Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks.

To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute new seed bank sources for species that are affected by the distance to natural lands and roads.

Should I stay or should I go? A habitat-dependent dispersal kernel improves prediction of movement.

The analysis of animal movement within different landscapes may increase our understanding of how landscape features affect the perceptual range of animals. Perceptual range is linked to movement probability of an animal via a dispersal kernel, the latter being generally considered as spatially invariant but could be spatially affected. We hypothesize that spatial plasticity of an animal's dispersal kernel could greatly modify its distribution in time and space. After radio tracking the movements of walking insects (Cosmopolites sordidus) in banana plantations, we considered the movements of individuals as states of a Markov chain whose transition probabilities depended on the habitat characteristics of current and target locations. Combining a likelihood procedure and pattern-oriented modelling, we tested the hypothesis that dispersal kernel depended on habitat features. Our results were consistent with the concept that animal dispersal kernel depends on habitat features. Recognizing the plasticity of animal movement probabilities will provide insight into landscape-level ecological processes.

Development and evaluation of a new method for sampling and monitoring the symphylid population in pineapple.

BACKGROUND: Symphylids (Hanseniella sp.) are polyphagous soilborne parasites. Today, symphylid populations on pineapple are monitored by observing root symptoms and the presence of symphylids at the bottom of basal leaves. The authors developed a reliable method with a bait and trap device to monitor symphylid populations in pineapple or fallow crops. The spatial distribution of the symphylid populations was evaluated using the variance/mean ratios and spatial analyses based on Moran's and Geary's indices. The method has been tested to monitor symphylid populations at different developmental stages of pineapple. RESULTS: Adding potato baits to the soil samples increased the trapping efficiency of symphylids when compared with 'soil only' and 'bait only' methods. The handling of the samples is also facilitated by the new device. Results showed that the vertical distribution of symphylids may be uniform deeply inside the soil profile under pineapple, up to 50 cm. Results showed that symphylid populations are highly aggregated, showing a spot area about 4-6 m wide for their development. CONCLUSION: The new method allows better and easier evaluation of symphylid populations. It may be very useful in the evaluation of new IPM methods to control symphylids under pineapple.