Cabon A., Martínez-Vilalta J., Martínez de Aragón J., Poyatos R., De Cáceres M. (2018) Applying the eco-hydrological equilibrium hypothesis to model root distribution in water-limited forests. Ecohydrology. : 0-0.EnllaçDoi: 10.1002/eco.2015
Drought is a key driver of vegetation dynamics, but plant water-uptake patterns and consequent plant responses to drought are poorly understood at large spatial scales. The capacity of vegetation to use soil water depends on its root distribution (RD). However, RD is extremely variable in space and difficult to measure in the field, which hinders accurate predictions of water fluxes and vegetation dynamics. We propose a new method to estimate RD within water balance models, assuming that vegetation is at eco-hydrological equilibrium (EHE). EHE conditions imply that vegetation optimizes RD such that transpiration is maximized within the limits of bearable drought stress, characterized here by species-specific hydraulic thresholds. Optimized RD estimates were validated against RD estimates obtained by model calibration from sap flow or soil moisture from 38 forest plots in Catalonia (NE Spain). In water-limited plots, optimized RD was similar to calibrated RD, but estimates diverged with higher water availability, suggesting that the EHE may not be assumed when water is not limiting. Thereafter, we applied the optimization procedure at the regional scale, to estimate RD for the water-limited forests of Catalonia. Regional variations of optimum RD reproduced many expected patterns in response to climate, soil physical properties, forest structure, and species hydraulic traits. We conclude that RD optimization, based on the EHE hypothesis and a simple description of plant hydraulics, produces realistic estimates of RD that can be used for model parameterization and shows promise to improve our ability to forecast vegetation dynamics under increased drought. © 2018 John Wiley & Sons, Ltd.
De Cáceres M., Martin-StPaul N., Turco M., Cabon A., Granda V. (2018) Estimating daily meteorological data and downscaling climate models over landscapes. Environmental Modelling and Software. 108: 186-196.EnllaçDoi: 10.1016/j.envsoft.2018.08.003
High-resolution meteorological data are necessary to understand and predict climate-driven impacts on the structure and function of terrestrial ecosystems. However, the spatial resolution of climate reanalysis data and climate model outputs is often too coarse for studies at local/landscape scales. Additionally, climate model projections usually contain important biases, requiring the application of statistical corrections. Here we present ‘meteoland’ an R package that integrates several tools to facilitate the estimation of daily weather over landscapes, both under current and future conditions. The package contains functions: (1) to interpolate daily weather including topographic effects; and (2) to correct the biases of a given weather series (e.g., climate model outputs). We illustrate and validate the functions of the package using weather station data from Catalonia (NE Spain), re-analysis data and climate model outputs for a specific county. We conclude with a discussion of current limitations and potential improvements of the package. © 2018
Ameztegui A., Cabon A., De Cáceres M., Coll L. (2017) Managing stand density to enhance the adaptability of Scots pine stands to climate change: A modelling approach. Ecological Modelling. 356: 141-150.EnllaçDoi: 10.1016/j.ecolmodel.2017.04.006
In the Mediterranean region most climatic forecasts predict longer and more intense drought periods that can affect tree growth and mortality over broad geographic regions. One of the silvicultural treatments that has gained currency to lessen the impacts of climatic change is the reduction of stand density by thinning. However, we lack information on how the response of forest stands to different thinning treatments will be affected by climate change, and on the post-thinning temporal dynamics of water balance, specifically blue and green water. We adopted a modelling approach to explore the long-term effects of different thinning intensities on forest dynamics and water balance under climate change scenarios, coupling an individual-based model of forest dynamics (SORTIE-ND) with a mechanistic model of soil moisture dynamics and plant drought stress. We used as a case study three Scots pine plots across a gradient of climatic conditions, and we assessed the effect of site, three climatic scenarios and eight thinning intensities on tree growth, stand productivity, tree drought stress and blue water. The best thinning intensity in terms of stand productivity was obtained when between 20 and 40% of the basal area was removed, whereas the final stand stock rapidly decreased at higher thinning intensities. Moreover, the decrease in final basal area occurred at lower thinning intensities the drier the site conditions. Moderate and heavy thinnings (>30%) doubled basal area increment (BAI) of the following years in all the plots, although the effect vanished after 30–40 years, independently of the site and climate scenario. As expected, thinning was simulated to have an overall positive effect on the blue water yield and tree water status, which increased and also tended to last longer for higher thinning intensities. However, the magnitude of this effect on tree water status was most dependent on the site and climatic scenario, as drier conditions generally raised stronger and longer lasting reductions in drought stress for a given thinning intensity. Furthermore, our results highlight the existence of a site- and climate-dependent trade-off between the gain in stand productivity and the improvement in tree water status obtained by thinning, particularly for moderate or heavy thinning intensities. Our simulations suggest that thinning is a useful management tool to mitigate climate change but strongly argue against the application of general recipes across sites and appeals for carefully taking into consideration local climatic trajectories for management planning. © 2017 Elsevier B.V.
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