Forest Structure and Distribution across the Geographic Range of the Giant Panda Up-scaling from Plots to the Entire Region Jianguo (Jack) Liu (Michigan.

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Presentation transcript:

Forest Structure and Distribution across the Geographic Range of the Giant Panda Up-scaling from Plots to the Entire Region Jianguo (Jack) Liu (Michigan State University) Zhiyun Ouyang (Chinese Academy of Sciences) Jiaguo Qi (Michigan State University) Andrés Viña (Michigan State University)

Historical Range Current Range Giant Panda’s Geographic Range

Giant Panda Habitat  Altitudinal range between m  <45 o slopes  Require forest cover (deciduous & coniferous)  >95% of diet is composed of bamboo

Remote Sensing for Panda Habitat Assessment  Limited to provide information on forest cover (usually through non-hierarchical spectral classification algorithms)  Understory bamboo cover has been neglected due to the difficulty in isolating it from forest canopy

Objectives  Assess the spatial distribution of forests  Evaluate the structural characteristics of the forests at plot scales  Develop techniques for up-scaling from plots to nature reserves, mountain regions and to the entire panda geographic range

Field Data  440 sampling plots:  Forest cover/type  Elevation, slope, aspect  Tree/bamboo stem density & basal area  Tree/bamboo species composition  84 plots exhibited panda signs

Qionglai Mountain Region Forest Cover & Panda Habitat Landsat TM + SRTM-DEM

Conservation Plans at Regional Scales Xu, et al Diversity and Distributions 12: Establishment of key (K) areas to locate new nature reserves and linkage (L) areas to connect different nature reserves Qionglai Mountain Region

What about information on bamboo distribution ? Hypothesis: Forests with bamboo have particular phenological signatures that can be used to map their distribution across broad geographic regions.

Panda Habitat Distribution MODIS Data (250 m / pixel) Viña et al Remote Sensing of Environment 112: Wolong Nature Reserve

Suite of Surrogates of Canopy Characteristics fAPAR Viña & Gitelson Geophys. Res. Lett. Percent Canopy Cover Gitelson et al Remote Sens. Environ. Chlorophyll Content & Green LAI Gitelson et al Geophys. Res. Lett. Canopy Moisture Hunt & Rock Remote Sens. Environ.

MODIS Data (500 m / pixel) Panda Habitat Distribution Current Geographic Range

Analyses at Species Level Chao-Sorensen Floristic Similarity Index (Chao et al Ecol. Lett.) A Qinling Mountain Region

Phenologic Similarity  Principal Coordinates of phenologic similarity (1- euclidean distance) MODIS Data (500 m / pixel)

Conclusions  Forests are a very conspicuous land cover type (40-50%)  Areas that are habitat for the giant pandas represent ~25% of the forest areas  Some species associations can be isolated and mapped using their characteristic phenological signatures

Next Steps  Continue collecting field and remotely sensed data in all the mountain regions comprising the giant panda geographic range  Perform time series analyses in the entire geographic range to evaluate phenological traits (using high temporal resolution MODIS data) that can be related with different species associations  Evaluate relationships between local spatial heterogeneity and species richness using intermediate (e.g., Landsat) and high spatial resolution data (e.g., IKONOS)

Acknowledgements  NASA – Terrestrial Ecology and Biodiversity Program  NASA – Land Cover/Land Use Change Program  National Science Foundation  National Natural Science Foundation of China  Global Land Cover Facility, University of Maryland