globalchange  > 气候减缓与适应
DOI: 10.3390/rs11010093
WOS记录号: WOS:000457935600093
论文题名:
Predictive Ecosystem Mapping of South-Eastern Australian Temperate Forests Using Lidar-Derived Structural Profiles and Species Distribution Models
作者: Fedrigo, Melissa1,2; Stewart, Stephen B.1,3; Roxburgh, Stephen H.2; Kasel, Sabine1; Bennett, Lauren T.4; Vickers, Helen1; Nitschke, Craig R.1
通讯作者: Fedrigo, Melissa
刊名: REMOTE SENSING
ISSN: 2072-4292
出版年: 2019
卷: 11, 期:1
语种: 英语
英文关键词: Cool Temperate Rainforest ; decision-tree ; ecological vegetation class ; ecotone ; mixed forest ; plant area volume density ; random forest ; stand structure
WOS关键词: NEAREST-NEIGHBOR IMPUTATION ; CLIMATE-CHANGE ; BIODIVERSITY ; CLASSIFICATION ; FIELD ; INTERPOLATION ; TOPOGRAPHY ; CONVERSION ; LANDSCAPE ; DIVERSITY
WOS学科分类: Remote Sensing
WOS研究方向: Remote Sensing
英文摘要:

Modern approaches to predictive ecosystem mapping (PEM) have not thoroughly explored the use of characteristic' gradients, which describe vegetation structure (e.g., light detection and ranging (lidar)-derived structural profiles). In this study, we apply a PEM approach by classifying the dominant stand types within the Central Highlands region of south-eastern Australia using both lidar and species distribution models (SDMs). Similarity percentages analysis (SIMPER) was applied to comprehensive floristic surveys to identify five species which best separated stand types. The predicted distributions of these species, modelled using random forests with environmental (i.e., climate, topography) and optical characteristic gradients (Landsat-derived seasonal fractional cover), provided an ecological basis for refining stand type classifications based only on lidar-derived structural profiles. The resulting PEM model represents the first continuous distribution map of stand types across the study region that delineates ecotone stands, which are seral communities comprised of species typical of both rainforest and eucalypt forests. The spatial variability of vegetation structure incorporated into the PEM model suggests that many stand types are not as continuous in cover as represented by current ecological vegetation class distributions that describe the region. Improved PEM models can facilitate sustainable forest management, enhanced forest monitoring, and informed decision making at landscape scales.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/126064
Appears in Collections:气候减缓与适应

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作者单位: 1.Univ Melbourne, Fac Sci, Sch Ecosyst & Forest Sci, 500 Yarra Blvd, Richmond, Vic 3121, Australia
2.CSIRO, Land & Water Business Unit, GPO Box 1700, Canberra, ACT 2601, Australia
3.CSIRO, Land & Water Business Unit, 15 Coll Rd, Sandy Bay 7005, Australia
4.Univ Melbourne, Fac Sci, Sch Ecosyst & Forest Sci, 4 Water St, Creswick 3363, Australia

Recommended Citation:
Fedrigo, Melissa,Stewart, Stephen B.,Roxburgh, Stephen H.,et al. Predictive Ecosystem Mapping of South-Eastern Australian Temperate Forests Using Lidar-Derived Structural Profiles and Species Distribution Models[J]. REMOTE SENSING,2019-01-01,11(1)
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