Habitat Use by Nekton along a Stream-Order Gradient in a Louisiana Estuary

We examined patterns of habitat use by fishes and decapod crustaceans in a seemingly pristine tidal stream system that drains into southeastern coastal Louisiana, northern Gulf of Mexico. The study area centered on a relatively unaltered mesohaline saltmarsh nested within more heavily degraded conditions. Monthly sampling (February–November 2004) stratified along a stream-order gradient examined changes in nekton abundance, species richness, and community structure. Analyses were based on a microhabitat approach used to characterize nekton responses to spatial gradients of water depth, temperature, dissolved oxygen, salinity, turbidity, bottom slope, stream width, and distance to mouth. Thirty taxa were identified from 3,757 individuals collected in 82 seine samples. Seven fishes and three decapods constituted >95% of the community structure. Analyses detected the effects of stream order on fish community structure and associated environmental variables. Spatial differences of environmental variables across stream order were attributed to the geomorphology and hydrology of the study area. A factor analysis resolved eight environmental variables into four orthogonal axes that explained 80% of environmental variation. We interpreted factor 1 as a stream-order axis, factor 2 as a morphological axis, factor 3 as a seasonal axis, and factor 4 as a salinity axis. Differences in use of four-dimensional factor space by dominant species reflected habitat selection and species residency status.     

Mapping conservation priorities and connectivity pathways under climate change for tropical ecosystems

Climate change and land use conversion are global threats to biodiversity. Protected areas and biological corridors have been historically implemented as biodiversity conservation measures and suggested as tools within planning frameworks to respond to climate change. However, few applications to national protected areas systems considering climate change in tropical countries exist. Our goal is to define new priority areas for biodiversity conservation and biological corridors within an existing protected areas network. We aim at preserving samples of all biodiversity under climate change and facilitate species dispersal to reduce the vulnerability of biodiversity. The analysis was based on a three step strategy: i) protect representative samples of various levels of terrestrial biodiversity across protected area systems given future redistributions under climate change, ii) identify and protect areas with reduced climate velocities where populations could persist for relatively longer periods, and iii) ensure species dispersal between conservation areas through climatic connectivity pathways. The study was integrated into a participatory planning approach for biodiversity conservation in Costa Rica. Results showed that there should be an increase of 11 % and 5 % on new conservation areas and biological corridors respectively. Our approach integrates climate change into the design of a network of protected areas for tropical ecosystems and can be applied to other biodiversity rich areas to reduce the vulnerability of biodiversity to global warming.     

Configuring the neighbourhood effect in irregular cellular automata based models

Cellular automata (CA) models have been widely employed to simulate urban growth and land use change. In order to represent urban space more realistically, new approaches to CA models have explored the use of vector data instead of traditional regular grids. However, the use of irregular CA-based models brings new challenges as well as opportunities. The most strongly affected factor when using an irregular space is neighbourhood. Although neighbourhood definition in an irregular environment has been reported in the literature, the question of how to model the neighbourhood effect remains largely unexplored. In order to shed light on this question, this paper proposed the use of spatial metrics to characterise and measure the neighbourhood effect in irregular CA-based models. These metrics, originally developed for raster environments, namely the enrichment factor and the neighbourhood index, were adapted and applied in the irregular space employed by the model. Using the results of these metrics, distance-decay functions were calculated to reproduce the push-and-pull effect between the simulated land uses. The outcomes of a total of 55 simulations (5 sets of different distance functions and 11 different neighbourhood definition distances) were compared with observed changes in the study area during the calibration period. Our results demonstrate that the proposed methodology improves the outcomes of the urban growth simulation model tested and could be applied to other irregular CA-based models.     

Construction and assessment of a logistic regression model applied to short-term forecasting of thunderstorms in León (Spain)

Forecasting thunderstorms is one of the most difficult tasks in weather prediction due to the scarce knowledge on how to characterise the mechanisms taking part in the formation of thunderstorms. New tools based upon the objective recognition of appropriate conceptual models have been developed in the last years. A good example of this are the statistical models, based on variables that characterise the preconvective atmospheric conditions.This paper presents the results obtained by applying a short-term forecast model to thunderstorms during the summer periods in León (Spain). This model makes use of the logistic function as a binary forecasting technique determining storm/no storm. The logistic function used was a combination of 15 previously selected meteorological variables. The model has been constructed with the data collected on 152 occasions, and it has been verified on 77 other occasions.The skill scores obtained show that the use of statistical models combining the data, provided by variables characterizing the preconvective conditions and the triggering mechanisms, represent an important step in the difficult task of short-term thunderstorm forecasting.     

Isotopic and Elemental Composition of Marine Macrophytes as Biotracers of Nutrient Recycling Within a Coastal Lagoon in Baja California,Mexico

Nutrient sources of San Quintin Bay, a coastal lagoon affected by coastal upwelling off Baja California (Mexico), were traced using generalized additive (mixed) models (GAMM) to the stable nitrogen isotopic composition, C:N and N content of two co-occurring macrophytes (the macroalgae Ulva spp. and the seagrass Zostera marina). The geochemical tracers followed a spatial trend that partly responded to the long-term nutrient gradient from the ocean towards the interior of the bay. N content in Z. marina and Ulva spp. decreased linearly (while C:N increased) towards the middle section of the bay to concentration levels that indicate potential N limitation for growth. Concurrently midway into the bay (6–9 km), the δ¹⁵N of both macrophytes showed a gradual enrichment in ¹⁵N reflecting progressive denitrification. The spatial pattern of δ¹⁵N and the decrease in C:N of the macrophytes towards the innermost section of the bay indicated an additional nonoceanic source of dissolved nitrogen in this zone. The similarity of the δ¹⁵N pattern of Z. marina and Ulva spp. implies that their δ¹⁵N composition is mainly controlled by the availability of N, in spite of the physiological differences between taxa. A better fit of GAMM to N content and C:N was obtained for Z. marina than for Ulva spp. indicating that the former delineate more steadily and smoothly the influence of upwelling along the spatial gradient. Nonetheless, Ulva spp. may be analyzed in combination with Z. marina to characterize the environmental conditions at the time of sampling.     

A multiresolution strategy for solving landslides using the Particle Finite Element Method

We present an approach for the simulation of landslides using the Particle Finite Element Method of the second generation. In this work, the multiphase nature (granular phase and water) of the phenomenon is considered in a staggered fashion using a single, indeformable Finite Element mesh. A fractional step and a monolithic strategy are used for the water flow and granular phase, respectively. In this way, the maximum accuracy with minimal computational times is reached. The method is completed by adding the interaction terms due to drag and pressure forces, together with a moving mesh strategy to reduce the size of the computational domain.     

Growth pattern and changes in abundance of the endangered bat star Asterina stellifera

The sea star Asterina stellifera has declined during the last decade and is currently abundant only in the southern limit of its former range. We surveyed this population over 5 years to model individual growth and explore the relationship of changes in local abundance with variation in environmental factors and the reproductive status of individuals. Our results show that A. stellifera is a species with slow growth and a relatively long lifespan. Contrary to expectations for temperate species, growth rates were fairly constant through the year and therefore models including seasonal oscillations were inappropriate. The abundance of this species increased significantly from early spring to early summer, likely due to augmented activity and small‐scale aggregation during the reproductive season that affected our estimates of abundance. No significant recruitment occurred during the 5 years studied. The lack of recruitment during long periods and the slow individual growth rates make A. stellifera particularly vulnerable to local extinction. This study was performed prior to the arrival in the study area of the invasive kelp Undaria pinnatifida and side‐gilled sea slug Pleurobranchaea maculata, species that threaten the community structure where A. stellifera lives. Therefore, the information reported here will be essential to assessing the impacts of these exotic species on this sea star population.