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Hufkens, K.

Publications and source records attributed to Hufkens, K..

5 recordsLinked to original sources

rsofun: A model-data integration framework for simulating ecosystem processes

Mechanistic vegetation models serve to estimate terrestrial carbon fluxes and climate impacts on ecosystems across diverse biotic and abiotic conditions. Systematically informing them with data is key for enhancing their predictive accuracy and estimating uncertainty. Here we present the Simulating Optimal FUNctioning {rsofun} R package, providing a computationally efficient and parallelizable implementation of the P-model for site-scale simulations of ecosystem photosynthesis, complemented with functionalities for Bayesian model-data integration and estimation of parameters and uncertainty. We describe a use case to demonstrate the package functionalities for modelling ecosystem gross CO2 uptake at one flux measurement site, including model sensitivity analysis, Bayesian parameter calibration, and prediction uncertainty estimation. {rsofun} lowers the bar of entry to ecosystem modelling and model-data integration and serves as an open-access resource for model development and dissemination.

ecology↗

Phenology across scales: an intercontinental analysis of leaf-out dates in temperate deciduous tree communities

AimTo quantify the intra-community variability of leaf-out (ICVLo) among dominant trees in temperate deciduous forests, assess its links with specific and phylogenetic diversity, identify its environmental drivers, and deduce its ecological consequences with regard to radiation received and exposure to late frost. LocationEastern North America (ENA) and Europe (EUR). Time period2009-2022 Major taxa studiedTemperate deciduous forest trees. MethodsWe developed an approach to quantify ICVLo through the analysis of RGB images taken from phenological cameras. We related ICVLo to species richness, phylogenetic diversity and environmental conditions. We quantified the intra-community variability of the amount of radiation received and of exposure to late frost. ResultsLeaf-out occurred over a longer time interval in ENA than in EUR. The sensitivity of leaf-out to temperature was identical in both regions (-3.4 days per {degrees}C). The distributions of ICVLo were similar in EUR and ENA forests, despite the latter being more species-rich and phylogenetically diverse. In both regions, cooler conditions and an earlier occurrence of leaf-out resulted in higher ICVLo. ICVLo resulted in a ca. 8% difference of radiation absorption over spring among individual trees. Forest communities in ENA had shorter safety margins as regards the exposure to late frosts, and were actually more frequently exposed to late frosts. Main conclusionsWe conducted the first intercontinental analysis of the variability of leaf-out at the scale of tree communities. North American and European forests showed similar ICVLo, in spite of their differences in terms of species richness and phylogenetic diversity, highlighting the relevance of environmental controls on ICVLo. We quantified two ecological implications of ICVLo (difference in terms of radiation absorption and exposure to late frost), which should be explored in the context of ongoing climate change, which affects trees differently according to their phenological niche.

ecology↗

Moonlight synchronous flights across three western palearctic swifts mirror size dependent prey preferences

Recent studies have suggested the presence of moonlight mediated behaviour in avian aerial insectivores, such as swifts. At the same time swift species also show differences in prey (size) preferences. Here, we use the combined analysis of state-of-the-art activity logger data across three swift species, the Common, Pallid and Alpine swifts, to quantify flight height and activity responses to crepuscular and nocturnal light conditions. Our results show a significant response in flight heights to moonlight illuminance for Common and Pallid swifts, while a moonlight driven response is absent in Alpine swifts. Swift flight responses followed the size dependent altitude gradient of their insect prey. We show a weak relationship between night-time illuminance driven responses and twilight ascending behaviour, suggesting a decoupling of both crepuscular and night-time behaviour. We suggest that swifts optimise their flight behaviour to adapt to favourable night-time light conditions, driven by light responsive and size-dependent vertical insect stratification and weather conditions.

animal behavior and cognition↗

Deep learning for satellite image forecasting of vegetation greenness

The advent of abundant Earth observation data enables the development of novel predictive methods for forecasting climate impacts on the state and health of terrestrial ecosystems. Here, we target the spatial and temporal variations of land surface reflectance and vegetation greenness, measuring the density of green vegetation and active foliage area, conditioned on current and past climate and the local topography. We train two alternative recurrent deep learning models that rely on convolutional layers for forecasting the spatially resolved deviation of surface reflectance across a heterogeneous landscape from a specified initial state (Baseline Framework). We demonstrate efficiency of the Baseline Framework with respect to training convergence speed. Using data from diverse ecosystems and land cover types across Europe and following a standardized model evaluation framework (EarthNet2021 Challenge), results indicate increased performance in predicting surface greenness during drought events of the models presented here, compared to currently published benchmarks. Our results demonstrate how deep learning methods enable early-warning of vegetation responses to the impacts of climatic extreme events, such as the drought-related loss of green foliage.

plant biology↗

Acclimation of phenology relieves leaf longevity constraints in deciduous forests

Leaf phenology is key for regulating total growing season mass and energy fluxes. Long-term temporal trends towards earlier leaf unfolding are observed across Northern Hemisphere forests. Phenological dates also vary between years, whereby end-of-season (EOS) dates correlate positively with start-of-season (SOS) dates and negatively with growing season total net CO2 assimilation (Anet). These associations have been interpreted as the effect of a constrained leaf longevity or of premature carbon (C) sink saturation - with far-reaching consequences for long-term phenology projections under climate change and rising CO2. Here, we use multi-decadal ground and remote-sensing observations to show that the relationships between Anet and EOS are opposite at the interannual and the decadal time scales. A decadal trend towards later EOS persists in parallel with a trend towards increasing Anet - in spite of the negative Anet-EOS relationship at the interannual scale. This indicates that acclimation of phenology has enabled plants to transcend a constrained leaf longevity or premature C sink saturation over the course of several decades, leading to a more effective use of available light and a sustained extension of the vegetation CO2 uptake season over time.

ecology↗