Loading...
4 results
Search Results
Now showing 1 - 4 of 4
- A Cellular Automata Model of Spatio-Temporal Distribution of SpeciesPublication . Bioco, João; Silva, João; Canovas, Fernando; Fazendeiro, PauloCellular automata (CA) are discrete models frequently used in ecological and epidemiological studies due to the capacity to simulate dynamics systems and analyze their behavior. One of the applications of CA in ecology is in the analysis of the spatial distribution of species, where models are created and simulated in order to study the response of ecological systems to different kinds of exogenous or endogenous perturbations. In this study we describe an implementation of a cellular automaton model able to incorporate environmental data collected from different heterogeneous sources. To the user is given the power to produce and analyze different scenarios by combining the available variables at will. Different hypothesis regarding the individual contribution of each environmental variable can be promptly tested. As an illustrative example of the flexibility of our implementation we present a case study where, departing from a general additive model (GAM), validated in the literature, a possible explanation is given for the spatio-temporal distribution of two haplotypes of honeybees along Iberian Peninsula. Environmental data were used to describe every 30x30 second unit grid of the study area (World Geodetic System 1984 WGS84, geographical coordinates). The results of our model are compared and discussed at the light of the real data collected on the terrain. Curiously enough, both in the synthesized model and in the real data, one can observe that the frequency of African haplotypes decreases in a SW-NE trend, while that of west European lineage increases.
- Parameterization of an Agent-Based Model of Spatial Distribution of SpeciesPublication . Bioco, João; Fazendeiro, Paulo; Canovas, Fernando; Prata, PaulaAgent-based models (ABMs) have been widely applied in several fields such as ecology, biology, climate changes, engineering and many other fields. In ABMs approach, the behaviour of a system is determined by the local interactions between its individuals (agents), and the interactions between these individuals with the environment where they exist. Due to its interactions at the individual’s level, ABMs can produce quite realistic results regarding to the models behaviour. Therefore it is necessary to perform several analysis from the point of view of the models parametrization. In this paper we perform a parametric study in ways to analyze the implications of models parameterization in the models output, by implementing an agent-based model to simulate spatial distribution of species in an heterogeneous environment. The models output resulting from several parameters combination are compared and discussed.
- On the Modelling of Species Distribution: Logistic Regression Versus Density Probability FunctionPublication . Bioco, João; Prata, Paula; Canovas, Fernando; Fazendeiro, PauloThe concerns related to climate changes have been gaining attention in the last few years due to the negative impacts on the environment, economy, and society. To better understand and anticipate the effects of climate changes in the distribution of species, several techniques have been adopted comprising models of different complexity. In general, these models apply algorithms and statistical methods capable of predicting in a particular study area, the locations considered suitable for a species to survive and reproduce, given a set of eco-geographical variables that influence species behavior. Logistic regression algorithm and Probability density function are two common methods that can be used to model the species suitability. The former is a representative of a class of models that requires the availability (or imputation) of presence-absence data whereas the latter represents the models that only require presence data. Both approaches are compared regarding the capability to accurately predict the environmental suitability for species. On a different way, the behaviour of the species in the projected environments are analysed by simulating its potential distribution in the projected environment. A case study reporting results from two types of species with economical interest is presented: the strawberry tree (Arbutus unedo) in mainland Portugal, and the Apis mellifera (African Lineage) in the Iberian Peninsula.
- Prediction of the Arbutus unedo colonization time via an agent-based distribution modelPublication . Bioco, João; Prata, Paula; Canovas, Fernando; Fazendeiro, PauloSpecies distribution models (SDMs) have been used to predict the distribution of species in an environment. Usually, this prediction is based on previous species occurrence data. Nowadays, several species are facing climatic changes that impact the way species behave. Global warming has implicated species displacement from their natural habitat to new suitable places. SDMs can be used to anticipate possible impacts of the climatic changes in species distribution, preventing species extinction scenarios. New SDMs approaches are needed to give valuable information that better approximates these models to reality. This paper presents a novel approach to the prediction of species distribution. It starts by using an agent-based model (ABM) to establish an approximate mapping between the geological and the computational times. Afterwards, the implemented ABM can be used to predict the species distribution at different time intervals. The presented case study concerns the distribution of the Arbutus unedo in the Iberian peninsula, a species with relevant socio-economic impact in Portugal. The results show that the measurement of the geological time, supported by the approximate correspondence to the number of epochs of an ABM, can be a valuable tool for the prediction of the species distribution in a changing environmental scenario.