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Showing papers by "Oliver L. Phillips published in 2018"


Journal ArticleDOI
TL;DR: It is shown that gross emissions from forest fires are more than half as great as those from deforestation during drought years, which means that carbon emission inventories intended for accounting and developing policies need to take account of substantial forest fire emissions not associated to the deforestation process.
Abstract: Tropical carbon emissions are largely derived from direct forest clearing processes. Yet, emissions from drought-induced forest fires are, usually, not included in national-level carbon emission inventories. Here we examine Brazilian Amazon drought impacts on fire incidence and associated forest fire carbon emissions over the period 2003–2015. We show that despite a 76% decline in deforestation rates over the past 13 years, fire incidence increased by 36% during the 2015 drought compared to the preceding 12 years. The 2015 drought had the largest ever ratio of active fire counts to deforestation, with active fires occurring over an area of 799,293 km2. Gross emissions from forest fires (989 ± 504 Tg CO2 year−1) alone are more than half as great as those from old-growth forest deforestation during drought years. We conclude that carbon emission inventories intended for accounting and developing policies need to take account of substantial forest fire emissions not associated to the deforestation process.

450 citations


Journal ArticleDOI
Helge Bruelheide1, Jürgen Dengler2, Jürgen Dengler3, Oliver Purschke1, Jonathan Lenoir4, Borja Jiménez-Alfaro1, Borja Jiménez-Alfaro5, Stephan M. Hennekens6, Zoltán Botta-Dukát, Milan Chytrý7, Richard Field8, Florian Jansen9, Jens Kattge10, Valério D. Pillar11, Franziska Schrodt10, Franziska Schrodt8, Miguel D. Mahecha10, Robert K. Peet12, Brody Sandel13, Peter M. van Bodegom14, Jan Altman15, Esteban Álvarez-Dávila, Mohammed Abu Sayed Arfin Khan16, Mohammed Abu Sayed Arfin Khan3, Fabio Attorre17, Isabelle Aubin18, Christopher Baraloto19, Jorcely Barroso20, Marijn Bauters21, Erwin Bergmeier22, Idoia Biurrun23, Anne D. Bjorkman24, Benjamin Blonder25, Benjamin Blonder26, Andraž Čarni27, Andraž Čarni28, Luis Cayuela29, Tomáš Černý30, J. Hans C. Cornelissen31, Dylan Craven, Matteo Dainese32, Géraldine Derroire, Michele De Sanctis17, Sandra Díaz33, Jiří Doležal15, William Farfan-Rios34, William Farfan-Rios35, Ted R. Feldpausch36, Nicole J. Fenton37, Eric Garnier38, Greg R. Guerin39, Alvaro G. Gutiérrez40, Sylvia Haider1, Tarek Hattab41, Greg H. R. Henry42, Bruno Hérault38, Pedro Higuchi43, Norbert Hölzel44, Jürgen Homeier22, Anke Jentsch3, Norbert Jürgens45, Zygmunt Kącki46, Dirk Nikolaus Karger47, Dirk Nikolaus Karger48, Michael Kessler47, Michael Kleyer49, Ilona Knollová7, Andrey Yu. Korolyuk, Ingolf Kühn1, Daniel C. Laughlin50, Daniel C. Laughlin51, Frederic Lens14, Jacqueline Loos22, Frédérique Louault52, Mariyana Lyubenova53, Yadvinder Malhi25, Corrado Marcenò23, Maurizio Mencuccini, Jonas V. Müller54, Jérôme Munzinger38, Isla H. Myers-Smith55, David A. Neill, Ülo Niinemets, Kate H. Orwin56, Wim A. Ozinga57, Wim A. Ozinga6, Josep Peñuelas58, Aaron Pérez-Haase59, Aaron Pérez-Haase58, Petr Petřík15, Oliver L. Phillips60, Meelis Pärtel61, Peter B. Reich62, Peter B. Reich63, Christine Römermann64, Arthur Vinicius Rodrigues, Francesco Maria Sabatini1, Jordi Sardans58, Marco Schmidt, Gunnar Seidler1, Javier Silva Espejo65, Marcos Silveira20, Anita K. Smyth39, Maria Sporbert1, Jens-Christian Svenning24, Zhiyao Tang66, Raquel Thomas67, Ioannis Tsiripidis68, Kiril Vassilev69, Cyrille Violle38, Risto Virtanen70, Evan Weiher71, Erik Welk1, Karsten Wesche72, Karsten Wesche73, Marten Winter, Christian Wirth74, Christian Wirth10, Ute Jandt1 
Martin Luther University of Halle-Wittenberg1, Zürcher Fachhochschule2, University of Bayreuth3, University of Picardie Jules Verne4, University of Oviedo5, Wageningen University and Research Centre6, Masaryk University7, University of Nottingham8, University of Rostock9, Max Planck Society10, Universidade Federal do Rio Grande do Sul11, University of North Carolina at Chapel Hill12, Santa Clara University13, Leiden University14, Academy of Sciences of the Czech Republic15, Shahjalal University of Science and Technology16, Sapienza University of Rome17, Natural Resources Canada18, Florida International University19, Universidade Federal do Acre20, Ghent University21, University of Göttingen22, University of the Basque Country23, Aarhus University24, Environmental Change Institute25, Rocky Mountain Biological Laboratory26, University of Nova Gorica27, Slovenian Academy of Sciences and Arts28, King Juan Carlos University29, Czech University of Life Sciences Prague30, VU University Amsterdam31, University of Würzburg32, National University of Cordoba33, Wake Forest University34, National University of Saint Anthony the Abbot in Cuzco35, University of Exeter36, Université du Québec en Abitibi-Témiscamingue37, University of Montpellier38, University of Adelaide39, University of Chile40, IFREMER41, University of British Columbia42, Universidade do Estado de Santa Catarina43, University of Münster44, University of Hamburg45, University of Wrocław46, University of Zurich47, Swiss Federal Institute for Forest, Snow and Landscape Research48, University of Oldenburg49, University of Wyoming50, University of Waikato51, Institut national de la recherche agronomique52, Sofia University53, Royal Botanic Gardens54, University of Edinburgh55, Landcare Research56, Radboud University Nijmegen57, Spanish National Research Council58, University of Barcelona59, University of Leeds60, University of Tartu61, University of Minnesota62, University of Sydney63, University of Jena64, University of La Serena65, Peking University66, Iwokrama International Centre for Rain Forest Conservation and Development67, Aristotle University of Thessaloniki68, Bulgarian Academy of Sciences69, University of Oulu70, University of Wisconsin–Eau Claire71, International Institute of Minnesota72, American Museum of Natural History73, Leipzig University74
TL;DR: It is shown that global trait composition is captured by two main dimensions that are only weakly related to macro-environmental drivers, which reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale.
Abstract: Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

349 citations


Journal ArticleDOI
TL;DR: The state of knowledge regarding MTF tree mortality is reviewed, a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates are created, and the next steps for improved understanding and reduced prediction are identified.
Abstract: Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change.

306 citations


Journal ArticleDOI
TL;DR: It was found that subtle differences in elevation – which control soil chemistry and hydrology – profoundly influenced the structure, composition and diversity of the canopy of old‐growth forest.
Abstract: Topography is a key driver of tropical forest structure and composition, as it constrains local nutrient and hydraulic conditions within which trees grow. Yet, we do not fully understand how changes in forest physiognomy driven by topography impact other emergent properties of forests, such as their aboveground carbon density (ACD). Working in Borneo – at a site where 70-m-tall forests in alluvial valleys rapidly transition to stunted heath forests on nutrient-depleted dip slopes – we combined field data with airborne laser scanning and hyperspectral imaging to characterise how topography shapes the vertical structure, wood density, diversity and ACD of nearly 15 km2 of old-growth forest. We found that subtle differences in elevation – which control soil chemistry and hydrology – profoundly influenced the structure, composition and diversity of the canopy. Capturing these processes was critical to explaining landscape-scale heterogeneity in ACD, highlighting how emerging remote sensing technologies can provide new insights into long-standing ecological questions.

179 citations


Journal ArticleDOI
TL;DR: This pipeline provides a conservative estimate of a species’ area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.
Abstract: Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species’ area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.

128 citations


Journal ArticleDOI
TL;DR: In this article, a method of automatic tree crown delineation based only on very high resolution images from WorldView-2 satellite and apply it to a region of the Atlantic rain forest with highly heterogeneous tropical canopy cover is presented.
Abstract: Mapping tropical tree species at landscape scales to provide information for ecologists and forest managers is a new challenge for the remote sensing community. For this purpose, detection and delineation of individual tree crowns (ITCs) is a prerequisite. Here, we present a new method of automatic tree crown delineation based only on very high resolution images from WorldView-2 satellite and apply it to a region of the Atlantic rain forest with highly heterogeneous tropical canopy cover – the Santa Genebra forest reserve in Brazil. The method works in successive steps that involve pre-processing, selection of forested pixels, enhancement of borders, detection of pixels in the crown borders, correction of shade in large trees and, finally, segmentation of the tree crowns. Principally, the method uses four techniques: rolling ball algorithm and mathematical morphological operations to enhance the crown borders and ease the extraction of tree crowns; bimodal distribution parameters estimations to identify the shaded pixels in the gaps, borders, and crowns; and focal statistics for the analysis of neighbouring pixels. Crown detection is validated by comparing the delineated ITCs with a sample of ITCs delineated manually by visual interpretation. In addition, to test if the spectra of individual species are conserved in the automatic delineated crowns, we compare the accuracy of species prediction with automatic and manual delineated crowns with known species. We find that our method permits detection of up to 80% of ITCs. The seven species with over 10 crowns identified in the field were mapped with reasonable accuracy (30.5–96%) given that only WorldView-2 bands and texture features were used. Similar classification accuracies were obtained using both automatic and manual delineation, thereby confirming that species’ spectral responses are preserved in the automatic method and thus permitting the recognition of species at the landscape scale. Our method might support tropical forest applications, such as mapping species and canopy characteristics at the landscape scale.

89 citations


Journal ArticleDOI
TL;DR: Results indicate that even limited sampling of heights can be used to refine height–diameter allometries, and recommends aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.
Abstract: Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height. Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally-derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement. Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally-derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with estimates using measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches. Our results indicate that even remarkably limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.

75 citations


Journal ArticleDOI
Jean-François Bastin, Ervan Rutishauser1, James R. Kellner2, Sassan Saatchi3, Raphaël Pélissier4, Bruno Hérault, Ferry Slik, Jan Bogaert5, Charles De Cannière6, Andrew R. Marshall7, Andrew R. Marshall8, John R. Poulsen9, Patricia Alvarez-Loyayza10, Ana Andrade, Albert Angbonga-Basia, Alejandro Araujo-Murakami, Luzmila Arroyo11, Narayanan Ayyappan12, Narayanan Ayyappan13, Celso Paulo de Azevedo14, Olaf Bánki15, Nicolas Barbier4, Jorcely Barroso15, Hans Beeckman16, Robert Bitariho17, Pascal Boeckx18, Katrin Boehning-Gaese19, Hilandia Brandão20, Francis Q. Brearley21, Mireille Breuer-Ndoundou Hockemba22, Roel J. W. Brienen23, José Luís Camargo, Ahimsa Campos-Arceiz, Benoît Cassart24, Benoît Cassart25, Jérôme Chave26, Robin L. Chazdon27, Georges Chuyong28, David B. Clark29, Connie J. Clark9, Richard Condit10, Eurídice N. Honorio Coronado, Priya Davidar11, Thalès de Haulleville5, Thalès de Haulleville16, Laurent Descroix, Jean-Louis Doucet5, Aurélie Dourdain30, Vincent Droissart4, Thomas Duncan31, Javier Silva Espejo32, Santiago Espinosa33, Nina Farwig34, Adeline Fayolle5, Ted R. Feldpausch35, Antonio Ferraz3, Christine Fletcher, Krisna Gajapersad36, Jean François Gillet5, Iêda Leão do Amaral20, Christelle Gonmadje37, James Grogan38, David Harris39, Sebastian K. Herzog, Jürgen Homeier40, Wannes Hubau16, Stephen P. Hubbell41, Stephen P. Hubbell1, Koen Hufkens18, Johanna Hurtado42, Narcisse Guy Kamdem37, Elizabeth Kearsley18, David Kenfack1, Michael Kessler43, Nicolas Labrière44, Yves Laumonier45, Susan G. Laurance46, William F. Laurance46, Simon L. Lewis23, Moses Libalah37, Gauthier Ligot5, Jon Lloyd47, Jon Lloyd48, Thomas E. Lovejoy47, Yadvinder Malhi49, Beatriz Schwantes Marimon50, Ben Hur Marimon Junior50, Emmanuel H. Martin51, Paulus Matius52, Victoria Meyer3, Casimero Mendoza Bautista53, Abel Monteagudo-Mendoza, Arafat S. Mtui, David A. Neill, Germaine Alexander Parada Gutierrez, Guido Pardo, Marc P. E. Parren, Narayanaswamy Parthasarathy12, Oliver L. Phillips23, Nigel C. A. Pitman, Pierre Ploton4, Quentin Ponette24, B.R. Ramesh12, Jean Claude Razafimahaimodison, Maxime Réjou-Méchain4, Samir Gonçalves Rolim13, Hugo Romero Saltos54, Luiz Marcelo Brum Rossi13, Wilson Roberto Spironello20, Francesco Rovero, Philippe Saner43, Denise Sasaki, Mark Schulze, Marcos Silveira15, James Singh55, Plinio Sist, Bonaventure Sonké37, J. Daniel Soto, Cintia Rodrigues de Souza13, Juliana Stropp56, Martin J. P. Sullivan23, Ben Swanepoel22, Hans ter Steege14, Hans ter Steege57, John Terborgh46, John Terborgh58, Nicolas Texier6, Takeshi Toma, Renato Valencia59, Luis Valenzuela, Leandro Valle Ferreira60, Fernando Cornejo Valverde20, Tinde van Andel14, Rodolfo Vasque, Hans Verbeeck18, Pandi Vivek11, Jason Vleminckx61, Vincent A. Vos, Fabien Wagner62, Papi Puspa Warsudi52, Verginia Wortel, Roderick Zagt63, Donatien Zebaze37 
Smithsonian Tropical Research Institute1, Brown University2, California Institute of Technology3, Centre national de la recherche scientifique4, Gembloux Agro-Bio Tech5, Université libre de Bruxelles6, University of the Sunshine Coast7, University of York8, Duke University9, Field Museum of Natural History10, Pondicherry University11, French Institute of Pondicherry12, Empresa Brasileira de Pesquisa Agropecuária13, Naturalis14, Universidade Federal do Acre15, Royal Museum for Central Africa16, Mbarara University of Science and Technology17, Ghent University18, Goethe University Frankfurt19, Amazon.com20, Manchester Metropolitan University21, Wildlife Conservation Society22, University of Leeds23, Université catholique de Louvain24, École Normale Supérieure25, Paul Sabatier University26, University of Connecticut27, University of Buea28, University of Missouri–St. Louis29, University of the French West Indies and Guiana30, Oregon State University31, University of La Serena32, Universidad Autónoma de San Luis Potosí33, University of Marburg34, University of Exeter35, Conservation International36, University of Yaoundé I37, Smith College38, Royal Botanic Garden Edinburgh39, University of Göttingen40, University of California, Los Angeles41, Organization for Tropical Studies42, University of Zurich43, Agro ParisTech44, Center for International Forestry Research45, James Cook University46, George Mason University47, Imperial College London48, Environmental Change Institute49, Universidade do Estado de Mato Grosso50, Sokoine University of Agriculture51, Mulawarman University52, Universidad Mayor53, Universidad Yachay Tech54, Forestry Commission55, Federal University of Alagoas56, University of Amsterdam57, Florida Museum of Natural History58, Pontificia Universidad Católica del Ecuador59, Museu Paraense Emílio Goeldi60, University of California, Berkeley61, National Institute for Space Research62, Tropenbos International63
TL;DR: In this paper, a pan-tropical model was proposed to predict plot-level forest structure properties and biomass from only the largest trees, which can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions.
Abstract: Aim Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan-tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location Time period Pan-tropical. Early 21st century. Major taxa studied Methods Woody plants. Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results Main conclusions Measuring the largest trees in tropical forests enables unbiased predictions of plot- and site-level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium-sized trees (50-70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate-diameter classes relative to other continents. Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change.

74 citations


Journal ArticleDOI
TL;DR: Large leaf‐to‐air temperature differences that were influenced strongly by radiation and differences in leaf temperature between 2 species due to variation in leaf width and stomatal conductance are found.
Abstract: Given anticipated climate changes, it is crucial to understand controls on leaf temperatures including variation between species in diverse ecosystems. In the first study of leaf energy balance in tropical montane forests, we observed current leaf temperature patterns on 3 tree species in the Atlantic forest, Brazil, over a 10‐day period and assessed whether and why patterns may vary among species. We found large leaf‐to‐air temperature differences (maximum 18.3 °C) and high leaf temperatures (over 35 °C) despite much lower air temperatures (maximum 22 °C). Leaf‐to‐air temperature differences were influenced strongly by radiation, whereas leaf temperatures were also influenced by air temperature. Leaf energy balance modelling informed by our measurements showed that observed differences in leaf temperature between 2 species were due to variation in leaf width and stomatal conductance. The results suggest a trade‐off between water use and leaf thermoregulation; Miconia cabussu has more conservative water use compared with Alchornea triplinervia due to lower transpiration under high vapour pressure deficit, with the consequence of higher leaf temperatures under thermal stress conditions. We highlight the importance of leaf functional traits for leaf thermoregulation and also note that the high radiation levels that occur in montane forests may exacerbate the threat from increasing air temperatures.

70 citations


Journal ArticleDOI
TL;DR: In this article, a simple yet general model for estimating forest carbon stocks using airborne laser scanning (ALS) derived canopy height and canopy cover as input metrics was developed for Borneo.
Abstract: . Borneo contains some of the world's most biodiverse and carbon-dense tropical forest, but this 750 000 km2 island has lost 62 % of its old-growth forests within the last 40 years. Efforts to protect and restore the remaining forests of Borneo hinge on recognizing the ecosystem services they provide, including their ability to store and sequester carbon. Airborne laser scanning (ALS) is a remote sensing technology that allows forest structural properties to be captured in great detail across vast geographic areas. In recent years ALS has been integrated into statewide assessments of forest carbon in Neotropical and African regions, but not yet in Asia. For this to happen new regional models need to be developed for estimating carbon stocks from ALS in tropical Asia, as the forests of this region are structurally and compositionally distinct from those found elsewhere in the tropics. By combining ALS imagery with data from 173 permanent forest plots spanning the lowland rainforests of Sabah on the island of Borneo, we develop a simple yet general model for estimating forest carbon stocks using ALS-derived canopy height and canopy cover as input metrics. An advanced feature of this new model is the propagation of uncertainty in both ALS- and ground-based data, allowing uncertainty in hectare-scale estimates of carbon stocks to be quantified robustly. We show that the model effectively captures variation in aboveground carbon stocks across extreme disturbance gradients spanning tall dipterocarp forests and heavily logged regions and clearly outperforms existing ALS-based models calibrated for the tropics, as well as currently available satellite-derived products. Our model provides a simple, generalized and effective approach for mapping forest carbon stocks in Borneo and underpins ongoing efforts to safeguard and facilitate the restoration of its unique tropical forests.

49 citations


Journal ArticleDOI
TL;DR: There is high correlation (r = −0.75) between the annual anomaly of tropical forest woody growth and the annual mean of the El Niño 3.4 index, driven mainly by strong correlations with anomalies of soil water deficit, vapour pressure deficit and shortwave radiation.
Abstract: Meteorological extreme events such as El Nino events are expected to affect tropical forest net primary production (NPP) and woody growth, but there has been no large-scale empirical validation of this expectation. We collected a large high-temporal resolution dataset (for 1-13 years depending upon location) of more than 172 000 stem growth measurements using dendrometer bands from across 14 regions spanning Amazonia, Africa and Borneo in order to test how much month-to-month variation in stand-level woody growth of adult tree stems (NPPstem) can be explained by seasonal variation and interannual meteorological anomalies. A key finding is that woody growth responds differently to meteorological variation between tropical forests with a dry season (where monthly rainfall is less than 100 mm), and aseasonal wet forests lacking a consistent dry season. In seasonal tropical forests, a high degree of variation in woody growth can be predicted from seasonal variation in temperature, vapour pressure deficit, in addition to anomalies of soil water deficit and shortwave radiation. The variation of aseasonal wet forest woody growth is best predicted by the anomalies of vapour pressure deficit, water deficit and shortwave radiation. In total, we predict the total live woody production of the global tropical forest biome to be 2.16 Pg C yr-1, with an interannual range 1.96-2.26 Pg C yr-1 between 1996-2016, and with the sharpest declines during the strong El Nino events of 1997/8 and 2015/6. There is high geographical variation in hotspots of El Nino-associated impacts, with weak impacts in Africa, and strongly negative impacts in parts of Southeast Asia and extensive regions across central and eastern Amazonia. Overall, there is high correlation (r = -0.75) between the annual anomaly of tropical forest woody growth and the annual mean of the El Nino 3.4 index, driven mainly by strong correlations with anomalies of soil water deficit, vapour pressure deficit and shortwave radiation.This article is part of the discussion meeting issue 'The impact of the 2015/2016 El Nino on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Journal ArticleDOI
TL;DR: This paper explored patterns of tree diversity and composition in two peatland forest types (peatland pole forests and palm swamps) using 26 forest plots distributed over a large area of northern Peru.
Abstract: Western Amazonia is known to harbour some of Earth's most diverse forests, but previous floristic analyses have excluded peatland forests which are extensive in northern Peru and are among the most environmentally extreme ecosystems in the lowland tropics. Understanding patterns of tree species diversity in these ecosystems is important both for quantifying beta‐diversity in this region, and for understanding determinants of diversity more generally in tropical forests. Here we explore patterns of tree diversity and composition in two peatland forest types – palm swamps and peatland pole forests – using 26 forest plots distributed over a large area of northern Peru. We place our results in a regional context by making comparisons with three other major forest types: terra firme forests (29 plots), white‐sand forests (23 plots) and seasonally‐flooded forests (11 plots). Peatland forests had extremely low (within‐plot) alpha‐diversity compared with the other forest types that were sampled. In particular, peatland pole forests had the lowest levels of tree diversity yet recorded in Amazonia (20 species per 500 stems, Fisher's alpha 4.57). However, peatland pole forests and palm swamps were compositionally different from each other as well as from other forest types in the region. Few species appeared to be peatland endemics. Instead, peatland forests were largely characterised by a distinctive combination of generalist species and species previously thought to be specialists of other habitats, especially white‐sand forests. We suggest that the transient nature and extreme environmental conditions of Amazonian peatland ecosystems have shaped their current patterns of tree composition and diversity. Despite their low alpha‐diversity, the unique combination of species found in tree communities in Amazonian peatlands augment regional beta‐diversity. This contribution, alongside their extremely high carbon storage capacity and lack of protection at national level, strengthens their status as a conservation priority.

Journal ArticleDOI
TL;DR: In this article, the authors employed the acetylene inhibition technique and the 15N-nitrate labeling method to quantify N2 and N2O emission rates for long-term experimentally N-enriched treatments in primary and secondary tropical montane forest.
Abstract: Nitrogen (N) deposition is projected to substantially increase in the tropics over the coming decades, which is expected to lead to enhanced N saturation and gaseous N emissions from tropical forests (via NO, N2O, and N2). However, it is unclear how N deposition in tropical forests influences both the magnitude of gaseous loss of nitrogen and its partitioning into the N2 and N2O loss mechanisms. Here, for the first time, we employed the acetylene inhibition technique and the 15N-nitrate labeling method to quantify N2 and N2O emission rates for long-term experimentally N-enriched treatments in primary and secondary tropical montane forest. We found that during laboratory incubation under aerobic conditions long-term increased N addition of up to 100 kg N ha−1 yr−1 at Jianfengling forest, China, did not cause a significant increase in either N2O or N2 emissions, or N2O/N2. However, under anaerobic conditions, N2O emissions decreased and N2 emissions increased with increasing N addition in the secondary forest. These changes may be attributed to substantially greater N2O reduction to N2 during denitrification, further supported by the decreased N2O/N2 ratio with increasing N addition. No such effects were observed in the primary forest. In both forests, N addition decreased the contribution of denitrification while increasing the contribution of co-denitrification and heterotrophic nitrification to N2O production. Denitrification was the predominant pathway to N2 production (98–100%) and its contribution was unaffected by N addition. Despite the changes in the contributions of denitrification to N2O gas emissions, we detected no change in the abundance of genes associated with denitrification. While the mechanisms for these different responses are not yet clear, our results indicate that the effects of N deposition on gaseous N loss were ecosystem-specific in tropical forests and that the microbial processes responsible for the production of N gases are sensitive to N inputs.

Journal ArticleDOI
TL;DR: In this article, the authors evaluated ecosystem C stocks in contrasting land-use systems across a topographically, climatically, and edaphically near-homogeneous landscape in southern Amazonia and investigated the soil, litter, fine root and aboveground biomass (AGB) stocks of soybean plantations.

Journal ArticleDOI
TL;DR: The authors reviewed recent scientific progress relating to four major systems that could exhibit threshold behaviour: ice sheets, the Atlantic meridional overturning circulation (AMOC), tropical forests and ecosystem responses to ocean acidification.
Abstract: This article reviews recent scientific progress, relating to four major systems that could exhibit threshold behaviour: ice sheets, the Atlantic meridional overturning circulation (AMOC), tropical forests and ecosystem responses to ocean acidification. The focus is on advances since the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). The most significant developments in each component are identified by synthesizing input from multiple experts from each field. For ice sheets, some degree of irreversible loss (timescales of millennia) of part of the West Antarctic Ice Sheet (WAIS) may have already begun, but the rate and eventual magnitude of this irreversible loss is uncertain. The observed AMOC overturning has decreased from 2004–2014, but it is unclear at this stage whether this is forced or is internal variability. New evidence from experimental and natural droughts has given greater confidence that tropical forests are adversely affected by drought. The ecological and socio-economic impacts of ocean acidification are expected to greatly increase over the range from today’s annual value of around 400, up to 650 ppm CO2 in the atmosphere (reached around 2070 under RCP8.5), with the rapid development of aragonite undersaturation at high latitudes affecting calcifying organisms. Tropical coral reefs are vulnerable to the interaction of ocean acidification and temperature rise, and the rapidity of those changes, with severe losses and risks to survival at 2 °C warming above pre-industrial levels. Across the four systems studied, however, quantitative evidence for a difference in risk between 1.5 and 2 °C warming above pre-industrial levels is limited.

Journal ArticleDOI
TL;DR: In this paper, stable isotope 15NH4+ and 15NO3− tracers were applied as solutions to the forest floor to examine the fates of different forms of N in a tropical montane primary forest with low background atmospheric N deposition.

Journal ArticleDOI
TL;DR: It is suggested that the isotope effects of denitrification for soils may vary greatly among regions and soil types and that gaseous N losses may have been overestimated for terrestrial ecosystems in previous studies in which lower fractionation factors were applied.

Journal ArticleDOI
21 Jun 2018-PLOS ONE
TL;DR: The data suggest that moisture is a key driver of turnover, with longer dry seasons favoring greater rates of tree turnover and thus lower biomass, having important implications in the context of climate change, given the increases in drought frequency in many tropical forests.
Abstract: Using data from 50 long-term permanent plots from across Venezuelan forests in northern South America, we explored large-scale patterns of stem turnover, aboveground biomass (AGB) and woody productivity (AGWP), and the relationships between them and with potential climatic drivers. We used principal component analysis coupled with generalized least squares models to analyze the relationship between climate, forest structure and stem dynamics. Two major axes associated with orthogonal temperature and moisture gradients effectively described more than 90% of the environmental variability in the dataset. Average turnover was 1.91 ± 0.10% year-1 with mortality and recruitment being almost identical, and close to average rates for other mature tropical forests. Turnover rates were significantly different among regions (p < 0.001), with the lowland forests in Western alluvial plains being the most dynamic, and Guiana Shield forests showing the lowest turnover rates. We found a weak positive relationship between AGB and AGWP, with Guiana Shield forests having the highest values for both variables (204.8 ± 14.3 Mg C ha-1 and 3.27 ± 0.27 Mg C ha-1 year-1 respectively), but AGB was much more strongly and negatively related to stem turnover. Our data suggest that moisture is a key driver of turnover, with longer dry seasons favoring greater rates of tree turnover and thus lower biomass, having important implications in the context of climate change, given the increases in drought frequency in many tropical forests. Regional variation in AGWP among Venezuelan forests strongly reflects the effects of climate, with greatest woody productivity where both precipitation and temperatures are high. Overall, forests in wet, low elevation sites and with slow turnover stored the greatest amounts of biomass. Although faster stand dynamics are closely associated with lower carbon storage, stem-level turnover rates and woody productivity did not show any correlation, indicating that stem dynamics and carbon dynamics are largely decoupled from one another.

Journal ArticleDOI
TL;DR: It is indicated, for the first time based on quantitative and standardized multi-site temporal data, that concerted structural changes caused by vegetation encroachment are occurring at the ecotone between the two largest biomes in Brazil.
Abstract: In the “Cerrado”–Amazon ecotone in central Brazil, recent studies suggest some encroachment of forest into savanna, but how, where, and why this might be occurring is unclear. To better understand this phenomenon, we assessed changes in the structure and dynamics of tree species in three vegetation types at the “Cerrado”–Amazon ecotone that are potentially susceptible to encroachment: open “cerrado” (OC), typical “cerrado” (TC) and dense woodland (DW). We estimated changes in density, basal area and aboveground biomass of trees with diameter ≥ 10 cm over four inventories carried out between 2008 and 2015 and classified the species according to their preferred habitat (savanna, generalist, or forest). There was an increase in all structural parameters assessed in all vegetation types, with recruitment and gains in basal area and biomass greater than mortality and losses. Thus, there were net gains between the first and final inventories in density (OC: 3.4–22.9%; TC: 1.8–12.6%; DW: 0.2–8.3%), in basal area (OC: 8.3–18.2%; TC: 2–12.7%; DW: 2.3–8.9%), and in biomass (OC: 10.6–16.4%; TC: 1–12%; DW: 5.2–18.7%). Furthermore, all vegetation types also experienced net gains in forest and generalist species relative to savanna species. A decline in recruitment of savanna species was a likely consequence of vegetation encroachment and environmental changes. Our results indicate, for the first time based on quantitative and standardized multi-site temporal data, that concerted structural changes caused by vegetation encroachment are occurring at the ecotone between the two largest biomes in Brazil.

Journal ArticleDOI
TL;DR: The remaining forests in the extensive contact zone between southern Amazonia (seasonal rain forest) and the Cerrado (savanna) biomes are at risk due to intense land-use and climate change as mentioned in this paper.
Abstract: Background: The remaining forests in the extensive contact zone between southern Amazonia (seasonal rain forest) and the Cerrado (savanna) biomes are at risk due to intense land-use and climate cha...

Journal ArticleDOI
TL;DR: The hypotheses that local-scale variation in intra- and interspecific spatial patterns of dominant tree species is affected by i) demographic rates of recruitment and mortality following severe droughts, ii) local variation in edaphic properties, and iii) occupation of species in the vertical layer of the forest are tested.
Abstract: Monodominant forests are characterized by the strong influence of a single species on the structure and diversity of the community In the tropics, monodominant forests are rare exceptions within the generally highly diverse tropical forest biome Some studies have shown that tree monodominance may be a transient state caused by successional and demographic variation among species over time Working in a Brosimum rubescens Taub (Moraceae) monodominant forest at the southern edge of Amazonia, we tested the hypotheses that local-scale variation in intra- and interspecific spatial patterns of dominant tree species is affected by i) demographic rates of recruitment and mortality following severe droughts, ii) local variation in edaphic properties, and iii) occupation of species in the vertical layer of the forest We quantified intra- and interspecific spatial patterns and edaphic associations of the five most abundant species using aggregation and association distance indices, and examined changes over time We found some support for all hypotheses Thus, intra- and interspecific spatial patterns of most species varied over time, principally after severe drought, emphasizing species-level variability and their interactions in sensitivity to this disturbance, even as B rubescens monodominance was maintained While positive and negative spatial associations with edaphic properties provide evidence of habitat specialization, the absence of negative spatial associations of B rubescens with edaphic properties indicates that this species experiences little environmental restriction, and this may be one of the factors that explain its monodominance Spatial repulsion and attraction between species in the same and in different vertical layers, respectively, indicates niche overlap and differentiation, while changes over time indicate that the relationships between species are dynamic and affected by drought disturbance

DatasetDOI
01 Jan 2018
TL;DR: In this article, the authors examined how the number of trees sampled affects the performance of locally-derived height-diameter allometries, and evaluated different methods for sampling trees for height measurement.
Abstract: 1. Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height. 2. Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally-derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement. 3. Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally-derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with estimates using measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches. 4. Our results indicate that even remarkably limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.