Spatial modelling Research Papers - Academia.edu (original) (raw)

In the boreal forest, fire, insects, and logging all affect spatial patterns in forest age and species composition. In turn, spatial legacies in age and composition can facilitate or constrain further disturbances and have important consequences for forest spatial structure and sustainability. However, the complex three-way interactions among fire, insects, and logging and their combined effects on forest spatial structure have seldom been investigated. We used a spatially explicit landscape simulation model to examine these interactions. Specifically, we investigated how the amount and the spatial scale of logging (cutblock size) in combination with succession, fire, and spruce budworm outbreaks affect area burned and area defoliated. Simulations included 30 replicates of 300 years for each of 19 different disturbance scenarios. More disturbances increased both the fragmentation and the proportion of coniferous species and imposed additional constraints on the extent of each disturbance. We also found that harvesting legacies affect fire and budworm differently due to differences in forest types consumed by each disturbance. Contrary to expectation, budworm defoliation did not affect area burned at the temporal scales studied and neither amount of logging nor cutblock size influenced defoliation extent. Logging increased fire size through conversion of more of the landscape to early seral, highly flammable forest types. Although logging increased the amount of budworm host species, spruce budworm caused mortality was reduced due to reductions in forest age. In general, we found that spatial legacies do not influence all disturbances equally and the duration of a spatial legacy is limited when multiple disturbances are present. Further information on post-disturbance succession is still needed to refine our understanding of long-term disturbance interactions.

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- Biological Sciences, Environmental Sciences, Spatial modelling, Forest Management

In the last five decades for which tuna fishing data are available, the interannual ENSO signal (SOI) and the related Pacific Decadal Oscillation (PDO) suggest two different regimes characterized by higher intensity and frequency of either El Niño or La Niña events. Recent estimates from a statistical population dynamics model (MULTIFAN-CL) suggest that recruitment of three tuna species in the Pacific are correlated with these climate indices. While tropical tuna species like skipjack (Katsuwonus pelamis) and yellowfin (Thunnus albacares) had higher recruitments during El Niñ o events, the subtropical albacore species (Thunnus alalunga) showed the opposite pattern with low recruitment during El Niñ o and high recruitment during La Niñ a. The potential explanatory mechanisms for such relationships between recruitment and climate are investigated with a spatial environmental population model (SEPODYM). The model is a two-dimensional coupled physical-biological interaction model at the ocean basin scale, and contains environmental and spatial components used to constrain the movement and the recruitment of tuna. Input datasets for the model are sea surface temperature, oceanic currents and new primary production that are simulated fields from a three-dimensional coupled physical-biogeochemical model. The hypothesis that the spatial dynamics of temperature, currents (advection), food availability and predation constrain tuna recruitment is evaluated with an application of SEPODYM to skipjack. Simulation results showed that this hypothesis can reproduce fluctuations in the population that are similar to those estimated from the statistical model.

- by Patrick Lehodey
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- Oceanography, Climate, Sea surface temperature, Spatial modelling

To achieve the goal of poverty reduction, as encapsulated within the Millennium Development Goals, the collection, analysis, and use of geographic information as it relates to the multidimensionality of poverty offers a starting point. The spatial handling of poverty is an emerging paradigm for which researches on the spatial modelling of poverty are required. Attempting to contribute to a better understanding of poverty mapping, this paper examines GIS suitability for use in poverty application areas. GIS analysis functions most appropriate for use in specific poverty mapping tasks are examined. The uses are identified as data integration of socio-economic, environmental, cultural data, etc.; delineation of areas lying within a specified threshold distance from selected features or places; deriving further data from spatial analysis for multivariate analysis of poverty; deriving straight-line and network distances; visualisation and presentation of the results of poverty analysis. ...

- by Felicia Akinyemi
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- Spatial Analysis, Spatial modelling, Poverty Reduction, Digital mapping

An estimated 80% of all information has a spatial reference. Information about households as well as environmental data can be linked to precise locations in the real world. This offers benefits for combining different datasets via the spatial location and, furthermore, spatial indicators such as distance and accessibility can be included in analyses and models. HSpatial patterns of real-world social

- by Peter Hintze and +1
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- Spatial Analysis, Spatial modelling, University of Southern California, Social Science

This study aims to predict the spatial distribution of tropical deforestation. Landsat images dated 1974Landsat images dated , 1986Landsat images dated and 1991 were classified in order to generate digital deforestation maps which locate deforestation and forest persistence areas. The deforestation maps were overlaid with various spatial variables such as the proximity to roads and to settlements, forest fragmentation, elevation, slope and soil type to determine the relationship between deforestation and these explanatory variables. A multi-layer perceptron was trained in order to estimate the propensity to deforestation as a function of the explanatory variables and was used to develop deforestation risk assessment maps. The comparison of risk assessment map and actual deforestation indicates that the model was able to classify correctly 69% of the grid cells, for two categories: forest persistence versus deforestation. Artificial neural networks approach was found to have a great potential to predict land cover changes because it permits to develop complex, non-linear models.

- by Henri Puig
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- Risk assessment, Multidisciplinary, Spatial modelling, Tropical deforestation

In less developed countries the recent high rates of urban expansion are often associated with the emergence of informal settlements that may exaggerate social and environmental problems and impede sustainable development. An enhanced understanding of informal development may, therefore, be a key for future success in its effective management. This paper explores possibilities offered by progress in Geo-Information Science and spatial modelling to improve understanding of informal settlements development through comprehensive spatio-temporal analyses. First, it investigates spatial and temporal patterns of the growth of the informal settlements in Sancaktepe district of Istanbul between 1990 and 2005. Second, using a logistic regression model an analysis of the driving forces of informal development and prediction of probable locations of new informal settlements are performed. A list of spatial factors that are correlated to informal development is compiled and used to build six logistic regression models for different time steps between 1990 and 2005. Population density, slope, and proportion of informal settlements in the neighbourhood were found to be the main predictors influencing spatial development of informal settlements during the study period. The performance of the models is evaluated and validated to identify those which best explain the informal development in the study area. As a result, three models built for 1990-1995 and 1995-2000 were selected to generate probability maps of informal settlements development showing the likelihood for each location to be informally developed in the future.

- by Olena Dubovyk and +1
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- Management, Decision Making, Sustainable Development, Modeling

Metropolisation process brings numerous benefits to the quality of urban life and environment but at the same time leads to problems such as uncontrolled development, urban sprawl, congestion and the increasing cost of public services to cater for new infrastructure. Apart from that socio-economic disparity between regions becomes more significant, compounded by increasing rate urban poverty and the risk of social exclusion. Thus, the activities of controlling and monitoring urban development are crucial. The understanding of the urban system that promotes urban growth is also imperative for the purpose of policy making, formulating development strategies as well as development plans preparation. Apparently, the dynamic nature of planning and monitoring of development such as in Klang Valley, the fastest growing region in Malaysia, necessitates a 'tool' for continuous monitoring, evaluation and analysis of current environment as well as assessing the capacity for future development. As such, the development of a comprehensive database and GIS-based planning application under the project named "Application of Geographical Information System for Klang Valley Region (AGISwlk)" was initiated in 1995. The implementation of AGISwlk had been directed toward organisation of the system to facilitate immediate query and analysis, monitoring of development planning as well as spatial modelling. The project had since undergone intensive enhancement in its database structure, data quantity and quality, analysis approach and techniques as well as system customisation and integration to include the ability to provide alternatives in development scenarios. The application was further enhanced to include the development of AGISwlk web-based GIS application and establishment of the Integrated Land use Assessment (ILA) model. This paper will discuss the development, organisation and application of GIS for urban metropolitan management of Klang Valley Region, Malaysia.

- by Ahmad Nazri
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- Social Exclusion, Urban Poverty, Urban Development, Urban Sprawl
- by Mesfin Mergia
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- Spatial modelling, Water scarcity, Virtual Water and Water Footprint

We analyze scientific literature that report tools to spatially model ecosystem services (ES). In the 65 articles reviewed, the most used model starting in 2001 was SWAT and starting in 2009 the most commonly used was InVEST. Eighty percent of the scientific articles have been published from 2010 to 2015 suggesting that spatial modeling of ES is an emergent research field. Only 4 of the 9 tools encountered in our review are backed by papers, the others only offer grey literature. The spatial modeling of ES is mainly done in the U.S.A. and China, and the most frequently evaluated ES are related to hydrological services (water provision and quality treatment), climate regulation and soil formation. Most of the studies are done along hydrological basins, at different spatial scales and based upon different map resolution ranging from 20 to 900 m. With concern, we observe the lack of validation of the spatial models and the tools' lack of integrated validation modules. As long as the tools used to spatially model ecosystem services continue to be used as black boxes, the models they generate will suffer from a high degree of uncertainty and will not be reliable for decision making purposes.

Modelling of land use changes as a function of its biophysical and socio-economic driving forces provides insights into the extent and location of land use changes and its effects. The CLUE modelling framework is a methodology to model near future land use changes based upon actual and past land use conditions. This paper describes how changes in land use are allocated in the model. A statistical analysis of the quantitative relationships between the actual land use distribution and (potential) driving forces or proxies of these forces underlies the allocation procedure. Based upon thus derived multiple regression equations, areas with potential for increase or decrease in cover percentage of a certain land use type are identified. Actual allocation is modified by autonomous developments and competition between land use types. A multi-scale approach is followed to account for the scale dependencies of driving factors of land use change. This approach provides a balance between bottom-up effects as result of local conditions and top-down effects as result of changes at national and regional scales. The modelling approach is illustrated with examples of scenario simulations of land use change in Ecuador.

- by K. Kok
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- Statistical Analysis, Multidisciplinary, Ecological Modelling, Land Use Change

Since its development in the early 1980s, the mass-balance approach incorporated in the Ecopath software has been widely used for constructing food-web models of marine and other ecosystems. Generalizations on the structure and functioning of such ecosystems, relevant to the issue of fisheries impacts, have been developed and these have affected the evolution of the Ecopath approach. Thus, the description of the average state of an ecosystem, using Ecopath proper, now serves to parametrize systems of coupled difference and differential equations, which are used to depict changes in biomasses and trophic interactions in time (Ecosim) and space (Ecospace). The outcomes of these simulations can then be used to modify the initial parametrization, and the simulations are rerun until external validation is achieved. This reconceptualization of the Ecopath approach as an iterative process, which helps address issues of structural uncertainty, does not increase its input requirements markedly. Rather, it has become possible, through a Bayesian resampling routine, to explicitly consider the numerical uncertainty associated with these inputs. We present the key features of the reconceptualized approach, and two indices based thereon for quantifying the ecosystem impacts of fisheries. We conclude with a brief discussion of its limitations, both present and intrinsic. 2000 International Council for the Exploration of the Sea

- by Villy Christensen
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- Multidisciplinary, Protein Structure and Function, Food web, Spatial modelling

Temperature is a key determinant of environmental suitability for transmission of human malaria, modulating endemicity in some regions and preventing transmission in others. The spatial modelling of malaria endemicity has become increasingly sophisticated and is now central to the global scale planning, implementation, and monitoring of disease control and regional efforts towards elimination, but existing efforts to model the constraints of temperature on the malaria landscape at these scales have been simplistic. Here, we define an analytical framework to model these constraints appropriately at fine spatial and temporal resolutions, providing a detailed dynamic description that can enhance large scale malaria cartography as a decision-support tool in public health. We defined a dynamic biological model that incorporated the principal mechanisms of temperature dependency in the malaria transmission cycle and used it with fine spatial and temporal resolution temperature data to eva...

- by Anand Patil
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- Geography, Time Series, Public Domain, Medical Microbiology

The paper shows spatial estimation of soil loss applying USLE equation in the area of Kolubara district. Apart from the erosion factor and vegetative cover factor, soil erodibility (K factor) is a key parameter for soil erosion modelling. The erodibility factor in the area of Kolubara district was calculated using the Wishmaier and Smith method. The land in the study area is mainly used for agriculture and C factor was determined by Corine Land Cover 2000. The objective of this study was to assess the applicability of a simple methodology, based on the application of USLE model, to determine the erosion intensity of certain soil types. In the area of Kolubara district the most common soil category is the one not threatened by water erosion covering 53.9% of the total territory. 15.6% is low threatened, 14.7 % moderately threatened, 9.51% is highly threaten and very high threatened is 6.23% of the total territory. Compared to the area they cover, extremely endangered soils are Haplic Cambisol (Dystric), Haplic Cambisol (Eutric, Skeletic) and Haplic Cambisol (Eutric).

- by Snezana Belanovic and +1
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- Soil Science, Erosion, Spatial modelling, Soil Type

A new paradigm has emerged for management of coral reefs in an era of changing climate – managing for resilience. A fundamental need for such management to be effective is our ability to measure and map coral reef resilience. We review the resilience concept and factors that may make a coral reef more or less resilient to climate-driven impacts, and focus on recent advances in a trio of technologies: remote sensing, spatial distribution modeling, and ecosystem simulation; that promise to improve our ability to quantify coral reef resilience across reefs. Remote sensing allows direct mapping of several ecosystem variables that influence reef resilience, including coral and algal cover, as well as a range of coral reef stressors, as exemplified by three case studies. Spatial distribution modeling allows exploitation of statistical relationships between mappable environmental variables and factors that influence resilience but which cannot be mapped directly, such as herbivore biomass. Ecosystem simulation modeling allows predictions to be made for the trajectories of reef ecosystems, given their initial state, interactions between ecosystem components, and a realistic current and future disturbance regime. Together, these technologies have the potential to allow production of coral reef resilience maps. We conclude with a fourth case study that illustrates
integration of resilience maps into a multi-objective decision support framework. Implementation of the managing for resilience paradigm is still in its infancy, but the rapidly advancing technologies reviewed here can provide the resilience maps needed for its successful operationalization.

- by Simon J. Pittman
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- Marine Ecology, Coral Reef Ecosystems, Coral Reefs, Statistical machine learning

Reaction–diffusion systems often play an important role in systems biology when developmental processes are involved. Traditional methods of modelling and simulating such systems require substantial prior knowledge of mathematics and/or simulation algorithms. Such skills may impose a challenge for biologists, when they are not equally well-trained in mathematics and computer science. Coloured Petri nets as a high-level and graphical language offer an attractive alternative, which is easily approachable. In this paper, we investigate a coloured Petri net framework integrating deterministic, stochastic and hybrid modelling formalisms and corresponding simulation algorithms for the modelling and simulation of reaction–diffusion processes that may be closely coupled with signalling pathways, metabolic reactions and/or gene expression. Such systems often manifest multiscaleness in time, space and/or concentration. We introduce our approach by means of some basic diffusion scenarios, and test it against an established case study, the Brusselator model.

- by Mary-Ann Blätke
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- Petri Nets, Spatial modelling, Reaction-Diffusion Systems, Coloured Petri Nets

Geometallurgy is an emerging, cross-disciplinary field that integrates spatial models of rock properties with time-based outcomes of mining and treatment processes. Geometallurgical variables include any rock property that has a positive or negative effect on the business. Some of the more critical geometallurgical variables include recovery, grindability, throughput, power consumption, mineralogy and content of deleterious materials. These variables drive project

- by John Vann
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- Spatial modelling, Power Consumption, Sample Selection, Data Model

Commuter preferences for transit service quality are of great importance to transit service providers and regulatory agencies. The point of view of potential passengers is fundamental for evaluating transit service quality as they are envisaged to be the real consumers of the planned services and can therefore be considered the most suitable judges. A stated preference survey of daily commuters to the central business district (CBD) in the city of Dar-es-Salaam, Tanzania, was carried out to elicit preferences towards the proposed Dar Rapid Transit (DART) service. Preferences towards the proposed DART service are considered to vary based on the residential location of the potential users. These preferences are evaluated on the attributes travel time, fare and comfort. A binary logit model was applied to establish utility functions that were analysed spatially in a GIS, where a utility value was computed for each spatial unit. This paper accordingly analyses spatial variation of transit service quality preferences for the proposed DART service using geo-spatial techniques. The study uses a scenario-based approach to evaluate the effect of the proposed DART service by comparing the 'without DART' scenario, a case representing the existing public transport (daladala), and a 'DART' scenario, representing the future proposed DART system. The results indicate that the proposed DART attributes considered in the study have a significant effect on DART service quality. The results further reveal that utility values are significantly varying spatially, particularly dependent upon distance to CBD. Comfort is the most important attribute in zones up to 5 km from the CBD, travel fare is more important in zones between 5 and 15 km from the CBD, while travel time is more important in zones beyond 15 km distance from the CBD. The overall results indicate that the DART is likely to be more attractive than the existing public transport system.

- by Mark Zuidgeest
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- Human Geography, Public Transport, Transport Geography, Service Quality

Let {(Y i , X i ), i ∈ Z N } be a stationary real-valued (d+1)-dimensional spatial processes. Denote by x → q p (x), p ∈ (0, 1), x ∈ R d , the spatial quantile regression function of order p, characterized by P{Y i ≤ q p (x)|X i = x} = p.... more

- by Keming Yu
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- Econometrics, Statistics, Time Series, Quantile Regression

and sharing with colleagues.

- by F. Patrick Graz and +1
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- Grazing and Range Management, Spatial modelling

To forecast resource and fishery responses to artificial reefs deployed within no-take marine protected areas, we discuss an application of E, a policy evaluation tool based on spatially explicit simulation of ecosystem dynamics. We analyse a recent initiative to establish human-made reefs inside Marine Special Areas in Hong Kong. Simulations commence with a static mass-balanced model of trophic flows among he functional groups of an ecosystem (E), which is then used to structure dynamic simulations of the biomass fluxes in response to fishing (E). Spatial modelling is achieved through definition of dispersion, foraging, and predator avoidance parameters for each group in relation to a range of defined habitats (E). The ecosystem model comprised 27 functional groups and 7 sectors of the Hong Kong fishery, which were assumed to increase their catching power by 3% year 1. Seven fishery sectors and gear types are defined, and their operations are simulated spatially to maximize operating profit within the areas where they are allowed to fish. Parameters for E, E, fishery, and habitats were obtained from recent surveys and assessments. Additional parameter values were obtained from meta-analyses and other literature on fishes of the South China Sea. More than 250 fish species were assigned to reef-associated and non-reef-associated functional groups with the help of an expert consultation. Results express average spatial responses to fishing and protected reefs. First, E was used to evaluate biomass responses and catch returns from a range of artificial reefs/marine protected area complexes in which size, perimeter, and corridor design were varied according to biogeographical theory. Benefits that might be deliberately forgone to obtain the cooperation of fishers by allowing them to fish designated reefs were also estimated. Secondly, five specific policy scenarios were evaluated using a spatial map of Hong Kong waters. Gains and losses to different fishery sectors were tracked, along with shifts in the species composition of the catches. While small protected areas with human-made reefs achieve little to avert collapse of the fisheries or a shift towards catches of low-value species, larger protected areas can do much to restore valuable fisheries for reefassociated fish. Precise results, but not the overall patterns, are sensitive to uncertainties in many model parameters.

- by Tony Pitcher
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- Structural Dynamics, Multidisciplinary, South China Sea, Spatial modelling

"Lo sviluppo tecnologico che ha segnato il passaggio alla società dell’informazione ha rivoluzionato profondamente il campo della Geomatica sia sul versante dei sistemi di acquisizione che di quelli di gestione dei dati. Questi ultimi hanno conosciuto una diffusione sempre maggiore grazie allo sviluppo delle tecnologie informatiche che hanno contribuito a trasformarli da strumenti cartografici a sistemi che permettono elaborate analisi spaziali e tematiche. L’esigenza di documentare i sempre più diffusi interventi di trasformazione urbana necessita l’integrazione delle funzioni di rappresentazione e analisi dei dati spaziali dei GIS con il livello di specializzazione geometrico-semantico necessario per rappresentare la complessità dei beni culturali coinvolti in queste trasformazioni. Attraverso l’analisi degli standard nell’ambito della gestione della documentazione metrica dei beni culturali verranno delineate queste esigenze cui si cercherà di dare risposta per mezzo dei linguaggi, modelli di dati e sistemi che la Geomatica ha a disposizione per la gestione delle informazioni spaziali. La progettazione ed implementazione di un modello semantico multiscala sulla base delle specifiche CityGML avrà lo scopo di sperimentare le caratteristiche di questo modello dei dati per la gestione della cartografia urbana a grande scala e le potenzialità applicative della tecnologia XML che ha già diverse applicazioni sul versante della documentazione dei beni culturali. Attraverso l’analisi dei modelli spaziali bi e tridimensionali e la loro formalizzazione logico-matematica saranno prese in considerazione le problematiche della gestione da parte dei DBMS della componente 3D del dato geometrico, elemento essenziale per la documentazione dei processi di trasformazione urbani che riguardano i beni architettonici. L’implementazione dei dati in un database XML e in Geodatabase relazionale avrà lo scopo di sperimentare le possibilità applicative di questi sistemi in relazione alle esigenze evidenziate nella rappresentazione ed analisi delle componenti geometrica e tematica dell’informazione spaziale."

THESIS SUMMARY
Background: The Indian sub-continent has not only wealthy landscapes environment to support huge population, but also has big challenging problems of vector borne disease epidemics across the country. India has become host for all kinds of virus of malaria, dengue, chikungunya, and JE, and also endemic host for filariasis parasites. The burden of vector borne disease is increasing day by day; and therefore, the both intervention measures of both mosquito vector control and the treatment to prevent the disease transmission through the appropriate control strategy in most efficient way. The implementation of conventional method of vector control in the field has significant effect, however, the problem is not manageable and it has been increased steadily. Therefore, the present study is designed for choosing the remote sensing and GIS for mapping the geographical distribution of vector borne diseases, and to study the environmental aspects of the vector borne diseases for 6 decades in India, and a geo-spatial analysis to study the both vector ecology and disease epidemics, and hence, to arrive the probability of spatial prediction of vector borne disease transmission risk in India.
Materials and Methods: The present study is designed for digital mapping of vector borne disease prevalence in the country for the past 58 years (1955 to 2012). The Remote sensing and GIS has been significantly developed for ecological modeling with special emphasis on vectors and vector borne disease epidemics. The Arc View 3.2, Arc View Spatial analysis and Arc View image analyst, GIS software used to create a systematic grid sampling method for conducting the reconnaissance survey and mapping mosquito breeding surface maps. GARMIN 12XL GPS was used to collect the mosquito reconnaissance survey for mosquito vectors in the city. A systematic grid sampling was applied to conduct a rapid survey for mapping Aedes species mosquitogenic condition in the urban areas and the site coordinates of houses information with breeding habitats positive in the grid sectors was collected using GPS. The Indian satellite data (IRS LISS-II, and LISS-III) was used to mapping the use/ land cover of metropolitan area, mapping of mosquitogenic condition, and linked with vector borne disease epidemic transmission. The Indian remote sensing IRS LISS-I, data and IRS WiFS remote sensing data was analyzed, using the maximum likelihood classification for land use land cover classification, and mapping of potential breeding habits of Malaria and JE vectors in India. The mosquito potential breeding surface of malaria, dengue, chikungunya, JE and filariasis was calculated for the each ward and which was mapped with graduated colors.
Result and Discussion: The image classification of the spectral signature of the satellite data imported in to the GIS platform to create the buffer zones of the average adult mosquito flight range of 2.5 km radius around the breeding habitats for mapping the breeding habitats and describing the areas at risk of disease transmission. Land use / land cover dynamics, urban sprawl and irregular growth of urban development and industrial growths are fueled to the development of suitable environment fuelling for malaria, JE, and dengue epidemics and also providing conducing environment for malaria and filariasis endemic. The coefficient model of rainfall and temperature with the mosquito abundance are highly correlated with the normalized difference vegetation index (NDVI), and it is useful in the estimation of mosquito larval abundance and used to predict adult abundance 7 days in advance and also estimating Anopheline malaria vector mosquito abundance in the mosquito habitats of rice fields using remote sensing spectral signatures. The results of logistic regression model provides the spatial agreement between the observed and predicted values of larval index within a buffer around the trap location of rice fields which suitable for vector breeding of malaria and JE. Discriminant analysis could able to correctly distinguish between villages with high and low vector abundance, with an overall accuracy of 90%. Regression results found both transitional swamp and unmanaged pasture proportions to be predictive of vector abundance during the wet season. The virtual GPS under the GIS umbrella was used to conduct a rapid survey with 0.5km distance interval (grid sampling procedures) for assessing the mosquitogenic condition and for mapping the sectors positives for dengue and chikungunya vector mosquitoes (Aedes aegypti or Ae. albopictus) breeding habitats (water storage vessels, plastic and cement containers, tires, plastic cups, coconut cells, tree holes, flower vessels, fridge, stone grinder, etc.,) with accurate site specifications, and the mean value of positive habitats was analyzed by quintiles method for mapping the field situation. The remote sensing data was used for landscape determinants of anopheline mosquito larval habitats. Since, the range of monsoon temperature and the relative humidity has the good agreement with the profusion of mosquito’s vector breeding with respect to space and time. The vegetation indices have the distinctiveness of high sensitivity to soil background, which alters the local environment to vector abundance (sand fly, the vector of Visceral Leishmaniasis / Kala-azar) and disease transmission. Climate and soil types have been progressively affect the vegetation growth and density, and then the conditions on the surrounding environment. Geographical information systems (GIS) and remote sensing were used to identify important geographical risk factors and stratify a region into different areas of transmission risk, thereby providing a guideline to mapping the areas under the risk of visceral leishmaniasis transmission in India. The present study shows that spatial agreement was existed between the environmental variables and the vector borne disease epidemic transmission, and thus, the remote sensing and GIS tool has been used to mapping disease transmission risk zones.
Conclusion: The integrated hybrid remote sensing and GIS techniques was used to mapping the vector breeding potential areas vulnerable to risk of disease transmission and is provided the possible information on reliable estimates of and mapping of malaria, filariasis, JE, and dengue vector breeding habitats, and facilitate to estimate the people at risk of vector borne disease transmission. And perhaps, provides the disease epidemiological information along with geo-coordinates of site specific combined with multispectral satellite data of land use / land cover. It is concluded that remote sensing, GPS, and GIS are effectively useful to identify, delineate and mapping of vector mosquitoes potential breeding surface areas and studying the mosquitogenic conditions in the urban agglomeration, and used to control and management of the vector borne disease transmission, perhaps, may also be GIS based surveillance is the best solution for epidemic control and management of the present situation epidemic in the country.

- by Masimalai Palaniyandi
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- Health Geography, Vector-Borne Disease, Malaria, Community Health

The dynamics of benthic invertebrate communities in Muuga Bay was described in connection with large-scale dredging activities. The spatial extent and duration of the effects were
assessed by multivariate analysis and spatial modelling. In general, dredging had moderate effects on benthic invertebrates both in space and time. Still, dredging resulted in an elevated biomass of bivalves, namely that of Macoma balthica. These bivalves were more impacted on flat bottoms
compared to steep slopes.

- by Robert Aps and +1
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- Ecology, Multivariate Analysis, Spatial modelling, Interaction effect

Abstract: A prospectivity model for iron oxide-coppergold (IOCG) mineralisation has been completed for Namibia and Zambia. The model is based on the mineral systems approach and uses the geographic information systems (GIS) based fuzzy... more

- by Henry Cook
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- Fuzzy Logic, System Approach, Copper, Spatial modelling

Spatial modelling was applied to self-reported schistosomiasis data from over 2.5 million school students from 12,399 schools in all regions of mainland Tanzania. The aims were to derive statistically robust prevalence estimates in small geographical units (wards), to identify spatial clusters of high and low prevalence and to quantify uncertainty surrounding prevalence estimates. The objective was to permit informed decision-making for targeting of resources by the Tanzanian national schistosomiasis control programme. Bayesian logistic regression models were constructed to investigate the risk of schistosomiasis in each ward, based on the prevalence of self-reported schistosomiasis and blood in urine. Models contained covariates representing climatic and demographic effects and random effects for spatial clustering. Degree of urbanisation, median elevation of the ward and median normalised difference vegetation index (NDVI) were significantly and negatively associated with schistosomiasis prevalence. Most regions contained wards that had >95% certainty of schistosomiasis prevalence being >10%, the selected threshold for bi-annual mass chemotherapy of school-age children. Wards with >95% certainty of schistosomiasis prevalence being >30%, the selected threshold for annual mass chemotherapy of school-age children, were clustered in north-western, south-western and south-eastern regions. Large sample sizes in most wards meant raw prevalence estimates were robust. However, when uncertainties were investigated, intervention status was equivocal in 6.7-13.0% of wards depending on the criterion used. The resulting maps are being used to plan the distribution of praziquantel to participating districts; they will be applied to prioritising control in those wards where prevalence was unequivocally above thresholds for intervention and might direct decision-makers to obtain more information in wards where intervention status was uncertain.

- by Alan Fenwick
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- Microbiology, Zoology, Spatial Analysis, Decision Making

Conservation managers require accurate and timely information on the occurrence, size and viability of populations, but this is often difficult for cryptic species living at low densities over large areas. This study aimed to provide such information for tigers in the 36 400-km 2 Kerinci Seblat (KS) region, Sumatra, by identifying and assessing subpopulation viability under different management strategies. 2. Tiger occurrence was mapped within a geographical information system (GIS) using repeat detection-non-detection surveys to incorporate a function of detection probability into a logistic regression model. The landscape variables that influenced tiger occupancy were then used to construct a spatially explicit habitat model to identify core areas. 3. The number of tigers within each core area was estimated by calculating the area of different forest types and their respective tiger densities as determined through camera trapping. The viability of each subpopulation was then assessed under different management scenarios using a population viability analysis (PVA). 4. Tiger occurrence was negatively correlated with distance to public roads. Four core tiger areas were identified, all predominantly located within KS National Park, estimated to support subpopulations of 21, 105, 16 and three adult tigers, respectively. PVA showed that the three larger subpopulations could be demographically viable if well protected. However, if poaching removed ≥ 3 tigers per year, then only the largest subpopulation would not reach extinction within 50 years. Connectivity to this large subpopulation would ensure survival of the smaller subpopulations, through providing a source of tigers to offset poaching losses.

- by Jeremy Holden
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- Ecology, Applied Ecology, Logistic Regression, Population viability analysis

Missing or incomplete data on actors' positions can cause significant problems in political analysis. Research on missing values suggests the use of multiple imputation methods rather than case deletion, but few studies have yet considered the non-ignorable problem -positions that are hidden for strategic purposes. We examine this problem and discuss the advantages and drawbacks of (i) multiple imputation as implemented in AMELIA; (ii) a computationally easy but, in the context of spatial modelling, straightforward measure of indifference and (iii) a conditional averaging algorithm, LDM, which seeks to reasonably fix actors' positions in the policy space pre-and post-imputation. The analysis suggests that actors biased by the status quo strategically hide their more supportive positions. Although none of the existing methods -which produce quite different results -is perfectly suited for imputing hidden positions, LDM has the highest hit rate for the conjectured more supportive position.

- by Thomas König
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- Economics, European Union Politics, Spatial modelling, Incomplete Data

This paper presents the data preparation and processing steps that were taken to provide inputs for the MOLAND model application for the Greater Dublin Region. The model requires spatial and socioeconomic data by county for the beginning and end years of the calibration period i.e. 1990, 2000 and 2006. In addition, projections of socio-economic variables are required for implementing different scenarios. Basic data requirements of the new transport model and description of related data collection works are also presented. Heretofore detailed information and justification for approaches taken in preparing data for ingestion to MOLAND has been undocumented. This paper aims to address that gap. Therefore the steps that have been taken to prepare and process these datasets are described in detail including background information, interpretation and processing methods used and the main assumptions and generalisations adopted.

- by Harutyun Shahumyan and +4
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- Land Use Model, Cellular Automata, Employment, Suitability

The Southern Forests study area covers an area of about six million hectares of southeastern New South Wales, south of Oberon and Kiama and east of Albury and Boorowa (latitude 33° 02'-37 ° 06' S; longitude 146° 56'-147° 06' E). The total area of existing vegetation mapped was three million hectares (3 120 400 hectares) or about 50% of the study area. Terrestrial, wetland and estuarine vegetation of the Southern Forests region were classified into 206 vegetation groups and mapped at a scale between 1: 25 000 and 1: 100 000. The classification was based on a cluster analysis of detailed field surveys of vascular plants, as well as field knowledge in the absence of field survey data. The primary classification was based on 3740 vegetation samples with full floristics cover abundance data. Additional classifications of full floristics presence-absence and tree canopy data were carried out to guide mapping in areas with few full floristic samples. The mapping of extant vegetation was carried out by tagging vegetation polygons with vegetation codes, guided by expert knowledge, using field survey data classified into vegetation groups, remote sensing, and other environmental spatial data. The mapping of pre-1750 vegetation involved tagging of soils mapping with vegetation codes at 1: 100 000 scale, guided by spatial modelling of vegetation groups using generalised additive statistical models (GAMS), and expert knowledge. Profiles of each of the vegetation groups on the CD-ROM* provide key indicator species, descriptions, statistics and lists of informative plant species. The 206 vegetation groups cover the full range of natural vegetation, including rainforests, moist eucalypt forests, dry shrub forests, grassy forests, mallee low forests, heathlands, shrublands, grasslands and wetlands. There are 138 groups of Eucalyptus forests or woodlands, 12 rainforest groups, and 46 non-forest groups. Of the 206 groups, 193 were classified and mapped in the study area. Thirteen vegetation groups were not mapped because of their small size and lack of samples, or because they fell outside the study area. Updated regional extant and pre-1750 vegetation maps of southern New South Wales have been produced in 2005, based on those originally prepared in 2000 for the southern Regional Forest Agreement (RFA). Further validation and remapping of extant vegetation over 10% of the study area has subsequently improved the quality of the vegetation map, and removed some of the errors in the original version. The revised map provides a reasonable representation of native vegetation at a scale between 1: 25 000 and 1: 100 000 across the study area. In 2005 native vegetation covers 50% of the study area. Environmental pressures on the remaining vegetation include clearing, habitat degradation from weeds and nutrification, severe droughts, changing fire regimes, and urbanisation. Grassy woodlands and forests, temperate grasslands, and coastal and riparian vegetation have been the most reduced in areal extent. Over 90% of the grassy woodlands and temperate grasslands have been lost. Conservation of the remaining vegetation in these formations is problematic because of the small, discontinuous, and degraded nature of the remaining patches of vegetation.

- by Nicholas Gellie
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- Remote Sensing, Fire Ecology, Fire History, Fire Behaviour

Global circulation models all forecast that climate change will increase mean temperatures and change precipitation regimes. As a result, traditional coffee growing regions may disappear and new regions may appear. At the same time, demand for high quality, responsibly-sourced coffee continues to grow globally. For sustainable sources of coffee, participants in the global coffee supply chain need to know where coffee will grow in the future and how the suitability of these areas will change over time. With this information, the supply chain then needs to develop appropriate site-specific mitigation and adaptation strategies for both the short-and the long-term to guarantee coffee supply as well as to support improved livelihoods for rural communities. In this paper we firstly quantify the impact of climate change on the suitability of land to grow coffee in a case study in Nicaragua and on acidity content of beverage coffee in a case study in the Veracruz Department of Mexico. Secondly we propose site-specific adaptation strategies and finally identify critical potential impacts of climate change on the overall supply chain and the implications for all actors in the system. We conclude the paper by identifying key directions for future research to seek mitigation and adaptation strategies at both the community and the supply-chain level.

- by Kathleen Schepp and +1
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- Climate Change, Supply Chain, Spatial modelling, Case Study

The development of a Pan-European Ecological Network is now widely recognised as an important policy initiative in support of protected Natura 2000 sites. The site selection is based on habitats as defined in the Annex I of the Habitats Directive. Whilst there is information about the presence of these habitats in Natura 2000 sites, there is no detail of their distribution elsewhere in Europe. The present paper describes a methodology that identifies the spatial distribution of habitats across Europe so that their actual extent can be determined. Five methodological steps are involved starting with selection of appropriate spatial data sets, defining knowledge rules from the descriptions of Annex I habitats, continuing with additional ecological expert knowledge when needed, implementation of the models, and finally the validation. Spatial distribution models were derived for 27 habitats representing the most significant ecosystems. This spatial modelling approach is illustrated with one detailed example. Validation showed that mapping accuracy depends on the habitat description available but also upon its spatial character. Thus widespread habitats such as forests were accurately assessed whereas dispersed classes such as freshwater systems were more difficult to assess. Possible methodological improvements are suggested, such as inclusion of vegetation relevés to improve the knowledge rules. Extension of the methodology to other habitats would require a moderate effort since data collection and processing has now been completed and it is this which is the most time consuming part of the process. We conclude that our method maps widespread European habitats with unprecedented accuracy.

- by Stephan Hennekens
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- Engineering, Remote Sensing, Ecological Networks, Urban Landscape

The Hermann's tortoise (Testudo hermanni) is increasingly threatened in Western Europe and in Italy because of habitat loss, pollution, and illegal removal of free-ranging individuals for the pet trade. Hence, the conservation and appropriate management of the various populations is mandatory, and the few remnant, isolated populations inhabiting urban parks and heavily altered landscapes may be particularly important. An urban population of Hermann's tortoises was studied by capture-mark-recapture procedures in an 'urban green area' in Rome ('Insugherata' Natural Reserve), between March 2001 and October 2005. A spatial modelling approach (logistic regression, with forward stepwise addition model) was developed to investigate which proximate landscape factors influenced the presence/absence of the tortoises. Eight different variables were considered for this model. We found that a single variable (SHRUBS, i.e. Mediterranean dry macchia-like vegetation) was positively correlated to the presence of tortoises, and one to their absence (ECOTONE, i.e. ecotone area constituted by different types of shrubs growing on a relatively wet substratum). The tortoise activity deviated significantly from the null hypothesis of an equal activity throughout the year, with the higher peaks of activity in May, June, and August, and reduced activity in March and April. The conservation implications of our study were also discussed.

- by Lorenzo Rugiero
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- Zoology, Western Europe, Ecology, Ecological Modelling

Archaeobotanical studies are currently being carried out on all the plant remains retrieved from the high alpine site where the Iceman ''Ö tzi'' was found (3,210 m a.s.l.). Preliminary results already show a great diversity of species (121 taxa) mainly originating from lower regions, which must have been transported to the Tisenjoch site by a number of vectors. Spatial modelling has been carried out for one part of the plant remains unequivocally assignable to the Iceman. The resulting patterns indicate that post-depositional displacement processes have affected the material, and even the mummified body itself. It is demonstrated that the influence of cross-contamination resulting from the recovery attempts preceding the excavations can be ruled out by thorough selection of sampled areas and layers. The archaeobotanical results, together with current data from other research fields, strongly suggest that the Iceman had died in an area about 5 m south-west of the position where he was discovered in 1991.

- by Klaus Oeggl
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- Archaeology, Geology, Palaeoenvironment, Archaeobotany

Chile has more than half of the temperate forests in the southern hemisphere. These have been included among the most threatened eco-regions in the world, because of the high degree of endemism and presence of monotypic genera. In this study, we develop empirical models to investigate present and future spatial patterns of woody species richness in temperate forests in south-central Chile. Our aims are both to increase understanding of species richness patterns in such forests and to develop recommendations for forest conservation strategies. Our data were obtained at multiple spatial scales, including field sampling, climate, elevation and topography data, and land-cover and spectrally derived variables from satellite sensor imagery. Climatic and land-cover variables most effectively accounted for tree species richness variability, while only weak relationships were found between explanatory variables and shrub species richness. The best models were used to obtain prediction maps of tree species richness for 2050, using data from the Hadley Centre's HadCM3 model. Current protected areas are located far from the areas of highest tree conservation value and our models suggest this trend will continue. We therefore suggest that current conservation strategies are insufficient, a trend likely to be repeated across many other areas. We propose the current network of protected areas should be increased, prioritizing sites of both current and future importance to increase the effectiveness of the national protected areas system. In this way, target sites for conservation can also be chosen to bring other benefits, such as improved water supply to populated areas.

- by Luis Cayuela
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- Conservation, Modeling, Biodiversity, Temperate Forests

Livestock remains the world's largest user of land and is strongly related to grassland and feed-crop production. Assessments of environmental impacts of livestock farming require detailed knowledge of the presence of livestock, farming practices, and environmental conditions. The present Europewide livestock distribution information is generally restricted to a spatial resolution of NUTS 2 (province level). This paper presents a modelling approach to determine the spatial distribution of livestock at the landscape level. Location factors for livestock occurrence were explored and applied to consistent and harmonized EU-wide regional statistics to produce a detailed spatial distribution of livestock numbers. Both an expert-based and an empirical approach were applied in order to disaggregate the data to grid level. The resulting livestock maps were validated. Results differ between the two downscaling approaches but also between livestock types and countries. While both the expert-based and empirical approach are equally suited to modelling herbivores, in general, the spatial distribution of monogastrics can be better modelled by applying the empirical approach.

- by Igor Staritsky
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- Landscape Ecology, Earth Sciences, Landscape, Biological Sciences

Background: Geographical access to health care facilities is known to influence health services usage. As societies age, accessibility to health care becomes an increasingly acute public health concern. It is known that seniors tend to have lower mobility levels, and it is possible that this may negatively affect their ability to reach facilities and services. Therefore, it becomes important to examine the mobility situation of seniors vis-a-vis the spatial distribution of health care facilities, to identify areas where accessibility is ...

- by Matthew J. Roorda and +1
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- Human Geography, Health Care, Travel Behaviour, Transportation

Spatial interpolation is frequently used to predict values across a landscape enabling the spatial variation and patterns of a property to be quantified. Inverse distance weighting (IDW), ordinary kriging (OK), regression kriging (RK), and partial least squares (PLS) regression are interpolation techniques typically used where the region of interest's spatial extent is relatively small and observations are numerous and regularly spaced. In the current era of data 'mining' and utilisation of sparse data, the above criteria are not always fully met, increasing model uncertainties. Furthermore, regression modelling and kriging techniques require good judgement, experience, and expertise by the practitioner compared with IDW with its more rudimentary approach. In this study we compared spatial predictions derived from IDW, PLS, RK, and OK for Pinus radiata volume mean annual increment (referred to as 300 Index) and mean top height at age twenty (referred to as Site Index) across New Zealand using cross-validation techniques. Validation statistics (RMSE, ME, and R 2 ) show that RK, OK, and IDW provided predictions that were less biased and of greater accuracy than PLS predictions. Standard deviation of rank (SDR) and mean rank (MR) validation statistics showed similar results with OK the most consistent (SDR) predictor, whereas RK had the lowest mean rank (MR), closely followed by IDW. However, the mean performance rankings for validation observations classified according to their distance to the nearest model data point indicate that although PLS provided the poorest predictions at relatively close separation distances (<2 km), in the medium range ($4-8 km) performance was of similar ranking to that of the other techniques, and at greater separation distances PLS outperformed the other techniques. Maps illustrating the spatial variation of P. radiata forest productivity are provided. ß

- by Tim Payn and +1
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- Data Mining, Forest Ecology And Management, Forest Ecology, Biological Sciences

A Community health assessment (CHA) involves the use of Geographic Information Systems (GIS) in conjunction with other software to analyze health and population data and perform numerical-spatial problem solving. There has been little research on identifying how public health professionals integrate this software during typical problem solving scenarios. A better understanding of this is needed to answer the "What" and the "How". The "What" identifies the specific software being used and the "How" explains the way they are integrated together during problem solving steps. This level of understanding will highlight the role of GIS utilization during problem solving and suggest to developers how GIS can be enhanced to better support data analysis during community health assessment. An online survey was developed to identify the information technology used during CHA analysis. The tasks were broken down into steps and for our analysis these steps...

- by Bambang Parmanto
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- Human Geography, Information Technology, Spatial Analysis, Data Analysis

This paper presents LANDFORM, a customized GIS application for semi-automated classification of landform elements, based on topographic attributes like curvature or elevation percentile. These parameters are derived from a Digital Elevation Model (DEM) and used as thresholds for the classification of landform elements like crests, flats, depressions and slopes. With a new method, slopes were further subdivided into upper, mid and lower slopes at significant breakpoints along slope profiles. The paper discusses the results of a fuzzy set algorithm used to compare the similarity between the map generated by LANDFORM and the visual photo-interpretation conducted by a soil expert over the same area. The classification results can be used in applications related to precision agriculture, land degradation studies, and spatial modelling applications where landscape morphometry is identified as an influential factor in the processes under study.

Based on the daily sea level pressure (SLP) circulation catalogue obtained by Esteban, Martin-Vide and Mases, Int J Climatol 26:1501-1515 for Western Europe, high-resolution maps of daily maximum and minimum temperature, mean daily precipitation and daily precipitation probability have been obtained for Andorra (Pyrenees). The 20 daily-circulation patterns cover the period 1960-2001 and were generated using new approaches based on the rotated principal component analysis (PCA) and clustering technique. The final maps of Andorra associated with each circulation pattern have been constructed using altitude, latitude, continentality and solar radiation as multiple regression predictors (Ninyerola, Pons and Roure, Int J Climatol 20: [1823][1824][1825][1826][1827][1828][1829][1830][1831][1832][1833][1834][1835][1836][1837][1838][1839][1840][1841] 2000). The daily temperature and rainfall series used from Andorran, French and Catalan/ Spanish weather stations have been checked for data quality. The results confirm the complexity of the spatial distribution of meteorological phenomena over mountainous areas such as in Andorra, and show the importance of the Mediterranean and Atlantic influence upon the climate of this country of the Pyrenees. On the other hand, different tests have been made showing that the classification results could improve the resulting interpolated climate maps by the use of the circulation-pattern frequencies.

Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop 1 km resolution population density models for China's chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for 1/4 of the sample data which were not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China's first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives.

- by Thomas Van Boeckel
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- Bioinformatics, Epidemiology, Modeling, Life Sciences

a b s t r a c t a r t i c l e i n f o JEL classification: C21 E43 E58 E62 F42

- by Peter Claeys
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- Econometrics, Fiscal policy, Applied Economics, Emerging Market

A hydrologic pond model was developed that simulates daily spatial and temporal variations (area, volume and height) of temporary ponds around Barkedji, a village located in the Ferlo Region in Senegal. The model was tested with rainfall input data from a meteorological station and from Tropical Rainfall Measuring Mission (TRMM) satel-5 lites. During calibration phase, we used climatic, hydrologic and topographic field data of Barkedji pond collected daily during the 2002 rainy season. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) and a QuickBird satellite image acquired in August 2005 (2.5 m pixel size) were used to apply the hydrologic model to all ponds (98 ponds) of the study area. With input 10 rainfall data from the meteorological station, simulated water heights values for years 2001 and 2002 were significantly correlated with observed water heights for Furdu, Mous 2 and Mous 3 ponds, respectively with 0.81, 0.67 and 0.88 Nash coefficients. With rainfall data from TRMM satellite as model input, correlations were lower, particularly for year 2001. For year 2002, the results were acceptable with 0.61, 0.65 and 15

- by V. Soti and +1
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- Remote Sensing, Seasonality, Spatial modelling, Digital Elevation Model

The effect of dredging on the biomass structure of benthic invertebrate communities was examined at 9 sites in the northeastern Baltic Sea during 2002-2007. We analyzed whether and how bottom topography, depth and sediment type contributed to these relationships. In general, the effects of dredging on benthic invertebrates were weak. Dredging clearly increased the biomass of bivalves but the communities recovered in about a year. Bottom topography affected the response of invertebrates to dredging. Flat bottoms were more sensitive to dredging compared to sites situating on slopes. Spatial modelling was proved as a useful tool to predict spatial variability in the effects of dredging on benthic invertebrate communities.

- by Andreas G . Heiss
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- Archaeology, Geology, Palaeoenvironment, Archaeobotany

— La région des Trois-Lacs, à l'ouest du plateau suisse, est très bien documentée pour la période comprise entre 3850 et 3350 av. J.-C. environ. Deux cultures archéologiques différentes de part et d'autre du Jura sont avérées. Elles sont mêlées dans le site de Concise fouillé entre 1996 et 2000. Les variations des styles céramiques y semblent liées à des mouvements de populations. Nous avons cherché à modéliser la dynamique de ces mouvements à l'aide d'un graphe et sur la base d'hypothèses ethno-archéologiques. Notre stratégie visait, d'une part, à rendre compte de la diffusion de ces cultures par une marche aléatoire (destinée à restituer la notion de diffusion technologique par le mariage) et, d'autre part, à qualifier chaque site avec des indicateurs topologiques. Au final, nous avons confronté les résultats archéologiques avec ceux du modèle. Cette approche nous permet de proposer des pistes de réflexions quant aux types de relations entretenues entre communautés. Graphes • Marche aléatoire • Modélisation spatiale • Néolithique moyen • Peuplement • Plateau suisse • Styles céramiques • Topologie Abstract.— Spatial modeling of the settlement process of the Swiss Plateau during the Middle Neolithic.— The region of Three Lakes, to the west of the Swiss Plateau, is highly documented for the period between roughly 3850 and 3350 before J.-C. It appears that two different archeological cultures existed on either side of the Jura. Both figured at the Concise site, excavated between 1996 and 2000. Variations in pottery styles seem to be linked to population movements. We sought to model the dynamics of these movements with a graph and on the basis of ethno-archaeological hypotheses. Our strategy was to first account for the spread of these cultures through the random walk of individuals (in an attempt to restore the concept of technology diffusion through marriage) and, secondly, to characterize each site with topological indicators. Finally, we compared the archaeological results with those of the model. This approach allows us to suggest ways of approaching the types of relations maintained between communities. Ceramic Styles • Graphs • Middle Neolithic • Random Walk • Settlement • Spatial Modeling • Swiss Plateau • Topology Resumen.— Modelización espacial de la dinámica de poblamiento de la meseta suiza en el Neolítico medio.— La región de los Tres-Lagos, al oeste de la meseta suiza, esta muy documentada para el periodo aproximadamente entre 3850 y 3350 a.J.-C. Dos culturas arqueológicas distintas existen de lado y otro del Jura, pero se han mezclado en el sitio Concise, excavado entre 1996 y 2000. Las variaciones de los estilos cerámicos parecen ligadas a movimientos poblacionales. Hemos tratado una modelización de estos movimientos con la ayuda de un grafo y con la base de hipótesis etno-arqueológicas. Nuestra estrategia trataba de abarcar, de un lado, la difusión de estas culturas usando de un itinerario aleatorio (con el fin de restituir la noción de difusión tecnológica a través del matrimonio) y, de otro lado, calificando cada sitio con indicadores topológicos. Al final, se han confrontado los resultados arqueológicos con los del modelo. Este acercamiento permite proponer direcciones de reflexiones sobre los tipos de relaciones llevadas entre comunidades. Estilos cerámicos • Grafos • Itinerario aleatorio • Meseta suiza • Modelización espacial • Neolítico medio • Poblamiento • Topología

- by Elena Burri-Wyser
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- Spatial Analysis, Spatial Modeling, Pottery (Archaeology), Graph Theory

During the last 20 years, ecologists discovered the importance of including spatial relationships in models of species distributions. Among the latest developments in modelling how species are spatially structured are eigenfunction-based spatial filtering methods such as Moran's eigenvector maps (MEM) and principal coordinates of neighbour matrices (PCNM). Although these methods are very powerful and flexible, they are only suited to study distributions resulting from non-directional spatial processes. The asymmetric eigenvector map (AEM) framework, a new eigenfunction-based spatial filtering method, fills this theoretical gap. AEM was specifically designed to model spatial structures hypothesized to be produced by directional spatial processes. Water currents, prevailing wind on mountainsides, river networks, and glaciations at historical time scales are some of the situations where AEM can be used. This paper presents three applications of the method illustrating different combinations of: sampling schemes (regular and irregular), data types (univariate and multivariate), and spatial scales (metres, kilometres, and hundreds of kilometres). The applications include the distribution of a crustacean (Atya) in a river, bacterial production in a lake, and the distribution of the copepodite stages of a crustacean on the Atlantic oceanic shelf. In each application, a comparison is made between AEM, MEM, and PCNM. No environmental components were included in the comparisons. AEM was a strong predictor in all cases, explaining 59.8% for Atya distribution, 51.4% of the bacterial production variation, and 38.4% for the copepodite distributions. AEM outperformed MEM and PCNM in these applications, offering a powerful and more appropriate tool for spatial modelling of species distributions under directional forcing and leading to a better understanding of the processes at work in these systems.

- by Pierre Pepin
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- Modeling, Crustacea, Ecology, Rivers

Predicting the impact of land-use change on water and salt generation from upland areas at a catchment scale is a difficult task. Across large catchments there are often limited field measurements, and so predictions are forced to rely on modelling. However, at this scale input data for models is usually restricted to information surfaces such as rainfall, geology, and surface topography, and hence the complexity of modelling approaches need to match the complexity of the available data.

- by Matthew Stenson and +1
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- Spatial modelling, Water balance

Over the last few decades it has become increasingly obvious that disturbance, whether natural or anthropogenic in origin, is ubiquitous in ecosystems. Disturbance-related processes are now considered to be important determinants of the composition, structure and function of ecological systems. However, because disturbance and succession processes occur across a wide range of spatio-temporal scales their empirical investigation is difficult. To counter these difficulties much use has been made of spatial modelling to explore the response of ecological systems to disturbance(s) occurring at spatial scales from the individual to the landscape and above, and temporal scales from minutes to centuries. Here we consider such models by contrasting two alternative motivations for their development and use: prediction and exploration, with a focus on forested ecosystems. We consider the two approaches to be complementary rather than competing. Predictive modelling aims to combine knowledge (understanding and data) with the goal of predicting system dynamics; conversely, exploratory models focus on developing understanding in systems where uncertainty is high. Examples of exploratory modelling include model-based explorations of generic issues of criticality in ecological systems, whereas predictive models tend to be more heavily data-driven (e.g. species distribution models). By considering predictive and exploratory modelling alongside each other, we aim to illustrate the range of methods used to model succession and disturbance dynamics and the challenges involved in the model-building and evaluation processes in this arena.

- by James Millington
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- Evolutionary Biology, Plant Biology, Ecology, System Dynamics