Biology subjects

Schaepman, M. E.

Publications and source records attributed to Schaepman, M. E..

6 recordsLinked to original sources

bioRxiv2023

Terrestrial land cover shapes fish diversity in major subtropical rivers

Freshwater biodiversity is critically affected by human modifications of terrestrial land use and land cover (LULC)1,2. Yet, knowledge of the spatial extent and magnitude of LULC-aquatic biodiversity linkages is still surprisingly limited, impeding the implementation of optimal management strategies3. Here, we compiled fish diversity data across a 160,000-km2 subtropical river catchment in Thailand characterized by exceptional biodiversity4 yet intense anthropogenic alterations5, and attributed fish species richness and community composition to contemporary terrestrial LULC across the catchment. We estimated a spatial range of LULC effects extending up to about 20 km upstream from sampling sites, and explained nearly 60 % of the variance in the observed species richness, associated with major LULC categories including croplands, forest, and urban areas. We find that integrating both spatial range and magnitudes of LULC effects is needed to accurately predict fish species richness. Further, projected LULC changes showcase future gains and losses of fish species richness across the river network and offer a scalable basis for riverine biodiversity conservation and land management, allowing for potential mitigation of biodiversity loss in highly diverse yet data-deficient tropical to sub-tropical riverine habitats.

ecology↗

bioRxiv2023

Association of leaf spectral variation with functional genetic variants

The application of in-field and aerial spectroscopy to assess functional and phylogenetic variation in plants has led to novel ecological insights and supports global assessments of plant biodiversity. Understanding how plant genetic variation influences reflectance spectra will help harness this potential for biodiversity monitoring and improve understanding of why plants differ in functional responses to environmental change. Here, we use a well-resolved genetic mapping population derived from Multi-parent Advanced Generation Inter-cross (MAGIC) lines of Nicotiana attenuata to associate genetic differences with differences in leaf spectra between plants in a field experiment in their natural environment. We analyzed the leaf reflectance spectra using a hand-held spectroradiometer (350-2500 nm) on 616 fully genotyped plants of N. attenuata grown in a randomized block design. We tested three approaches to conducting Genome-Wide Association Studies on spectral variants. We introduce a new Hierarchical Spectral Clustering with Parallel Analysis (HSC-PA) method. This method efficiently captured the variation in our high-dimensional dataset and allowed us to discover a novel association, between a locus on chromosome 1 and the 734-1143 nm spectral range, spanning the red-edge and near-infrared regions that are sensitive to leaf structure and photosynthetic activity. This locus contains a candidate gene annotated as carbonic anhydrase, an enzyme involved in CO2 hydration and regulation of photosynthetic efficiency, suggesting a physiological link between variation in leaf optical properties and carbon assimilation. In contrast, an approach treating single wavelengths as phenotypes identified the same associations as HSC-PA, but without the statistical power to pinpoint significant associations. An index-based approach, which reduces complex spectra to a few dimensionless variables, detected two significant associations for ARDSI_Cw (a water-content-related index) with loci on chromosome 1 near genes annotated as a Zeta toxin domain-containing protein, and an Exocyst subunit Exo70 family protein. While these findings are biologically plausible, they represent a very narrow subset of the spectral variation captured by HSC-PA. The HSC-PA approach supports a comprehensive understanding of the genetic determinants of leaf spectral variation which is data-driven but human-interpretable, and lays a robust foundation for future research in linking plant genetics with biodiversity monitoring, large-scale ecological assessment and remote-sensing applications.

ecology↗

bioRxiv2023

Inferring genetic structure of European beech from observations of spectral phenotypes

Biodiversity loss presents a growing threat to the global environment, and systematic and spatially contiguous monitoring is needed to inform mitigation strategies. Monitoring of genetic diversity within species, a key factor when assessing biodiversity loss, is laborious and could be supported by scalable phenotypic observations allowing inferences about genetic variation. We studied genetic and phenotypic variation in one of Europes most prevalent forest-forming trees, the common beech Fagus sylvatica L., using whole-genome sequence data and spectral phenotypes from 219 individuals at 23 sites across the species natural range. Spectral phenotypes were collected under standardized illumination and observation conditions from the same top-of-canopy leaves used for nuclear DNA extraction. We found that spectral and environmental information accounted for 77% of the variance along the first two principal coordinates representing genetic structure among sampled individuals, where spectral phenotypes contributed 12% to the prediction of genetic structure. Further, we identified 14 SNPs (single nucleotide polymorphisms), of which two were located within annotated genes, that showed significant associations with variation in leaf reflectance. Our study demonstrates how linking spectral and genomic variation in tree species may be upscaled to the remote observations to support monitoring, understanding and mitigating loss of genetic diversity within species.

plant biology↗

bioRxiv2022

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↗

bioRxiv2021

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↗

bioRxiv2021

Variation in reflectance spectroscopy of European beech leaves captures phenology and biological hierarchies despite measurement uncertainties

The measurement of leaf optical properties (LOP) using reflectance and scattering properties of light allows a continuous, time-resolved, and rapid characterization of many species traits including water status, chemical composition, and leaf structure. Variation in trait values expressed by individuals result from a combination of biological and environmental variations. Such species trait variations are increasingly recognized as drivers and responses of biodiversity and ecosystem properties. However, little has been done to comprehensively characterize or monitor such variation using leaf reflectance, where emphasis is more often on species average values. Furthermore, although a variety of platforms and protocols exist for the estimation of leaf reflectance, there is neither a standard method, nor a best practise of treating measurement uncertainty which has yet been collectively adopted. In this study, we investigate what level of uncertainty can be accepted when measuring leaf reflectance while ensuring the detection of species trait variation at several levels: within individuals, over time, between individuals, and between populations. As a study species, we use an economically and ecologically important dominant European tree species, namely Fagus sylvatica. We first use fabrics as standard material to quantify the measurement uncertainties associated with leaf clip (0.0001 to 0.4 reflectance units) and integrating sphere measurements (0.0001 to 0.01 reflectance units) via error propagation. We then quantify spectrally resolved variation in reflectance from F. sylvatica leaves. We show that the measurement uncertainty associated with leaf reflectance, estimated using a field spectroradiometer with attached leaf clip, represents on average a small portion of the spectral variation within a single individual sampled over time (2.7 {+/-} 1.7%), or between individuals (1.5 {+/-} 1.3% or 3.4 {+/-} 1.7%, respectively) in a set of monitored F. sylvatica trees located in Swiss and French forests. In all forests, the spectral variation between individuals exceeded the spectral variation of a single individual measured within one week. However, measurements of variation within an individual at different canopy positions over time indicate that sampling design (e.g., standardized sampling, and sample size) strongly impacts our ability to measure between-individual variation. We suggest best practice approaches towards a standardized protocol to allow for rigorous quantification of species trait variation using leaf reflectance. HighlightsO_LIWe partition biological variation from measurement uncertainty for leaf spectra. C_LIO_LIMeasurement uncertainty represents ca. 3% of spectral variation among beech trees. C_LIO_LIBiological variation within an individual increases by 80% as leaves mature. C_LIO_LIMaxima of uncertainty correspond to maxima of biological variation (water content). C_LIO_LIWe recommend procedures to quantify biological variation in spectral measurements. C_LI

ecology↗