Using the Spatial Population Abundance Dynamics Engine for conservation management

1. An explicit spatial understanding of population dynamics is often critical for effective management of wild populations. Sophisticated approaches are available to simulate these dynamics, but are largely either spatially homogeneous or agent based, and thus best suited to small spatial or tempora...

Full description

Bibliographic Details
Published in:Methods in Ecology and Evolution
Main Authors: Beeton, NJ, McMahon, CR, Williamson, GJ, Potts, J, Bloomer, J, Bester, MN, Forbes, LK, Johnson, CN
Format: Article in Journal/Newspaper
Language:English
Published: Wiley-Blackwell Publishing 2015
Subjects:
Online Access:https://doi.org/10.1111/2041-210X.12434
http://ecite.utas.edu.au/103028
id ftunivtasecite:oai:ecite.utas.edu.au:103028
record_format openpolar
spelling ftunivtasecite:oai:ecite.utas.edu.au:103028 2023-05-15T14:03:25+02:00 Using the Spatial Population Abundance Dynamics Engine for conservation management Beeton, NJ McMahon, CR Williamson, GJ Potts, J Bloomer, J Bester, MN Forbes, LK Johnson, CN 2015 https://doi.org/10.1111/2041-210X.12434 http://ecite.utas.edu.au/103028 en eng Wiley-Blackwell Publishing http://dx.doi.org/10.1111/2041-210X.12434 Beeton, NJ and McMahon, CR and Williamson, GJ and Potts, J and Bloomer, J and Bester, MN and Forbes, LK and Johnson, CN, Using the Spatial Population Abundance Dynamics Engine for conservation management, Methods in Ecology and Evolution, 6, (12) pp. 1407-1416. ISSN 2041-210X (2015) [Refereed Article] http://ecite.utas.edu.au/103028 Environmental Sciences Environmental Science and Management Wildlife and Habitat Management Refereed Article PeerReviewed 2015 ftunivtasecite https://doi.org/10.1111/2041-210X.12434 2019-12-13T22:04:36Z 1. An explicit spatial understanding of population dynamics is often critical for effective management of wild populations. Sophisticated approaches are available to simulate these dynamics, but are largely either spatially homogeneous or agent based, and thus best suited to small spatial or temporal scales. These approaches also often ignore financial decisions crucial to choosing management approaches on the basis of cost-effectiveness. 2. We created a user-friendly and flexible modelling framework for simulating these population issues at large spatial scales the Spatial Population Abundance Dynamics Engine (SPADE). SPADE is based on the Spatio-Temporal Animal Reduction (STAR) model (McMahon etal . 2010) and uses a reactiondiffusion approach to model population trajectories and a cost-benefit analysis technique to calculate optimal management strategies over long periods and across broad spatial scales. It expands on STAR by incorporating species interactions and multiple concurrent management strategies, and by allowing full user control of functional forms and parameters. 3. We used SPADE to simulate the eradication of feral domestic cats Felis catus on sub-Antarctic Marion Island (Bester etal ., South African Journal of Wildlife Research, 32, 2002, 65) and compared modelled outputs to observed data. The parameters of the best-fitting model reflected the conditions of the management programme, and the model successfully simulated the observed movement of the cat population to the southern and eastern portion of the island under hunting pressure. We further demonstrated that none of the management strategies would likely have been successful within a reasonable time frame if performed in isolation. 4. Spatial Population Abundance Dynamics Engine is applicable to a wide range of population management problems and allows easy generation, modification and analysis of management scenarios. It is a useful tool for the planning, evaluation and optimisation of the management of wild populations and can be used without specialised training. Article in Journal/Newspaper Antarc* Antarctic Marion Island eCite UTAS (University of Tasmania) Antarctic McMahon ENVELOPE(65.148,65.148,-70.835,-70.835) Methods in Ecology and Evolution 6 12 1407 1416
institution Open Polar
collection eCite UTAS (University of Tasmania)
op_collection_id ftunivtasecite
language English
topic Environmental Sciences
Environmental Science and Management
Wildlife and Habitat Management
spellingShingle Environmental Sciences
Environmental Science and Management
Wildlife and Habitat Management
Beeton, NJ
McMahon, CR
Williamson, GJ
Potts, J
Bloomer, J
Bester, MN
Forbes, LK
Johnson, CN
Using the Spatial Population Abundance Dynamics Engine for conservation management
topic_facet Environmental Sciences
Environmental Science and Management
Wildlife and Habitat Management
description 1. An explicit spatial understanding of population dynamics is often critical for effective management of wild populations. Sophisticated approaches are available to simulate these dynamics, but are largely either spatially homogeneous or agent based, and thus best suited to small spatial or temporal scales. These approaches also often ignore financial decisions crucial to choosing management approaches on the basis of cost-effectiveness. 2. We created a user-friendly and flexible modelling framework for simulating these population issues at large spatial scales the Spatial Population Abundance Dynamics Engine (SPADE). SPADE is based on the Spatio-Temporal Animal Reduction (STAR) model (McMahon etal . 2010) and uses a reactiondiffusion approach to model population trajectories and a cost-benefit analysis technique to calculate optimal management strategies over long periods and across broad spatial scales. It expands on STAR by incorporating species interactions and multiple concurrent management strategies, and by allowing full user control of functional forms and parameters. 3. We used SPADE to simulate the eradication of feral domestic cats Felis catus on sub-Antarctic Marion Island (Bester etal ., South African Journal of Wildlife Research, 32, 2002, 65) and compared modelled outputs to observed data. The parameters of the best-fitting model reflected the conditions of the management programme, and the model successfully simulated the observed movement of the cat population to the southern and eastern portion of the island under hunting pressure. We further demonstrated that none of the management strategies would likely have been successful within a reasonable time frame if performed in isolation. 4. Spatial Population Abundance Dynamics Engine is applicable to a wide range of population management problems and allows easy generation, modification and analysis of management scenarios. It is a useful tool for the planning, evaluation and optimisation of the management of wild populations and can be used without specialised training.
format Article in Journal/Newspaper
author Beeton, NJ
McMahon, CR
Williamson, GJ
Potts, J
Bloomer, J
Bester, MN
Forbes, LK
Johnson, CN
author_facet Beeton, NJ
McMahon, CR
Williamson, GJ
Potts, J
Bloomer, J
Bester, MN
Forbes, LK
Johnson, CN
author_sort Beeton, NJ
title Using the Spatial Population Abundance Dynamics Engine for conservation management
title_short Using the Spatial Population Abundance Dynamics Engine for conservation management
title_full Using the Spatial Population Abundance Dynamics Engine for conservation management
title_fullStr Using the Spatial Population Abundance Dynamics Engine for conservation management
title_full_unstemmed Using the Spatial Population Abundance Dynamics Engine for conservation management
title_sort using the spatial population abundance dynamics engine for conservation management
publisher Wiley-Blackwell Publishing
publishDate 2015
url https://doi.org/10.1111/2041-210X.12434
http://ecite.utas.edu.au/103028
long_lat ENVELOPE(65.148,65.148,-70.835,-70.835)
geographic Antarctic
McMahon
geographic_facet Antarctic
McMahon
genre Antarc*
Antarctic
Marion Island
genre_facet Antarc*
Antarctic
Marion Island
op_relation http://dx.doi.org/10.1111/2041-210X.12434
Beeton, NJ and McMahon, CR and Williamson, GJ and Potts, J and Bloomer, J and Bester, MN and Forbes, LK and Johnson, CN, Using the Spatial Population Abundance Dynamics Engine for conservation management, Methods in Ecology and Evolution, 6, (12) pp. 1407-1416. ISSN 2041-210X (2015) [Refereed Article]
http://ecite.utas.edu.au/103028
op_doi https://doi.org/10.1111/2041-210X.12434
container_title Methods in Ecology and Evolution
container_volume 6
container_issue 12
container_start_page 1407
op_container_end_page 1416
_version_ 1766274068762329088