Center for Systems Integration and Sustainability

Journal or Book Title: Journal of Biogeography.

Keywords: Ailuropoda melanoleuca; China; land surface phenology; model transferability; MODIS; remote sensing; species distribution model; WDRVI; wildlife habitat monitoring; Wolong Nature Reserve

Year Published: 2011

Aim Temporal transferability is an important issue when habitat models are used
beyond the time frame corresponding to model development, but has not
received enough attention, particularly in the context of habitat monitoring.
While the combination of remote sensing technology and habitat modelling
provides a useful tool for habitat monitoring, the effect of incorporating remotely
sensed data on model transferability is unclear. Therefore, our objectives were to
assess how different satellite-derived variables affect temporal transferability of
habitat models and their usefulness for habitat monitoring.

Location Wolong Nature Reserve, Sichuan Province, China.

Methods We modelled giant panda habitat with the maximum entropy algorithm
using panda presence data collected in two time periods and four different sets of
predictor variables representing land surface phenology. Each predictor variable set
contained either a time series of smoothed wide dynamic range vegetation index
(WDRVI) or 11 phenology metrics, both derived from single-year or multi-year (i.e.
3-year) remotely sensed imagery acquired by the Moderate Resolution Imaging
Spectroradiometer (MODIS). We evaluated the ability of models obtained with
these four variable sets to predict giant panda habitat within and across time periods
by using threshold-independent and threshold-dependent evaluation methods and
five indices of temporal transferability.

Results Our results showed that models developed with the four variable sets
were all useful for characterizing and monitoring giant panda habitat. However,
the models developed using multi-year data exhibited significantly higher
temporal transferability than those developed using single-year data. In
addition, models developed with phenology metrics, especially when using
multi-year data, exhibited significantly higher temporal transferability than those
developed with the time series.

Main conclusions The integration of land surface phenology, captured by high
temporal resolution remotely sensed imagery, with habitat modelling constitutes
a suitable tool for characterizing wildlife habitat and monitoring its temporal
dynamics. Using multi-year phenology metrics reduces model complexity,
multicollinearity among predictor variables and variability caused by interannual
climatic fluctuations, thereby increasing the temporal transferability of
models. This study provides useful guidance for habitat monitoring through the
integration of remote sensing technology and habitat modelling, which may be
useful for the conservation of the giant panda and many other species.

DOI: 10.1111/j.1365-2699.2011.02479.x

Type of Publication: Journal Article