The leaf area index (LAI) is not only an important parameter used to describe the geometry of vegetation canopy but also a key input variable for ecological models. One of the most commonly used methods for LAI estimation is to establish an empirical relationship between the LAI and the vegetation index (VI). However, the LAI-VI relationships had high seasonal variability, and they differed among phenophases and VIs. In this study, the LAI-VI relationships in different phenophases and for different VIs (i.e., the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and near-infrared reflectance of vegetation (NIRv)) were investigated based on 82 site-years of LAI observed data and the Moderate Resolution Imaging Spectroradiometer (MODIS) VI products. Significant LAI-VI relationships were observed during the vegetation growing and declining periods. There were weak LAI-VI relationships (p > 0.05) during the flourishing period. The accuracies for the LAIs estimated with the piecewise LAI-VI relationships based on different phenophases were significantly higher than those estimated based on a single LAI-VI relationship for the entire vegetation active period. The average root mean square error (RMSE) ± standard deviation (SD) value for the LAIs estimated with the piecewise LAI-VI relationships was 0.38 ± 0.13 (based on the NDVI), 0.41 ± 0.13 (based on the EVI) and 0.41 ± 0.14 (based on the NIRv), respectively. In comparison, it was 0.46 ± 0.13 (based on the NDVI), 0.55 ± 0.15 (based on the EVI) and 0.55 ± 0.15 (based on the NIRv) for those estimated with a single LAI-VI relationship. The performance of the three VIs in estimating the LAI also varied among phenophases. During the growing period, the mean RMSE ± SD value for the estimated LAIs was 0.30 ± 0.11 (LAI-NDVI relationships), 0.37 ± 0.11 (LAI-EVI relationships) and 0.36 ± 0.13 (LAI-NIRv relationships), respectively, indicating the NDVI produced significantly better LAI estimations than those from the other two VIs. In contrast, the EVI produced slightly better LAI estimations than those from the other two VIs during the declining period (p > 0.05), and the mean RMSE ± SD value for the estimated LAIs was 0.45 ± 0.16 (LAI-NDVI relationships), 0.43 ± 0.23 (LAI-EVI relationships) and 0.45 ± 0.25 (LAI-NIRv relationships), respectively. Hence, the piecewise LAI-VI relationships based on different phenophases were recommended for the estimations of the LAI instead of a single LAI-VI relationship for the entire vegetation active period. Furthermore, the optimal VI in each phenophase should be selected for the estimations of the LAI according to the characteristics of vegetation growth.

Taxus wallichiana Zucc. (Himalayan yew) is subject to international and national conservation measures because of its over-exploitation and decline over the last 30 years. Predicting the impact of climate change on T. wallichiana's distribution might help protect the wild populations and plan effective ex situ measures or cultivate successfully. Considering the complexity of climates and the uncertainty inherent in climate modeling for mountainous regions, we integrated three Representative Concentration Pathways (RCPs) (i.e., RCP2.6, RCP4.5, RCP8.5) based on datasets from 14 Global Climate Models of Coupled Model Intercomparison Project, Phase 5 to: (1) predict the potential distribution of T. wallichiana under recent past (1960-1990, hereafter ''current'') and future (2050s and 2070s) scenarios with the species distribution model MaxEnt.; and (2) quantify the climatic factors influencing the distribution. In respond to the future warming climate scenarios, (1) highly suitable areas for T. wallichiana would decrease by 31-55% at a rate of 3-7%/ 10a; (2) moderately suitable areas would decrease by 20-30% at a rate of 2-4%/10a; (3) the average elevation of potential suitable sites for T. wallichiana would shift upslope by 390 m (15%) to 948 m (36%) at a rate of 42-100 m/10a. Average annual temperature (contribution rate ca. 61%), isothermality and temperature seasonality (20%), and annual precipitation (17%) were the main climatic variables affecting T. wallichiana habitats. Prior protected areas and suitable planting areas must be delimited from the future potential distributions, especially the intersection areas at different suitability levels. It is helpful to promote the sustainable utilization of this precious resource by prohibiting exploitation and ex situ restoring wild resources, as well as artificially planting considering climate suitability.

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