Showing papers in "Ecological Modelling in 1999"

TL;DR: In this paper, a mini-review of 50 individual-based animal population models shows that the majority of them are driven by pragmatic motivation, which does not explicitly refer to theoretical ecology.

TL;DR: Some of the most important papers of the first workshop about ANNs in ecological modelling are presented, including two algorithms frequently used; one supervised network, the backpropagation algorithm; and one unsupervisednetwork, the Kohonen self-organizing mapping algorithm.

TL;DR: In this paper, the authors developed an analytical solution to a simplified daily integral of Farquhar's model by considering the general diurnal patterns of meteorological variables (radiation, temperature and humidity).

TL;DR: In this paper, the authors assessed the occurrence of a common river bird, the Plumbeous Redstart Rhyacornis fuliginosus, along 180 independent streams in the Indian and Nepali Himalaya.

TL;DR: This paper describes how changes in land use are allocated in the CLUE modelling framework, a methodology to model near future land use changes based upon actual and past land use conditions.

TL;DR: In this paper, a daily water balance model is presented to quantify the intensity and duration of drought in forest stands, where the main aim is to quantify rainfall and evapotranspiration.

TL;DR: In this paper, the sensitivity of one algorithm for prediction of geographic distributions of species from point data to depth of geographic information was tested for three species of North American birds, i.e., Pygmy Nuthatch Sitta pygmaea, Barred Owl Strix varia, and Lark Bunting Calamospiza melanocorys.

TL;DR: The mechanisms of habitat selection in red-winged blackbirds and marsh wrens are determined using neural interpretation diagrams, relevances, and sensitivity analyses and it is suggested that a neural network model that is trained with a data set from a wetland where all the interacting species are present is used.

TL;DR: In this article, the authors applied network analysis to a Halodule wrightii community in Goose Creek Bay, St. Marks National Wildlife Refuge, Florida, USA, during January and February 1994 where they sampled a wide variety of taxa.

TL;DR: In this article, a modified production efficiency model (PEM) was proposed for terrestrial primary production over large areas and demonstrated the utility of PEM for large-scale primary production modeling.

TL;DR: The basic concepts of frequentist and Bayesian techniques for the identification of model parameters and the estimation of model prediction uncertainty are briefly reviewed in this paper, where a simple example with synthetically generated data sets of a model for microbial substrate conversion is used as a didactical tool for analyzing strengths and weaknesses of both techniques in the context of environmental system identification.

TL;DR: In this paper, a hybrid simulation approach to modelling forest ecosystems is provided, and the representation of stand-level net primary production and nutrient cycling in forecast is described. But, the authors do not consider the impact of alternative stand level management scenarios on long-term site productivity.

TL;DR: Fitness measures from unified foraging theory that are theoretically and computationally compatible with individual-based fish models are developed, causing a fish to select habitat that maximizes its expected probability of survival over a specified time horizon.

TL;DR: In this article, a lumped conceptual rainfall runoff model was applied at a daily timestep to 16 small catchments in the Maroondah region of Victoria, Australia.

TL;DR: Data from an enriched estuary in the eastern United States, Chesapeake Bay, were used to train, validate and test the development of a neural network model for estimating primary production of phytoplankton.

TL;DR: In this paper, a comprehensive forest growth model (CenW) is described, which links the flows of carbon, energy, nutrients and water in trees and soil organic matter, and is validated against experimental data obtained for Pinus radiata from the Biology of Forest Growth (BFG) site near Canberra, Australia.

TL;DR: In this paper, a deterministic regression tree analysis model (DISTRIB) and a stochastic migration model (SHIFT) were used to examine potential distributions of ∼66 individual species of eastern US trees under a 2×CO2 climate change scenario.

TL;DR: In this paper, a framework linking an ecosystem process model with a spatial landscape model (LANDIS) was discussed to examine forest species responses to climate warming for a large, heterogeneous landscape in northern Wisconsin, USA.

TL;DR: This paper describes an approach based on a relatively new technique, support vector machines (SVMs), and contrasts this with more established algorithms such as linear spectral mixture models (LSMM) and artificial neural networks (ANN).

TL;DR: In this article, a model for the estimation of lead concentration in grasses using urban descriptors easily accessible and to study the specific effect of each descriptor on lead concentration was proposed.

TL;DR: It is suggested that this model could be used to study mosaic-like patterns in rain forests, installation of slowly dispersing species, speciation hypotheses and landscape scale dynamics of rain forests.

TL;DR: In this paper, the Allee effect is introduced into intraspecific and two-species competitive models and the authors use phase plane analysis and simulation to investigate the dynamics of these models.

TL;DR: Developing structural dynamic models which are models using goal functions to reflect a current change of the properties of the biological components in the models to facilitate the estimation of parameters is discussed.

TL;DR: An overview of lessons learned from studying, applying, and launching of Bayesian decision analysis—influence diagrams and belief networks in particular—in the field of resource and environmental management is made.

TL;DR: The lesson contained in the review is that even with just twelve papers more or less explicitly oriented towards ecological theory, elements of a theory that might emerge from individual-based modelling in the future can already be identified.

TL;DR: In this paper, a comparison of the ability of multiple linear regression (MLR) and artificial neural networks (ANN) to predict fish spatial occupancy and abundance in a mesotrophic reservoir is presented.

TL;DR: In this article, a large series of wildfire records of the Regional Forest Service of Liguria (northern Italy) from 1986 to 1993 was examined for agreement with power-law behavior between frequency of occurrence and size of the burned area.

TL;DR: In this paper, the structural, functional and system-level symptoms of four chemical stresses, acidification, copper, oil and pesticide contamination in freshwater ecosystems were presented, along with a set of comprehensive ecological indicators for assessing the impacts of chemical stress on freshwater ecosystem health.

TL;DR: The comprehensive aquatic systems model (CASM) was adapted for estimating ecological risks posed by toxic chemicals in rivers, lakes, and reservoirs in Quebec, Canada as discussed by the authors, which provides the capability to estimate the probability of changes in the biomass of multiple populations of primary producers and consumers as a function of the concentration of dissolved chemical contaminant.

TL;DR: In this article, the authors used the Century 4.0 process-based ecosystem model to investigate the patterns of net primary productivity (NPP) along a transect across the boreal forests of central Canada and the influence of climate change, CO 2 fertilization and changing fire disturbance regimes on changes in NPP over time.