Biology subjects

Bontemps, J.-D.

Publications and source records attributed to Bontemps, J.-D..

2 recordsLinked to original sources

bioRxiv2024

Turning point in forest productivity revealed from 40 years of national forest inventory data

Aim: Global changes, such as changing climate or disruption in biogeochemical cycles, are affecting forest productivity worldwide. Trends in productivity are depending on the focal spatial scale and on the considered time window, stable trends at large spatial scale can mask divergence at smaller scale while short time windows limit the capacity to reveal non-linear trends such as turning points. Capitalizing on 40 years of national forest inventory data from more than 100 tree species we explored trends in forest productivity at the regional level across 4 biogeographical regions. Location: France Time period: 1978-2022 Major taxa studied: 146 tree species Methods: We fitted two classes of models, a first one explicitly estimating temporal trends and a second one including no temporal components but climatic variables reflecting changing temperature and water availability. Results: We find a decrease in productivity in 95% of the regions and a high contrast in trend shapes between regions over the period studied: lowland regions with average temperature above 11.9{degrees}C showed linear negative trends in productivity since 1985 while colder lowland regions showed hump-shaped trends with turning points between 1985 and 2005, followed by declines in productivity. In mountainous regions, average climate did not appear to be a strong mediator of trend shapes. The temporal trends were reconstituted with high fidelity from the model including only climatic variables implying that changes in temperature and water availability are likely drivers of the reported trends. Main conclusion: These results illustrate the progression during the last decades of the adverse effects of climate change on forest productivity over the European forests. They suggest the expected changes over the 21st century that will put further pressure on forest productivity, impacting forest carbon sink potential and reducing sustainable rate of timber extraction.

ecology↗

bioRxiv2022

Gaining insight into the allometric scaling of trees by utilizing 3d reconstructed tree models - a SimpleForest study

Forestry utilizes volume predictor functions utilizing as input the diameter at breast height. Some of those functions take the power form Y = a * Xb. In fact this function is fundamental for the biology field of allometric scaling theories founded round about a century ago. The theory describes the relationships between organs/body parts and the complete body of organisms. With digital methods we can generate 3d forest point clouds non destructively in short time frames. SimpleForest is one free available tool which generates fully automated ground and tree models from high resoluted forest plots. Generated topological ordered cylinder models are called commonly QSMs. We use SimpleForest QSMs an build a function which estimates the total supported wood volume at any given point of the tree. As input we use the supported soft wood volume for those query points. Instead of measuring directly the soft wood volume we use as a proxy the number of supported twigs. We argue with the pipe model theory for the correctness of the proxy. We can use the named relationship to also filter our QSMs made of an open data set of tree clouds. The filter corrects overestimated radii. And we compare the corrected QSM volume against the harvested reference data for 66 felled trees. We also found QSM data of TreeQSM, a competitive and broadly accepted QSM modeling tool. Our RMSE was less than 40% of the tree QSM RMSE. And for other error measures, the r2adj. and the CCC, the relative improvement looked even better with 27% and 21% respectively. We consider this manuscript as highly impactful because of the magnitude of quality improvement we do. The relation between soft volume and total volume distributions seems to be really strong and tree data can easily also be used as example data for the generic field of allometric scaling.

bioinformatics↗