Relevant bibliographies by topics / Landscape ecology Mathematical models

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Landscape ecology Mathematical models'

Author: Grafiati
Published: 11 December 2022
Last updated: 25 January 2023

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Journal articles on the topic "Landscape ecology Mathematical models"

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Gobattoni, Federica, Giuliana Lauro, Roberto Monaco, and Raffaele Pelorosso. "Mathematical Models in Landscape Ecology: Stability Analysis and Numerical Tests." Acta Applicandae Mathematicae 125, no. 1 (2012): 173–92. http://dx.doi.org/10.1007/s10440-012-9786-z.

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Camacho-Aguilar, Elena, Aryeh Warmflash, and David A. Rand. "Quantifying cell transitions in C. elegans with data-fitted landscape models." PLOS Computational Biology 17, no. 6 (2021): e1009034. http://dx.doi.org/10.1371/journal.pcbi.1009034.

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Increasing interest has emerged in new mathematical approaches that simplify the study of complex differentiation processes by formalizing Waddington’s landscape metaphor. However, a rational method to build these landscape models remains an open problem. Here we study vulval development in C. elegans by developing a framework based on Catastrophe Theory (CT) and approximate Bayesian computation (ABC) to build data-fitted landscape models. We first identify the candidate qualitative landscapes, and then use CT to build the simplest model consistent with the data, which we quantitatively fit using ABC. The resulting model suggests that the underlying mechanism is a quantifiable two-step decision controlled by EGF and Notch-Delta signals, where a non-vulval/vulval decision is followed by a bistable transition to the two vulval states. This new model fits a broad set of data and makes several novel predictions.
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BAAKE, ELLEN. "DIPLOID MODELS ON SEQUENCE SPACE." Journal of Biological Systems 03, no. 02 (1995): 343–49. http://dx.doi.org/10.1142/s0218339095000320.

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The “decoupled” version of the selection mutation as adapted to (binary) sequence space is investigated. For diploid analogues of the single-peaked landscape, dominance effects on error thresholds are found both in the deterministic and the stochastic case. For more complicated landscapes, nonlinear oscillations may emerge during the transition to equidistribution.
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Deneu, Benjamin, Maximilien Servajean, Pierre Bonnet, Christophe Botella, François Munoz, and Alexis Joly. "Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment." PLOS Computational Biology 17, no. 4 (2021): e1008856. http://dx.doi.org/10.1371/journal.pcbi.1008856.

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Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models (SDM) and in line with predictions of landscape ecology and island biogeography, CNN could grasp how local landscape structure affects prediction of species occurrence in SDMs. The prediction can thus reflect the signatures of entangled ecological processes. Although previous machine-learning based SDMs can learn complex influences of environmental predictors, they cannot acknowledge the influence of environmental structure in local landscapes (hence denoted “punctual models”). In this study, we applied CNNs to a large dataset of plant occurrences in France (GBIF), on a large taxonomical scale, to predict ranked relative probability of species (by joint learning) to any geographical position. We examined the way local environmental landscapes improve prediction by performing alternative CNN models deprived of information on landscape heterogeneity and structure (“ablation experiments”). We found that the landscape structure around location crucially contributed to improve predictive performance of CNN-SDMs. CNN models can classify the predicted distributions of many species, as other joint modelling approaches, but they further prove efficient in identifying the influence of local environmental landscapes. CNN can then represent signatures of spatially structured environmental drivers. The prediction gain is noticeable for rare species, which open promising perspectives for biodiversity monitoring and conservation strategies. Therefore, the approach is of both theoretical and practical interest. We discuss the way to test hypotheses on the patterns learnt by CNN, which should be essential for further interpretation of the ecological processes at play.
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Doll, Jason C., and Stephen J. Jacquemin. "Bayesian Model Selection in Fisheries Management and Ecology." Journal of Fish and Wildlife Management 10, no. 2 (2019): 691–707. http://dx.doi.org/10.3996/042019-jfwm-024.

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Abstract Researchers often test ecological hypotheses relating to a myriad of questions ranging from assemblage structure, population dynamics, demography, abundance, growth rate, and more using mathematical models that explain trends in data. To aid in the evaluation process when faced with competing hypotheses, we employ statistical methods to evaluate the validity of these multiple hypotheses with the goal of deriving the most robust conclusions possible. In fisheries management and ecology, frequentist methodologies have largely dominated this approach. However, in recent years, researchers have increasingly used Bayesian inference methods to estimate model parameters. Our aim with this perspective is to provide the practicing fisheries ecologist with an accessible introduction to Bayesian model selection. Here we discuss Bayesian inference methods for model selection in the context of fisheries management and ecology with empirical examples to guide researchers in the use of these methods. In this perspective we discuss three methods for selecting among competing models. For comparing two models we discuss Bayes factor and for more complex models we discuss Watanabe–Akaike information criterion and leave-one-out cross-validation. We also describe what kinds of information to report when conducting Bayesian inference. We conclude this review with a discussion of final thoughts about these model selection techniques.
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Moulogianni, Christina. "Comparison of Selected Mathematical Programming Models Used for Sustainable Land and Farm Management." Land 11, no. 8 (2022): 1293. http://dx.doi.org/10.3390/land11081293.

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The aim of this study is to compare three mathematical programing models used for sustainable land and farm management. The sample for the comparison was 219 agricultural holdings participating as beneficiaries of the measure ‘Modernization of agricultural holdings’ in the Rural Development Plan at the Region of Central Macedonia in Greece. Using the crop plan of the agricultural land of these farms the mathematical programming models calculate the optimum solution under different and conflicting goals. The results of the methodologies of Linear Programming (LP), of Positive Mathematical Programming (PMP) and Weighted Goal Programming (WGP), are compared in terms of the proposed agricultural land changes. The sustainability of farms is measured with the use of eleven economic, social, and environmental indicators. Each model has some unique advantages and disadvantages that can enable it to be implemented in particular situations. In the conclusions to this research the characteristics of each model are highlighted.
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França, Luciano Cavalcante de Jesus, Danielle Piuzana Mucida, Reynaldo Campos Santana, Marcelino Santos de Morais, Lucas Rezende Gomide, and Carlos Valdir de Meneses Bateira. "AHP APPROACH APPLIED TO MULTI-CRITERIA DECISIONS IN ENVIRONMENTAL FRAGILITY MAPPING." FLORESTA 50, no. 3 (2020): 1623. http://dx.doi.org/10.5380/rf.v50i3.65146.

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Geographic Information System tools, combined with mathematical methods for complex geospatial scientific investigations, are essential for environmental zoning. Among these tools, environmental fragility models evaluate criteria related to the physical attributes of the landscape to ensure multi-disciplinarity of the information plans used in a study. However, questions are raised on the priority allotted to each criterion or environmental factor within a multi-criteria analysis model. In this sense, the analytic hierarchy process is another mathematical model that is used in decision theory, which sorts criteria hierarchically. This study aims to use the AHP method as a tool to support multi-criteria decision making as applied to environmental fragility mapping, using the Jequitinhonha River Basin, Minas Gerais, Brazil, as a case study. The application of the AHP method provided a hierarchy of five important environmental criteria for the environmental fragility mapping. The use of AHP allowed the modeling of empirical evaluations in mathematically consistent results, to provide better conciseness in geospatial processes. Therefore, it is an adequate method to minimize subjectivity in environmental and territorial planning. It can also help the management of priority zones for conservation, preservation, or ecological restoration.
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Kershenbaum, Arik, Lewi Stone, Burt P. Kotler, and Leon Blaustein. "Predation Risk can Drive Cycles in Zoonotic Disease Prevalence." Israel Journal of Ecology and Evolution 56, no. 3-4 (2010): 281–95. http://dx.doi.org/10.1560/ijee.56.3-4.281.

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The recent increase in human cases of leishmaniasis in northern Israel has been accompanied by dramatic anthropogenic changes in the landscape that affect the behavioral ecology of one of its mammalian reservoirs, the rock hyrax,Procavia capensis.Hyraxes migrate from refuge to refuge, presumably following forage availability, but their migration patterns are strongly affected by the availability and spacing of the rock piles that form their den sites and give them protection from predators. We therefore expect changes in predation risk to influence the ability of hyrax groups to migrate from site to site. We combine mathematical metapopulation models of hyrax behavioral ecology, as well as compartmental models of disease dynamics, to investigate the effect of microhabitat alteration and varying perceived predation risk on disease incidence. Our models indicate that such fine-scale alterations in predation risk can have surprising effects on pathogen prevalence, leading to the emergence of epizootic cycles. Regular (predictable) cycles and chaotic (unpredictable) cycles may occur as predation risk is reduced. Under some conditions, cycles may result from very small changes in predation risk or environmental conditions. Our models show regions of sensitive dependence on environmental and predatory conditions, leading us to predict the possibility of the emergence of chaotic disease cycles as the result of small environmental disturbances.
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Zhao, Jingyang, Maryam Ramin, Vincent Cheng, and George B. Arhonditsis. "Competition patterns among phytoplankton functional groups: How useful are the complex mathematical models?" Acta Oecologica 33, no. 3 (2008): 324–44. http://dx.doi.org/10.1016/j.actao.2008.01.007.

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Srivastava, Malvika, and Joshua L. Payne. "On the incongruence of genotype-phenotype and fitness landscapes." PLOS Computational Biology 18, no. 9 (2022): e1010524. http://dx.doi.org/10.1371/journal.pcbi.1010524.

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The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, implying that genotype-phenotype landscapes with only simple sign epistasis motifs will always give rise to single-peaked fitness landscapes under such selection. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.
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Dissertations / Theses on the topic "Landscape ecology Mathematical models"

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Moore, Cordelia Holly. "Defining and predicting species-environment relationships : understanding the spatial ecology of demersal fish communities." University of Western Australia. Faculty of Natural and Agricultural Sciences, 2009. http://theses.library.uwa.edu.au/adt-WU2010.0002.

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[Truncated abstract] The aim of this research was to define key species-environment relationships to better understand the spatial ecology of demersal fish. To help understand these relationships a combination of multivariate analyses, landscape analysis and species distribution models were employed. Of particular interest was to establish the scale at which these species respond to their environment. With recent high resolution surveying and mapping of the benthos in five of Victoria's Marine National Parks (MNPs), full coverage bathymetry, terrain data and accurate predicted benthic habitat maps were available for each of these parks. This information proved invaluable to this research, providing detailed (1:25,000) benthic environmental data, which facilitated the development and implementation of a very targeted and robust sampling strategy for the demersal fish at Cape Howe MNP. The sampling strategy was designed to provide good spatial coverage of the park and to represent the park's dominant substrate types and benthic communities, whilst also satisfying the assumptions of the statistical and spatial analyses applied. The fish assemblage data was collected using baited remote underwater stereo-video systems (stereo- BRUVS), with a total of 237 one-hour drops collected. Analysis of the video footage identified 77 species belonging to 40 families with a total of 14,449 individual fish recorded. ... This research revealed that the statistical modelling techniques employed provided an accurate means for predicting species distributions. These predicted distributions will allow for more effective management of these species by providing a robust and spatially explicit map of their current distribution enabling the identification and prediction of future changes in these species distributions. This research demonstrated the importance of the benthic environment on the spatial distribution of demersal fish. The results revealed that different species responded to different scales of investigation and that all scales must be ix considered to establish the factors fish are responding to and the strength and nature of this response. Having individual, continuous and spatially explicit environmental measures provided a significant advantage over traditional measures that group environmental and biological factors into 'habitat type'. It enabled better identification of individual factors, or correlates, driving the distribution of demersal fish. The environmental and biological measures were found to be of ecological relevance to the species and the scale of investigation and offered a more informative description of the distributions of the species examined. The use of species distribution modelling provided a robust means for the characterisation of the nature and strength of these relationships. In addition, it enabled species distributions to be predicted accurately across unsampled locations. Outcomes of the project include a greater understanding of how the benthic environment influences the distribution of demersal fish and demonstrates a suite of robust and useful marine species distribution tools that may be used by researcher and managers to understand, monitor, manage and predict marine species distributions.
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Romey, Bernard Timothy. "Modeling Spawning Habitat Potential for Chum (Onchorhynchus keta) and Pink Salmon (O. gorbuscha) in Relation to Landscape Characteristics in Coastal Southeast Alaska." PDXScholar, 2018. https://pdxscholar.library.pdx.edu/open_access_etds/4252.

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In response to the increasing need for ecosystem services throughout the Southeast Alaska region, decision makers are tasked with balancing the need for natural resources with salmon conservation. However, accurate historical and current information on salmonid population abundance, freshwater distribution, and habitat quality are sparse with limited resolution for large portions of this remote and rugged landscape. Here, I created Intrinsic Potential (IP) models for chum and pink salmon to predict the potential for portions of coastal rivers to provide high-quality spawning habitat. I developed IP models for both species from field redd surveys and synthetic habitat variables derived from 1-m resolution digital elevation models. The surveys were performed at 49 study reaches in five coastal drainage basins on the north end of Chichagof Island, Southeast Alaska. I used a spatially balanced random sampling design that included field surveys for redds during two field seasons with contrasting precipitation patterns and disparate adult salmon escapements. The IP models predict probable spawning habitat for both species based on persistent landform characteristics and hydrologic processes that control the formation and distribution of spawning habitat across the landscape. Selection of persistent reach variables for both species IP models was informed by principal component analysis (PCA), resource selection ratios, random forest modeling, and regression models of field and synthetic variable comparisons. I observed primarily one spawning strategy by chum salmon associated with mainstem channels, and two distinct spawning strategies for pink salmon related to small moderate-gradient channels and tributaries, and lower drainage basin mainstem channels. The relationships suggest that chum and pink salmon primarily selected for unconstrained channel types in large-and small-size channels, with chum salmon being more selective toward the larger mainstem channels, and pink salmon selecting for smaller channels and tributaries. The prediction of chum salmon redd presence within a specific reach for both high and low streamflow regimes was explained by channel gradient, floodplain width, and mean annual flow in order of importance. In general, chum salmon redds were observed in larger unconstrained low-gradient floodplain reaches where accumulation of deposited gravels and adequate flow produce habitat heterogeneity suitable for spawning. Pink salmon redd presence for both survey years was explained by channel gradient, reach elevation, and mean annual flow, in order of importance. Specifically, when flows allowed upstream access, spawning pink salmon utilized smaller moderate-gradient channels where substrate size and flows were better suited to their smaller body size. Remotely sensed persistent fish habitat data is valuable information for helping understand fish population distributions across the landscape. These synthetic metrics enabled the identification and evaluation of persistent landscape features as probable predictors of IP. Validation of LiDAR-derived channel characteristics indicated channel lengths measured from the DEM were 12% longer than field measured channel length, primarily for channels wider than 10 meters. Thus, understanding the limitations of the data is important so that decision makers do not unintentionally set unrealistic objectives. This research highlights the utility of using IP models with high resolution remote sensing to expand known distributions and quality of spawning habitat for these two species in Southeast Alaska coastal streams.
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Martin, Yvonne. "Modelling geomorphology in landscape evolution." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0030/NQ27198.pdf.

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Font, Moragón Carme. "Mathematical models for energy and landscape integrated analysis in agroecosystems." Doctoral thesis, Universitat Autònoma de Barcelona, 2016. http://hdl.handle.net/10803/399906.

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Els models matemàtics s'utilitzen per explicar fenòmens naturals. Com que els fenòmens naturals són molt complexes, per tal d'aprofundir en el seu comportament i ser capaç de fer prediccions sobre ells, es necessita passar per un procés de simplificació. En el procés de creació del model, el sistema es tradueix a llenguatge matemàtic que permet l'estudi del sistema des d'un nou punt de vista. En aquesta tesi, es consideren models estadístics per estudiar el comportament dels agroecosistemes a diferents escales espacials. L'objectiu d'aquest treball és estudiar la relació entre fluxos d'energia, canvis de cobertes del sòl, la funcionalitat del paisatge i la biodiversitat que subjau en els agroecosistemes. Per a això, es proposen models basats en tals matèries. Les principals unitats d'anàlisi seran les cobertes del sòl, quan treballem a escala regional, i els usos del sòl, a escala local. En el segon capítol, es presenta un model de pertorbació-complexitat intermèdia (IDC) dels paisatges culturals. Aquest enfocament té com a objectiu avaluar com els diferents nivells de pertorbacions antropogèniques sobre els ecosistemes afecten la capacitat d'acollir la biodiversitat en funció de l'heterogeneïtat d'usos sòl. S'aplica a l'illa de Mallorca, enmig de la zona activa de la biodiversitat mediterrània, a escala regional i de paisatge. El model utilitza la pertorbació exercida pels agricultors que alteren la producció primària neta a través del canvi d'usos del sòl, així com l'eliminació d'una part d'ella, juntament amb l'índex de Shannon-Wiener de la diversitat d'usos del sòl. El model es prova en un disseny experimental a dues escales al llarg de tres punts de temps. La riquesa d'espècies d'aus nidificants i hivernants, preses com a indicador de la biodiversitat, s'utilitza en una anàlisi factorial exploratori. Seguint la idea presentada en el segon capítol, en el tercer capítol es presenta un mètode per descriure la relació entre els indicadors d'heterogeneïtat d'usos del sòl, i l'apropiació humana de la producció primària neta en una regió determinada. Aquestes quantitats són vistes com a funcions del vector de proporcions de les cobertes de sòl, que al seu torn es tracta com un vector aleatori els valors del qual depenen de la unitat de terreny que s'observa. Presentem el mètode suposant, en primer lloc, que el vector de proporcions segueix una distribució uniforme en el símplex. Després, considerem com a punt de partida un conjunt de dades mostals, de manera que primer hem d'obtenir una estimació de la seva distribució de probabilitat teòrica, i en segon lloc, generem una mostra de grans dimensions seguint la distribució estimada. Apliquem aquest procediment a dades de l'illa de Mallorca en tres moments de temps diferents. L'objectiu principal aquí és calcular el valor esperat de la diversitat del paisatge com a funció del nivell d'apropiació humana. Aquesta funció està relacionada amb l'anomenada hipòtesi d'energia i espècies, i amb l'hipòtesi de la Pertorbació Intermèdia. Finalment, el quart capítol està dedicat a tractar els processos interns dels agroecosistemes. Per a aquest propòsit, es proposa un graf que representa el patró de fluxos d'energia en un agroecosistema. Utilitzem aquest graf per calcular el nivell d'emmagatzematge d'energia dins de l'agroecosistema, així com la informació inclosa en aquesta xarxa de fluxos, a escales tant local com de paisatge. Per tant, es proposa un model d'anàlisi integrat d'energia i paisatge (ELIA) que avalua tant la complexitat dels bucles d'energia interna, com la informació continguda en tota la xarxa de fluxos d'energia soci-metabòliques, per tal de correlacionar aquesta interacció d'informació energètica amb l'estructura funcional del paisatge. A l'annex, es suggereix una millora de l'indicador d'informació. ELIA es prova en el Vallès, a la Regió Metropolitana de Barcelona.
Mathematical models are used to better explain natural phenomena. Since natural phenomena are very complex, in order to delve into their behaviour and be able to do predictions over them, a simplification process of such systems is needed. In the process of creating the model, the system is translated into mathematical language that allows the study of the system from a new point of view. In this thesis, statistical models are considered to study the behaviour of agroecosystems at different spatial scales. The aim of this work is to study the relation between energy flows, land cover changes, landscape functionality and the biodiversity that underlies in agroecosystems. For this, models based on such matters are proposed. The main units of analysis will be the land covers, when we work at regional scale, and the land uses, at local scale. In the second chapter, an intermediate disturbance-complexity model (IDC) of cultural landscapes is presented. This approach is aimed at assessing how different levels of anthropogenic disturbance on ecosystems affect the capacity to host biodiversity depending on the land matrix heterogeneity. It is applied to the Mallorca Island, amidst the Mediterranean biodiversity hotspot, at regional and landscape scales. The model uses the disturbance exerted by farmers altering the Net Primary Production (NPP) through land use change, as well as removing a share of it, together with Shannon-Wiener index of land use diversity. The model is tested with a twofold-scalar experimental design of a set of landscape units along three time points. Species richness of breeding and wintering birds, taken as a biodiversity proxy, is used in an exploratory factor analysis. Following the idea presented in the second chapter, in the third chapter we present a method to describe the relation between indicators of the land matrix heterogeneity, and the human appropriation of the net primary production in a given region. These quantities are viewed as functions of the vector of proportions of the different land covers, which is in turn treated as a random vector whose values depend on the particular small terrain cell that is observed. We illustrate the method assuming first that the vector of proportions follows a uniform distribution on the simplex. We then consider as starting point a raw dataset of proportions for each cell, for which we must first obtain an estimate of its theoretical probability distribution, and secondly generate a sample of large size from it. We apply this procedure to real historical data of the Mallorca Island in three different time points. The main goal here is to compute the mean value of the land covers diversity as a function of the level of human appropriation of net primary production. This function is related to the so-called Energy-Species hypothesis and to the Intermediate Disturbance Hypothesis. Finally, fourth chapter is devoted to deal with agroecosystems internal processes. For this purpose, a graph to represent the pattern of energy flows in an agroecosystem is presented. We use this graph model to calculate the level of energy storage within the agroecosystem provided by its ‘internal feedback’, as well as the information embedded in this network of flows, at local and landscape scales. Thus, we propose an Energy-Landscape Integrated Analysis (ELIA) model that assesses both the complexity of internal energy loops, and the information held in the whole network of socio-metabolic energy fluxes, so as to correlate this energy-information interplay with the functional landscape structure. In the annex, an improvement of the information indicator is suggested. ELIA is tested in the Vallès County of the Barcelona Metropolitan Region.
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Ng, Desmond. "Micro-economic evolution of the firm : an organizational ecology perspective." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=27383.

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Selection and adaptation paradigms have been jointly employed in the derivation of a theoretical model of firm evolution. This construct enabled researchers to explore: "why are there so many different kinds of organizations?". In that, evolutionary influences and adaptive firm behaviour were simultaneous forces that shape the survival of organizational forms over time. Such a notion was applied towards a dynamic programming context. This dynamic programming model was translated into a computer simulation such that an empirical representation of firm evolution was depicted.
The results from four computer simulations confirmed the selection and adaptation propositions described in this research. The simulations found evolutionary forces to be significant determinants to differentiating firm survival. While, adaptive firm behaviour only served to prolong organizational survivability with in the confines of the selection forces of the market.
Future organizational research should focus on expanding the dimensions of strategic adaptation, strategic, voluntarism, niche width dynamics, organizational inertia theory and organizational slack. By addressing these areas, a more comprehensive depiction of organizational evolution could be attained.
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Reynolds, Joel Howard. "Multi-criteria assessment of ecological process models using pareto optimization /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/6377.

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Gouhier, Tarik Claude. "The role of disturbance cycles in marine mussel metapopulations /." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=98713.

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In marine environments, the open system (OS) theory, whereby populations are assumed to be well connected through large-scale dispersal, is currently being challenged by studies demonstrating limited dispersal. Using a novel metapopulation framework featuring nonequilibrium within-site disturbance cycles and limited dispersal, I investigate the large-scale response of marine mussel populations to changes in oceanographic productivity. By altering the fecundity parameter, I am able to shift from open to dynamically-coupled systems (DCS), thereby generating predictions that can be used to test the connectivity of marine populations. Within-site disturbance cycles scale-up and drive regional dynamics in both OS and DCS. Fast disturbance cycles induce synchronized oscillations that promote regional extinction risk in response to changes in oceanographic productivity for DCS but not OS. Slow disturbance cycles maintain spatial variability and temporal stability in both OS and DCS. These predictions can be used to test the applicability of OS theories to natural coastal ecosystems.
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Roy, Roger A. "An Application of Landscape Design to Student Academic Success." Fogler Library, University of Maine, 2006. http://www.library.umaine.edu/theses/pdf/RoyRA2006.pdf.

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Huson, Leslie William. "Statistical approaches to sensitivity analysis of mathematical models : applications in ecology." Thesis, Imperial College London, 1985. http://hdl.handle.net/10044/1/37731.

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Meile, Christof D. "An inverse model for reactive transport in biogeochemical systems : application to biologically-enhanced pore water transport (irrigation) in aquatic sediments." Thesis, Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/25816.

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Books on the topic "Landscape ecology Mathematical models"

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Drew, C. Ashton. Predictive species and habitat modeling in landscape ecology: Concepts and applications. Springer, 2011.

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Institut fundamentalʹnykh problem biologii (Rossiĭskai︠a︡ akademii︠a︡ nauk) та Institut ėkologii Volzhskogo basseĭna (Rossiĭskai︠a︡ akademii︠a︡ nauk), ред. Regionalʹnai︠a︡ modelʹ globalʹnykh izmeneniĭ prirodnoĭ sredy. Nauka, 2003.

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1946-, Reynolds James F., and Tenhunen John D. 1946-, eds. Landscape function and disturbance in Arctic tundra. Springer, 1996.

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Ecosystem function in Savannas: Measurement and modeling at landscape to global scales. CRC Press, 2011.

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Long, Donald G. Development of management prescriptions for modeling disturbance regimes and succession in the Interior Columbia River Basin: Draft version. U.S. Department of Agriculture, Forest Service and U.S. Department of the Interior, Bureau of Land Managent, 1997.

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Penelope, Morgan, Running S. W, and Intermountain Research Station (Ogden, Utah), eds. FIRE-BGC--a mechanistic ecological process model for simulating fire succession on coniferous forest landscapes of the northern Rocky Mountains. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.

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Keane, Robert E. FIRE-BGC, a mechanistic ecological process model for simulating fire succession on coniferous forest landscapes of the northern Rocky Mountains. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.

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Keane, Robert E. FIRE-BGC, a mechanistic ecological process model for simulating fire succession on coniferous forest landscapes of the northern Rocky Mountains. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.

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1956-, Swihart Robert K., and Moore Jeffrey E. 1974-, eds. Conserving biodiversity in agricultural landscapes: Model-based planning tools. Purdue University Press, 2004.

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Canham, Charles Draper William, 1954-, Cole Jonathan, and Lauenroth William K, eds. Models in ecosystem science. Princeton University Press, 2003.

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Book chapters on the topic "Landscape ecology Mathematical models"

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Frauenthal, James C. "Analysis of Age-Structure Models." In Mathematical Ecology. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-69888-0_6.

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Urban, Dean L., and David O. Wallin. "Introduction to Markov Models." In Learning Landscape Ecology. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6374-4_8.

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Nisbet, R. M., and W. S. C. Gurney. "The Formulation of Age-Structure Models." In Mathematical Ecology. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-69888-0_5.

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Levin, Simon A. "Population Models and Community Structure in Heterogeneous Environments." In Mathematical Ecology. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-69888-0_12.

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Levin, Simon A. "Random Walk Models of Movement and Their Implications." In Mathematical Ecology. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-69888-0_7.

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Hethcote, Herbert W. "Three Basic Epidemiological Models." In Applied Mathematical Ecology. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-61317-3_5.

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Hethcote, Herbert W., and Simon A. Levin. "Periodicity in Epidemiological Models." In Applied Mathematical Ecology. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-61317-3_8.

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Levin, Simon A. "Models in Ecotoxicology: Methodological Aspects." In Applied Mathematical Ecology. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-61317-3_13.

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Aron, Joan L. "Simple Versus Complex Epidemiological Models." In Applied Mathematical Ecology. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-61317-3_7.

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Farina, Almo. "Principles, theory, and models." In Landscape Ecology in Action. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4082-9_1.

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Conference papers on the topic "Landscape ecology Mathematical models"

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Bratus, A. S., T. Yakushkina, S. Drozhzhin, and I. Samokhin. "Mathematical Models of Evolution for Replicator Systems: Fitness Landscape Adaptation." In Mathematical Biology and Bioinformatics. IMPB RAS - Branch of KIAM RAS, 2018. http://dx.doi.org/10.17537/icmbb18.54.

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Pi, Yajie, Xueyan Song, and Jizhou Sun. "Mathematical Models, GRASP Algorithms and Fitness Landscape Analysis for Aircraft Gate Assignment Problem." In 2014 Tenth International Conference on Computational Intelligence and Security (CIS). IEEE, 2014. http://dx.doi.org/10.1109/cis.2014.14.

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Yedavalli, Rama K., and Nagini Devarakonda. "Qualitative Principles of Ecology and Their Implications in Quantitative Engineering Systems." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2621.

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In this paper, we briefly review some fundamental qualitative features of ecological sign stability and transform these principles of ecology to a set of mathematical results in matrix theory with quantitative information, which is usually encountered in engineering sciences. This type of cross fertilization of ideas of life sciences and engineering sciences is deemed to be highly beneficial to both fields. In particular, we show in this paper what effect the signs of elements of a matrix have on the matrix properties such as eigenvalues and condition number. Similarly, it is also shown that under some assumptions on the magnitudes of the elements, predator-prey phenomenon in ecology renders some special properties like ‘normality’ to matrices. It is also shown that these predator-prey models have better robustness properties when compared to other matrices. The results presented in this paper can assist in the use of ecological system principles to build highly robust engineering systems.
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Mays, Antje, and Oya Y. Rieger. "Legacy Missions in Times of Change: Defining and Shaping Collections in the 21st Century." In Charleston Library Conference. Purdue Univeristy, 2020. http://dx.doi.org/10.5703/1288284317167.

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Despite the rapidly changing information and technology landscape, collections remain at the heart of academic libraries, signifying their enduring importance in providing access to our cultural heritage. Given broader trends in research and the current information ecology of an increasingly networked, distributed, and licensed environment, building collections and developing collection polices is increasingly ambiguous. These trends impact librarians in form of ever-expanding portfolios, diffusion of effort, weakened sense of focus, and a rising sense of persistent yet unmet needs for developing new skills. This paper outlines current research on collection trends and summarizes the interactive exchanges from the 2019 Charleston Conference Lively Session (https://sched.co/UZR5). Through live polling, session participants identified key trends in libraries and collections: Key trends included business models, budget constraints, consortium deals, continued importance of subscribed content, access vs. ownership, digitization of unique local collections, digital humanities, digital scholarship, library publishing projects, growing library investments in Open Access (OA), and collection diversification efforts with a view to equity and social justice. Among emerging library services, data services and digitization ranked highest in importance. The most-cited wish-list items included transformative deals, stronger campus partnerships, more OA projects, reduced copyright barriers in sharing homegrown digitized video content, as well as skill development in Counter 5 and data analysis. Existing physical and digital preservation programs received only lower-middle strength ratings. Among long-established library characteristics, collection policies, subscribed content, interlibrary loan, and consortial borrowing and lending retained enduring value and high rankings in importance. Tensions continue between ownership, borrowing, and access.
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Rasul, Hoshyar, Khuncha Abdalqadir, and Sarko Sleman. "The Role of Green Infrastructure in Achieving Socio-Spatial Dimensions in Housing Sustainability." In مؤتمرات الآداب والعلوم الانسانية والطبيعية. شبكة المؤتمرات العربية, 2021. http://dx.doi.org/10.24897/acn.64.68.29720214.

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Planning sustainable communities is a complex process that addresses the key areas of equitable economic, environmental and social sustainability. Nowadays the sustainable communities became the core objective in the view of building new world facing the multi and various challenges. Socio-spatial dimension represents greenspace networks integration into new development. Protecting and enhancing the existing physical assets are the pillars to achieve this goal. Green infrastructure is a new concept of planning and design that consists primarily of a hybrid hydrological / drainage network, complementing and linking existing green areas with built-in infrastructure that provides ecological functions. Green infrastructure plans apply the basic principles of landscape ecology as well as appropriate solutions for roofing and shading in urban environments, specifically: a multi-scale approach with a clear attention to the pattern, social and spatial relationships, and emphasis on social and environmental interactions. This research focuses on the socio-spatial planning communities in the view point of sustainability, analyzing previous studies, models and applications that illustrate possible spatial configurations of the green infrastructure to support and strengthen social relations with the physical side of the built environment, especially in residential neighbourhoods. The study presents theoretical models to understanding the social sustainability and guidelines for sympathetic the green infrastructure and its impact on achieving socio-spatial sustainability, taking (Sulaimaniyah Heights Residential Complex) in Sulaimaniyah city as a case study of one of the housing complexes that is still under construction, following the analytical quantitative approach methodology. The results show the importance of green infrastructure (GI) to obtain social sustainability through the use of green infrastructure as a tool to achieve socio-spatial sustainability in housing projects in areas with moderate climatic conditions.
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Frolova, Irina Igorevna, Dmitry Olegovich Tailakov, Nikita Konstantinovich Kayurov, et al. "Digital Platform for E&P Assets Business Process Optimization with a Module for Estimation and Optimizing of Portfolio of Investment Projects for Oil and Gas Production. Case Study." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/208155-ms.

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Abstract Due to increase in cost and complexity of oil and gas production processes it becomes necessary to develop a platform for automated analysis of the main business processes of oil and gas assets for the automatic formation of investment projects portfolios for oil and gas production, taking into account the variability of technical and infrastructural characteristics, the mutual influence of objects and profitability indicators. The paper presents a description of platform prototype designed to form an optimized portfolio of investment projects for oil and gas production. The platform was developed using a process ontology, modern optimization tools and up-to-date techniques. The peculiarity of the proposed platform is in the use of a process ontology, which allows to link the life-time processes of objects with each other and throughout the entire time of asset assessment. The platform makes it easy to operate with real objects and their characteristics. The platform is based on the following models: – simulation model - repeats the business processes of the enterprise, indicating bottlenecks and improvement zones for management, it is a set of direct mathematical problems; – optimization model - creates opportunities for multi-criteria analysis, by eliminating manual processing, for modeling and managing various processes, as well as creating a wide range of development options (geological capabilities, geophysical interpretation, etc.). It is a solution to inverse problems with respect to specified criteria related to economic indicators. This paper shows the effect of implementing software based on the digital twin of enterprise processes, implemented as an integrated platform with the ability to connect specialized programs and simulators (SAP, 1C, IPM GAP, Repos, Eclipse, etc.) To calculate the economic indicators (FCF, NPV, PI, DPP) of individual investment projects and the formation, the possibilities of process optimization were taken into account in order to achieve the target indicators of the enterprise. As a result of the optimization, there is an enumeration of the options according to the algorithm and the selection of the most optimal ones, taking into account a variety of technological, landscape and hydrodynamic characteristics. Thus, a high-quality assessment of investment projects and taking into account a variety of characteristics when forming a portfolio of investment projects when forming a strategy for the development of an oil and gas asset is required. The novelty of the work lies in the developed multi-criteria optimization model. As a result of the performed work, the accuracy of calculations of technical and economic indicators and the optimality of the selected project portfolios for a given target function, taking into account the restrictions, implemented on the basis of digital twins of key business processes of oil and gas enterprises, were confirmed.
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