Isabel Fuentes-Santos

Forest fire spatial pattern analysis in Galicia (NW Spain)

Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years.

Evaluation of self‐thinning models and estimation methods in multilayered sessile animal populations

Self-thinning (ST) models have been widely used in the last decades to describe population dynamics under intraspecific competition in plant and animal communities. Nevertheless, their applicability in animal populations is subjected to the appropriate inclusion of space occupancy and energy requirements. Specifically, the disposition of gregarious sessile animals in complex matrices hampers the application of classical ST models. This paper reviews the self-thinning models, regression methods (central tendency and frontier techniques) and discrimination criteria currently applied for gregarious sessile species through application to the analysis of mussel populations (Mytilus galloprovincialis) grown in suspended culture. In addition, we propose to model the temporal evolution of site occupancy in the stochastic frontier function (SFF). Our results confirm that the number of layers should be included in the classical bidimensional ST model for the analysis of multilayered populations. The estimated parameters obtained by the different fitting techniques depended on the measurement method of the variables in the model. This, together with the proximity between the space and food self-thinning theoretical exponents (SST and FST, respectively) highlights the difficulty in discriminating the competition limiting factor (space/food) from the self-thinning exponent. On the other hand, the SFF provided congruent results for biomass and individual mass analysis, in contrast to the lack of robustness observed for the central tendency regression methods. Furthermore, the SFF approach allowed a dynamic interpretation of the ST process providing insight into the temporal evolution of site occupancy. These results highlight the suitability of the stochastic frontier approach in the analysis of self-thinning dynamics in sessile animal populations.

Solar irradiance dictates settlement timing and intensity of marine mussels

Identifying the environmental factors driving larval settlement processes is crucial to understand the population dynamics of marine invertebrates. This work aims to go a step ahead and predict larval presence and intensity. For this purpose we consider the influence of solar irradiance, wind regime and continental runoff on the settlement processes. For the first time, we conducted a 5-years weekly monitoring of Mytilus galloprovincialis settlement on artificial suspended substrates, which allowed us to search for interannual variability in the settlement patterns. Comparison between the seasonal pattern of larval settlement and solar irradiance, as well as the well-known effect of solar irradiance on water temperature and food availability, suggest that solar irradiance indirectly influences the settlement process, and support the use of this meteorological variable to predict settlement occurrence. Our results show that solar irradiance allows predicting the beginning and end of the settlement cycle a month in advance: Particularly we have observed that solar irradiance during late winter indirectly drives the timing and intensity of the settlement onset, Finally, a functional generalise additive model, which considers the influence of solar irradiance and continental runoff on the settlement process, provides an accurate prediction of settlement intensity a fortnight in advance.

Characterizing individual variability in mussel (Mytilus galloprovincialis) growth and testing its physiological drivers using Functional Data Analysis

Determining the magnitude and causes of intrinsic variability is a main issue in the analysis of bivalve growth. Inter-individual variability in bivalve growth has been attributed to differences in the physiological performance. This hypothesis has been commonly tested comparing the physiological rates of fast and slow growers after size differentiation has occurred. This experimental design may detect a link between growth and physiological performance, but we cannot interpret the posterior physiological performance as a driver for the prior growth variability. Considering these limitations, this work introduces a new methodological framework for the analysis of bivalve growth variability. We have conducted sequential measurements of size and physiological performance (feeding, digestion and metabolic rates) in even-sized mussels growing under homogeneous environmental conditions. This experimental design allows us to distinguish between changes over time within individuals, i.e. growth and trends in the physiological rates, from differences between individuals with respect to a baseline level. In addition, Functional Data Analysis provides powerful tools to summarize all the information obtained in the exhaustive sampling scheme and to test whether differences in the physiological performance enhance growth dispersion. Our results report an increasing dispersion in both size and physiological performance over time. Although mussels grew during the experiment, it is difficult to detect any increasing or decreasing temporal pattern in their feeding, digestion and metabolic rates due to the large inter-individual variability. Comparison between the growth and physiological patterns of mussels with final size above (fast growers) and below (slow growers) the median found that fast growers had larger feeding and digestion rates and lower metabolic expenditures during the experimental culture than mussels with slow growth, which agrees with the hypothesis of a physiological basis for bivalve growth variability.

From classical to nonparametric growth models: towards comprehensive modelling of mussel growth patterns

Understanding biological processes, such as growth, is crucial to development management and sustainability plans for bivalve populations. Von Bertalanffy and Gompertz models have been commonly used to fit bivalve growth. These models assume that individual growth is only determined by size, overlooking the effects of environmental and intrinsic conditions on growth patterns. The comparison between classical models and nonparametric GAM (generalized additive models) fits conducted in this work shows that the latter provide a more realistic approach of mussel growth measured in terms of shell length, and dry weight of hard and soft tissues. GAM fits detected a reduction in growth during the cold season, under unfavourable nutritional conditions. These fits also captured the decoupling between hard and soft tissue growth, widely addressed in the literature but not incorporated in growth models. In addition a GAM fit of condition index allowed us to explain annual changes in resources allocation, identifying the asymptotic growth of shell and the effects of the reproductive cycle on soft tissue fluctuations.