globalchange  > 过去全球变化的重建
DOI: 10.1371/journal.pone.0152009
论文题名:
Predictive Models of Primary Tropical Forest Structure from Geomorphometric Variables Based on SRTM in the Tapajós Region, Brazilian Amazon
作者: Polyanna da Conceição Bispo; João Roberto dos Santos; Márcio de Morisson Valeriano; Paulo Maurício Lima de Alencastro Graça; Heiko Balzter; Helena França; Pitágoras da Conceição Bispo
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2016
发表日期: 2016-4-18
卷: 11, 期:4
语种: 英语
英文关键词: Forests ; Forest ecology ; Trees ; Terrain ; Dendrology ; Forecasting ; Topography ; Biodiversity
英文摘要: Surveying primary tropical forest over large regions is challenging. Indirect methods of relating terrain information or other external spatial datasets to forest biophysical parameters can provide forest structural maps at large scales but the inherent uncertainties need to be evaluated fully. The goal of the present study was to evaluate relief characteristics, measured through geomorphometric variables, as predictors of forest structural characteristics such as average tree basal area (BA) and height (H) and average percentage canopy openness (CO). Our hypothesis is that geomorphometric variables are good predictors of the structure of primary tropical forest, even in areas, with low altitude variation. The study was performed at the Tapajós National Forest, located in the Western State of Pará, Brazil. Forty-three plots were sampled. Predictive models for BA, H and CO were parameterized based on geomorphometric variables using multiple linear regression. Validation of the models with nine independent sample plots revealed a Root Mean Square Error (RMSE) of 3.73 m2/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO. The coefficient of determination between observed and predicted values were r2 = 0.32 for CO, r2 = 0.26 for H and r2 = 0.52 for BA. The models obtained were able to adequately estimate BA and CO. In summary, it can be concluded that relief variables are good predictors of vegetation structure and enable the creation of forest structure maps in primary tropical rainforest with an acceptable uncertainty.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0152009&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/25383
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Ciência e Tecnologia Ambiental, Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brazil;Centre for Landscape and Climate Research, Department of Geography, University of Leicester, Leicester, United Kingdom;Divisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais (INPE), São José dos Campos, São Paulo, Brazil;Divisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais (INPE), São José dos Campos, São Paulo, Brazil;Coordenação de Dinâmica Ambiental, Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Amazonas, Brazil;Centre for Landscape and Climate Research, Department of Geography, University of Leicester, Leicester, United Kingdom;National Centre for Earth Observation, University of Leicester, Leicester, United Kingdom;Ciência e Tecnologia Ambiental, Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brazil;Departamento de Ciências Biológicas, Faculdade de Ciências e Letras de Assis, Universidade Estadual Paulista (UNESP), Assis, São Paulo, Brazil

Recommended Citation:
Polyanna da Conceição Bispo,João Roberto dos Santos,Márcio de Morisson Valeriano,et al. Predictive Models of Primary Tropical Forest Structure from Geomorphometric Variables Based on SRTM in the Tapajós Region, Brazilian Amazon[J]. PLOS ONE,2016-01-01,11(4)
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