Abstract
Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.
Highlights
Advanced spatial assessment and monitoring of biodiversity in today’s rapidly changing world is vital for managing future biological resources and a key element of several 2020 targets of the Convention on Biological Diversity [1,2] and the Intergovernmental Platform on Biodiversity and Ecosystem Services [3]
In contrast to existing evidence (S1 Table), the new product captures the frequency of cloud cover at substantially increased spatial resolution
We have shown how global cloud dynamics can be quantified in unprecedented spatial detail and that cloud-associated factors are significantly associated with the distribution of various aspects of biodiversity habitats over large spatial scales
Summary
Advanced spatial assessment and monitoring of biodiversity in today’s rapidly changing world is vital for managing future biological resources and a key element of several 2020 targets of the Convention on Biological Diversity [1,2] and the Intergovernmental Platform on Biodiversity and Ecosystem Services [3]. Cloud cover and precipitation are prime examples of important environmental factors that can have significant spatial variability at grains lower than 2 km [8] and are difficult to interpolate [9]. In the tropics, seasonal variability of cloud cover is typically more important than day length and solar angle in reducing available solar irradiance, with multi-fold ecological consequences [14]. These effects are difficult to observe in other remotely sensed products including vegetation indices, which for many parts of the world do not show much change throughout the year [15]. Several decades of satellite data offer new opportunities to characterize our planet by providing data globally with consistent methodology and, critically, spatially contiguous observations at high spatial resolution
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