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While forest degradation rates and extent exceed deforestation in the Brazilian Amazon, less attention is given to the factors controlling its spatial distribution. No quantified correlation exists between changes of forest structure due to anthropogenic disturbances and dynamics of land use and cover change occurring at broader spatial levels. This study examines the influence of multi-scale landscape structure factors (i.e. spatial composition, configuration and dynamic of land use/cover) on primary forest’s aboveground biomass (AGB), spanning from low to highly degraded, in Paragominas municipality (Pará state). We used random forest models to identify the most important landscape predictors of degradation and clustering methods to analyze their distribution and interactions. We found that 58% of the variance of AGB could be explained by metrics reflecting land use practices and agricultural dynamics around primary forest patches and that their spatial patterns were not randomly distributed. Forest degradation is mainly driven by fragmentation effects resulting from old deforestation and colonization events linked with cropland expansion (e.g. soybean and maize) coupled with high accessibility to market. To a lesser extent, degradation is driven by recent and ongoing (1985–2015) deforestation and fragmentation in slash-and-burn agricultural areas, characterized by heterogeneous mosaics of pastures and fallow lands combined with high use of fire. Our findings highlight the potential of landscape-level framework and remotely sensed land cover data for a thorough understanding of the distribution of forest degradation across human-modified landscapes. Addressing these spatial determinants by looking at agricultural dynamics beyond forest cover is necessary to improve forest management which has major implications for biodiversity, carbon and other ecosystem services.

1. Considerable debate surrounds the extent to which tropical forests can be managed for resource extraction while conserving biodiversity and ecosystem properties, which depend on functional composition. Here we evaluate the compatibility of these aims by examining the effects of logging on taxonomic and functional diversity and composition in a tropical forest. 2. Twenty years after selective logging, we inventoried 4140 stems regenerating in logging gaps and adjacent undisturbed areas, and we integrated a database of 13 functional traits describing leaf and wood economics of tropical trees. 3. We found no differences in taxonomic and functional richness among habitats, but logging gaps had significantly higher taxonomic and functional evenness. 4. Logging also effected striking, long-term changes in both species and functional composition. In particular, the xylem density of recruits in logging gaps was 6% less than in unlogged forests, leaves were 11% less tough and had 6—13% greater mineral nutrient concentrations. 5. Synthesis and applications. Our results suggest that managers of tropical forests should limit overall surface area converted to logging gaps by creating fewer, larger gaps during selective logging, to reduce impacts on the taxonomic and functional composition of the regenerating stand.

1. Relationships between tropical rain forest biomass and environmental factors have been determined at regional scales, e.g. the Amazon Basin, but the reasons for the high variability in forest biomass at local scales are poorly understood. Interactions between topography, soil properties, tree growth and mortality rates, and treefalls are a likely reason for this variability. 2. We used repeated measurements of permanent plots in lowland rain forest in French Guiana to evaluate these relationships. The plots sampled topographic gradients from hilltops to slopes to bottomlands, with accompanying variation in soil waterlogging along these gradients. Biomass was calculated for >175 tree species in the plots, along with biomass productivity and recruitment rates. Mortality was determined as standing dead and treefalls. 3. Treefall rates were twice as high in bottomlands as on hilltops, and tree recruitment rates, radial growth rates and the abundance of light-demanding tree species were also higher. 4. In the bottomlands, the mean wood density was 10% lower than on hilltops, the basal area 29% lower and the height:diameter ratio of trees was lower, collectively resulting in a total woody biomass that was 43% lower in bottomlands than on hilltops. 5. Biomass productivity was 9% lower in bottomlands than on hilltops, even though soil Olsen P concentrations were higher in bottomlands. 6. Synthesis. Along a topographic gradient from hilltops to bottomlands there were higher rates of treefall, which decreased the stand basal area and favoured lower allocation to height growth and recruitment of light-demanding species with low wood density. The resultant large variation in tree biomass along the gradient shows the importance of determining site characteristics and including these characteristics when scaling up biomass estimates from stand to local or regional scales.

A standardized rapid inventory method providing information on both tree species diversity and aboveground carbon stocks in tropical forests will be an important tool for evaluating efforts to conserve biodiversity and to estimate the carbon emissions that result from deforestation and degradation (REDD). Herein, we contrast five common plot methods differing in shape, size, and effort requirements to estimate tree diversity and aboveground tree biomass (AGB). We simulated the methods across six Neotropical forest sites that represent a broad gradient in forest structure, tree species richness, and floristic composition, and we assessed the relative performance of methods by evaluating the bias and precision of their estimates of AGB and tree diversity. For a given sample of forest area, a 'several small' (< 1 ha) sampling strategy led to a smaller coefficient of variation (CV) in the estimate of AGB than a 'few large' one. The effort (person-days) required to achieve an accurate AGB estimate (< 10% CV), however, was greater for the smallest plots (0.1 ha) than for a compromise approach using 0.5 ha modified Gentry plots, which proved to be the most efficient method to estimate AGB across all forest types. Gentry plots were also the most efficient at providing accurate estimates of tree diversity (< 10% CV of Hill number). We recommend the use of the 0.5 ha modified Gentry plot method in future rapid inventories, and we discuss a set of criteria that should inform any choice of inventory method.

The expansion of selective logging in tropical forests may be an important source of global carbon emissions. However, the effects of logging practices on the carbon cycle have never been quantified over long periods of time. We followed the fate of more than 60 000 tropical trees over 23 years to assess changes in aboveground carbon stocks in 48 1.56-ha plots in French Guiana that represent a gradient of timber harvest intensities, with and without intensive timber stand improvement (TSI) treatments to stimulate timber tree growth. Conventional selective logging led to emissions equivalent to more than a third of aboveground carbon stocks in plots without TSI (85 Mg C/ha), while plots with TSI lost more than one-half of aboveground carbon stocks (142 Mg C/ha). Within 20 years of logging, plots without TSI sequestered aboveground carbon equivalent to more than 80% of aboveground carbon lost to logging (-70.7 Mg C/ha), and our simulations predicted an equilibrium aboveground carbon balance within 45 years of logging. In contrast, plots with intensive TSI are predicted to require more than 100 years to sequester aboveground carbon lost to emissions. These results indicate that in some tropical forests aboveground carbon storage can be recovered within half a century after conventional logging at moderate harvest intensities.

1. Modelling growth strategies among tropical trees is an important objective in predicting the response of tree dynamics to selective logging and in gaining insights into the ecological processes that structure tree communities in managed tropical forests. 2. We developed a disturbance index to model the effects of distance to and area of logging gaps on stem radial growth rates. This index was tested using census data of 43 neotropical tree species, representing a variety of life-history strategies and developmental stages, from a selectively logged forest at Paracou, French Guiana. Growth strategies were analyzed in light of two indicators: the inherent species growth rate (when disturbance index is null) and the species reaction (change in growth rate) to logging gaps. 3. Across species, the predicted inherent growth rates in unlogged forest ranged from 0·25 to 6·47 mm year⁻¹, with an average growth of 2·29 mm year⁻¹. Ontogenetic shifts in inherent growth rate were found in 26 of the 43 species. 4. Species growth response to logging gaps varied widely among species but was significantly positive for 27 species. The effect of ontogeny on growth response to logging was retained for 14 species, and species with inherent fast growth rate (5 mm year⁻¹) responded less to logging gap disturbances than did species with slow inherent growth (1 mm year⁻¹). 5. Functional traits explained 19-42% of the variation in the inherent growth rate and in species' response across all developmental stages. Whereas maximum diameters and seed mass were strong predictors of inherent growth rate, maximum height, wood density, mode of germination and stem architecture were additionally involved in tree growth response. 6. Synthesis and applications: This study provides a necessary framework for developing predictive post-logging growth models for the thousands of species comprising tropical forests and is sufficiently general to apply to a broad range of managed tropical forests.

We investigated the relationship between habitat association and physiological performance in four congeneric species pairs exhibiting contrasting distributions between seasonally flooded and terra firme habitats in lowland tropical rain forests of French Guiana, including Virola and Iryanthera (Myristicaceae), Symphonia (Clusiaceae), and Eperua (Caesalpiniaceae). We analyzed 10-year data sets of mapped and measured saplings (stems 150 cm in height and <10 cm diameter at breast height [dbh]) and trees (stems 10 cm dbh) across 37.5 ha of permanent plots covering a 300-ha zone, within which seasonally flooded areas (where the water table never descends below 1 m) have been mapped. Additionally, we tested the response of growth, survival, and leaf functional traits of these species to drought and flood stress in a controlled experiment. We tested for habitat preference using a modification of the torus translation method. Strong contrasting associations of the species pairs of Iryanthera, Virola, and Symphonia were observed at the sapling stage, and these associations strengthened for the tree stage. Neither species of Eperua was significantly associated with flooded habitats at the sapling stage, but E. falcata was significantly and positively associated with flooded forests at the tree stage, and trees of E. grandiflora were found almost exclusively in nonflooded habitats. Differential performance provided limited explanatory support for the observed habitat associations, with only congeners of Iryanthera exhibiting divergent sapling survival and tree growth. Seedlings of species associated with flooded forest tended to have higher photosynthetic capacity than their congeners at field capacity. In addition, they tended to have the largest reductions in leaf gas exchange and growth rate in response to experimental drought stress and the least reductions in response to experimental inundation. The corroboration of habitat association with differences in functional traits and, to a lesser extent, measures of performance provides an explanation for the regional coexistence of these species pairs. We suggest that specialization to seasonally flooded habitats may explain patterns of adaptive radiation in many tropical tree genera and thereby provide a substantial contribution to regional tree diversity.

Tropical forest degradation from selective logging, fire and edge effects is a major driver of carbon and biodiversity loss 1 – 3 , with annual rates comparable to those of deforestation 4 . However, its actual extent and long-term impacts remain uncertain at global tropical scale 5 . Here we quantify the magnitude and persistence of multiple types of degradation on forest structure by combining satellite remote sensing data on pantropical moist forest cover changes 4 with estimates of canopy height and biomass from spaceborne 6 light detection and ranging (LiDAR). We estimate that forest height decreases owing to selective logging and fire by 15% and 50%, respectively, with low rates of recovery even after 20 years. Agriculture and road expansion trigger a 20% to 30% reduction in canopy height and biomass at the forest edge, with persistent effects being measurable up to 1.5 km inside the forest. Edge effects encroach on 18% (approximately 206 Mha) of the remaining tropical moist forests, an area more than 200% larger than previously estimated 7 . Finally, degraded forests with more than 50% canopy loss are significantly more vulnerable to subsequent deforestation. Collectively, our findings call for greater efforts to prevent degradation and protect already degraded forests to meet the conservation pledges made at recent United Nations Climate Change and Biodiversity conferences. A global survey on the magnitude and persistence of moist forest cover change and canopy height following degradation using satellite remote sensing data finds that the effects are substantial and persist for decades.

The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted—modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster-growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits. These results provide not only a holistic pan-Amazonian picture of tree death but large-scale evidence for the overarching importance of the growth–survival trade-off in driving tropical tree mortality. Tree mortality has been shown to be the dominant control on carbon storage in Amazon forests, but little is known of how and why Amazon forest trees die. Here the authors analyse a large Amazon-wide dataset, finding that fast-growing species face greater mortality risk, but that slower-growing individuals within a species are more likely to die, regardless of size.

Aim: Large trees (d.b.h. ≥70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan-tropical scales. Location: Pan-tropical. Methods: Aboveground biomass (AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights (AICcwi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB/density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results: Density of large trees explained c. 70% of the variation in pan-tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean) ± 105.0 (SD) Mg ha⁻¹] versus Palaeotropical forests (Africa 418.3 ± 91.8 Mg ha⁻¹; Asia 393.3 ± 109.3 Mg ha⁻¹). Pan-tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions: Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in-depth analyses of the community dynamics of large trees.