Predicción de la potencialidad de los bosques esclerófilos españoles mediante redes neuronales artificiales

Holm oak and cork oak forests are between the most important sclerophyllous formations in the Mediterranean Iberia. In order to study their potentiality, an artificial neural network model, with a feedforward BP algorithm, has been applied. The elevation, continentality, insolation, annual rainfall, annual mean temperature, mean temperature of the coldest month and mean temperature of the warmest month are the used bioclimatic variables with a 10 km resolution. The neural networks seem a highly predictive powerful tool. Different patterns in the response of the studied forests have been shown. The holm oak presents a continuous and wide potential simulate range. Meanwhile the cork oak potential area is fragmented and restricted, in accordance with its actual distribution area. The lack of both forests in the eastern and southern warm zones of Iberian Peninsula is the main discrepancy with previous potential vegetation proposals.Encinares y alcornocales son dos de las formaciones esclerófilas más importantes de la Iberia mediterránea. Para conocer cual es su potencialidad en el territorio español se ha empleado un modelo generado mediante redes neuronales artificiales con un algoritmo de retropropagación de errores que conduce la información siempre hacia delante. Las variables bioclimáticas empleadas como predictores son: altitud, continentalidad, insolación, precipitación total, temperatura media anual, temperatura media de las mínimas del mes más frío y temperatura media de las máximas del mes más cálido, con una resolución de 10 km. Las redes neuronales se perfilan como una herramienta de gran poder predictivo. Se aprecian patrones de respuesta diferente para las formaciones estudiadas. Mientras que para la encina se simula un área potencial continua y extensa, para el alcornoque se obtiene un área fragmentada y restringida, que se ajusta bastante a su presencia actual. La principal discrepancia del modelo presentado con esquemas de vegetación potencial anteriores radica en la ausencia de encinares y alcornocales en zonas térmicas del Levante y sur peninsular

Trophic consequences of introduced species: comparative impacts of increased inter-specific versus intra-specific competitive interactions

1. Invasive species can cause substantial ecological impacts on native biodiversity. Whilst ecological theory attempts to explain the processes involved in the trophic integration of invaders into native food webs and their competitive impacts on resident species, results are equivocal. In addition, quantifying the relative strength of impacts from non-native species (inter-specific competition) versus the release of native conspecifics (intra-specific competition) is important but rarely completed. 2. Two model non-native fishes, the globally invasive Cyprinus carpio and Carassius auratus, and the model native fish Tinca tinca, were used in a pond experiment to test how increased intra- and inter-specific competition influenced trophic niches and somatic growth rates. This was complemented by samples collected from three natural fish communities where the model fishes were present. The isotopic niche, calculated using stable isotope data, represented the trophic niche. 3. The pond experiment used additive and substitutive treatments to quantify the trophic niche variation that resulted from intra- and inter-specific competitive interactions. Although the trophic niche sizes of the model species were not significantly altered by any competitive treatment, they all resulted in patterns of inter-specific niche divergence. Increased inter-specific competition caused the trophic niche of T. tinca to shift to a significantly higher trophic position, whereas intra-specific competition caused its position to shift towards elevated 13C. These patterns were independent of impacts on fish growth rates, which were only significantly altered when inter-specific competition was elevated. 4. In the natural fish communities, patterns of trophic niche partitioning between the model fishes was evident, with no niche sharing. Comparison of these results with those of the experiment revealed the most similar results between the two approaches were for the niche partitioning between sympatric T. tinca and C. carpio. 5. These results indicate that trophic niche divergence facilitates the integration of introduced species into food webs, but there are differences in how this manifests between introductions that increase inter- and intra-specific competition. In entirety, these results suggest that the initial ecological response to an introduction appears to be a trophic re-organisation of the food web that minimises the trophic interactions between competing species

Predicting habitat suitability with Machine Learning models: the potential area of Pinus sylvestris L. in the Iberian Peninsula

We present a modelling framework for predicting forest areas. The framework is obtained by integrating a machine learning software suite within the GRASS Geographical Information System (GIS) and by providing additional methods for predictive habitat modelling. Three machine learning techniques (Tree-Based Classification, Neural Networks and Random Forest) are available in parallel for modelling from climatic and topographic variables. Model evaluation and parameter selection are measured by sensitivity-specificity ROC analysis, while the final presence and absence maps are obtained through maximisation of the kappa statistic. The modelling framework is applied at a resolution of 1 km with Iberian subpopulations of Pinus sylvestris L. forests. For this data set, the most accurate algorithm is Breiman`s random forest, an ensemble method which provides automatic combination of tree-classifiers trained on bootstrapped subsamples and randomised variable sets. All models show a potential area of P. sylvestris for the Iberian Peninsula which is larger than the present one, a result corroborated by regional pollen analyses

Evidence of non-stationary relationships between climate and forest responses: Increased sensitivity to climate change in Iberian forests

Climate and forest structure are considered major drivers of forest demography and productivity. However, recent evidence suggests that the relationships between climate and tree growth are generally non-stationary (i.e. non-time stable), and it remains uncertain whether the relationships between climate, forest structure, demography and productivity are stationary or are being altered by recent climatic and structural changes. Here we analysed three surveys from the Spanish Forest Inventory covering c. 30 years of information and we applied mixed and structural equation models to assess temporal trends in forest structure (stand density, basal area, tree size and tree size inequality), forest demography (ingrowth, growth and mortality) and above-ground forest productivity. We also quantified whether the interactive effects of climate and forest structure on forest demography and aboveground forest productivity were stationary over two consecutive time periods. Since the 1980s, density, basal area and tree size increased in Iberian forests, and tree size inequality decreased. In addition, we observed reductions in ingrowth and growth, and increases in mortality. Initial forest structure and water availability mainly modulated the temporal trends in forest structure and demography. The magnitude and direction of the interactive effects of climate and forest structure on forest demography changed over the two time periods analysed indicating non-stationary relationships between climate, forest structure and demography. Above-ground forest productivity increased due to a positive balance between ingrowth, growth and mortality. Despite increasing productivity over time, we observed an aggravation of the negative effects of climate change and increased competition on forest demography, reducing ingrowth and growth, and increasing mortality. Interestingly, our results suggest that the negative effects of climate change on forest demography could be ameliorated through forest management, which has profound implications for forest adaptation to climate change

Adding a third dimension to the edge of a species’ range: altitude and genetic structuring in mountainous landscapes

In addition to the topographical and ecological barriers, other landscape features may also subtly influence the patterns of gene flow and spatial genetic structuring at species’ borders. This paper focuses on the role played by altitudinal gradients that characterize mountainous landscapes. We formulate and test the hypothesis that when the distribution boundaries of plant species intersect mountainous landscapes, altitudinal gradients in ecological conditions may considerably enhance population subdivision and genetic structuring at the regional level. Using amplified fragment length polymorphism markers, we studied genetic diversity and differentiation in a set of 21 peripheral populations of the evergreen shrub Lavandula latifolia Med. (Labiatae) at its southernmost distribution limit in the Betic mountain ranges of southern Spain. Population size and abundance, and within-population genetic diversity, varied predictably with altitude, being highest at middle elevations and declining steadily towards both the upper and lower altitudinal distribution margins. Genetic differentiation tended to follow the opposite trend. These altitudinal patterns result from variation with elevation in the relative influence of gene flow and drift on the distribution of genetic variation. Genetic drift prevails around the upper and lower altitudinal limits, whereas a situation closer to a drift-gene flow equilibrium exists at the center of the altitudinal distribution. Altitudinal variation in the relative influences of gene flow and drift appears as an essential element in the interpretation of regional genetic structuring of L. latifolia at its mountainous distribution edge, and a factor which may influence the evolutionary potential of peripheral populations and the likelihood of local adaptation.Peer reviewe