1,355 research outputs found

    Increasing dominance of large lianas in Amazonian forests

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    Ecological orthodoxy suggests that old-growth forests should be close to dynamic equilibrium, but this view has been challenged by recent findings that neotropical forests are accumulating carbon and biomass, possibly in response to the increasing atmospheric concentrations of carbon dioxide. However, it is unclear whether the recent increase in tree biomass has been accompanied by a shift in community composition. Such changes could reduce or enhance the carbon storage potential of old-growth forests in the long term. Here we show that non-fragmented Amazon forests are experiencing a concerted increase in the density, basal area and mean size of woody climbing plants (lianas). Over the last two decades of the twentieth century the dominance of large lianas relative to trees has increased by 1.7–4.6% a year. Lianas enhance tree mortality and suppress tree growth, so their rapid increase implies that the tropical terrestrial carbon sink may shut down sooner than current models suggest. Predictions of future tropical carbon fluxes will need to account for the changing composition and dynamics of supposedly undisturbed forests

    Assessment of Bias in Pan-Tropical Biomass Predictions

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    Above-ground biomass (AGB) is an essential descriptor of forests, of use in ecological and climate-related research. At tree- and stand-scale, destructive but direct measurements of AGB are replaced with predictions from allometric models characterizing the correlational relationship between AGB, and predictor variables including stem diameter, tree height and wood density. These models are constructed from harvested calibration data, usually via linear regression. Here, we assess systematic error in out-of-sample predictions of AGB introduced during measurement, compilation and modeling of in-sample calibration data. Various conventional bivariate and multivariate models are constructed from open access data of tropical forests. Metadata analysis, fit diagnostics and cross-validation results suggest several model misspecifications: chiefly, unaccounted for inconsistent measurement error in predictor variables between in- and out-of-sample data. Simulations demonstrate conservative inconsistencies can introduce significant bias into tree- and stand-scale AGB predictions. When tree height and wood density are included as predictors, models should be modified to correct for bias. Finally, we explore a fundamental assumption of conventional allometry, that model parameters are independent of tree size. That is, the same model can provide predictions of consistent trueness irrespective of size-class. Most observations in current calibration datasets are from smaller trees, meaning the existence of a size dependency would bias predictions for larger trees. We determine that detecting the absence or presence of a size dependency is currently prevented by model misspecifications and calibration data imbalances. We call for the collection of additional harvest data, specifically under-represented larger trees

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

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    types: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.Copyright © 2014 Macmillan Publishers Limited. All rights reserved.This is an open-access articleForest 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.NASA Earth System Science Fellowship (NESSF

    Drought impacts on children's respiratory health in the Brazilian Amazon.

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    notes: PMCID: PMC3893650types: Journal Article; Research Support, Non-U.S. Gov'tThis is an open access article that is freely available in ORE or from the publisher's web site. Please cite the published version.Drought conditions in Amazonia are associated with increased fire incidence, enhancing aerosol emissions with degradation in air quality. Quantifying the synergic influence of climate and human-driven environmental changes on human health is, therefore, critical for identifying climate change adaptation pathways for this vulnerable region. Here we show a significant increase (1.2%-267%) in hospitalisations for respiratory diseases in children under-five in municipalities highly exposed to drought. Aerosol was the primary driver of hospitalisations in drought affected municipalities during 2005, while human development conditions mitigated the impacts in 2010. Our results demonstrated that drought events deteriorated children's respiratory health particularly during 2005 when the drought was more geographically concentrated. This indicates that if governments act on curbing fire usage and effectively plan public health provision, as a climate change adaptation procedure, health quality would improve and public expenditure for treatment would decrease in the region during future drought events.Natural Environment Research Council (NERC)Economic and Social Research Council (ESRC

    Long-term carbon sink in Borneo's forests halted by drought and vulnerable to edge effects

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    Less than half of anthropogenic carbon dioxide emissions remain in the atmosphere. While carbon balance models imply large carbon uptake in tropical forests, direct on-the-ground observations are still lacking in Southeast Asia. Here, using long-term plot monitoring records of up to half a century, we find that intact forests in Borneo gained 0.43 Mg C ha‾¹ per year (95% CI 0.14—0.72, mean period 1988-2010) above-ground live biomass. These results closely match those from African and Amazonian plot networks, suggesting that the world's remaining intact tropical forests are now en masse out-of-equilibrium. Although both pan-tropical and long-term, the sink in remaining intact forests appears vulnerable to climate and land use changes. Across Borneo the 1997-1998 El Niño drought temporarily halted the carbon sink by increasing tree mortality, while fragmentation persistently offset the sink and turned many edge-affected forests into a carbon source to the atmosphere

    Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data

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    Tropical forests are a key component of the global carbon cycle, and mapping their carbon density is essential for understanding human influences on climate and for ecosystem-service-based payments for forest protection. Discrete-return airborne laser scanning (ALS) is increasingly recognised as a high-quality technology for mapping tropical forest carbon, because it generates 3D point clouds of forest structure from which aboveground carbon density (ACD) can be estimated. Area-based models are state of the art when it comes to estimating ACD from ALS data, but discard tree-level information contained within the ALS point cloud. This paper compares area-based and tree-centric models for estimating ACD in lowland old-growth forests in Sabah, Malaysia. These forests are challenging to map because of their immense height. We compare the performance of (a) an area-based model developed by Asner and Mascaro (2014), and used primarily in the neotropics hitherto, with (b) a tree-centric approach that uses a new algorithm (itcSegment\textit{itcSegment}) to locate trees within the ALS canopy height model, measures their heights and crown widths, and calculates biomass from these dimensions. We find that Asner and Mascaro's model needed regional calibration, reflecting the distinctive structure of Southeast Asian forests. We also discover that forest basal area is closely related to canopy gap fraction measured by ALS, and use this finding to refine Asner and Mascaro's model. Finally, we show that our tree-centric approach is less accurate at estimating ACD than the best-performing area-based model (RMSE 18% vs 13%). Tree-centric modelling is appealing because it is based on summing the biomass of individual trees, but until algorithms can detect understory trees reliably and estimate biomass from crown dimensions precisely, areas-based modelling will remain the method of choice.This project was supported by a grant through the Human Modified Tropical Forests programme of NERC (NE/K016377/1). We thank members of the NERC Airborne Remote Sensing Facility and NERC Data Analysis Node for collecting and processing the data (project code MA14-14). David Coomes was supported by an International Academic Fellowship from the Leverhulme Trust. Lindsay Banin contributed field allometry data which were collected during her PhD at University Leeds, supported by NERC and a RGS Henrietta Hutton Grant. Oliver Phillips, Simon Lewis and Lan Qie provided census data collected as part of an ERC Advanced Grant (T-Forces)

    Large-scale patterns of turnover and basal area change in Andean forests

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    General patterns of forest dynamics and productivity in the Andes Mountains are poorly characterized. Here we present the first large-scale study of Andean forest dynamics using a set of 63 permanent forest plots assembled over the past two decades. In the North-Central Andes tree turnover (mortality and recruitment) and tree growth declined with increasing elevation and decreasing temperature. In addition, basal area increased in Lower Montane Moist Forests but did not change in Higher Montane Humid Forests. However, at higher elevations the lack of net basal area change and excess of mortality over recruitment suggests negative environmental impacts. In North-Western Argentina, forest dynamics appear to be influenced by land use history in addition to environmental variation. Taken together, our results indicate that combinations of abiotic and biotic factors that vary across elevation gradients are important determinants of tree turnover and productivity in the Andes. More extensive and longer-term monitoring and analyses of forest dynamics in permanent plots will be necessary to understand how demographic processes and woody biomass are responding to changing environmental conditions along elevation gradients through this century

    Methods to estimate aboveground wood productivity from long-term forest inventory plots

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    Forest inventory plots are widely used to estimate biomass carbon storage and its change over time. While there has been much debate and exploration of the analytical methods for calculating biomass, the methods used to determine rates of wood production have not been evaluated to the same degree. This affects assessment of ecosystem fluxes and may have wider implications if inventory data are used to parameterise biospheric models, or scaled to large areas in assessments of carbon sequestration. Here we use a dataset of 35 long-term Amazonian forest inventory plots to test different methods of calculating wood production rates. These address potential biases associated with three issues that routinely impact the interpretation of tree measurement data: (1) changes in the point of measurement (POM) of stem diameter as trees grow over time; (2) unequal length of time between censuses; and (3) the treatment of trees that pass the minimum diameter threshold (“recruits”). We derive corrections that control for changing POM height, that account for the unobserved growth of trees that die within census intervals, and that explore different assumptions regarding the growth of recruits during the previous census interval. For our dataset we find that annual aboveground coarse wood production (AGWP; in Mg ha−1 year−1 of dry matter) is underestimated on average by 9.2% if corrections are not made to control for changes in POM height. Failure to control for the length of sampling intervals results in a mean underestimation of 2.7% in annual AGWP in our plots for a mean interval length of 3.6 years. Different methods for treating recruits result in mean differences of up to 8.1% in AGWP. In general, the greater the length of time a plot is sampled for and the greater the time elapsed between censuses, the greater the tendency to underestimate wood production. We recommend that POM changes, census interval length, and the contribution of recruits should all be accounted for when estimating productivity rates, and suggest methods for doing this.European UnionUK Natural Environment Research CouncilGordon and Betty Moore FoundationCASE sponsorship from UNEP-WCMCRoyal Society University Research FellowshipERC Advanced Grant “Tropical Forests in the Changing Earth System”Royal Society Wolfson Research Merit Awar

    Evaluating the potential of full-waveform lidar for mapping pan-tropical tree species richness

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    AIM: Mapping tree species richness across the tropics is of great interest for effective conservation and biodiversity management. In this study, we evaluated the potential of full‐waveform lidar data for mapping tree species richness across the tropics by relating measurements of vertical canopy structure, as a proxy for the occupation of vertical niche space, to tree species richness. LOCATION: Tropics. TIME PERIOD: Present. MAJOR TAXA STUDIED: Trees. METHODS: First, we evaluated the characteristics of vertical canopy structure across 15 study sites using (simulated) large‐footprint full‐waveform lidar data (22 m diameter) and related these findings to in‐situ tree species information. Then, we developed structure–richness models at the local (within 25–50 ha plots), regional (biogeographical regions) and pan‐tropical scale at three spatial resolutions (1.0, 0.25 and 0.0625 ha) using Poisson regression. RESULTS: The results showed a weak structure–richness relationship at the local scale. At the regional scale (within a biogeographical region) a stronger relationship between canopy structure and tree species richness across different tropical forest types was found, for example across Central Africa and in South America [R^{2} ranging from .44–.56, root mean squared difference as a percentage of the mean (RMSD%) ranging between 23–61%]. Modelling the relationship pan‐tropically, across four continents, 39% of the variation in tree species richness could be explained with canopy structure alone (R^{2} = .39 and RMSD% = 43%, 0.25‐ha resolution). MAIN CONCLUSIONS: Our results may serve as a basis for the future development of a set of structure–richness models to map high resolution tree species richness using vertical canopy structure information from the Global Ecosystem Dynamics Investigation (GEDI). The value of this effort would be enhanced by access to a larger set of field reference data for all tropical regions. Future research could also support the use of GEDI data in frameworks using environmental and spectral information for modelling tree species richness across the tropics
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