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Morsdorf, F.

Publications and source records attributed to Morsdorf, F..

3 recordsLinked to original sources

Remote sensing-based forest modeling reveals positive effects of functional diversity on productivity at local spatial scale

O_LIForest biodiversity is critical for many ecosystem functions and services at plot scale, but it is uncertain how biodiversity influences ecosystem functioning across environmental gradients and contiguous larger areas. We used remote sensing and process-based terrestrial biosphere modeling to explore functional diversity-productivity relationships at multiple scales for a heterogeneous forest site in Switzerland. C_LIO_LIWe ran the biosphere model with empirical data about forest structure and composition derived from ground-based surveys, airborne laser scanning and imaging spectroscopy for the years 2006-2015 at 10x10-m spatial resolution. We then related the model outputs forest productivity to functional diversity under observed and experimental model conditions. C_LIO_LIFunctional diversity increased productivity significantly (p < 0.001) across all simulations at 20x20-m to 30x30-m scale, but at 100x100-m scale positive relationships disappeared under homogeneous soil conditions. C_LIO_LIWhereas local functional diversity was an important driver of productivity, environmental context (especially soil depth, texture and water availability) underpinned the variation of productivity (and functional diversity) at larger spatial scales. Integration of remotely-sensed information on canopy composition and structure into terrestrial biosphere models helps fill the knowledge gap about how plant biodiversity affects carbon cycling and biosphere feedbacks onto climate over large contiguous areas. C_LI

ecology↗

Individual tree-based vs pixel-based approaches to mapping forest functional traits and diversity by remote sensing

Trait-based approaches, focusing on the functional characteristics of vascular plants in a community, have been increasingly used in plant ecology and biodiversity research. Compared with traditional field survey (which typically samples individual trees), remote sensing enables quantifying functional traits over large contiguous areas, but assigning trait values to biological units such as species and individuals is difficult with pixel-based approaches. We used a subtropical forest landscape in China to compare an approach based on LiDAR-delineated individual tree crowns (ITCs) with a pixel-based approach for assessing functional traits from remote sensing data. We compared trait distributions, trait-trait relationships and functional diversity metrics obtained by the two approaches at changing grain and extent. We found that morphological traits derived from airborne laser scanning showed more differences between ITC- and pixel-based approaches than physiological traits estimated by imaging spectroscopy data. Pixel sizes approximating average tree crowns yielded similar results as ITCs, but 95th quantile height and foliage height diversity tended to be overestimated and leaf area index underestimated relative to ITC-based values. With increasing pixel size, the differences to ITC- based trait values became larger and less trait variance was captured, indicating information loss. The consistency of ITC- and pixel-based functional richness measures also decreased with increasing pixel grain, and changed with the observed extent for functional diversity monitoring. We conclude that whereas ITC-based approaches in principle allow partitioning of variation between individuals, genotypes and species, at high resolution, pixel-based approaches come close to this and can be suitable for assessing ecosystem-scale trait variation by weighting individuals and species according to coverage.

ecology↗

A spatial fingerprint of land-water linkage of biodiversity uncovered by remote sensing and environmental DNA

Aquatic and terrestrial ecosystems are tightly connected via spatial flows of organisms and resources. Such land-water linkages integrate biodiversity across ecosystems and suggest a spatial association of aquatic and terrestrial biodiversity. However, knowledge about this spatial extent is limited. By combining satellite remote sensing (RS) and environmental DNA (eDNA) extraction from river water across a 740-km2 mountainous catchment, we identify a characteristic spatial land-water fingerprint. Specifically, we find a spatial association of riverine eDNA diversity with RS spectral diversity of terrestrial ecosystems upstream, peaking at a 400 m distance yet still detectable up to a 3.3 km radius. Our findings testify that biodiversity patterns in rivers can be linked to the functional diversity of surrounding terrestrial ecosystems and provide a dominant scale at which these linkages are strongest. Such spatially explicit information is necessary for a functional understanding of land-water linkages and provides a reference scale for adequate conservation and landscape management decisions.

ecology↗