Abstract
Measuring and monitoring tree diversity is a prerequisite for altering biodiversity loss and the sustainable management of forest ecosystems. High temporal satellite remote sensing, recording difference in species phenology, can facilitate the extraction of timely, standardized and reliable information on tree diversity, complementing or replacing traditional field measurements. In this study, we used multispectral and multi-seasonal remotely sensed data from the Sentinel-2 satellite sensor along with geodiversity data for estimating local tree diversity in a Mediterranean forest area. One hundred plots were selected for in situ inventory of tree species and measurement of tree diversity using the Simpson’s (D1) and Shannon (H′) diversity indices. Four Sentinel-2 scenes and geodiversity variables, including elevation, aspect, moisture, and basement rock type, were exploited through a random forest regression algorithm for predicting the two diversity indices. The multi-seasonal models presented the highest accuracy for both indices with an R2 up to 0.37. In regard to the single season, spectral-only models, mid-summer and mid-autumn model also demonstrated satisfactory accuracy (max R2 = 0.28). On the other hand, the accuracy of the spectral-only early-spring and early-autumn models was significant lower (max R2 = 0.16), although it was improved with the use of geodiversity information (max R2 = 0.25).
Highlights
Starting from the 1990s, there has been an international recognition and a sense of urgency for natural capital conservation and altering of the accelerating biodiversity loss observed during the past 50 years [1]
The Mediterranean area has been characterized as a biodiversity hotspot [4] due to its high floristic richness and distinguished endemism; both attributes reveal the important biogeographical peculiarities existing in a relative limited areal extent [5,6]
Based on spectral variables models, the results indicate that predictions of the examined tree diversity indices (H and D1) were more accurate using multi-seasonal (R2 = 0.31, root mean square error (RMSE) = 0.33, mean absolute error (MAE) = 0.27 and R2 = 0.37, RMSE = 0.18, MAE = 0.15 for H and D1, respectively) imagery
Summary
Starting from the 1990s, there has been an international recognition and a sense of urgency for natural capital conservation and altering of the accelerating biodiversity loss observed during the past 50 years [1]. Tree species richness and diversity in these ecosystems, as well as a high degree of endemism, which is evidenced by the presence of 201 endemic taxa (species and subspecies) [7], play a crucial role in supporting forest biodiversity It is an important factor for ecosystem functioning, productivity and provision of multiple ecosystem services [11,12]. Effective conservation of tree diversity in the Mediterranean forests is a critical priority, urging the need for the establishment of an effective, operational approach, capable of providing assessment of the baseline state of tree diversity as well as facilitating identification of early warning signs of diversity change at multiple spatial scales This information is crucial for designing and introducing policies and management actions for halting tree diversity decline and creating more resilient forest areas [15]
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