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In the face of global change, declines in environmental quality are of increasing concern, especially in shallow coastal areas, densely populated and commonly affected by nutrient enrichment. The warm temperate Mondego estuary (Western Portugal), in common with many other shallow estuarine areas, is exhibiting increased macroalgalgrowth due to nutrientenrichment. The increase of macroalgal biomass and possible shift of other primary producers resulting from eutrophication, may have profound effects on estuarine trophic chain. The present paper examined the performance of a holistic Stochastic Dynamic Methodology (SDM) in predicting the tendencies of three representative trophic levels as a response to the increase of nutrient concentrations. Therefore, the proposed methodology has been developed by focusing on the interactions between conceptually isolated key-components, such as primary producers (macroalgae and seagrass), some relevant benthic macroinvertebrates, wading birds and changes in local physicochemical conditions. The dynamic model developed was preceded by a conventional multivariate statistical procedure (stepwise multiple regression analysis) performed to discriminate the significant relationships between prevailing biological and environmental variables. Since this statistical analysis is static, the dataset recorded from the field included true gradients of habitat changes.

Information on plant seed dispersal, natural loss dynamics of seeds and germination are critical for understanding natural regeneration mechanisms. The aim of this study was to assess the effect of different forest stand densities on seedfall, seed predation, and seedling germination of two populations of the endangered Spanish black Pine forests located at lower (Central population) and higher elevation near the limit of the species’ range (peripheral population) in the Cuenca Mountains of Central Spain. The seed predation and germination experiment also included a nested site preparation treatment. Seed fall varied significantly between 2006 and 2005 or 2007 in both populations. During the only mast year of 2006, higher seedfall was observed at lower elevation and in higher density stands. Predation rates were influenced by the seed crop since predators consumed more than 75 % of seeds in years with lower production and less than 15 % in a mast year. Seed germination is influenced by forest habitat, stand density and soil scalping. For common habitat types, and in a high seed production year, better seed germination rates were observed in medium and dense stands (25–30 and 35–40 m2 ha−1, respectively, in terms of basal area). No statistical difference in seed germination rate was found for Spanish black pine forest at its ecological distribution limit between lower and higher densities (15–20 and 35–40 m2 ha−1, in terms of basal area). In both sites, closed stands with soil scalping exhibited higher germination rates.

In this research work, we specifically address post-dispersal Spanish black pine (Pinus nigra Arn. ssp salzmannii) seed predation at two different locations, one being the most common and representative location for the species and the other located on areas at their ecological limit of distribution in Cuenca Mountain (Spain). A modelling approach was employed to analyze the effect of stand and site characteristics and climate variables on the post-dispersal predation process. Each predator group (ants, rodents and birds) was evaluated by excluding the other two with different experimental devices. Our study demonstrates that the percent of removal was related with the seed rain patterns being lower in the high seed rain year of 2006 (mean ± se 11.15 ± 3.7% of removed seeds) than in the low seed rain years of 2005 and 2007 (81.71 ± 6.0% and 87.29 ± 6.6% of removed seeds respectively). In high seed production years, birds were the most important predators and rodents were the less important predator group in both Los Palancares y Agregados and Ensanche de Las Majadas. No conclusion can be obtained in low seed production years due to the high seed removal percentage by all predator groups. Experimental site and overstory density were no significant with respect to seed predation. Modelling approach show that the seed removal percentage is influenced by seed production year (MastY) a temporal effect within the year, measured by the day variable (Day) and a climatic variable (accumulated averaged maximum air temperatures 20 days before survey date, AaMAT). Further developments include the construction of stochastic models to predict the effects of climate-related variables or microhabitat characteristics on seed losses, contributing to reduce uncertainty in post-dispersal Spanish black pine seed predation dynamics and to provide credible tools to decision-makers and forest managers.Key words: mast year; post-dispersal seed predation; Pinus nigra; Mediterranean region. Resumen Modelización de predación post-dispersión de semillas de pino laricio en el Centro-este de EspañaEl presente trabajo de investigación se centra en la predación post-dispersión acontecida en dos áreas forestales, una localizada en la zona de distribución característica del pino laricio (Pinus nigra Arn ssp salzmannii) y otra en su límite ecológico de distribución dentro de la Serranía de Cuenca (España). El efecto que sobre la predación post-dispersión tienen la densidad arbórea, diferentes variables climáticas y varias características de cada masa forestal fue evaluado mediante la creación de diferentes modelos. Cada grupo de predadores (hormigas, ratones y pájaros) fue analizado por exclusión de los otros dos mediante diferentes dispositivos experimentales. Nuestro estudio demuestra que el porcentaje de semilla predada estuvo relacionado con la lluvia de semillas, siendo menor en 2006, año de abundante producción (media ± estandar error: 11.15 ± 3.7% de semillas predadas) que en 2005 y 2007, años de escasa producción de semilla (81.71 ...

Ecological indicatorsBenthic macroinvertebrates Biological metricsStochastic-dynamic methodology a b s t r a c tAs an improvement of a previous work [Cabecinha, E., Cortes, R., Cabral, J.A., 2004. Performance of a stochastic-dynamic modelling methodology for running waters ecological assessment. Ecol. Modell. 175,[303][304][305][306][307][308][309][310][311][312][313][314][315][316][317], the present paper examined the applicability of a holistic stochastic-dynamic methodology (StDM) in predicting the tendencies of benthic macroinvertebrate metrics from mountain streams facing expected scenarios either: (1) of pollution increase due to the agricultural intensification; or (2) of farming activity abandonment becoming less pollutant as a non-point source. The StDM is a sequential modelling process developed in order to predict the ecological status of changed ecosystems, from which management strategies can be designed. These procedures focus on the interactions between conceptually isolated key-components, such as some relevant trophic and taxonomic metrics and changes in local environmental conditions. The dataset recorded from the field included true gradients of environmental changes. The samples of aquatic macroinvertebrate, environmental and physical-chemical data were collected from four watersheds of mountain rivers in Northeast Portugal, between 1983 and 1985. The dynamic model developed was preceded by a conventional multivariate statistical procedure performed to discriminate the significant relationships between the selected components of the studied watersheds. The model validation was based on independent data from a watershed not included in the model construction. Overall, the simulation results are encouraging since they seem to demonstrate the StDM reliability in capturing the stochastic environmental dynamics of the studied aquatic ecosystems facing agricultural scenarios that will characterize the region, namely by predicting credible behavioural patterns for the selected metrics.

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This research was aimed to assess the spatial and temporal trends in the zooplankton community of Aguieira reservoir at the Mondego catchment (Iberian Peninsula, Portugal) in response to some environmental variables. A total of 24 zooplankton as well as water samples were collected in the months of March (spring), May (early summer), September (late summer) and December (winter) of 2010 and 2011. The data from these samples was obtained by the Descriptive (range, percentage) and multivariate statistics (Non-metric Dimensional Scaling (n-MDS), Bray-Curtis distance,

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