or other processes is challenging because we do not understand the sensitivity of conventional remote sensing methods to changes in aboveground carbon density (ACD) caused by disturbance events. Here we use ultra-high-density drone lidar to quantify the impact of a blowdown disturbance on ACD in a lowland rain forest in Costa Rica. We show that the blowdown decreased ACD by at least 17.6%, increased the number of canopy gaps, and altered the gap size-frequency distribution. Analyses of a canopy-height transition matrix indicate departure from steady-state conditions. This event will initiate a transient sink requiring an estimated 24-49 years to recover pre-disturbance ACD. Our results suggest that blowdowns of this magnitude and extent can remain undetected by conventional satellite optical imagery but are likely to alter ACD decades after they occur.

Use of Multi-Temporal LiDAR to Quantify Fertilization Effects on Stand Volume and Biomass in Late-Rotation Coastal Douglas-Fir Forests

Forest fertilization is common in coastal British Columbia as a means to increase wood production and potentially enhance carbon sequestration. Generally, the effects of fertilization are determined by measuring sample plots pre- and post-treatment, resulting in fertilization effects being determined for a limited portion of the treatment area. Applications of remote sensing-based enhanced forest inventories have allowed for estimations to expand to the wider forested area. However, these applications have not focused on monitoring the effects of silvicultural treatments. The objective of this research was to examine if a multi-temporal application of the LiDAR area-based method can be used to detect the fertilization effects on volume, biomass, and height in a second-growth Douglas-fir (Pseudotsuga menziesii) stand. The study area on Vancouver Island was fertilized in January 2007, and sample plots were established in 2011. LiDAR acquisitions were made in 2004, prior to fertilization, and in 2008, 2011, and 2016, covering both treated and untreated areas. A total of 29 paired LiDAR blocks, comprised of four 20 m resolution raster cells, were selected on either side of the fertilization boundary for analysis of the effects across several different stand types differing in the percentage of Douglas-fir, site index, and age. Random forest (RF) plot-level models were developed to estimate total stem volume and total stem biomass for each year of LiDAR acquisition using an area-based approach. Plot level results showed an increase in stem volume by 13% fertilized over control from 2005 to 2011, which was similar to a 14% increase in above-ground carbon stocks estimated using a tree-ring stand reconstruction approach. Plot-level RF models showed R2 values of 0.86 (volume) and 0.92 (biomass) with relative cross-validated root mean square errors of 12.5% (volume) and 11.9% (biomass). For both the sample plots and LiDAR blocks, statistical results indicated no significant differences in volume or biomass between treatments. However, significant differences in height increments were detected between treatments in LiDAR blocks. The results from this research highlight the promising potential for the use of enhanced forest inventory methods to rapidly expand the assessment of treatment effects beyond sample plots to the stand, block, or landscape level.

Promoting sustainability education through hands-on approaches: a tree carbon sequestration exercise in a Singapore green space

During a university class project related to climate change mitigation strategies, we utilized a university green space as a "living laboratory" for collaborative learning exercise to estimate landscape-level carbon biomass storage. The key objective of the exercise was to foster sustainability awareness with regard to the effectiveness of tree-planting initiatives to offset carbon emissions. Collaborative learning is a process by which students work together in small groups to accomplish a common goal. As experiences are active, social and student-owned, the process leads to the development of a variety of cognitive and transferable skills that are beneficial in academia and the workplace. Through data collection/analysis, the carbon biomass exercise not only allowed students to assess critically the efficacy of a tree-planting initiative as a means to sequester carbon, but they became aware of the difficulties in performing research on complex environmental issues. The intention of the research was to give students an opportunity to practice data collection, data analysis, problem solving, teamwork, communication and scientific literacy skills, meanwhile utilizing the campus open green space to enhance the knowledge discovery process. Informal assessment and discussions with students demonstrated that the activity was successful in reaching a wide range of students with varying backgrounds and initial attitudes about climate change mitigating strategies, which was our objective. Our case study demonstrates how learning objectives can be integrated with university sustainability initiatives to improve learning and student engagement. Finally, we see green spaces as dynamic settings for learning about physical processes and issues related to environmental management and sustainability.

Assessing Typhoon-Induced Canopy Damage Using Vegetation Indices in the Fushan Experimental Forest, Taiwan

Cyclonic windstorms profoundly affect forest structure and function throughout the tropics and subtropics. Remote sensing techniques and vegetation indices (VIs) have improved our ability to characterize cyclone impacts over broad spatial scales. Although VIs are useful for understanding changes in forest cover, their consistency on detecting changes in vegetation cover is not well understood. A better understanding of the similarities and differences in commonly used VIs across disturbance events and forest types is needed to reconcile the results from different studies. Using Landsat imagery, we analyzed the change between pre- and post-typhoon VI values (ΔVIs) of four VIs for five typhoons (local name of cyclones in the North Pacific) that affected the Fushan Experimental Forest of Taiwan. We found that typhoons varied in their effect on forest canopy cover even when they had comparable trajectories, wind speeds, and rainfall. Most VIs measured a decrease in forest cover following typhoons, ranging from −1.18% to −19.87%; however, the direction of ΔVI–topography relationships varied among events. All typhoons significantly increased vegetation heterogeneity, and ΔVI was negatively related to pre-typhoon VI across all typhoons. Four of the five typhoons showed that more frequently affected sites had greater VI decreases. VIs ranged in their sensitivity to detect typhoon-induced changes in canopy coverage, and no single VI was most sensitive across all typhoons. Therefore, we recommend using VIs in combination—for example Normalized Difference Infrared Index (NDII) and Enhanced Vegetation Index (EVI), when comparing cyclone-disturbance-induced changes in vegetation cover among disturbances and across forests.

Uncovering spatial and ecological variability in gap size frequency distributions in the Canadian boreal forest

Analyses characterizing canopy gaps are required to improve our understanding of spatial and structural variations in forest canopies and provide insight into ecosystem-level successional processes. Gap size frequency distributions (GSFD) are indicative of ecological processes and disturbance patterns. To date, GSFD in boreal forest ecosystems have not been systematically quantified over large areas using a single consistent data source. Herein we characterized GSFDs across the entirety of the Canadian boreal forest using transects of airborne laser scanning (ALS) data. ALS transects were representatively sampled within eight distinct Canadian boreal ecozones. Gaps were detected and delineated from the ALS-derived canopy height model as contiguous canopy openings ≥8 m² with canopy heights ≤3 m. Gaps were then stratified by ecozone and forest type (i.e. coniferous, broadleaf, mixedwood, wetland-treed), and combinations thereof, and GSFDs were calculated for each stratum. GSFDs were characterized by the scaling parameter of the power-law probability distribution, lambda (λ) and Kolmogorov-Smirnov tests confirmed that GSFDs for each stratum followed a power-law distribution. Pairwise comparisons between ecozones, forest types, and combinations thereof indicated significant differences between estimates of λ. Scaling parameters were found to be more variable by ecozone (1.96-2.31) than by forest type (2.15-2.21). These results contrast those of similar studies done in tropical forest environments, whereby λ was found to be relatively consistent across a range of site types, geological substrates, and forest types. The geographic range considered herein is much larger than that of previous studies, and broad-scale patterns in climate, landforms, and soils that are reflected in the definition of unique ecozones, likely also influence gap characteristics.

Testing for changes in biomass dynamics in large-scale forest datasets

Tropical forest responses to climate and atmospheric change are critical to the future of the global carbon budget. Recent studies have reported increases in estimated above-ground biomass (EAGB) stocks, productivity, and mortality in old-growth tropical forests. These increases could reflect a shift in forest functioning due to global change and/or long-lasting recovery from past disturbance. We introduce a novel approach to disentangle the relative contributions of these mechanisms by decomposing changes in whole-plot biomass fluxes into contributions from changes in the distribution of gap-successional stages and changes in fluxes for a given stage. Using 30 years of forest dynamic data at Barro Colorado Island, Panama, we investigated temporal variation in EAGB fluxes as a function of initial EAGB (EAGB_i ) in 10 × 10 m quadrats. Productivity and mortality fluxes both increased strongly with initial quadrat EAGB. The distribution of EAGB (and thus EAGB_i ) across quadrats hardly varied over 30 years (and seven censuses). EAGB fluxes as a function of EAGB_i varied largely and significantly among census intervals, with notably higher productivity in 1985-1990 associated with recovery from the 1982-1983 El Niño event. Variation in whole-plot fluxes among census intervals was explained overwhelmingly by variation in fluxes as a function of EAGB_i , with essentially no contribution from changes in EAGB_i distributions. The high observed temporal variation in productivity and mortality suggests that this forest is very sensitive to climate variability. There was no consistent long-term trend in productivity, mortality, or biomass in this forest over 30 years, although the temporal variability in productivity and mortality was so strong that it could well mask a substantial trend. Accurate prediction of future tropical forest carbon budgets will require accounting for disturbance-recovery dynamics and understanding temporal variability in productivity and mortality.

Landscape Representation by a Permanent Forest Plot and Alternative Plot Designs in a Typhoon Hotspot, Fushan, Taiwan

Permanent forest dynamics plots have provided valuable insights into many aspects of forest ecology. The evaluation of their representativeness within the landscape is necessary to understanding the limitations of findings from permanent plots at larger spatial scales. Studies on the representativeness of forest plots with respect to landscape heterogeneity and disturbance effect have already been carried out, but knowledge of how multiple disturbances affect plot representativeness is lacking—particularly in sites where several disturbances can occur between forest plot censuses. This study explores the effects of five typhoon disturbances on the Fushan Forest Dynamics Plot (FFDP) and its surrounding landscape, the Fushan Experimental Forest (FEF), in Taiwan where typhoons occur annually. The representativeness of the FFDP for the FEF was studied using four topographical variables derived from a digital elevation model and two vegetation indices (VIs), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII), calculated from Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI data. Representativeness of four alternative plot designs were tested by dividing the FFDP into subplots over wider elevational ranges. Results showed that the FFDP neither represents landscape elevational range (<10%) nor vegetation cover (<7% of the interquartile range, IQR). Although disturbance effects (i.e., ΔVIs) were also different between the FFDP and the FEF, comparisons showed no under- or over-exposure to typhoon damage frequency or intensity within the FFDP. In addition, the ΔVIs were of the same magnitudes in the plots and the reserve, and the plot covered 30% to 75.9% of IQRs of the reserve ΔVIs. Unexpectedly, the alternative plot designs did not lead to increased representation of damage for 3 out of the 4 tested typhoons and they did not suggest higher representativeness of rectangular vs. square plots. Based on the comparison of mean Euclidian distances, two rectangular plots had smaller distances than four square or four rectangular plots of the same area. Therefore, this study suggests that the current FFDP provides a better representation of its landscape disturbances than alternatives, which contained wider topographical variation and would be more difficult to conduct ground surveys. However, upscaling needs to be done with caution as, in the case of the FEF, plot representativeness varied among typhoons.

Carbon Dynamics in a Human-Modified Tropical Forest: A Case Study Using Multi-Temporal LiDAR Data

Tropical forests hold significant amounts of carbon and play a critical role on Earth´s climate system. To date, carbon dynamics over tropical forests have been poorly assessed, especially over vast areas of the tropics that have been affected by some type of disturbance (e.g., selective logging, understory fires, and fragmentation). Understanding the multi-temporal dynamics of carbon stocks over human-modified tropical forests (HMTF) is crucial to close the carbon cycle balance in the tropics. Here, we used multi-temporal and high-spatial resolution airborne LiDAR data to quantify rates of carbon dynamics over a large patch of HMTF in eastern Amazon, Brazil. We described a robust approach to monitor changes in aboveground forest carbon stocks between 2012 and 2018. Our results showed that this particular HMTF lost 0.57 m·yr−1 in mean forest canopy height and 1.38 Mg·C·ha−1·yr−1 of forest carbon between 2012 and 2018. LiDAR-based estimates of Aboveground Carbon Density (ACD) showed progressive loss through the years, from 77.9 Mg·C·ha−1 in 2012 to 53.1 Mg·C·ha−1 in 2018, thus a decrease of 31.8%. Rates of carbon stock changes were negative for all time intervals analyzed, yielding average annual carbon loss rates of −1.34 Mg·C·ha−1·yr−1. This suggests that this HMTF is acting more as a source of carbon than a sink, having great negative implications for carbon emission scenarios in tropical forests. Although more studies of forest dynamics in HMTFs are necessary to reduce the current remaining uncertainties in the carbon cycle, our results highlight the persistent effects of carbon losses for the study area. HMTFs are likely to expand across the Amazon in the near future. The resultant carbon source conditions, directly associated with disturbances, may be essential when considering climate projections and carbon accounting methods.

Urban Forest Growth and Gap Dynamics Detected by Yearly Repeated Airborne Light Detection and Ranging (LiDAR): A Case Study of Cheonan, South Korea

Understanding forest dynamics is important for assessing the health of urban forests, which experience various disturbances, both natural (e.g., treefall events) and artificial (e.g., making space for agricultural fields). Therefore, quantifying three-dimensional changes in canopies is a helpful way to manage and understand urban forests better. Multitemporal airborne light detection and ranging (LiDAR) datasets enable us to quantify the vertical and lateral growth of trees across a landscape scale. The goal of this study is to assess the annual changes in the 3-D structures of canopies and forest gaps in an urban forest using annual airborne LiDAR datasets for 2012–2015. The canopies were classified as high canopies and low canopies by a 5 m height threshold. Then, we generated pixel- and plot-level canopy height models and conducted change detection annually. The vertical growth rates and leaf area index showed consistent values year by year in both canopies, while the spatial distributions of the canopy and leaf area profile (e.g., leaf area density) showed inconsistent changes each year in both canopies. In total, high canopies expanded their foliage from 12 m height, while forest gap edge canopies (including low canopies) expanded their canopies from 5 m height. Annual change detection with LiDAR datasets might inform about both steady growth rates and different characteristics in the changes of vertical canopy structures for both high and low canopies in urban forests.

Compositional response of Amazon forests to climate change

Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.

Fine-scale processes shape ecosystem service provision by an Amazonian hyperdominant tree species

Conspecific distance and density-dependence is a key driver of tree diversity in natural forests, but the extent to which this process may influence ecosystem service provision is largely unknown. Drawing on a dataset of >135,000 trees from the Peruvian Amazon, we assessed its manifestation in biomass accumulation and seed production of Brazil nut (Bertholletia excelsa) which plays a keystone role in carbon sequestration and NTFP harvesting in Amazonia. For the first time, we find both negative and positive effects of conspecific proximity on seed production and above ground biomass at small and large nearest neighbour distances, respectively. Plausible explanations for negative effects at small distances are fine-scale genetic structuring and competition for shared resources, whereas positive effects at large distances are likely due to increasing pollen limitation and suboptimal growth conditions. Finally, findings suggest that most field plots in Amazonia used for estimating carbon storage are too small to account for distance and density-dependent effects and hence may be inadequate for measuring species-centric ecosystem services.

Biodiversity monitoring, earth observations and the ecology of scale

Human activity and land-use change are dramatically altering the sizes, geographical distributions and functioning of biological populations worldwide, with tremendous consequences for human well-being. Yet our ability to measure, monitor and forecast biodiversity change - crucial to addressing it - remains limited. Biodiversity monitoring systems are being developed to improve this capacity by deriving metrics of change from an array of in situ data (e.g. field plots or species occurrence records) and Earth observations (EO; e.g. satellite or airborne imagery). However, there are few ecologically based frameworks for integrating these data into meaningful metrics of biodiversity change. Here, I describe how concepts of pattern and scale in ecology could be used to design such a framework. I review three core topics: the role of scale in measuring and modelling biodiversity patterns with EO, scale-dependent challenges linking in situ and EO data and opportunities to apply concepts of pattern and scale to EO to improve biodiversity mapping. From this analysis emerges an actionable approach for measuring, monitoring and forecasting biodiversity change, highlighting key opportunities to establish EO as the backbone of global-scale, science-driven conservation.

The limited contribution of large trees to annual biomass production in an old-growth tropical forest

Although the importance of large trees regarding biodiversity and carbon stock in old-growth forests is undeniable, their annual contribution to biomass production and carbon uptake remains poorly studied at the stand level. To clarify the role of large trees in biomass production, we used data of tree growth, mortality, and recruitment monitored during 20 yr in 10 4-ha plots in a species-rich tropical forest (Central African Republic). Using a random block design, three different silvicultural treatments, control, logged, and logged + thinned, were applied in the 10 plots. Annual biomass gains and losses were analyzed in relation to the relative biomass abundance of large trees and by tree size classes using a spatial bootstrap procedure. Although large trees had high individual growth rates and constituted a substantial amount of biomass, stand-level biomass production decreased with the abundance of large trees in all treatments and plots. The contribution of large trees to annual stand-level biomass production appeared limited in comparison to that of small trees. This pattern did not only originate from differences in abundance of small vs. large trees or differences in initial biomass stocks among tree size classes, but also from a reduced relative growth rate of large trees and a relatively constant mortality rate among tree size classes. In a context in which large trees are increasingly gaining attention as being a valuable and a key structural characteristic of natural forests, the present study brought key insights to better gauge the relatively limited role of large trees in annual stand-level biomass production. In terms of carbon uptake, these results suggest, as already demonstrated, a low net carbon uptake of old-growth forests in comparison to that of logged forests. Tropical forests that reach a successional stage with relatively high density of large trees progressively cease to be carbon sinks as large trees contribute sparsely or even negatively to the carbon uptake at the stand level.

Aboveground Carbon Storage and Its Links to Stand Structure, Tree Diversity and Floristic Composition in South-Eastern Tanzania

African savannas and dry forests represent a large, but poorly quantified store of biomass carbon and biodiversity. Improving this information is hindered by a lack of recent forest inventories, which are necessary for calibrating earth observation data and for evaluating the relationship between carbon stocks and tree diversity in the context of forest conservation (for example, REDD+). Here, we present new inventory data from south-eastern Tanzania, comprising more than 15,000 trees at 25 locations located across a gradient of aboveground woody carbon (AGC) stocks. We find that larger trees disproportionately contribute to AGC, with the largest 3.7% of individuals containing half the carbon. Tree species diversity and carbon stocks were positively related, implying a potential functional relationship between the two, and a ‘win–win’ scenario for conservation; however, lower biomass areas also contain diverse species assemblages meaning that carbon-oriented conservation may miss important areas of biodiversity. Despite these variations, we find that total tree abundance and biomass is skewed towards a few locally dominant species, with eight and nine species (5.7% of the total) accounting for over half the total measured trees and carbon, respectively. This finding implies that carbon production in these areas is channelled through a small number of relatively abundant species. Our results provide key insights into the structure and functioning of these heterogeneous ecosystems and indicate the need for novel strategies for future measurement and monitoring of carbon stocks and biodiversity, including the use for larger plots to capture spatial variations in large tree density and AGC stocks, and to allow the calibration of earth observation data.

Fragmentation increases wind disturbance impacts on forest structure and carbon stocks in a western Amazonian landscape

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 ha 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.

Impacts of increasing typhoons on the structure and function of a subtropical forest: reflections of a changing climate

Due to their destructive and sporadic nature, it is often difficult to evaluate and predict the effects of typhoon on forest ecosystem patterns and processes. We used a 21-yr record of litterfall rates to explore the influence of typhoon frequency and intensity, along with other meteorological variables, on ecosystem dynamics in a subtropical rainforest. Over the past half century there has been an increasing frequency of strong typhoons (category 3; >49.6 m s⁻¹; increase of 1.5 typhoons/decade) impacting the Fushan Experimental Forest, Taiwan. At Fushan strong typhoons drive total litterfall mass with an average of 1100 kg ha⁻¹ litterfall typhoon⁻¹. While mean typhoon season litterfall has been observed to vary by an order of magnitude, mean litterfall rates associated with annual leaf senescence vary by <20%. In response to increasing typhoon frequency, total annual litter mass increased gradually over the 21-year record following three major typhoons in 1994. Monthly maximum wind speed was predictive of monthly litterfall, yet the influence of precipitation and temperature was only evident in non-typhoon affected months. The response of this subtropical forest to strong typhoons suggests that increasing typhoon frequency has already shifted ecosystem structure and function (declining carbon sequestration and forest stature).

Ancient human disturbances may be skewing our understanding of Amazonian forests

Although the Amazon rainforest houses much of Earth's biodiversity and plays a major role in the global carbon budget, estimates of tree biodiversity originate from fewer than 1,000 forest inventory plots, and estimates of carbon dynamics are derived from fewer than 200 recensus plots. It is well documented that the pre-European inhabitants of Amazonia actively transformed and modified the forest in many regions before their population collapse around 1491 AD; however, the impacts of these ancient disturbances remain entirely unaccounted for in the many highly influential studies using Amazonian forest plots. Here we examine whether Amazonian forest inventory plot locations are spatially biased toward areas with high probability of ancient human impacts. Our analyses reveal that forest inventory plots, and especially forest recensus plots, in all regions of Amazonia are located disproportionately near archaeological evidence and in areas likely to have ancient human impacts. Furthermore, regions of the Amazon that are relatively oversampled with inventory plots also contain the highest values of predicted ancient human impacts. Given the long lifespan of Amazonian trees, many forest inventory and recensus sites may still be recovering from past disturbances, potentially skewing our interpretations of forest dynamics and our understanding of how these forests are responding to global change. Empirical data on the human history of forest inventory sites are crucial for determining how past disturbances affect modern patterns of forest composition and carbon flux in Amazonian forests.

Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon

Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependence upon tree mortality from wind disturbance has seldom been quantified, which is important because wind disturbance often kills clusters of trees due to large treefalls killing surrounding neighbors. We examine (1) the causes of differential mortality between adult trees from a 300-ha blowdown event in the Peruvian region of the northwestern Amazon, (2) how accounting for spatial dependence affects mortality predictions, and (3) how incorporating both differential mortality and spatial dependence affect the landscape level estimation of necromass produced from the blowdown. Standard regression and spatial regression models were used to estimate how stem diameter, wood density, elevation, and a satellite-derived disturbance metric influenced the probability of tree death from the blowdown event. The model parameters regarding tree characteristics, topography, and spatial autocorrelation of the field data were then used to determine the consequences of non-random mortality for landscape production of necromass through a simulation model. Tree mortality was highly non-random within the blowdown, where tree mortality rates were highest for trees that were large, had low wood density, and were located at high elevation. Of the differential mortality models, the non-spatial models overpredicted necromass, whereas the spatial model slightly underpredicted necromass. When parameterized from the same field data, the spatial regression model with differential mortality estimated only 7.5% more dead trees across the entire blowdown than the random mortality model, yet it estimated 51% greater necromass. We suggest that predictions of forest carbon loss from wind disturbance are sensitive to not only the underlying spatial dependence of observations, but also the biological differences between individuals that promote differential levels of mortality.

Spatial Configuration of Drought Disturbance and Forest Gap Creation across Environmental Gradients

Climate change is increasing the risk of drought to forested ecosystems. Although drought impacts are often anecdotally noted to occur in discrete patches of high canopy mortality, the landscape effects of drought disturbances have received virtually no study. This study characterized the landscape configuration of drought impact patches and investigated the relationships between patch characteristics, as indicators of drought impact intensity, and environmental gradients related to water availability to determine factors influencing drought vulnerability. Drought impact patches were delineated from aerial surveys following an extreme drought in 2011 in southwestern Australia, which led to patchy canopy dieback of the Northern Jarrah Forest, a Mediterranean forest ecosystem. On average, forest gaps produced by drought-induced dieback were moderate in size (6.6 ± 9.7 ha, max = 85.7 ha), compact in shape, and relatively isolated from each other at the scale of several kilometers. However, there was considerable spatial variation in the size, shape, and clustering of forest gaps. Drought impact patches were larger and more densely clustered in xeric areas, with significant relationships observed with topographic wetness index, meteorological variables, and stand height. Drought impact patch clustering was more strongly associated with the environmental factors assessed (R² = 0.32) than was patch size (R² = 0.21); variation in patch shape remained largely unexplained (R² = 0.02). There is evidence that the xeric areas with more intense drought impacts are ‘chronic disturbance patches’ susceptible to recurrent drought disturbance. The spatial configuration of drought disturbances is likely to influence ecological processes including forest recovery and interacting disturbances such as fire. Regime shifts to an alternate, non-forested ecosystem may occur preferentially in areas with large or clustered drought impact patches. Improved understanding of drought impacts and their patterning in space and time will expand our knowledge of forest ecosystems and landscape processes, informing management of these dynamic systems in an uncertain future.

The Impact of Fine-Scale Disturbances on the Predictability of Vegetation Dynamics and Carbon Flux

Predictions from forest ecosystem models are limited in part by large uncertainties in the current state of the land surface, as previous disturbances have important and lasting influences on ecosystem structure and fluxes that can be difficult to detect. Likewise, future disturbances also present a challenge to prediction as their dynamics are episodic and complex and occur across a range of spatial and temporal scales. While large extreme events such as tropical cyclones, fires, or pest outbreaks can produce dramatic consequences, small fine-scale disturbance events are typically much more common and may be as or even more important. This study focuses on the impacts of these smaller disturbance events on the predictability of vegetation dynamics and carbon flux. Using data on vegetation structure collected for the same domain at two different times, i.e. “repeat lidar data”, we test high-resolution model predictions of vegetation dynamics and carbon flux across a range of spatial scales at an important tropical forest site at La Selva Biological Station, Costa Rica. We found that predicted height change from a height-structured ecosystem model compared well to lidar measured height change at the domain scale (~150 ha), but that the model-data mismatch increased exponentially as the spatial scale of evaluation decreased below 20 ha. We demonstrate that such scale-dependent errors can be attributed to errors predicting the pattern of fine-scale forest disturbances. The results of this study illustrate the strong impact fine-scale forest disturbances have on forest dynamics, ultimately limiting the spatial resolution of accurate model predictions.

Tropical rain forest structure, tree growth and dynamics along a 2700-m elevational transect in Costa Rica

Rapid biological changes are expected to occur on tropical elevational gradients as species migrate upslope or go extinct in the face of global warming. We established a series of 9 1-ha plots in old-growth tropical rainforest in Costa Rica along a 2700 m relief elevational gradient to carry out long-term monitoring of tropical rain forest structure, dynamics and tree growth. Within each plot we mapped, identified, and annually measured diameter for all woody individuals with stem diameters >10 cm for periods of 3-10 years. Wood species diversity peaked at 400-600 m and decreased substantially at higher elevations. Basal area and stem number varied by less than two-fold, with the exception of the 2800 m cloud forest summit, where basal area and stem number were approximately double that of lower sites. Canopy gaps extending to the forest floor accounted for <3% of microsites at all elevations. Height of highest crowns and the coefficient of variation of crown height both decreased with increasing elevation. Rates of turnover of individuals and of stand basal area decreased with elevation, but rates of diameter growth and stand basal area showed no simple relation to elevation. We discuss issues encountered in the design and implementation of this network of plots, including biased sampling, missing key meteorological and biomass data, and strategies for improving species-level research. Taking full advantage of the major research potential of tropical forest elevational transects will require sustaining and extending ground based studies, incorporation of new remotely-sensed data and data-acquisition platforms, and new funding models to support decadal research on these rapidly-changing systems.

Long-term decline of the Amazon carbon sink

Atmospheric carbon dioxide records indicate that the land surface has acted as a strong global carbon sink over recent decades, with a substantial fraction of this sink probably located in the tropics, particularly in the Amazon. Nevertheless, it is unclear how the terrestrial carbon sink will evolve as climate and atmospheric composition continue to change. Here we analyse the historical evolution of the biomass dynamics of the Amazon rainforest over three decades using a distributed network of 321 plots. While this analysis confirms that Amazon forests have acted as a long-term net biomass sink, we find a long-term decreasing trend of carbon accumulation. Rates of net increase in above-ground biomass declined by one-third during the past decade compared to the 1990s. This is a consequence of growth rate increases levelling off recently, while biomass mortality persistently increased throughout, leading to a shortening of carbon residence times. Potential drivers for the mortality increase include greater climate variability, and feedbacks of faster growth on mortality, resulting in shortened tree longevity. The observed decline of the Amazon sink diverges markedly from the recent increase in terrestrial carbon uptake at the global scale, and is contrary to expectations based on models.

Taking a closer look: disentangling effects of functional diversity on ecosystem functions with a trait-based model across hierarchy and time

Biodiversity and ecosystem functioning (BEF) research has progressed from the detection of relationships to elucidating their drivers and underlying mechanisms. In this context, replacing taxonomic predictors by trait-based measures of functional composition (FC)-bridging functions of species and of ecosystems-is a widely used approach. The inherent challenge of trait-based approaches is the multi-faceted, dynamic and hierarchical nature of trait influence: (i) traits may act via different facets of their distribution in a community, (ii) their influence may change over time and (iii) traits may influence processes at different levels of the natural hierarchy of organization. Here, we made use of the forest ecosystem model 'LPJ-GUESS' parametrized with empirical trait data, which creates output of individual performance, community assembly, stand-level states and processes. To address the three challenges, we resolved the dynamics of the top-level ecosystem function 'annual biomass change' hierarchically into its various component processes (growth, leaf and root turnover, recruitment and mortality) and states (stand structures, water stress) and traced the influence of different facets of FC along this hierarchy in a path analysis. We found an independent influence of functional richness, dissimilarity and identity on ecosystem states and processes and hence biomass change. Biodiversity effects were only positive during early succession and later turned negative. Unexpectedly, resource acquisition (growth, recruitment) and conservation (mortality, turnover) played an equally important role throughout the succession. These results add to a mechanistic understanding of biodiversity effects and place a caveat on simplistic approaches omitting hierarchical levels when analysing BEF relationships. They support the view that BEF relationships experience dramatic shifts over successional time that should be acknowledged in mechanistic theories.

Demographic drivers of tree biomass change during secondary succession in northeastern Costa Rica

Second-growth tropical forests are an important global carbon sink. As current knowledge on biomass accumulation during secondary succession is heavily based on chronosequence studies, direct estimates of annual rates of biomass accumulation in monitored stands are largely unavailable. We evaluated the contributions of tree diameter increment, recruitment, and mortality to annual tree biomass change during succession for three groups of tree species: second-growth (SG) specialists, generalists, and old-growth (OG) specialists. We monitored six second-growth tropical forests that varied in stand age and two old-growth forests in northeastern Costa Rica. We monitored these over a period of 8 to 16 years. To assess rates of biomass change during secondary succession, we compared standing biomass and biomass dynamics between second-growth forest stages and old-growth forest, and evaluated the effect of stand age on standing biomass and biomass dynamics in second-growth forests. Standing tree biomass increased with stand age during succession, whereas the rate of biomass change decreased. Biomass change was largely driven by tree diameter increment and mortality, with a minor contribution from recruitment. The relative importance of these demographic drivers shifted over succession. Biomass gain due to tree diameter increment decreased with stand age, whereas biomass loss due to mortality increased. In the age range of our second-growth forests, 10-41 years, SG specialists dominated tree biomass in second-growth forests. SG specialists, and to a lesser extent generalists, also dominated stand-level biomass increase due to tree diameter increment, whereas SG specialists largely accounted for decreases in biomass due to mortality. Our results indicate that tree growth is largely driving biomass dynamics early in succession, whereas both growth and mortality are important later in succession. Biomass dynamics are largely accounted for by a few SG specialists and one generalist species, Pentaclethra macroloba. To assess the generality of our results, similar long-term studies should be compared across tropical forest landscapes.

Amazonian landscapes and the bias in field studies of forest structure and biomass

Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9-98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy.

Perturbations in the carbon budget of the tropics

The carbon budget of the tropics has been perturbed as a result of human influences. Here, we attempt to construct a 'bottom-up' analysis of the biological components of the budget as they are affected by human activities. There are major uncertainties in the extent and carbon content of different vegetation types, the rates of land-use change and forest degradation, but recent developments in satellite remote sensing have gone far towards reducing these uncertainties. Stocks of carbon as biomass in tropical forests and woodlands add up to 271 ± 16 Pg with an even greater quantity of carbon as soil organic matter. Carbon loss from deforestation, degradation, harvesting and peat fires is estimated as 2.01 ± 1.1 Pg annum(-1); while carbon gain from forest and woodland growth is 1.85 ± 0.09 Pg annum(-1). We conclude that tropical lands are on average a small carbon source to the atmosphere, a result that is consistent with the 'top-down' result from measurements in the atmosphere. If they were to be conserved, they would be a substantial carbon sink. Release of carbon as carbon dioxide from fossil fuel burning in the tropics is 0.74 Pg annum(-1) or 0.57 MgC person(-1) annum(-1) , much lower than the corresponding figures from developed regions of the world.

Large-scale wind disturbances promote tree diversity in a Central Amazon forest

Canopy gaps created by wind-throw events, or blowdowns, create a complex mosaic of forest patches varying in disturbance intensity and recovery in the Central Amazon. Using field and remote sensing data, we investigated the short-term (four-year) effects of large (>2000 m²) blowdown gaps created during a single storm event in January 2005 near Manaus, Brazil, to study (i) how forest structure and composition vary with disturbance gradients and (ii) whether tree diversity is promoted by niche differentiation related to wind-throw events at the landscape scale. In the forest area affected by the blowdown, tree mortality ranged from 0 to 70%, and was highest on plateaus and slopes. Less impacted areas in the region affected by the blowdown had overlapping characteristics with a nearby unaffected forest in tree density (583±46 trees ha⁻¹) (mean±99% Confidence Interval) and basal area (26.7±2.4 m² ha⁻¹). Highly impacted areas had tree density and basal area as low as 120 trees ha⁻¹ and 14.9 m² ha⁻¹, respectively. In general, these structural measures correlated negatively with an index of tree mortality intensity derived from satellite imagery. Four years after the blowdown event, differences in size-distribution, fraction of resprouters, floristic composition and species diversity still correlated with disturbance measures such as tree mortality and gap size. Our results suggest that the gradients of wind disturbance intensity encompassed in large blowdown gaps (>2000 m²) promote tree diversity. Specialists for particular disturbance intensities existed along the entire gradient. The existence of species or genera taking an intermediate position between undisturbed and gap specialists led to a peak of rarefied richness and diversity at intermediate disturbance levels. A diverse set of species differing widely in requirements and recruitment strategies forms the initial post-disturbance cohort, thus lending a high resilience towards wind disturbances at the community level.

Scale criticality in estimating ecosystem carbon dynamics

Scaling is central to ecology and Earth system sciences. However, the importance of scale (i.e. resolution and extent) for understanding carbon dynamics across scales is poorly understood and quantified. We simulated carbon dynamics under a wide range of combinations of resolution (nine spatial resolutions of 250 m, 500 m, 1 km, 2 km, 5 km, 10 km, 20 km, 50 km, and 100 km) and extent (57 geospatial extents ranging from 108 to 1 247 034 km(2) ) in the southeastern United States to explore the existence of scale dependence of the simulated regional carbon balance. Results clearly show the existence of a critical threshold resolution for estimating carbon sequestration within a given extent and an error limit. Furthermore, an invariant power law scaling relationship was found between the critical resolution and the spatial extent as the critical resolution is proportional to A(n) (n is a constant, and A is the extent). Scale criticality and the power law relationship might be driven by the power law probability distributions of land surface and ecological quantities including disturbances at landscape to regional scales. The current overwhelming practices without considering scale criticality might have largely contributed to difficulties in balancing carbon budgets at regional and global scales.

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y⁻¹ over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y⁻¹, and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y⁻¹. Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.

The world’s tropical forests represent a terrestrial carbon sink, yet its size is uncertain. Espírito-Santo et al. characterize full Amazon disturbances combining forest inventories and remote sensing data, and use statistical modelling to quantify the Amazon aboveground forest carbon balance.

Spatial scale and sampling resolution affect measures of gap disturbance in a lowland tropical forest: implications for understanding forest regeneration and carbon storage

Treefall gaps play an important role in tropical forest dynamics and in determining above-ground biomass (AGB). However, our understanding of gap disturbance regimes is largely based either on surveys of forest plots that are small relative to spatial variation in gap disturbance, or on satellite imagery, which cannot accurately detect small gaps. We used high-resolution light detection and ranging data from a 1500 ha forest in Panama to: (i) determine how gap disturbance parameters are influenced by study area size, and the criteria used to define gaps; and (ii) to evaluate how accurately previous ground-based canopy height sampling can determine the size and location of gaps. We found that plot-scale disturbance parameters frequently differed significantly from those measured at the landscape-level, and that canopy height thresholds used to define gaps strongly influenced the gap-size distribution, an important metric influencing AGB. Furthermore, simulated ground surveys of canopy height frequently misrepresented the true location of gaps, which may affect conclusions about how relatively small canopy gaps affect successional processes and contribute to the maintenance of diversity. Across site comparisons need to consider how gap definition, scale and spatial resolution affect characterizations of gap disturbance, and its inferred importance for carbon storage and community composition.

Response of an old-growth tropical rainforest to transient high temperature and drought

Tropical rainforests have experienced episodes of severe heat and drought in recent decades, and climate models project a warmer and potentially drier tropical climate over this century. However, likely responses of tropical rainforests are poorly understood due to a lack of frequent long-term measurements of forest structure and dynamics. We analyzed a 12-year record (1999-2010) of 47 817 annual measurements of canopy height to characterize the response of an old-growth Neotropical rainforest to the severe heat and drought associated with the 1997-1998 El Niño. Well-drained soils on slopes and plateaus experienced a threefold increase in the fraction of the landscape in gaps (≤2 m) and a reduction in the fraction in high canopy (>15 m) causing distributions of canopy height to depart from equilibrium for a period of 2-3 years. In contrast, forests on low-lying alluvial terraces remained in equilibrium and were nearly half as likely to experience upper canopy (>15 m) disturbance over the 12 years of observation. Variation in forest response across topographic positions suggests that tropical rainforests are more sensitive to moisture deficits than high temperature and that topography likely structures landscape-level variation in the severity of drought impacts.

Climate extremes and the carbon cycle

The terrestrial biosphere is a key component of the global carbon cycle and its carbon balance is strongly influenced by climate. Continuing environmental changes are thought to increase global terrestrial carbon uptake. But evidence is mounting that climate extremes such as droughts or storms can lead to a decrease in regional ecosystem carbon stocks and therefore have the potential to negate an expected increase in terrestrial carbon uptake. Here we explore the mechanisms and impacts of climate extremes on the terrestrial carbon cycle, and propose a pathway to improve our understanding of present and future impacts of climate extremes on the terrestrial carbon budget.

Quantifying variation in forest disturbance, and its effects on aboveground biomass dynamics, across the eastern United States

The role of tree mortality in the global carbon balance is complicated by strong spatial and temporal heterogeneity that arises from the stochastic nature of carbon loss through disturbance. Characterizing spatio-temporal variation in mortality (including disturbance) and its effects on forest and carbon dynamics is thus essential to understanding the current global forest carbon sink, and to predicting how it will change in future. We analyzed forest inventory data from the eastern United States to estimate plot-level variation in mortality (relative to a long-term background rate for individual trees) for nine distinct forest regions. Disturbances that produced at least a fourfold increase in tree mortality over an approximately 5 year interval were observed in 1-5% of plots in each forest region. The frequency of disturbance was lowest in the northeast, and increased southwards along the Atlantic and Gulf coasts as fire and hurricane disturbances became progressively more common. Across the central and northern parts of the region, natural disturbances appeared to reflect a diffuse combination of wind, insects, disease, and ice storms. By linking estimated covariation in tree growth and mortality over time with a data-constrained forest dynamics model, we simulated the implications of stochastic variation in mortality for long-term aboveground biomass changes across the eastern United States. A geographic gradient in disturbance frequency induced notable differences in biomass dynamics between the least- and most-disturbed regions, with variation in mortality causing the latter to undergo considerably stronger fluctuations in aboveground stand biomass over time. Moreover, regional simulations showed that a given long-term increase in mean mortality rates would support greater aboveground biomass when expressed through disturbance effects compared with background mortality, particularly for early-successional species. The effects of increased tree mortality on carbon stocks and forest composition may thus depend partly on whether future mortality increases are chronic or episodic in nature.

Deforestation and climate feedbacks threaten the ecological integrity of south-southeastern Amazonia

A mosaic of protected areas, including indigenous lands, sustainable-use production forests and reserves and strictly protected forests is the cornerstone of conservation in the Amazon, with almost 50 per cent of the region now protected. However, recent research indicates that isolation from direct deforestation or degradation may not be sufficient to maintain the ecological integrity of Amazon forests over the next several decades. Large-scale changes in fire and drought regimes occurring as a result of deforestation and greenhouse gas increases may result in forest degradation, regardless of protected status. How severe or widespread these feedbacks will be is uncertain, but the arc of deforestation in south-southeastern Amazonia appears to be particularly vulnerable owing to high current deforestation rates and ecological sensitivity to climate change. Maintaining forest ecosystem integrity may require significant strengthening of forest conservation on private property, which can in part be accomplished by leveraging existing policy mechanisms.