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    About

Ecological Modelling

Elsevier

1975-

ISSN: 0304-3800 (1872-7026)
Ecology - Ecological Modelling
APC costs unknown

Recent articles

1 show abstract
0304-3800 * * 29612737
Publication date: Available online 6 March 2019

Source: Ecological Modelling
Author(s): Tomasz E. Koralewski, John K. Westbrook, William E. Grant, Hsiao-Hsuan Wang


The mechanistic basis for problem-specific, question-driven ecological simulation models often includes general physical phenomena. Although linking general physical environmental process models with custom-written spatially-explicit ecological models appears conceptually straightforward, practical implementation of such structures is often problematic for ecological modellers and may require specific software engineering knowledge. We describe a general coupling framework that introduces an intermediate layer between the two types of models. We used a popular programming language (NetLogo) to implement a spatially-explicit simulation model for insect population growth and migration, and a commonly-used complex atmospheric dispersion model (HYSPLIT) to project air particle (here insect pest) transport, dispersion and deposition. We developed an algorithm that facilitates an ongoing dialogue between these two models. The dialogue takes place along a temporal scale with frequency and duration constrained only by the study objective. Our approach should be readily adaptable to analogous problems.
2 show abstract
0304-3800 * * 29998826
Publication date: Available online 5 April 2019

Source: Ecological Modelling
Author(s): P.J. García Nieto, E. García-Gonzalo, J.R. Alonso Fernández, C. Díaz Muñiz


Algal atypical productivity, also called eutrophication, is a process where the phosphorus content in the water, together with aquatic flora, increases, causing high Chlorophyll levels and affecting the water quality and its possible applications. Therefore, it is important to be able to anticipate such circumstance to avoid subsequent hazards. In this paper, a model that estimates the conditions where an abnormal growth of algae in reservoirs and lakes takes place is built. This method combines artificial bee colony and support vector machines algorithms to predict the eutrophication taking into account physical-chemical and biological data sampled in the Englishmen Lake and posterior analysis in a laboratory. The support vector machines parameters are tuned by means of the artificial bee colony algorithm, improving the accuracy of the procedure. For comparison sake, two other methods have been used to construct additional models, the M5 model tree and multilayer perceptron network. Two objectives are covered by this study: the forecasting of the algal proliferation by means of the model and, the ranking of the relative importance of the independent variables. Indeed, coefficients of determination of 0.92 for the Chlorophyll and 0.90 for the Total phosphorus concentrations were obtained using this hybrid method that optimizes the regression parameters. Furthermore, the results obtained with M5 model tree and multilayer perceptron network techniques were clearly worse. Finally, conclusions of this work are drawn in the final section.
3 show abstract
0304-3800 * * 30031672
Publication date: Available online 5 April 2019

Source: Ecological Modelling
Author(s): J.C. Giménez, L. Diaz-Balteiro, M. Bertomeu


Forest managers have struggled to develop several measures to mitigate the impacts of logging operations on soil erosion. Two measures have consisted in considering slope restrictions and limiting the size of clearcut harvest areas in timber harvest scheduling models by means of adjacency constraints. However, these constraints build on an externally predefined limit on harvest area valid to all stands regardless of their topographic features. Thus, we present a methodology to formulate maximum harvest area constraints for each stand on the basis of its topographic features and hydrological connectivity. Using a grid-based digital elevation model, we first introduce the concept of the “Effective Hydrological Neighborhood” and propose a method to compute it through the analyses of water flow directions and the LS topographic factor of the USLE. Then, we develop a recursive procedure to compute for each stand the maximum harvest area in any single period and in consecutive periods of the planning horizon. Finally, we formulate a set of maximum harvest area constraints for each stand. The methodology is applied to a eucalyptus plantation in northwestern Spain. The constraints can then be considered in strategic timber harvest scheduling models along with other constraints. In this way, the harvest plans derived at this planning level can be compatible with later solutions considering hydrological connectivity concerns at the tactical level.
4 show abstract
0304-3800 * * 30065470
Publication date: Available online 10 April 2019

Source: Ecological Modelling
Author(s): Diana E. LaScala-Gruenewald, Rohan S. Mehta, Yu Liu, Mark W. Denny


Animals must balance their rates of energetic intake and expenditure while foraging. Several mathematical models have been put forward as energetically optimal foraging strategies when the food environment is sparse (i.e., the distance between food patches in the environment is much larger than the distance from which the forager can perceive food). In particular, Lévy walks with a power law exponent approaching 1 are considered optimal for destructive foragers. However, these models have yet to explore the role of sensory perception in foraging success as the distance between food patches approaches the distance from which the forager can perceive food. Here, we used an agent-based modeling approach to address this question. Our results concur that lower values of the power law exponent (i.e. values approaching 1) result in the most food found, but in contrast to previous studies, we note that, in many cases, lower exponents are not optimal when we consider food found per unit distance traveled. For example, higher values of the exponent resulted in comparable or higher foraging success relative to lower values when the forager's range of sensory perception was restricted to an angle ± 30° from its current heading. In addition, we find that sensory perception has a larger effect on foraging success than the power law exponent. These results suggest that a deeper examination of how animals perceive food sources from a distance may affect longstanding assumptions regarding the optimality of Lévy walk foraging patterns, and lend support to the developing theoretical shift towards models that place increasing emphasis on how organisms interact with their environments.
5 show abstract
0304-3800 * * 30125225
Publication date: Available online 18 April 2019

Source: Ecological Modelling
Author(s): Xin Jin, Yanxiang Jin, Donghai Yuan, Xufeng Mao


Land-use/land-cover (LULC) data represent important inputs in hydrologic models. The LULC data can affect modelled watershed hydrologic processes by altering the rates of interception, infiltration, evapotranspiration and groundwater recharge that govern the timing and volume of surface and river runoff. A thorough understanding of the impacts of LULC resolution on hydrologic modelling is thus essential and important. Generally, differences in the resolution of LULC data in hydrologic modelling can result in different interpretation accuracies, LULC classifications and spatial resolutions for one-year LULC datasets; typically, such models only use one-year LULC datasets in the simulation period to simply the calculation process. But how would the model performance change if multiple years of LULC data were input into hydrologic models' To better understand the impacts of LULC resolution on hydrologic modelling, this study input four LULC datasets into the SWAT (Soil and Water Assessment Tool) model and compared the impacts of the LULC datasets on the hydrologic modelling results for a high-elevation, cold and mountainous watershed in Northwest China. The first three datasets describe the LULC in the year 2000 and are based on different interpretation accuracies, LULC classifications and spatial resolutions. The last dataset is the yearly LULC data over a 20-year period. To incorporate the yearly LULC dataset, we modified the HRU (hydrologic response unit) division method and SWAT computational structure. The main findings were as follows. (1) A yearly LULC dataset may result in a higher simulation complexity in the SWAT model because this involves the most LULC patches. (2) If multiple years of LULC data exist, a LULC dataset with smaller time intervals, e.g. yearly is necessary in streamflow modelling in SWAT to get better model performance, the model performance may improve by 2.2%–13.9% compared to one-year LULC datasets. (3) If only one-year LULC datasets exist, we suggest inputting a dataset with a high resolution and remote sensing interpretation accuracy and reduced numbers of LULC classification types into SWAT to improve the hydrologic model performance; with such an approach, the model performance may improve by 1.1%–6.9% compared to other one-year LULC datasets.
6 show abstract
0304-3800 * * 30225774
Publication date: Available online 29 April 2019

Source: Ecological Modelling
Author(s): Melinda K. Ehrich, Lora A. Harris
7 show abstract
0304-3800 * * 30366369
Publication date: 24 July 2019

Source: Ecological Modelling, Volume 404
Author(s): G. De La Fuente, V. Asnaghi, M. Chiantore, S. Thrush, P. Povero, P. Vassallo, M. Petrillo, C. Paoli


There is a strong scientific consensus that coastal marine ecosystems, and in particular the midlittoral zone, at the interface between terrestrial and marine realms, are seriously threatened by anthropogenic impacts, along with the goods and services they provide. Along Mediterranean shallow rocky reefs, brown macroalgae belonging to the Cystoseira genus (e.g. Cystoseira amentacea and Cystoseira compressa) are ecosystem engineers, locally creating a continuous fringe in the midlittoral zone, supporting high biodiversity and productivity and providing ecosystem services. A growing interest in the quantification of ecosystem relevance through their economic value aims at raising public awareness and supporting policy-makers in the process of creating new legal instruments supporting the preservation of biodiversity. In this framework, a methodology for ecological and monetary evaluation of natural capital, based on biophysical accounting and on emergy theory, is applied to the habitats of the upper midlittoral zone located above continuous and non-continuous Cystoseira fringe. The proposed approach is a quantitative measure able to analyse the overall functioning of the system and its efficiency in exploiting available resources. The mean economic value of the habitats in the midlittoral zone assessed through the present study is 1.28 em€/m2. Higher values, but associated with a larger variability, were observed in presence of continuous C. compressa fringe. Conversely, in the presence of a continuous C. amentacea fringe, a noticeable habitat-forming species, lower natural capital values were recorded possibly due to the attractive potential of this species in its understorey rather than in the above habitats, concurrently with a lower variability of the natural capital values (lower scatter), suggesting a deterministic homogeneity effect on the above midlittoral habitats. From this study, emergy analysis is confirmed to represent an effective and operative tool to provide a synthetic monetary assessment of natural capital making complex information easily accessible to different stakeholders, from general public to territorial managers.
8 show abstract
0304-3800 * * 30366370
Publication date: Available online 9 May 2019

Source: Ecological Modelling
Author(s): Q. Canelles, N. Aquilué, A. Duane, L. Brotons


Landscape models are comprehensive tools that allow for an understanding of landscape dynamics and a means of deriving future projections in the context of global change. Vegetation and ecological processes such as growth, death or regeneration are essential components of forest landscape dynamics, but their inclusion in landscape-level modelling frameworks is not straightforward as there is a trade-off between model feasibility, desirable complexity and the inclusion of relevant ecological processes. If models are to project future landscape dynamics, climatic influence on vegetation processes needs to be integrated; however, this usually leads to a major increment in model complexity. Here, a post-fire regeneration model (in terms of tree species) and a growth model (in terms of basal areas) is presented for Mediterranean forests including climate influences on such processes. The model captures vegetation dynamics at the stand level and accounts for post-fire regeneration and vegetation growth at the landscape level, with inclusion of the dynamically influencing effect of climate. The model was calibrated with 7709 inventory data plots and validated with 233 burned plots in the Mediterranean region of Catalonia (NE Spain). Results show that our model is able to accurately predict tree species post-fire regeneration and biomass growth. They also show that integration of climatic information represents a significant improvement on the predictive accuracy of the model. Overall, this study presents a generic approach to extend local vegetation dynamics information to the landscape level; furthermore, allowing the projection of vegetation dynamics under changing climatic conditions.

Graphical abstract






9 show abstract
0304-3800 * * 30401729
Publication date: 24 July 2019

Source: Ecological Modelling, Volume 404
Author(s): Perry J. Williams, William L. Kendall, Mevin B. Hooten


Choices in ecological research and natural resource management require balancing multiple, often competing objectives. Examples include maximizing species persistence in a wildlife conservation context, while minimizing cost, or balancing opposing stakeholder objectives when managing wildlife populations. Multiple-objective optimization (MOO) provides a unifying framework for solving multiple objective problems. Model selection is a critical component of ecological inference and prediction and requires balancing the competing objectives of model fit and model complexity. The tradeoff between model fit and model complexity provides a basis for describing the model-selection problem within the MOO framework. We discuss MOO and two strategies for solving the MOO problem; modeling preferences pre-optimization and post-optimization. Most conventional model selection methods can be formulated as solutions of MOO problems via specification of pre-optimization preferences. We reconcile model selection within the MOO framework. We also consider model selection using post-optimization specification of preferences. That is, by first identifying Pareto optimal solutions, and then selecting among them. We demonstrate concepts with an ecological application of model selection using avian species richness data in the continental United States.
10 show abstract
0304-3800 * * 30401730
Publication date: 24 July 2019

Source: Ecological Modelling, Volume 404
Author(s): Manoj Kumar, Naveen Kalra, Peter Khaiter, N.H. Ravindranath, Varsha Singh, Hukum Singh, Subrat Sharma, Shahryar Rahnamayan


The PhenoPine is a Growing Degree Day (GDD) simulation model that can be used to trace the phenology of pine (Pinus roxburghii) under changing regimes of ambient temperature rise. The PhenoPine was developed using field-based observations for pine – a dominant tree species under the “Chir Pine forests” of Indian Western Himalayan region. Phenological stages of pine have been worked out on the basis of GDD. The GDD was computed assuming zero degree Celsius as base temperature and the accumulated averaged values over different phenological stages for developing phenology of the tree. The model has been built in Fortran Simulation Translator. Initially, the model has been developed to trace the impacts of temperature considering temperature as the major driving force for the phenology, while the lack of data for other forces also made this an obvious choice. Simulation through the PhenoPine can be done to trace the stages of initiation and termination of needle (leaf) formation, litter fall, cone formation; and the longevity of each phases under the changing regime of temperature rise.
11 show abstract
0304-3800 * * 30435194
Publication date: 1 August 2019

Source: Ecological Modelling, Volume 405
Author(s): Nathan R. De Jager, Molly Van Appledorn, Timothy J. Fox, Jason J. Rohweder, Lyle J. Guyon, Andrew R. Meier, Robert J. Cosgriff, Benjamin J. Vandermyde


Simulation models are often used to identify hydrologic regimes suitable for different riparian or floodplain tree species. However, most existing models pay little attention to forest successional processes or other disturbances that may interact with the hydrologic regime of river systems to alter forest dynamics in space and time. In this study, we introduce a flood disturbance module to the LANDIS-II forest succession modelling framework to enable investigations into how inundation interacts with other disturbances and successional processes to alter floodplain forest cover and community dynamics. We illustrate the functionality of the model using a case study with multiple scenarios in the Upper Mississippi River floodplain, USA. We found that model predictions of total forest cover and the abundance of specific forest community types were generally related to uncertainty in the susceptibility of different species and age classes to inundation. By simulation year 100, increases or decreases in total forest cover and forest type distributions were roughly proportional to the initial differences in the susceptibility of species and age classes to inundation. The largest decrease in total forest cover was associated with a scenario that included disturbance by the emerald ash borer (Agrilus planipennis) and when using susceptibility parameters corresponding to the weakest flood tolerance. In contrast, changes in the composition of aboveground biomass were not sensitive to differences in susceptibility, and generally showed shifts toward later successional species with higher shade tolerance and longer lifespans for all scenarios. Our findings suggest that flood inundation interacts with other disturbances (e.g., insect outbreaks) and forest successional processes to alter forest abundance, distribution, and species composition in this system. Our modelling framework should allow for future studies that examine such interactions in other systems, and in the context of alternative hydrologic scenarios and other disturbance regimes.
12 show abstract
0304-3800 * * 30435195
Publication date: 1 August 2019

Source: Ecological Modelling, Volume 405
Author(s): Amelie Schmolke, Steven M. Bartell, Colleen Roy, Nicholas Green, Nika Galic, Richard Brain


The Topeka shiner, a small cyprinid fish, is a seminal example of an endangered aquatic species in the Midwestern USA. Populations and their associated critical habitats may experience potential direct and/or indirect effects from anthropogenic activity. However, potential impacts on fish populations from alterations in the food web are difficult to predict because they are based on complex dynamics of food web interactions. In order to simulate Topeka shiner population dynamics under different food-web scenarios, a hybrid modeling approach was developed by linking an aquatic food web model (comprehensive aquatic systems model, CASMTS) with a species-specific, individual-based population model (TS-IBM). The CASMTS was parameterized and calibrated to represent the waterbody conditions and aquatic species community in a small headwater pool in Iowa, representative of key habitat for the Topeka shiner within its geographical range. In the TS-IBM, life history, growth, and diet are represented and based on data available from the literature for the Topeka shiner and/or surrogate species. The two models are linked by the transfer of daily biomasses of Topeka shiner diet items. We simulated the effects of alterations of the food web on the Topeka shiner populations by systematically reducing the available prey base biomass. Reductions in different food groups had varying impacts on the simulated Topeka shiner populations and were dependent on the species’ preference for detritus consumption. Simulations also included predation and identified predator densities to which Topeka shiner populations were vulnerable. The hybrid model provides a platform for the assessment of potential direct and food-web mediated indirect effects of stressors for the purposes of risk assessment, habitat management, and species recovery plans.

Graphical abstract






13 show abstract
0304-3800 * * 30435196
Publication date: 24 July 2019

Source: Ecological Modelling, Volume 404
Author(s): Ming Sun, Yunzhou Li, Yiping Ren, Yong Chen


Management strategy evaluation (MSE) is an effective tool to evaluate the performance of harvest control rules (HCRs) and alternative management strategies. However, a comprehensive MSE framework advising management is still absent for the severely depleted Gulf of Maine (GoM) cod (Gadus morhua). In the present study, we developed a conceptual MSE framework and conditioned on this stock utilizing stock-specific parameterization. We highlighted the simulation of a few key processes with semi-independent sub-models and accounted for uncertainties from multiple sources. The simulated population dynamics was calibrated and validated against the historical trend in hindcasting. Forecasting simulations were also conducted and validated to examine the effectiveness in the context of uncertainty. Hindcasting results suggested that the calibrated MSE framework could capture the stock dynamics assuming different recruitment dynamics indicated by residuals lower than 5%. Forecasting stochastic runs demonstrated a minor disparity between management effects of fishing-mortality-based and catch-based HCRs when the segregated stock recruitment relationship was adopted with a difference in simulated spawning stock biomass lower than 10%. Additionally, the results were comparable to assessment and projections made in the stock assessment, indicating the robustness of the framework. The framework can potentially help disentangle complex issues related to the mixed fishery, decision-making, and performance evaluation of a monitoring system.

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Author can archive post-print (ie final draft post-refereeing)
Author cannot archive publisher's version/PDF
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  • Author's post-print on author's personal website immediately
  • Author's post-print on open access repository after an embargo period of between 12 months and 48 months
  • Permitted deposit due to Funding Body, Institutional and Governmental policy or mandate, may be required to comply with embargo periods of 12 months to 48 months
  • Author's post-print may be used to update arXiv and RepEC
  • Publisher's version/PDF cannot be used
  • Must link to publisher version with DOI
  • Author's post-print must be released with a Creative Commons Attribution Non-Commercial No Derivatives License
  • Publisher last reviewed on 03/06/2015


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For this journal no deals have been made concerning APC discount

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Impact

Journal Citation Reports (2017)

Impact factor: 2.507
Q2 (Ecology (59/158))

Scopus Journal Metrics (2017)

SJR: 1.084
SNIP: 1.088
Impact (Scopus CiteScore): 0.269
Quartile: Q2
CiteScore percentile: 70%
CiteScore rank: 9 out of 29
Cited by WUR staff: 816 times. (2014-2016)

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