The relevance of host overcrowding in wildlife epidemiology: A new spatially explicit aggregation index

2018 ◽  
Vol 84 ◽  
pp. 695-700 ◽  
Author(s):  
Eduardo Laguna ◽  
José A. Barasona ◽  
Roxana Triguero-Ocaña ◽  
Margarita Mulero-Pázmány ◽  
Juan José Negro ◽  
...  
Keyword(s):  
Spatially Explicit ◽  
Aggregation Index ◽  
Wildlife Epidemiology

Efficient synthetic generation of ecological data with preset spatial association of individuals

2021 ◽  
Author(s):  
Bogdan Strimbu ◽  
Andrei Paun ◽  
Alexandru Amarioarei ◽  
Mihaela M Paun ◽  
Victor Felix Strimbu
Keyword(s):  
Forest Ecosystems ◽  
Spatial Association ◽  
Spatial Arrangement ◽  
Spatially Explicit ◽  
Forest Stands ◽  
Ecological Data ◽  
Aggregation Index ◽  
Spatial Indices ◽  
Functional Software ◽  
Individual Trees

Many experiments are not feasible to be conducted as factorials. Simulations using synthetically generated data are viable alternatives to such factorial experiments. The main objective of the present research is to develop a methodology and a platform to synthetically generate spatially explicit forest ecosystems represented by points with a predefined spatial pattern. Using algorithms with polynomial complexity and parameters that control the number of clusters, the degree of clusterization, and the proportion of nonrandom trees, we show that spatially explicit forest ecosystems can be generated time efficiently, which enable large factorial simulations. The proposed method was tested on 1200 synthetically generated forest stands, each of 25 ha, using 10 spatial indices: Clark-Evans aggregation index, Ripley’s K, Besag’s L, Morisita’s dispersion index, Greig-Smith index, the size dominance index of Hui, index of nonrandomness of Pielou, directional index and mean directional index of Corral-Rivas, and size differentiation index of Von Gadow. The size of individual trees was randomly generated aiming at variograms like real forests. We obtained forest stands with the expected spatial arrangement and distribution of sizes in less than one hour. To ensure replicability of the study we have provided a free fully functional software that executes the stated tasks.

scholarly journals Estimation of European wild boar relative abundance and aggregation: a novel method in epidemiological risk assessment

2006 ◽  
Vol 135 (3) ◽  
pp. 519-527 ◽  
Author(s):  
P. ACEVEDO ◽  
J. VICENTE ◽  
U. HÖFLE ◽  
J. CASSINELLO ◽  
F. RUIZ-FONS ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Wild Boar ◽  
Porcine Circovirus ◽  
Test Statistic ◽  
Hunting Season ◽  
Aggregation Index ◽  
Simple Method ◽  
Abundance Estimates ◽  
Epidemiological Risk ◽  
Wildlife Epidemiology

Wild boars are important disease reservoirs. It is well known that abundance estimates are needed in wildlife epidemiology, but the expense and effort required to obtain them is prohibitive. We evaluated a simple method based on the frequency of faecal droppings found on transects (FBII), and developed a spatial aggregation index, based on the runs test statistic. Estimates were compared with hunting data, and with porcine circovirus and Aujeszky's disease virus seroprevalences and Mycobacterium tuberculosis complex and Metastrongylus spp. prevalence. The FBII and the aggregation index were correlated with the hunting index, but both of the former estimates correlated better than the latter with the disease prevalences. Hence, at least in habitats with high wild boar densities, the FBII combined with the aggregation index constitutes a cheap and reliable alternative for wild boar abundance estimation that can be used for epidemiological risk assessment, even outside the hunting season and in areas with no available data on hunting activities.

Agent-Based Computational Model

2017 ◽  
Author(s):  
Joshua M. Epstein
Keyword(s):  
Computational Model ◽  
Bounded Rationality ◽  
Time Scales ◽  
Spatially Explicit ◽  
Agent Based ◽  
Affective Component ◽  
Elementary Type ◽  
Social Component ◽  
Different Time Scales

This part describes the agent-based and computational model for Agent_Zero and demonstrates its capacity for generative minimalism. It first explains the replicability of the model before offering an interpretation of the model by imagining a guerilla war like Vietnam, Afghanistan, or Iraq, where events transpire on a 2-D population of contiguous yellow patches. Each patch is occupied by a single stationary indigenous agent, which has two possible states: inactive and active. The discussion then turns to Agent_Zero's affective component and an elementary type of bounded rationality, as well as its social component, with particular emphasis on disposition, action, and pseudocode. Computational parables are then presented, including a parable relating to the slaughter of innocents through dispositional contagion. This part also shows how the model can capture three spatially explicit examples in which affect and probability change on different time scales.

scholarly journals Territories of state-led aquaculture risk management: Thailand’s Plang Yai program

2020 ◽  
pp. 239965442096524
Author(s):  
Mariska JM Bottema ◽  
Simon R Bush ◽  
Peter Oosterveer
Keyword(s):  
Risk Management ◽  
Policy Instruments ◽  
Spatially Explicit ◽  
Financial Risks ◽  
Shared Resources ◽  
Globalizing World ◽  
Farmer Behavior ◽  
Key Policy ◽  
The Individual ◽  
High Degree

The Thai aquaculture sector faces a range of production, market and financial risks that extend beyond the private space of farms to include public spaces and shared resources. The Thai state has attempted to manage these shared risks through its Plang Yai (or ‘Big Area’) agricultural extension program. Using the lens of territorialization, this paper investigates how, through the Plang Yai program, risk management is institutionalized through spatially explicit forms of collaboration amongst farmers and between farmers and (non-)state actors. We focus on how four key policy instruments brought together under Plang Yai delimited multiple territories of risk management over shrimp and tilapia production in Chantaburi and Chonburi provinces. Our findings demonstrate how these policy instruments address risks through dissimilar but overlapping territories that are selectively biased toward facilitating the individual management of production risks, whilst enabling both the individual and collective management of market and financial risks. This raises questions about the suitability of addressing aquaculture risks by controlling farmer behavior through state-led designation of singular, spatially explicit areas. The findings also indicate the multiple roles of the state in territorializing risk management, providing a high degree of flexibility, which is especially valuable in landscapes shared by many users, connected to (global) value chains and facing diverse risks. In doing so we demonstrate that understanding the territorialization of production landscapes in a globalizing world requires a dynamic approach recognizing the multiplicity of territories that emerge in risk management processes.

scholarly journals Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks

2021 ◽  
Vol 7 (9) ◽  
pp. eaaz5236 ◽  
Author(s):  
Umakant Mishra ◽  
Gustaf Hugelius ◽  
Eitan Shelef ◽  
Yuanhe Yang ◽  
Jens Strauss ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spatial Heterogeneity ◽  
Surface Air Temperature ◽  
Spatially Explicit ◽  
Soil Profiles ◽  
Permafrost Region ◽  
Environmental Predictors ◽  
Soil Organic Carbon Stocks ◽  
Soc Stocks

Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that 1014−175+194 Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

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