scholarly journals The effect of colonization dynamics in competition for space in metacommunities

2021 ◽  
Author(s):  
Jorge Arroyo-Esquivel ◽  
Nathan G. Marculis ◽  
Alan Hastings
Keyword(s):  
Continuous Time ◽  
Habitat Suitability ◽  
Limiting Factor ◽  
Modeling Framework ◽  
Competition For Space ◽  
Time Modeling ◽  
Functional Forms ◽  
Colonization Dynamics ◽  
Main Factors ◽  
Metacommunity Dynamics

AbstractOne of the main factors that determines habitat suitability for sessile and territorial organisms is the presence or absence of another competing individual in that habitat. This type of competition arises in populations occupying patches in a metacommunity. Previous studies have looked at this process using a continuous-time modeling framework, where colonizations and extinctions occur simultaneously. However, different colonization processes may be performed by different species, which may affect the metacommunity dynamics. We address this issue by developing a discrete-time framework that describes these kinds of metacommunity interactions, and we consider different colonization dynamics. To understand potential dynamics, we consider specific functional forms that characterize the colonization and extinction processes of metapopulations competing for space as their limiting factor. We then provide a mathematical analysis of the models generated by this framework, and we compare these results to what is seen in nature and in previous models.

scholarly journals Continuous Time Representation and Modeling Framework for Analysis of Nonworker Activity-Travel Patterns: Tour and Episode Attributes

2003 ◽  
Vol 1831 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Rajul Misra ◽  
Chandra R. Bhat ◽  
Sivaramakrishnan Srinivasan
Keyword(s):  
San Francisco ◽  
Continuous Time ◽  
San Francisco Bay Area ◽  
Location Choice ◽  
Travel Patterns ◽  
Modeling Framework ◽  
Time Representation ◽  
Bay Area ◽  
Activity Duration ◽  
Travel Diary

A set of four econometric models is presented to examine the tour and episode-related attributes (specifically, mode choice, activity duration, travel times, and location choice) of the activity-travel patterns of non-workers, as a sequel to an earlier work by Bhat and Misra (2001), which presented a comprehensive continuous-time framework for representation and analysis of the activity-travel choices of nonworkers. Detailed descriptions of the first two components of the modeling framework related to the number and sequence of activity episodes are also presented. The proposed models using activity-travel data from the 1990 San Francisco Bay Area travel diary survey are estimated.

Geospatial Suitability Indices Toolbox (GSI Toolbox)

2021 ◽  
Author(s):  
Christina Saltus ◽  
Todd Swannack ◽  
S. McKay
Keyword(s):  
Habitat Suitability ◽  
Geometric Mean ◽  
Arithmetic Mean ◽  
Limiting Factor ◽  
Ecological Processes ◽  
Weighted Arithmetic ◽  
Suitability Index ◽  
Multiple Parameter ◽  
Spatially Distributed

Habitat suitability models are widely adopted in ecosystem management and restoration, where these index models are used to assess environmental impacts and benefits based on the quantity and quality of a given habitat. Many spatially distributed ecological processes require application of suitability models within a geographic information system (GIS). Here, we present a geospatial toolbox for assessing habitat suitability. The Geospatial Suitability Indices (GSI) toolbox was developed in ArcGIS Pro 2.7 using the Python® 3.7 programming language and is available for use on the local desktop in the Windows 10 environment. Two main tools comprise the GSI toolbox. First, the Suitability Index Calculator tool uses thematic or continuous geospatial raster layers to calculate parameter suitability indices based on user-specified habitat relationships. Second, the Overall Suitability Index Calculator combines multiple parameter suitability indices into one overarching index using one or more options, including: arithmetic mean, weighted arithmetic mean, geometric mean, and minimum limiting factor. The resultant output is a raster layer representing habitat suitability values from 0.0 to 1.0, where zero is unsuitable habitat and one is ideal suitability. This report documents the model purpose and development as well as provides a user’s guide for the GSI toolbox.

scholarly journals Towards improved, cost-effective surveillance of Ixodes ricinus ticks and associated pathogens using species distribution modelling

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Manuela Signorini ◽  
Anna-Sofie Stensgaard ◽  
Michele Drigo ◽  
Giulia Simonato ◽  
Federica Marcer ◽  
...  
Keyword(s):  
Ixodes Ricinus ◽  
Habitat Suitability ◽  
Pathogen Detection ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cost Effective ◽  
Limiting Factor ◽  
Sampling Effort ◽  
Remotely Sensed Data ◽  
Ecological Requirements

Various ticks exist in the temperate hilly and pre-alpine areas of Northern Italy, where Ixodes ricinus is the more important. In this area different tick-borne pathogen monitoring projects have recently been implemented; we present here the results of a twoyear field survey of ticks and associated pathogens, conducted 2009-2010 in North-eastern Italy. The cost-effectiveness of different sampling strategies, hypothesized a posteriori based on two sub-sets of data, were compared and analysed. The same two subsets were also used to develop models of habitat suitability, using a maximum entropy algorithm based on remotely sensed data. Comparison of the two strategies (in terms of number of ticks collected, rates of pathogen detection and model accuracy) indicated that monitoring at many temporary sites was more cost-effective than monthly samplings at a few permanent sites. The two model predictions were similar and provided a greater understanding of ecological requirements of I. ricinus in the study area. Dense vegetation cover, as measured by the normalized difference vegetation index, was identified as a good predictor of tick presence, whereas high summer temperatures appeared to be a limiting factor. The study suggests that it is possible to obtain realistic results (in terms of pathogens detection and development of habitat suitability maps) with a relatively limited sampling effort and a wellplanned monitoring strategy.

scholarly journals Hydrological real-time modeling using remote sensing data

2010 ◽  
Vol 7 (6) ◽  
pp. 8809-8835
Author(s):  
P. Meier ◽  
A. Frömelt ◽  
W. Kinzelbach
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Real Time ◽  
River Basin ◽  
Time Lag ◽  
Remote Sensing Data ◽  
Modeling Framework ◽  
Sensing Data ◽  
Soil Storage ◽  
Time Modeling

Abstract. Reliable real-time forecasts of the discharge can provide valuable information for the management of a river basin system. Sequential data assimilation using the Ensemble Kalman Filter provides a both efficient and robust tool for a real-time modeling framework. One key parameter in a hydrological system is the soil moisture which recently can be characterized by satellite based measurements. A forecasting framework for the prediction of discharges is developed and applied to three different sub-basins of the Zambezi River Basin. The model is solely based on remote sensing data providing soil moisture and rainfall estimates. The soil moisture product used is based on the back-scattering intensity of a radar signal measured by the radar scatterometer on board the ERS satellite. These soil moisture data correlate well with the measured discharge of the corresponding watershed if the data are shifted by a time lag which is dependent on the size and the dominant runoff process in the catchment. This time lag is the basis for the applicability of the soil moisture data for hydrological forecasts. The conceptual model developed is based on two storage compartments. The processes modeled include evaporation losses, infiltration and percolation. The application of this model in a real-time modeling framework yields good results in watersheds where the soil storage is an important factor. For the largest watershed a forecast over almost six weeks can be provided. However, the quality of the forecast increases significantly with decreasing prediction time. In watersheds with little soil storage and a quick response to rainfall events the performance is relatively poor.

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