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Wang Y, Liu J, Wennberg PO, He L, Bonal D, Köhler P, Frankenberg C, Sitch S, Friedlingstein P. Elucidating climatic drivers of photosynthesis by tropical forests. GLOBAL CHANGE BIOLOGY 2023. [PMID: 37401204 DOI: 10.1111/gcb.16837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 05/11/2023] [Accepted: 06/02/2023] [Indexed: 07/05/2023]
Abstract
Tropical forests play a pivotal role in regulating the global carbon cycle. However, the response of these forests to changes in absorbed solar energy and water supply under the changing climate is highly uncertain. Three-year (2018-2021) spaceborne high-resolution measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) provide a new opportunity to study the response of gross primary production (GPP) and more broadly tropical forest carbon dynamics to differences in climate. SIF has been shown to be a good proxy for GPP on monthly and regional scales. Combining tropical climate reanalysis records and other contemporary satellite products, we find that on the seasonal timescale, the dependence of GPP on climate variables is highly heterogeneous. Following the principal component analyses and correlation comparisons, two regimes are identified: water limited and energy limited. GPP variations over tropical Africa are more correlated with water-related factors such as vapor pressure deficit (VPD) and soil moisture, while in tropical Southeast Asia, GPP is more correlated with energy-related factors such as photosynthetically active radiation (PAR) and surface temperature. Amazonia is itself heterogeneous: with an energy-limited regime in the north and water-limited regime in the south. The correlations of GPP with climate variables are supported by other observation-based products, such as Orbiting Carbon Observatory-2 (OCO2) SIF and FluxSat GPP. In each tropical continent, the coupling between SIF and VPD increases with the mean VPD. Even on the interannual timescale, the correlation of GPP with VPD is still discernable, but the sensitivity is smaller than the intra-annual correlation. By and large, the dynamic global vegetation models in the TRENDY v8 project do not capture the high GPP seasonal sensitivity to VPD in dry tropics. The complex interactions between carbon and water cycles in the tropics illustrated in this study and the poor representation of this coupling in the current suite of vegetation models suggest that projections of future changes in carbon dynamics based on these models may not be robust.
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Affiliation(s)
- Yuan Wang
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
| | - Junjie Liu
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Paul O Wennberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
- Division of Engineering and Applied Science, California Institute of Technology, Pasadena, California, USA
| | - Liyin He
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
| | - Damien Bonal
- Université de Lorraine, AgroParisTech, INRAE, UMR Silva, Nancy, France
| | - Philipp Köhler
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
| | - Christian Frankenberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Pierre Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
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2
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Menezes J, Garcia S, Grandis A, Nascimento H, Domingues TF, Guedes AV, Aleixo I, Camargo P, Campos J, Damasceno A, Dias-Silva R, Fleischer K, Kruijt B, Cordeiro AL, Martins NP, Meir P, Norby RJ, Pereira I, Portela B, Rammig A, Ribeiro AG, Lapola DM, Quesada CA. Changes in leaf functional traits with leaf age: when do leaves decrease their photosynthetic capacity in Amazonian trees? TREE PHYSIOLOGY 2022; 42:922-938. [PMID: 33907798 DOI: 10.1093/treephys/tpab042] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 09/22/2020] [Accepted: 03/30/2021] [Indexed: 06/12/2023]
Abstract
Most leaf functional trait studies in the Amazon basin do not consider ontogenetic variations (leaf age), which may influence ecosystem productivity throughout the year. When leaf age is taken into account, it is generally considered discontinuous, and leaves are classified into age categories based on qualitative observations. Here, we quantified age-dependent changes in leaf functional traits such as the maximum carboxylation rate of ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco) (Vcmax), stomatal control (Cgs%), leaf dry mass per area and leaf macronutrient concentrations for nine naturally growing Amazon tropical trees with variable phenological strategies. Leaf ages were assessed by monthly censuses of branch-level leaf demography; we also performed leaf trait measurements accounting for leaf chronological age based on days elapsed since the first inclusion in the leaf demography, not predetermined age classes. At the tree community scale, a nonlinear relationship between Vcmax and leaf age existed: young, developing leaves showed the lowest mean photosynthetic capacity, increasing to a maximum at 45 days and then decreasing gradually with age in both continuous and categorical age group analyses. Maturation times among species and phenological habits differed substantially, from 8 ± 30 to 238 ± 30 days, and the rate of decline of Vcmax varied from -0.003 to -0.065 μmol CO2 m-2 s-1 day-1. Stomatal control increased significantly in young leaves but remained constant after peaking. Mass-based phosphorus and potassium concentrations displayed negative relationships with leaf age, whereas nitrogen did not vary temporally. Differences in life strategies, leaf nutrient concentrations and phenological types, not the leaf age effect alone, may thus be important factors for understanding observed photosynthesis seasonality in Amazonian forests. Furthermore, assigning leaf age categories in diverse tree communities may not be the recommended method for studying carbon uptake seasonality in the Amazon, since the relationship between Vcmax and leaf age could not be confirmed for all trees.
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Affiliation(s)
- Juliane Menezes
- Tropical Forest Sciences Graduate Program, National Institute of Amazonian Research (INPA), Manaus, Amazonas, Brazil
| | - Sabrina Garcia
- Laboratory of Biogeochemical Sciences, National Institute of Amazonian Research (INPA), Manaus, Amazonas 69067-375, Brazil
| | - Adriana Grandis
- Laboratory of Physiology and Ecology of Plants (Lafieco), Department of Botany, Biosciences Institute, University of Sao Paulo, Sao Paulo 05508-090, Brazil
| | - Henrique Nascimento
- Biodiversity Coordination (CBIO), National Institute of Amazonian Research (INPA), Manaus, Amazonas 69067-375, Brazil
| | - Tomas F Domingues
- Department of Biology-FFCLRP, University of Sao Paulo, Ribeirao Preto, Sao Paulo 14040-901, Brazil
| | - Alacimar V Guedes
- Forestry and Environmental Sciences Graduate Program (PPGCIFA), Federal University of Amazonas, Manaus, Amazonas 69067-005, Brazil
| | - Izabela Aleixo
- Laboratory of Biogeochemical Sciences, National Institute of Amazonian Research (INPA), Manaus, Amazonas 69067-375, Brazil
| | - Plínio Camargo
- Isotopic Ecology Laboratory of the Center for Nuclear Energy in Agriculture (CENA), University of Sao Paulo, Piracicaba, Sao Paulo 13416-000, Brazil
| | - Jéssica Campos
- Tropical Forest Sciences Graduate Program, National Institute of Amazonian Research (INPA), Manaus, Amazonas, Brazil
| | - Amanda Damasceno
- Ecology Graduate Program, National Institute of Amazonian Research, Manaus, Amazonas 69067-375, Brazil
| | - Renann Dias-Silva
- Zoology Graduate Program, Federal University of Amazonas, Manaus, Amazonas 69067-005, Brazil
| | - Katrin Fleischer
- School of Life Sciences, Technical University of Munich, Freising 85354, Germany
| | - Bart Kruijt
- Wageningen University & Research, 6700 AA PO Box 47 PB Wageningen, Netherlands
| | - Amanda L Cordeiro
- Tropical Forest Sciences Graduate Program, National Institute of Amazonian Research (INPA), Manaus, Amazonas, Brazil
- Department of Ecosystem Science and Sustainability, Warner College of Natural Resources, Colorado State University, Fort Collins, Colorado 80523-1476
| | - Nathielly P Martins
- Tropical Forest Sciences Graduate Program, National Institute of Amazonian Research (INPA), Manaus, Amazonas, Brazil
| | - Patrick Meir
- Research School of Biology, Australian National University (ANU), Canberra 2601, Australia
- School of Geosciences, University of Edinburgh, Edinburgh EH9 3FF, UK
| | - Richard J Norby
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Iokanam Pereira
- Tropical Forest Sciences Graduate Program, National Institute of Amazonian Research (INPA), Manaus, Amazonas, Brazil
| | - Bruno Portela
- Laboratory of Biogeochemical Sciences, National Institute of Amazonian Research (INPA), Manaus, Amazonas 69067-375, Brazil
| | - Anja Rammig
- School of Life Sciences, Technical University of Munich, Freising 85354, Germany
| | - Ana Gracy Ribeiro
- Tropical Forest Sciences Graduate Program, National Institute of Amazonian Research (INPA), Manaus, Amazonas, Brazil
| | - David M Lapola
- Center for Meteorological and Climatic Research Applied to Agriculture (CEPAGRI), University of Campinas, Campinas, Sao Paulo 13083-886, Brazil
| | - Carlos A Quesada
- Environmental Dynamics Coordination (CDAM), National Institute of Amazonian Research (INPA), Manaus, Amazonas 69067-375, Brazil
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Liu L, Chen X, Ciais P, Yuan W, Maignan F, Wu J, Piao S, Wang YP, Wigneron JP, Fan L, Gentine P, Yang X, Gong F, Liu H, Wang C, Tang X, Yang H, Ye Q, He B, Shang J, Su Y. Tropical tall forests are more sensitive and vulnerable to drought than short forests. GLOBAL CHANGE BIOLOGY 2022; 28:1583-1595. [PMID: 34854168 DOI: 10.1111/gcb.16017] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 11/18/2021] [Accepted: 11/21/2021] [Indexed: 06/13/2023]
Abstract
Our limited understanding of the impacts of drought on tropical forests significantly impedes our ability in accurately predicting the impacts of climate change on this biome. Here, we investigated the impact of drought on the dynamics of forest canopies with different heights using time-series records of remotely sensed Ku-band vegetation optical depth (Ku-VOD), a proxy of top-canopy foliar mass and water content, and separated the signal of Ku-VOD changes into drought-induced reductions and subsequent non-drought gains. Both drought-induced reductions and non-drought increases in Ku-VOD varied significantly with canopy height. Taller tropical forests experienced greater relative Ku-VOD reductions during drought and larger non-drought increases than shorter forests, but the net effect of drought was more negative in the taller forests. Meta-analysis of in situ hydraulic traits supports the hypothesis that taller tropical forests are more vulnerable to drought stress due to smaller xylem-transport safety margins. Additionally, Ku-VOD of taller forests showed larger reductions due to increased atmospheric dryness, as assessed by vapor pressure deficit, and showed larger gains in response to enhanced water supply than shorter forests. Including the height-dependent variation of hydraulic transport in ecosystem models will improve the simulated response of tropical forests to drought.
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Affiliation(s)
- Liyang Liu
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
- Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif sur Yvette, France
| | - Xiuzhi Chen
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif sur Yvette, France
| | - Wenping Yuan
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Fabienne Maignan
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif sur Yvette, France
| | - Jin Wu
- School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Ying-Ping Wang
- CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
| | | | - Lei Fan
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing, China
| | - Pierre Gentine
- Department of Earth & Environmental Engineering, Columbia University, New York, New York, USA
| | - Xueqin Yang
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
- Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China
| | - Fanxi Gong
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Hui Liu
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Chen Wang
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Xuli Tang
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Hui Yang
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif sur Yvette, France
| | - Qing Ye
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Bin He
- State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Jiali Shang
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, Ontario, Canada
| | - Yongxian Su
- Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China
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Influences of Climate Change and Human Activities on NDVI Changes in China. REMOTE SENSING 2021. [DOI: 10.3390/rs13214326] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The spatiotemporal evolution of vegetation and its influencing factors can be used to explore the relationships among vegetation, climate change, and human activities, which are of great importance for guiding scientific management of regional ecological environments. In recent years, remote sensing technology has been widely used in dynamic monitoring of vegetation. In this study, the normalized difference vegetation index (NDVI) and standardized precipitation–evapotranspiration index (SPEI) from 1998 to 2017 were used to study the spatiotemporal variation of NDVI in China. The influences of climate change and human activities on NDVI variation were investigated based on the Mann–Kendall test, correlation analysis, and other methods. The results show that the growth rate of NDVI in China was 0.003 year−1. Regions with improved and degraded vegetation accounted for 71.02% and 22.97% of the national territorial area, respectively. The SPEI decreased in 60.08% of the area and exhibited an insignificant drought trend overall. Human activities affected the vegetation cover in the directions of both destruction and restoration. As the elevation and slope increased, the correlation between NDVI and SPEI gradually increased, whereas the impact of human activities on vegetation decreased. Further studies should focus on vegetation changes in the Continental Basin, Southwest Rivers, and Liaohe River Basin.
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5
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Modolo GS, dos Santos VAHF, Ferreira MJ. Testing for functional significance of traits: Effect of the light environment in tropical tree saplings. Ecol Evol 2021; 11:6480-6492. [PMID: 34141233 PMCID: PMC8207416 DOI: 10.1002/ece3.7499] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 03/11/2021] [Accepted: 03/12/2021] [Indexed: 01/15/2023] Open
Abstract
Functional traits have been examined to explain the growth rates of forest communities in different sites. However, weak or nonexistent relations are often found, especially due to the following methodological aspects: 1) lack of an environmental context (e.g., light, water, or nutrient supply), 2) use of nonfunctional traits, 3) an approach that does not contemplate phenotypic integration, and 4) neglect of intraspecific variation.Here we measured relative growth rates, crown, and leaf traits in saplings of six tropical tree species growing in two light environments (Gap and Understory) to test whether contrasting light environments modulates trait-trait and trait-growth relationships. Moreover, we tested whether models that integrate traits of different dimensions of the plant (crown and leaf) improve the strength of trait-growth relations.Light availability changed both trait-trait and trait-growth relationships. Overall, in Understory, crown traits (crown length and total leaf area) have a stronger effect on growth rates, while physiological traits related to nutrient acquisition (nitrogen concentration), photochemical efficiency (chlorophyll pigments and chlorophyll a fluorescence), and biochemical efficiency (potassium use efficiency) are strong in Gap. Models including multiple traits explained growth rates better in Gap (up to 62%) and Understory (up to 47%), but just in Gap the best model comprises traits that are representative of different dimensions of the plant. Synthesis. We advanced the knowledge behind the light effects on tree sapling by posit that trait-trait and trait-growth relationships vary across light environments. Therefore, light availability is a key environmental factor to be considered when choosing the set of traits to be measured in functional approach studies using tropical tree saplings. In compliance with the phenotype integration hypothesis, functional traits are better predictors of growth rates when grouped in a set of traits of different dimensions of the plant that represent different functional mechanisms.
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6
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Pequeno PACL, Franklin E, Norton RA. Determinants of intra‐annual population dynamics in a tropical soil arthropod. Biotropica 2019. [DOI: 10.1111/btp.12731] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Pedro Aurélio Costa Lima Pequeno
- Natural Resources Program Federal University of Roraima Boa Vista Brazil
- Laboratory of Systematics and Ecology of Terrestrial Arthropods National Institute for Amazonia Research Manaus Brazil
| | - Elizabeth Franklin
- Laboratory of Systematics and Ecology of Terrestrial Arthropods National Institute for Amazonia Research Manaus Brazil
| | - Roy A. Norton
- College of Environmental Science and Forestry State University of New York Syracuse NY USA
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Gasparini KAC, Silva Junior CHL, Shimabukuro YE, Arai E, Aragão LEOCE, Silva CA, Marshall PL. Determining a Threshold to Delimit the Amazonian Forests from the Tree Canopy Cover 2000 GFC Data. SENSORS 2019; 19:s19225020. [PMID: 31752073 PMCID: PMC6891484 DOI: 10.3390/s19225020] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 11/06/2019] [Accepted: 11/13/2019] [Indexed: 11/16/2022]
Abstract
Open global forest cover data can be a critical component for Reducing Emissions from Deforestation and Forest Degradation (REDD+) policies. In this work, we determine the best threshold, compatible with the official Brazilian dataset, for establishing a forest mask cover within the Amazon basin for the year 2000 using the Tree Canopy Cover 2000 GFC product. We compared forest cover maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 90%, and 95%) with a forest cover map for the same year from the Brazilian Amazon Deforestation Monitoring Project (PRODES) data, produced by the National Institute for Space Research (INPE). We also compared the forest cover classifications indicated by each of these maps to 2550 independently assessed Landsat pixels for the year 2000, providing an accuracy assessment for each of these map products. We found that thresholds of 80% and 85% best matched with the PRODES data. Consequently, we recommend using an 80% threshold for the Tree Canopy Cover 2000 data for assessing forest cover in the Amazon basin.
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Affiliation(s)
- Kaio Allan Cruz Gasparini
- Divisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos – SP, Brazil; (C.H.L.S.J.); (E.A.)
- Correspondence:
| | | | - Yosio Edemir Shimabukuro
- Divisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos – SP, Brazil; (C.H.L.S.J.); (E.A.)
| | - Egidio Arai
- Divisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos – SP, Brazil; (C.H.L.S.J.); (E.A.)
| | | | - Carlos Alberto Silva
- Department of Geographical Sciences, University of Maryland, College Park, Maryland, MD 20740, USA;
| | - Peter L. Marshall
- Department of Forest Resources Management, The University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada;
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8
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Multi-Scale Association between Vegetation Growth and Climate in India: A Wavelet Analysis Approach. REMOTE SENSING 2019. [DOI: 10.3390/rs11222703] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Monsoon climate over India has high degree of spatio-temporal heterogeneity characterized by the existence of multi-climatic zones along with strong intra-seasonal, seasonal, and inter-annual variability. Vegetation growth of Indian forests relates to this climate variability, though the dependence structure over space and time is yet to be explored. Here, we present a comprehensive analysis of this association with quality-controlled satellite-based remote sensing dataset of vegetation greenness and radiation along with station based gridded precipitation datasets. A spatio-temporal time-frequency analysis using wavelets is performed to understand the relative association of vegetation growth with precipitation and radiation at different time scales. The inter-annual variation of forest greenness over the Tropical India are observed to be correlated with the seasonal monsoon precipitation. However, at inter and intra-seasonal scales, vegetation has a strong association with radiation in regions of high precipitation like the Western Ghats, Eastern Himalayas, and Northeast hills. Forests in Western Himalayas were found to be correlated more on the winter precipitation from western disturbances than the south west monsoon precipitation. Our results provide new and useful region-specific information for dynamic vegetation modelling in the Indian monsoon region that may further be used in understanding global vegetation-land-atmosphere interactions.
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9
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Huang K, Xia J. High ecosystem stability of evergreen broadleaf forests under severe droughts. GLOBAL CHANGE BIOLOGY 2019; 25:3494-3503. [PMID: 31276270 DOI: 10.1111/gcb.14748] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 06/20/2019] [Accepted: 06/24/2019] [Indexed: 06/09/2023]
Abstract
Global increase in drought occurrences threatens the stability of terrestrial ecosystem functioning. Evergreen broadleaf forests (EBFs) keep leaves throughout the year, and therefore could experience higher drought risks than other biomes. However, the recent temporal variability of global vegetation productivity or land carbon sink is mainly driven by non-evergreen ecosystems, such as semiarid grasslands, croplands, and boreal forests. Thus, we hypothesize that EBFs have higher stability than other biomes under the increasingly extreme droughts. Here we use long-term Standardized Precipitation and Evaporation Index (SPEI) data and satellite-derived Enhanced Vegetation Index (EVI) products to quantify the temporal stability (ratio of mean annual EVI to its SD), resistance (ability to maintain its original levels during droughts), and resilience (rate of EVI recovering to pre-drought levels) at biome and global scales. We identified significantly increasing trends of annual drought severity (SPEI range: -0.08 to -1.80), area (areal fraction range: 2%-19%), and duration (month range: 7.9-9.1) in the EBF biome over 2000-2014. However, EBFs showed the highest resistance of EVI to droughts, but no significant differences in resilience of EVI to droughts were found among biomes (forests, grasslands, savannas, and shrublands). Global resistance and resilience of EVI to droughts were largely affected by temperature and solar radiation. These findings suggest that EBFs have higher stability than other biomes despite the greater drought exposure. Thus, the conservation of EBFs is critical for stabilizing global vegetation productivity and land carbon sink under more-intense climate extremes in the future.
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Affiliation(s)
- Kun Huang
- Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China
- Center for Global Change and Ecological Forecasting, East China Normal University, Shanghai, China
| | - Jianyang Xia
- Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China
- Institute of Eco-Chongming, Shanghai, China
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10
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Temperature rising would slow down tropical forest dynamic in the Guiana Shield. Sci Rep 2019; 9:10235. [PMID: 31308403 PMCID: PMC6629855 DOI: 10.1038/s41598-019-46597-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 06/29/2019] [Indexed: 11/08/2022] Open
Abstract
Increasing evidence shows that the functioning of the tropical forest biome is intimately related to the climate variability with some variables such as annual precipitation, temperature or seasonal water stress identified as key drivers of ecosystem dynamics. How tropical tree communities will respond to the future climate change is hard to predict primarily because several demographic processes act together to shape the forest ecosystem general behavior. To overcome this limitation, we used a joint individual-based model to simulate, over the next century, a tropical forest community experiencing the climate change expected in the Guiana Shield. The model is climate dependent: temperature, precipitation and water stress are used as predictors of the joint growth and mortality rates. We ran simulations for the next century using predictions of the IPCC 5AR, building three different climate scenarios (optimistic RCP2.6, intermediate, pessimistic RCP8.5) and a control (current climate). The basal area, above-ground fresh biomass, quadratic diameter, tree growth and mortality rates were then computed as summary statistics to characterize the resulting forest ecosystem. Whatever the scenario, all ecosystem process and structure variables exhibited decreasing values as compared to the control. A sensitivity analysis identified the temperature as the strongest climate driver of this behavior, highlighting a possible temperature-driven drop of 40% in average forest growth. This conclusion is alarming, as temperature rises have been consensually predicted by all climate scenarios of the IPCC 5AR. Our study highlights the potential slow-down danger that tropical forests will face in the Guiana Shield during the next century.
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11
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Phenology and Seasonal Ecosystem Productivity in an Amazonian Floodplain Forest. REMOTE SENSING 2019. [DOI: 10.3390/rs11131530] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Several studies have explored the linkages between phenology and ecosystem productivity across the Amazon basin. However, few studies have focused on flooded forests, which correspond to c.a. 14% of the basin. In this study, we assessed the seasonality of ecosystem productivity (gross primary productivity, GPP) from eddy covariance measurements, environmental drivers and phenological patterns obtained from the field (leaf litter mass) and satellite measurements (enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer/multi-angle implementation correction (MODIS/MAIAC)) in an Amazonian floodplain forest. We found that ecosystem productivity is limited by soil moisture in two different ways. During the flooded period, the excess of water limits GPP (Spearman’s correlation; rho = −0.22), while during non-flooded months, GPP is positively associated with soil moisture (rho = 0.34). However, GPP is maximized when cumulative water deficit (CWD) increases (rho = 0.81), indicating that GPP is dependent on the amount of water available. EVI was positively associated with leaf litter mass (Pearson’s correlation; r = 0.55) and with GPP (r = 0.50), suggesting a coupling between new leaf production and the phenology of photosynthetic capacity, decreasing both at the peak of the flooded period and at the end of the dry season. EVI was able to describe the inter-annual variations on forest responses to environmental drivers, which have changed during an observed El Niño-Southern Oscillation (ENSO) year (2015/2016).
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Smith MN, Stark SC, Taylor TC, Ferreira ML, de Oliveira E, Restrepo-Coupe N, Chen S, Woodcock T, Dos Santos DB, Alves LF, Figueira M, de Camargo PB, de Oliveira RC, Aragão LEOC, Falk DA, McMahon SM, Huxman TE, Saleska SR. Seasonal and drought-related changes in leaf area profiles depend on height and light environment in an Amazon forest. THE NEW PHYTOLOGIST 2019; 222:1284-1297. [PMID: 30720871 DOI: 10.1111/nph.15726] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 01/04/2019] [Indexed: 06/09/2023]
Abstract
Seasonal dynamics in the vertical distribution of leaf area index (LAI) may impact the seasonality of forest productivity in Amazonian forests. However, until recently, fine-scale observations critical to revealing ecological mechanisms underlying these changes have been lacking. To investigate fine-scale variation in leaf area with seasonality and drought we conducted monthly ground-based LiDAR surveys over 4 yr at an Amazon forest site. We analysed temporal changes in vertically structured LAI along axes of both canopy height and light environments. Upper canopy LAI increased during the dry season, whereas lower canopy LAI decreased. The low canopy decrease was driven by highly illuminated leaves of smaller trees in gaps. By contrast, understory LAI increased concurrently with the upper canopy. Hence, tree phenological strategies were stratified by height and light environments. Trends were amplified during a 2015-2016 severe El Niño drought. Leaf area low in the canopy exhibited behaviour consistent with water limitation. Leaf loss from short trees in high light during drought may be associated with strategies to tolerate limited access to deep soil water and stressful leaf environments. Vertically and environmentally structured phenological processes suggest a critical role of canopy structural heterogeneity in seasonal changes in Amazon ecosystem function.
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Affiliation(s)
- Marielle N Smith
- Department of Forestry, Michigan State University, East Lansing, MI, 48824, USA
- Ecology & Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Scott C Stark
- Department of Forestry, Michigan State University, East Lansing, MI, 48824, USA
| | - Tyeen C Taylor
- Ecology & Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Mauricio L Ferreira
- Centro de Energia Nuclear na Agricultura (CENA), Universidade de São Paulo, Piracicaba, SP, 13416-000, Brazil
| | - Eronaldo de Oliveira
- Universidade Federal do Oeste do Pará (UFOPA), CEP 68040-255, Santarém, PA, Brazil
| | - Natalia Restrepo-Coupe
- Ecology & Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
- School of Life Sciences, University of Technology Sydney, Sydney, NSW, 2007, Australia
| | - Shuli Chen
- Ecology & Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Tara Woodcock
- Ecology & Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | | | - Luciana F Alves
- Center for Tropical Research, Institute of the Environment and Sustainability, UCLA, Los Angeles, CA, 90095, USA
| | - Michela Figueira
- Universidade Federal do Oeste do Pará (UFOPA), CEP 68040-255, Santarém, PA, Brazil
| | - Plinio B de Camargo
- Centro de Energia Nuclear na Agricultura (CENA), Universidade de São Paulo, Piracicaba, SP, 13416-000, Brazil
| | | | - Luiz E O C Aragão
- Instituto Nacional de Pesquisas Espaciais, 12227-010, São José dos Campos, SP, Brazil
- College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4RJ, UK
| | - Donald A Falk
- School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA
- Laboratory of Tree-Ring Research, University of Arizona, Tucson, AZ, 85721, USA
| | - Sean M McMahon
- Smithsonian Institution Forest Global Earth Observatory, Smithsonian Environmental Research Center, Edgewater, MD, 21037, USA
| | - Travis E Huxman
- Ecology and Evolutionary Biology and Center for Environmental Biology, University of California, Irvine, CA, 92629, USA
| | - Scott R Saleska
- Ecology & Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
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Spatiotemporal Rainfall Trends in the Brazilian Legal Amazon between the Years 1998 and 2015. WATER 2018. [DOI: 10.3390/w10091220] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Tropical forests play an important role as a reservoir of carbon and biodiversity, specifically forests in the Brazilian Amazon. However, the last decades have been marked by important changes in the Amazon, particularly those associated with climatic extremes. Quantifying the variability of rainfall patterns, hence, is essential for understanding changes and impacts of climate upon this ecosystem. The aim of this study was to analyse spatiotemporal trends in rainfall along the Brazilian Legal Amazon between 1998 and 2015. For this purpose, rainfall data derived from the Tropical Rainfall Measuring Mission satellite (TRMM) and nonparametric statistical methods, such as Mann–Kendall and Sen’s Slope, were used. Through this approach, some patterns were identified. No evidence of significant rainfall trends (p ≤ 0.05) for annual or monthly (except for September, which showed a significant negative trend) averages was found. However, significant monthly negative rainfall anomalies were found in 1998, 2005, 2010, and 2015, and positive in 1999, 2000, 2004, 2009, and 2013. The annual pixel-by-pixel analysis showed that 92.3% of the Brazilian Amazon had no rainfall trend during the period analysed, 4.2% had significant negative trends (p ≤ 0.05), and another 3.5% had significant positive trends (p ≤ 0.05). Despite no clear temporal rainfall trends for most of the Amazon had negative trends for September, corresponding to the peak of dry season in the majority of the region, and negative rainfall anomalies found in 22% of the years analysed, which indicate that water-dependent ecological processes may be negatively affected. Moreover, these processes may be under increased risk of disruption resulting from other drought-related events, such as wildfires, which are expect to be intensified by rainfall reduction during the Amazonian dry season.
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Santos VAHFD, Ferreira MJ, Rodrigues JVFC, Garcia MN, Ceron JVB, Nelson BW, Saleska SR. Causes of reduced leaf-level photosynthesis during strong El Niño drought in a Central Amazon forest. GLOBAL CHANGE BIOLOGY 2018; 24:4266-4279. [PMID: 29723915 DOI: 10.1111/gcb.14293] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 03/18/2018] [Accepted: 04/16/2018] [Indexed: 06/08/2023]
Abstract
Sustained drought and concomitant high temperature may reduce photosynthesis and cause tree mortality. Possible causes of reduced photosynthesis include stomatal closure and biochemical inhibition, but their relative roles are unknown in Amazon trees during strong drought events. We assessed the effects of the recent (2015) strong El Niño drought on leaf-level photosynthesis of Central Amazon trees via these two mechanisms. Through four seasons of 2015, we measured leaf gas exchange, chlorophyll a fluorescence parameters, chlorophyll concentration, and nutrient content in leaves of 57 upper canopy and understory trees of a lowland terra firme forest on well-drained infertile oxisol. Photosynthesis decreased 28% in the upper canopy and 17% in understory trees during the extreme dry season of 2015, relative to other 2015 seasons and was also lower than the climatically normal dry season of the following non-El Niño year. Photosynthesis reduction under extreme drought and high temperature in the 2015 dry season was related only to stomatal closure in both upper canopy and understory trees, and not to chlorophyll a fluorescence parameters, chlorophyll, or leaf nutrient concentration. The distinction is important because stomatal closure is a transient regulatory response that can reverse when water becomes available, whereas the other responses reflect more permanent changes or damage to the photosynthetic apparatus. Photosynthesis decrease due to stomatal closure during the 2015 extreme dry season was followed 2 months later by an increase in photosynthesis as rains returned, indicating a margin of resilience to one-off extreme climatic events in Amazonian forests.
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Affiliation(s)
| | | | | | - Maquelle Neves Garcia
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research, Manaus, Brazil
| | - João Vitor Barbosa Ceron
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research, Manaus, Brazil
| | - Bruce Walker Nelson
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research, Manaus, Brazil
| | - Scott Reid Saleska
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona
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Chlorophyll Fluorescence Data Reveals Climate-Related Photosynthesis Seasonality in Amazonian Forests. REMOTE SENSING 2017. [DOI: 10.3390/rs9121275] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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