Influence of habitat on nest location and reproductive output of Montagu’s Harriers breeding in natural vegetation

We examined distribution and breeding success of semi-colonial Montagu’s Harriers (Circus pygargus) in relation to habitat in Castellón province (eastern Spain). Breeding areas used by harriers at a 1-km2 scale were characterised by having intermediate percentages of scrub cover, their nesting habitat, and also had intermediate coverage of herbaceous crops and non-irrigated orchards. Out of all habitat variables considered, only the percentage of herbaceous crops within 500 m from individual nests had a positive and significant effect on breeding output of the species, suggesting that this habitat may be efficiently used by harriers to forage. Breeding output was also related to laying date and number of breeding neighbours within 500 m around nests, with pairs laying later and having a higher number of breeding neighbours showing lower fledged brood sizes. Number of neighbours (but not laying date) was positively related to scrub cover within 500 m and to cover of herbaceous crops within 2,000 m. Conservation actions for Montagu’s Harrier in the study area should be aimed at preserving areas of scrub with nearby presence of herbaceous crops or natural grasslands. However, habitat improvement for semi-colonial species such as Montagu’s Harrier may not result in a change of species distribution area, and good habitat areas may remain unoccupied, as social factors like presence of conspecifics play an important role in breeding area selection for these species.

A Finite Element Numerical Algorithm for Modelling and Data Fitting in Complex Systems

Numerical modelling methodologies are important by their application to engineering and scientific problems, because there are processes where analytical mathematical expressions cannot be obtained to model them. When the only available information is a set of experimental values for the variables that determine the state of the system, the modelling problem is equivalent to determining the hyper-surface that best fits the data. This paper presents a methodology based on the Galerkin formulation of the finite elements method to obtain representations of relationships that are defined a priori, between a set of variables: y = z(x1, x2,...., xd). These representations are generated from the values of the variables in the experimental data. The approximation, piecewise, is an element of a Sobolev space and has derivatives defined in a general sense into this space. The using of this approach results in the need of inverting a linear system with a structure that allows a fast solver algorithm. The algorithm can be used in a variety of fields, being a multidisciplinary tool. The validity of the methodology is studied considering two real applications: a problem in hydrodynamics and a problem of engineering related to fluids, heat and transport in an energy generation plant. Also a test of the predictive capacity of the methodology is performed using a cross-validation method.