Coupling in situ and remote sensing data to assess $\alpha$- and $\beta$-diversity over biogeographic gradients

TL;DR

This study integrates in situ botanical observations and remote sensing data to analyze plant and spectral diversity across France, identifying bioregions and exploring biodiversity patterns at a 5 km resolution.

Contribution

It presents a novel integration of in situ and remote sensing data for biodiversity assessment, revealing bioregional structures and diversity relationships at a national scale.

Findings

Identified five bioregions in France based on combined data.

Demonstrated the complementary strengths of in situ and remote sensing data.

Explored the relationship between plant and spectral diversity within bioregions.

Abstract

The mapping of plant biodiversity represents a fundamental stage in establishing conservation priorities, particularly in identifying groups of species that share ecological requirements or evolutionary histories. This is often achieved by assessing different spatial diversity patterns in plant population distributions. In this paper, we present two primary data sources crucial for biodiversity monitoring: in situ measurements from botanical observations and remote sensing (RS). In situ methods involve directly collecting data from specific sites, providing detailed insights into ecological patterns but often constrained by resource limitations. Integrating in situ and RS data highlights their complementary strengths, which depend on factors such as study scale, resolution, and logistical feasibility. While in situ approaches are characterized by precision, RS offers efficiency and extensive, repeated coverage. This research integrates in situ and RS data to analyze plant and spectral diversity across France at a spatial resolution of 5 km, encompassing over 23,000 grid cells. We employ four established diversity metrics leveraging the spatial distribution of 6,650 plant species and 250 spectral clusters (derived from MODIS data at a 500-meter resolution). Through bioregionalization network analysis combining these data sources, we identified five distinct bioregions that capture the biogeographical structure of plant biodiversity in France. Additionally, we explore the relationship between plant species diversity and spectral cluster diversity within and between these bioregions, offering novel insights into the spatial dynamics of plant biodiversity.