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Understanding ecosystem responses to compound disturbance regimes and the influence of specific sequences of events in determining ecosystem shifts remains a challenge. We use a modelling framework for Mediterranean-type ecosystems to assess the effects of fire–drought interactions on long-term vegetation dynamics and to identify disturbance-driven changes in trait composition (tree seeder vs. tree resprouter prevalence) and ecosystem state (forest vs. non-forest). Changes in tree seeder and the tree resprouter dominance show nonlinear, threshold-type trends over gradients of increasing compound disturbance frequency. Vegetation composition thresholds mostly occur in a narrow range of the compound fire–drought disturbance space. Additionally, trait compositional switches and the likelihood of sudden changes in ecosystem state are promoted by fire-drought interactions. Distinct sequences of disturbance events cause vegetation transitions, disrupting ecosystem resilience, even under moderate recurrence of individual disturbances. An extreme drought year followed by one or two large fire events promotes shifts from resprouter- to seeder dominance. Contrastingly, a large crown fire followed by an extreme drought promotes changes from seeder to resprouter dominance. This disturbance sequence is also a mechanism strong enough to trigger sudden shifts in ecosystem state (from forest to non-forest). Synthesis. Thresholds of change in vegetation composition occur over a narrow range of the modelled gradients of compound fire-drought recurrence, and the loss of ecosystem resilience is contingent on particular sequences of disturbance events. Overall, our findings highlight that disturbance interactions define the relative location of tipping points in ecosystem state, and that effects and feedbacks of compound disturbance regimes increase the long-term likelihood of sudden ecosystem shifts and, therefore, uncertainty in predicting vegetation state.

Mediterranean forests and fire regimes are closely intertwined. Global change is likely to alter both forest dynamics and wildfire activity, ultimately threatening the provision of ecosystem services and posing greater risks to society. In this paper we evaluate future wildfire behavior by coupling climate projections with simulation models of forest dynamics and wildfire hazard. To do so, we explore different forest management scenarios reflecting different narratives related to EU forestry (promotion of carbon stocks, reduction of water vulnerability, biomass production and business-as-usual) under the RCP 4.5 and RCP 8.5 climate pathways in the period 2020-2100. We used as a study model pure submediterranean Pinus nigra forests of central Catalonia (NE Spain). Forest dynamics were simulated from the 3rd National Forest Inventory (143 stands) using SORTIE-nd software based on climate projections under RCPs 4.5 and 8.5. The climate products were also used to estimate fuel moisture conditions (both live and dead) and wind speed. Fuel parameters and fire behavior were then simulated, selecting crown fire initiation potential and rate of spread as key indicators. The results revealed consistent trade-offs between forest dynamics, climate and wildfire. Despite the clear influence exerted by climate, forest management modulates fire behavior, resulting in different trends depending on the climatic pathway. In general, the maintenance of current practices would result in the highest rates of crown fire activity, while management for water vulnerability reduction is postulated as the best alternative to surmount the increasingly hazardous conditions envisaged in RCP 8.5., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Minimum water potential (Ψ min ) is a key variable for characterizing dehydration tolerance and hydraulic safety margins (HSMs) in plants. Ψ min is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample size and the underlying probability distribution. We compare alternative approaches to estimate Ψ min and assess the corresponding uncertainties and biases; propose statistically robust estimation methods based on extreme value theory (EVT); and assess the implications of our results for the characterization of hydraulic risk. Our results show that current estimates of Ψ min and HSMs are biased, as they are strongly affected by sample size. Because sampling effort is generally higher for species living in dry environments, the differences in current Ψ min estimates between these species and those living under milder conditions are partly artefactual. When this bias is corrected using EVT methods, resulting HSMs tend to increase substantially with resistance to embolism across species. Although data availability and representativeness remain the main challenges for proper determination of Ψ min , a closer look at Ψ distributions and the use of statistically robust methods to estimate Ψ min opens new ground for characterizing plant hydraulic risks., (© 2021 The Authors. New Phytologist © 2021 New Phytologist Foundation.)

Efforts to develop mechanistic tree growth models are hindered by the uncertainty of whether and when tree growth responses to environmental factors are driven by carbon assimilation or by biophysical limitations of wood formation. In this study, we used multiannual weekly wood-formation monitoring of two conifer species (Larix decidua and Picea abies) along a 900 m elevational gradient in the Swiss Alps to assess the biophysical effect of temperature and water potential on wood formation. To this end, we developed a model that simulates the effect of water potential on turgor-driven cambial division, modulated by the effect of temperature on enzymatic activity. The model reproduced the observed phenology of tracheid production, as well as intra- and interannual tracheid production dynamics of both species along the elevational gradient, although interannual model performance was lower. We found that temperature alone explains the onset of tracheid production, yet water potential appears necessary to predict the ending and the total amount of tracheids produced annually. We conclude that intra-annual cambial activity is strongly constrained by both temperature and water potential at all elevations, independently of carbon assimilation. At the interannual scale, biophysical constraints likely interact with other factors., (© 2020 The Authors. New Phytologist © 2020 New Phytologist Trust.)

The extent to which water availability can be used to predict the enlargement and final dimensions of xylem conduits remains an open issue. We reconstructed the time course of tracheid enlargement in Pinus sylvestris trees in central Spain by repeated measurements of tracheid diameter on microcores sampled weekly during a 2 yr period. We analyzed the role of water availability in these dynamics empirically through time-series correlation analysis and mechanistically by building a model that simulates daily tracheid enlargement rate and duration based on Lockhart's equation and water potential as the sole input. Tracheid enlargement followed a sigmoid-like time course, which varied intra- and interannually. Our empirical analysis showed that final tracheid diameter was strongly related to water availability during tracheid enlargement. The mechanistic model was calibrated and successfully validated (R 2  = 0.92) against the observed tracheid enlargement time course. The model was also able to reproduce the seasonal variations of tracheid enlargement rate, duration and final diameter (R 2  = 0.84-0.99). Our results support the hypothesis that tracheid enlargement and final dimensions can be modeled based on the direct effect of water potential on turgor-driven cell expansion. We argue that such a mechanism is consistent with other reported patterns of tracheid dimension variation., (© 2019 The Authors New Phytologist © 2019 New Phytologist Trust.)

Understanding ecosystem vulnerability is essential in risk management to anticipate disasters. While valuable efforts have been made to characterize vulnerability components (exposure, sensitivity, and response capacity) at particular ecosystem stages, there is still a lack of context-specific studies accounting for the temporal dimension of vulnerability. In this study, we developed a procedure to identify the main natural dynamics of monospecific and mixed forests and to assess the variations of sensitivity and response capacity to fire along successional dynamics. In the procedure, we generated forest chronosequences by summarizing the dynamics between consecutive surveys of permanent plots into a set of longer successional trajectories represented in a multidimensional space. Then, we calculated several variables of sensitivity and response capacity to fire of forest stages associated with each trajectory and we assessed their variation along succession. The procedure was applied to Mediterranean forests in Spain dominated by a pine species poorly adapted to severe crown fires. We found that forest vulnerability components varied differently among successional trajectories, which depended on the composition and structure of their initial stages and the environmental context in which they occurred. Autosuccessional dynamics of pine forests showed relatively low sensitivity to fire along trajectories. However, their response capacity was related to the changes in shrub cover. In contrast, diversifying dynamics showed an increasing sensitivity to fire, but also a higher response capacity the greater the functional diversity along succession. These results highlight the need for considering the temporal dimension of vulnerability in risk management and the importance of assessing sensitivity and response capacity as independent components of vulnerability that can be modified through management at critical forest stages., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Despite the huge resources invested in fire suppression, the impact of wildfires has considerably increased across the Mediterranean region since the second half of the 20th century. Modulating fire suppression efforts in mild weather conditions is an appealing but hotly-debated strategy to use unplanned fires and associated fuel reduction to create opportunities for suppression of large fires in future adverse weather conditions. Using a spatially-explicit fire-succession model developed for Catalonia (Spain), we assessed this opportunistic policy by using two fire suppression strategies that reproduce how firefighters in extreme weather conditions exploit previous fire scars as firefighting opportunities. We designed scenarios by combining different levels of fire suppression efficiency and climatic severity for a 50-year period (2000-2050). An opportunistic fire suppression policy induced large-scale changes in fire regimes and decreased the area burnt under extreme climate conditions, but only accounted for up to 18-22% of the area to be burnt in reference scenarios. The area suppressed in adverse years tended to increase in scenarios with increasing amounts of area burnt during years dominated by mild weather. Climate change had counterintuitive effects on opportunistic fire suppression strategies. Climate warming increased the incidence of large fires under uncontrolled conditions but also indirectly increased opportunities for enhanced fire suppression. Therefore, to shift fire suppression opportunities from adverse to mild years, we would require a disproportionately large amount of area burnt in mild years. We conclude that the strategic planning of fire suppression resources has the potential to become an important cost-effective fuel-reduction strategy at large spatial scale. We do however suggest that this strategy should probably be accompanied by other fuel-reduction treatments applied at broad scales if large-scale changes in fire regimes are to be achieved, especially in the wider context of climate change.

European agriculture is undergoing widespread changes that are likely to have profound impacts on farmland biodiversity. The development of tools that allow an assessment of the potential biodiversity effects of different land-use alternatives before changes occur is fundamental to guiding management decisions. In this study, we develop a resource-based model framework to estimate habitat suitability for target species, according to simple information on species' key resource requirements (diet, foraging habitat and nesting site), and examine whether it can be used to link land-use and local species' distribution. We take as a study case four steppe bird species in a lowland area of the north-eastern Iberian Peninsula. We also compare the performance of our resource-based approach to that obtained through habitat-based models relating species' occurrence and land-cover variables. Further, we use our resource-based approach to predict the effects that change in farming systems can have on farmland bird habitat suitability and compare these predictions with those obtained using the habitat-based models. Habitat suitability estimates generated by our resource-based models performed similarly (and better for one study species) than habitat based-models when predicting current species distribution. Moderate prediction success was achieved for three out of four species considered by resource-based models and for two of four by habitat-based models. Although, there is potential for improving the performance of resource-based models, they provide a structure for using available knowledge of the functional links between agricultural practices, provision of key resources and the response of organisms to predict potential effects of changing land-uses in a variety of context or the impacts of changes such as altered management practices that are not easily incorporated into habitat-based models.

Beta diversity can be measured in different ways. Among these, the total variance of the community data table Y can be used as an estimate of beta diversity. We show how the total variance of Y can be calculated either directly or through a dissimilarity matrix obtained using any dissimilarity index deemed appropriate for pairwise comparisons of community composition data. We addressed the question of which index to use by coding 16 indices using 14 properties that are necessary for beta assessment, comparability among data sets, sampling issues and ordination. Our comparison analysis classified the coefficients under study into five types, three of which are appropriate for beta diversity assessment. Our approach links the concept of beta diversity with the analysis of community data by commonly used methods like ordination and anova. Total beta can be partitioned into Species Contributions (SCBD: degree of variation of individual species across the study area) and Local Contributions (LCBD: comparative indicators of the ecological uniqueness of the sites) to Beta Diversity. Moreover, total beta can be broken up into within- and among-group components by manova, into orthogonal axes by ordination, into spatial scales by eigenfunction analysis or among explanatory data sets by variation partitioning., (© 2013 John Wiley & Sons Ltd/CNRS.)

Available data show that future changes in global change drivers may lead to an increasing impact of fires on terrestrial ecosystems worldwide. Yet, fire regime changes in highly humanised fire-prone regions are difficult to predict because fire effects may be heavily mediated by human activities We investigated the role of fire suppression strategies in synergy with climate change on the resulting fire regimes in Catalonia (north-eastern Spain). We used a spatially-explicit fire-succession model at the landscape level to test whether the use of different firefighting opportunities related to observed reductions in fire spread rates and effective fire sizes, and hence changes in the fire regime. We calibrated this model with data from a period with weak firefighting and later assess the potential for suppression strategies to modify fire regimes expected under different levels of climate change. When comparing simulations with observed fire statistics from an eleven-year period with firefighting strategies in place, our results showed that, at least in two of the three sub-regions analysed, the observed fire regime could not be reproduced unless taking into account the effects of fire suppression. Fire regime descriptors were highly dependent on climate change scenarios, with a general trend, under baseline scenarios without fire suppression, to large-scale increases in area burnt. Fire suppression strategies had a strong capacity to compensate for climate change effects. However, strong active fire suppression was necessary to accomplish such compensation, while more opportunistic fire suppression strategies derived from recent fire history only had a variable, but generally weak, potential for compensation of enhanced fire impacts under climate change. The concept of fire regime in the Mediterranean is probably better interpreted as a highly dynamic process in which the main determinants of fire are rapidly modified by changes in landscape, climate and socioeconomic factors such as fire suppression strategies.

Individuals who are carriers of deletions of various sizes that cause haploinsufficiency in the contiguous WT1 and PAX6 genes, located on chromosome 11p13 approximately 4 Mb centromeric to the BDNF gene, are susceptible to Wilms tumor, aniridia, mental retardation, genitourinary anomalies and obesity (WAGRO syndrome). The molecular characterization of the wide deletion 11p15.1p12 arr (18676926-36576388) x1 dn in a child with 3 years and 4 months of age only affected by aniridia, predicts not only other serious associated diseases, but also allows us to hypothesize a specific phenotype of mental impairment, conduct alterations and childhood obesity, possibly added to the onset of metabolic alterations. The variable appearance and/or description of haploinsufficiency for obesity susceptibility in the WAGR syndrome mainly depends on the critical region located within 80 kb of exon 1 of BDNF. The relationship between genetic variation based on the genotype combinations of the 4 gene SNPs tagging the BDNF gene and the body mass index (BMI) was studied. The polymorphic variability was similarly distributed in 218 children suffering a severe and non-syndromic obesity from families at high risk for obesity, as compared with 198 controls. The corroborated role of the BDNF gene as highly susceptible to severe syndromic obesity has not already been evidenced in the molecular basis of overweight attributed to the common polygenic principles. Its potential role as risk modifier variant to provoke more severe phenotype has not yet been demonstrated. Some genetic variants of brain-derived neurotrophic factor (BDNF) have resulted in important disorders of energy balance, but it is essential to know exactly their deleterious human capacity because they play a fundamental role in the development and plasticity of the central nervous system in regulating food intake. The existence of polymorphic amino acid changes of unknown functional significance in patients carrying the haploinsufficiency of the BDNF gene could constitute an adequate model to study in depth their effects., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The Caloplaca saxicola group is the main group of saxicolous, lobed-effigurate species within genus Caloplaca (Teloschistaceae, lichen-forming Ascomycota). A recent monographic revision by the first author detected a wide range of morphological variation. To confront the phenotypically based circumscription of these taxa and to resolve their relationships morphological and ITS rDNA data were obtained for 56 individuals representing eight Caloplaca species belonging to the C. saxicola group. We tested the monophyly of these eight morphospecies by performing maximum parsimony, maximum likelihood and two different types of Bayesian analyses (with and without a priori alignments). Restricting phylogenetic analyses to unambiguously aligned portions of ITS was sufficient to resolve, with high bootstrap support, five of the eight previously recognized species within the C. saxicola group. However, phylogenetic resolution of all or most of the eight species currently included as two distinct subgroups within the C. saxicola group was possible only by combining morphological characters and signal from ambiguously aligned regions with the unambiguously aligned ITS sites or when the entire ITS1 and 2 regions were not aligned a priori and included as an integral component of a Bayesian analysis (BAli-Phy). The C. arnoldii subgroup includes C. arnoldii, comprising four subspecies, and the C. saxicola subgroup encompasses seven species. Contrary to the C. saxicola subgroup, monophyly of taxa included within the C. arnoldii subgroup and their relationships could not be resolved with combined ITS and morphological data. Unequivocal morphological synapomorphies for all species except C. arnoldii and C. pusilla are recognized and presented.

In order to test hypotheses about changes in the environment induced by man, including climatic change, ecologists are sampling portions of the environment repeatedly across time. This paper describes a method for testing a space-time interaction in repeated ecological survey data, when there is no replication at the level of individual sampling units (sites). This methodological development is important for the analysis of long-term monitoring data, including systems under anthropogenic influence. In these systems, an interaction may indicate that the spatial structure of community composition has changed in the course of time or that the temporal evolution is not the same at all sites. This paper describes ANOVA models corresponding to the steps leading to a solution to the problem, which is based on the representation of space and time by principal coordinates of neighbor matrices (PCNM eigenfunctions) in the ANOVA. Numerical simulations showed that ANOVA Model 5 was the model of choice for the analysis of the space-time interaction because it always had correct rates of Type I error, and its power was always equal to or higher than those of other possible models of analysis. If the hypothesis of absence of interaction is not rejected, one cannot conclude that a change has occurred in the spatial structure of the response data across time; one should follow the ordinary rules of two-way ANOVA if testing the significance of the main factors is of interest. If the hypothesis of absence of interaction is rejected, one should model the spatial structure of each time period in a separate way. One can also conduct a single test involving a separate model of the spatial structure for each time period. This paper presents two applications to real ecological data.

Ecologists often face the task of studying the association between single species and one or several groups of sites representing habitat types, community types, or other categories. Besides characterizing the ecological preference of the species, the strength of the association usually presents a lot of interest for conservation biology, landscape mapping and management, and natural reserve design, among other applications. The indices most frequently employed to assess these relationships are the phi coefficient of association and the indicator value index (IndVal). We compare these two approaches by putting them into a broader framework of related measures, which includes several new indices. We present permutation tests to assess the statistical significance of species-site group associations and bootstrap methods for obtaining confidence intervals. Correlation measures, such as the phi coefficient, are more context-dependent than indicator values but allow focusing on the preference of the species. In contrast, the two components of an indicator value index directly assess the value of the species as a bioindicator because they can be interpreted as its positive predictive value and sensitivity. Ecologists should select the most appropriate index of association strength according to their objective and then compute confidence intervals to determine the precision of the estimate.

Beals smoothing is a multivariate transformation specially designed for species presence/absence community data containing noise and/or a lot of zeros. This transformation replaces the observed values of the target species by predictions of occurrence on the basis of its co-occurrences with the remaining species. In many applications, the transformed values are used as input for multivariate analyses. As Beals smoothing values provide a sense of "probability of occurrence", they have also been used for inference. However, this transformation can produce spurious results, and it must be used with caution. Here we study the statistical and ecological bases underlying the Beals smoothing function, and the factors that may affect the reliability of transformed values are explored using simulated data sets. Our simulations demonstrate that Beals predictions are unreliable for target species that are not related to the overall ecological structure. Furthermore, the presence of these "random" species may diminish the quality of Beals smoothing values for the remaining species. A statistical test is proposed to determine when observed values can be replaced with Beals smoothing predictions. Two real-data example applications are presented to illustrate the potentially false predictions of Beals smoothing and the necessary checking step performed by the new test.

In a double-blind, cross-over trial, progabide (PGB) and placebo were compared as add-on therapy in 59 patients with moderate to severe epilepsy. Eight patients did not complete the study, 4 because of adverse drug reactions (elevation of liver transaminases, 2; gastritis, 1; and acute psychosis, 1) and 4 because of administrative reasons. Among the remaining 51 patients, seizure frequency was reduced greater than 50% in 18 patients with PGB treatment and in 8 patients with placebo (p less than 0.05). The number of days with seizures was significantly (p = 0.034) reduced during PGB treatment. Both patients' and physicians' preferences at the end of the trial were in favor (p less than 0.01) of PGB. Mild clinical side effects were present in 54.7% of the patients treated with PGB and in 37.7% with placebo. Increase in liver transaminases was observed in 2 patients during the double-blind study and in 1 during the follow-up period. Our data show that PGB, as previously reported, is useful in 30-40% of patients who are not responding completely to other antiepileptic drugs (AEDs). The compound is well tolerated, but liver function must be monitored.