Showing papers in "Ecological Modelling in 2003"

TL;DR: In this paper, the authors used intrinsic and extrinsic measures of model performance to determine whether optimal models can be identified based on objective intrinsic criteria, without resorting to an independent test data set.

TL;DR: The PaD method was found to be the most useful as it gave the most complete results, followed by the Profile method that gave the contribution profile of the input variables, and the classical stepwise methods gave the poorest results.

TL;DR: A five-step methodology based on multi-scale segmentation and object relationship modelling based on Hierarchical patch dynamics to embrace the challenges of scale and hierarchy in landscapes and has tested two different ways to decompose complex natural environments into focal units.

TL;DR: In this paper, an integrated methodology for the assessment of estuarine trophic status (ASSETS) is described, which may be applied comparatively to rank the eutrophication status of the estuaries and coastal areas, and to address management options.

TL;DR: In this article, two artificial neural networks (ANNs), unsupervised and supervised learning algorithms, were applied to suggest practical approaches for the analysis of ecological data, and the results suggested that methodologies successively using two different neural networks are helpful to understand ecological data through ordination first, and then to predict target variables.

TL;DR: In this article, a mixed regressive-spatial autoregressive (MSA) model was proposed for spatial land use analysis, which is statistically sound in the presence of spatially dependent data, in contrast with the standard linear model.

TL;DR: In this article, the authors introduce the concept of Mahalanobis distance to bioclimatic modeling, and argue that the envelopes defined by this distance can better reflect the principle of central tendency as expressed by niche theory.

TL;DR: In this paper, the authors present an overview of the plant parameters summarised in this overview, i.e., albedo, interception capacity, maximum leaf area index, rooting depth, plant height and stomatal conductance, which are used as data for a wide range of published ecological and hydrological models.

TL;DR: The CO2FIX V.2 model as discussed by the authors is a multi-cohort ecosystem-level model based on carbon accounting of forest stands, including forest biomass, soils and products.

TL;DR: The RIVPACS philosophy is to develop statistical relationships between the fauna and the environmental characteristics of a large set of high quality reference sites which can be used to predict the macroinvertebrate fauna to be expected at any site in the absence of pollution or other environmental stress.

TL;DR: In this paper, an artificial neural network (ANN) is proposed to predict the algal bloom dynamics of the coastal waters of Hong Kong, where the commonly used back-propagation learning algorithm is employed for training the ANN.

TL;DR: CATCHSCAPE as mentioned in this paper is a Multi-Agent System (MAS) that enables us to simulate the whole catchment features as well as farmer's individual decisions, and the biophysical modules simulate the hydrological system with its distributed water balance, irrigation scheme management and crop and vegetation dynamics.

TL;DR: A method by means of which it is possible to produce georeferenced ecological information about the habitat requirements of different species through the combined use of empirical evaluation models and models based on expertise in geographical information system (GIS) environment is developed.

TL;DR: In this paper, a new methodology for global estimation of crop productivity is proposed, which integrates Erosion Productivity Impact Calculator (EPIC) model with Geographic Information System (GIS) and Inference Engine (IE) technique.

TL;DR: In this article, the role of prey refuges in simple predator-prey models other than the original Lotka-Volterra equations has been investigated in a continuous model that satisfies the principle of biomass conversion, and the effects with regard to the local stability of equilibrium points in the first quadrant, equilibrium density values and the long-term persistence of the populations.

TL;DR: In this paper, a nonparametric method and a Bayesian hierarchical modeling method are proposed for the detection of environmental thresholds, based on the reduction of deviance, while the Bayesian method is based on change in the response variable distribution parameters.

TL;DR: In this paper, a coupled physical-biogeochemical model was implemented for Sungo Bay, Shandong Province, China, where bivalve shellfish and kelp are the most important cultivated species.

TL;DR: In this paper, the authors compare BMC and MCMCMCMC and demonstrate that BMC is extremely inefficient in the sense that the prior parameter distribution, from which the BMC sample is drawn, is often a poor surrogate for the posterior parameter distribution.

TL;DR: The authors compare qualitative predictions of press perturbation response from community matrix models with those of a range of numerical simulations on the same models and conclude that system structure is of overriding importance.

TL;DR: In this article, an annual cropping system was compared with two novel perennial plant-based systems designed to address wind erosion and rising water tables in terms of their use of renewable indigenous resource, use of nonrenewable indigenous resources, their purchased inputs of energy and materials, and profitability.

TL;DR: In this paper, the authors integrate the available information to provide a theoretical interpretation of the recent physicochemical and biological changes in the Mondego estuarine ecosystem, which will be further used as basic framework for the development of a structurally dynamic model.

TL;DR: A modelling framework that treats the use of space by animals as a joint function of preference and accessibility and can be used to provide insights about the animals’ preference for different resources and types of movement is developed.

TL;DR: The HOllow-HUMmock (HOHUM) model as discussed by the authors is a dynamic, process-based simulation model simulating biological and physical processes leading to hummocks, hollows, and pools in boreal peatlands.

TL;DR: The animal, landscape and man simulation system (ALMaSS) as discussed by the authors was designed as a predictive tool for answering policy questions regarding the effect of changing landscape structure or management on key animal species in the Danish landscape.

TL;DR: The fuzzy model successfully demonstrated the potentials of exploring “embedded information” by combining data mining techniques with heuristic knowledge to predict algal biomass concentration in the eutrophic Taihu Lake, China.

TL;DR: In this paper, the nitrogen and phosphorus natural removal in the Vantaanjoki basin (Finland) was modelled using the SWAT hydrological model, which simulates the water cycle and the movement and transformations of nutrients.

TL;DR: In this paper, a spatial statistical analysis of lightning-caused fires in the province of Ontario, between 1976 and 1998, was carried out to investigate the spatial pattern of fires, the way they depart from randomness, and the scales at which spatial correlation occurs.

TL;DR: In this paper, a Light Use Efficiency (LUE) model of primary production parameterised with satellite information is proposed for the West African Sahel, where solar radiation is absorbed by plants to provide energy for photosynthesis, while moisture shortfalls control the efficiency of light usage.

TL;DR: In this paper, structural and functional properties of a physiological model (FinnFor) and a statistical model (Motti), developed independently, were analyzed in order to assess whether the former would provide the same prediction capacity as the latter, which is based on a huge body of long-term inventory data.

TL;DR: In this paper, a case study of a coastal dune plant (Scaevola plumieri ) along the coast of South Africa, using a mechanistic model based on summer water balance (SWB), and two correlative models (a profile and a group discrimination technique).