De Cáceres M., Coll L., Legendre P., Allen R.B., Wiser S.K., Fortin M.-J., Condit R., Hubbell S. (2019) Trajectory analysis in community ecology. Ecological Monographs. : 0-0.LinkDoi: 10.1002/ecm.1350
Ecologists have long been interested in how communities change over time. Addressing questions about community dynamics requires ways of representing and comparing the variety of dynamics observed across space. Until now, most analytical frameworks have been based on the comparison of synchronous observations across sites and between repeated surveys. An alternative perspective considers community dynamics as trajectories in a chosen space of community resemblance and utilizes trajectories as objects to be analyzed and compared using their geometry. While methods that take this second perspective exist, for example to test for particular trajectory shapes, there is a need for formal analytical frameworks that fully develop the potential of this approach. By adapting concepts and procedures used for the analysis of spatial trajectories, we present a framework for describing and comparing community trajectories. A key element of our contribution is the means to assess the geometric resemblance between trajectories, which allows users to describe, quantify, and analyze variation in community dynamics. We illustrate the behavior of our framework using simulated data and two spatiotemporal community data sets differing in the community properties of interest (species composition vs. size distribution of individuals). We conclude by evaluating the advantages and limitations of our community trajectory analysis framework, highlighting its broad domain of application and anticipating potential extensions. © 2019 by the Ecological Society of America
De Cáceres M., Martín-Alcón S., González-Olabarria J.R., Coll L. (2019) A general method for the classification of forest stands using species composition and vertical and horizontal structure. Annals of Forest Science. 76: 0-0.LinkDoi: 10.1007/s13595-019-0824-0
Key message: We present a novel approach to define pure- and mixed-forest typologies from the comparison of pairs of forest plots in terms of species identity, diameter, and height of their trees. Context: Forest typologies are useful for many purposes, including forest mapping, assessing habitat quality, studying forest dynamics, or defining sustainable management strategies. Quantitative typologies meant for forestry applications normally focus on horizontal and vertical structure of forest plots as main classification criteria, with species composition often playing a secondary role. The selection of relevant variables is often idiosyncratic and influenced by a priori expectations of the forest types to be distinguished. Aims: We present a general framework to define forest typologies where the dissimilarity between forest stands is assessed using coefficients that integrate the information of species composition with the univariate distribution of tree diameters or heights or the bivariate distribution of tree diameters and heights. Methods: We illustrate our proposal with the classification of forest inventory plots in Catalonia (NE Spain), comparing the results obtained using the bivariate distribution of diameters and heights to those obtained using either tree heights or tree diameters only. Results: The number of subtypes obtained using the tree diameter distribution for the calculation of dissimilarity was often the same as those obtained from the tree height distribution or to those using the bivariate distribution. However, classifications obtained using the three approaches were often different in terms of forest plot membership. Conclusion: The proposed classification framework is particularly suited to define forest typologies from forest inventory data and allows taking advantage of the bivariate distribution of diameters and heights if both variables are measured. It can provide support to the development of typologies in situations where fine-scale variability of topographic, climatic, and legacy management factors leads to fine-scale variation in forest structure and composition, including uneven-aged and mixed stands. © 2019, INRA and Springer-Verlag France SAS, part of Springer Nature.
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.LinkDoi: 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.
Caceres M.D., Martinez-Vilalta J., Coll L., Llorens P., Casals P., Poyatos R., Pausas J.G., Brotons L. (2015) Coupling a water balance model with forest inventory data to predict drought stress: The role of forest structural changes vs. climate changes. Agricultural and Forest Meteorology. 213: 77-90.LinkDoi: 10.1016/j.agrformet.2015.06.012
Mechanistic water balance models can be used to predict soil moisture dynamics and drought stress in individual forest stands. Predicting current and future levels of plant drought stress is important not only at the local scale, but also at larger, landscape to regional, scales, because these are the management scales at which adaptation and mitigation strategies are implemented. To obtain reliable predictions of soil moisture and plant drought stress over large extents, water balance models need to be complemented with detailed information about the spatial variation of vegetation and soil attributes. We designed, calibrated and validated a water balance model that produces annual estimates of drought intensity and duration for all plant cohorts in a forest stand. Taking Catalonia (NE Spain) as a case study, we coupled this model with plot records from two Spanish forest inventories in which species identity, diameter and height of plant cohorts were available. Leaf area index of each plant cohort was estimated from basal area using species-specific relationships. Vertical root distribution for each species in each forest plot was estimated by determining the distribution that maximized transpiration in the model, given average climatic conditions, soil attributes and stand density. We determined recent trends (period 1980-2010) in drought stress for the main tree species in Catalonia; where forest growth and densification occurs in many areas as a result of rural abandonment and decrease of forest management. Regional increases in drought stress were detected for most tree species, although we found high variation in stress changes among individual forest plots. Moreover, predicted trends in tree drought stress were mainly due to changes in leaf area occurred between the two forest inventories rather than to climatic trends. We conclude that forest structure needs to be explicitly considered in assessments of plant drought stress patterns and trends over large geographic areas, and that forest inventories are useful sources of data provided that reasonably good estimates of soil attributes and root distribution are available. Our approach coupled with recent improvements in forest survey technologies may allow obtaining spatially continuous and precise assessments of drought stress. Further efforts are needed to calibrate drought-related demographic processes before water balance and drought stress estimates can be fully used for the accurate prediction of drought impacts. © 2015 Elsevier B.V.
Martin-Alcon S., Coll L., De Caceres M., Guitart L., Cabre M., Just A., Gonzalez-Olabarria J.R. (2015) Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest. Canadian Journal of Forest Research. 45: 856-866.LinkDoi: 10.1139/cjfr-2014-0430
Wildfires play a major role in driving vegetation changes and can cause important environmental and economic losses in Mediterranean forests, especially where the dominant species lacks efficient postfire regeneration mechanisms. In these areas, postdisturbance vegetation management strategies need to be based on detailed, spatially continuous inventories of the burned area. Here, we present a methodology in which we combine airborne LiDAR and multispectral imagery to assess postfire regeneration types in a spatially continuous way, using a Mediterranean black pine (Pinus nigra Arn ssp. salzmannii) forest that burned in 1998 as a case study. Five postfire regeneration types were obtained by clustering field-plot data using Ward's method. Two of the five regeneration types presented high tree cover (one clearly dominated by hardwoods and the other dominated by pines), a third type presented low to moderate tree cover, being dominated by hardwoods, and the remaining two types matched to areas dominated by soil–herbaceous or shrub layers with very low or no tree cover (i.e., very low to no tree species regeneration). These five types of regeneration were used to conduct a supervised classification of remote sensing data using a nonparametric supervised classification technique. Compared with independent field validation points, the remote sensing based assessment method resulted in a global classification accuracy of 82.7%. Proportions of regeneration types in the study area indicated a general shift from the former pine-dominated forest toward hardwood dominance and showed no serious problems of regeneration failure. Our methodological approach appears to be appropriate for informing postdisturbance vegetation management strategies over large areas. © 2015, (publisher). All Rights Reserved.
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