Managing visitor access to seabird colonies: a spatial simulation and empirical observations
Managers of wildlife reserves have a range of tools available to them when considering the best way to provide visitor access while avoiding as many of the negative effects of human disturbance as possible. However, managers lack guidelines as to whether conservation interests are best met by spread...
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crwiley:10.1111/j.1474-919x.2007.00640.x 2024-06-02T08:13:49+00:00 Managing visitor access to seabird colonies: a spatial simulation and empirical observations BEALE, COLIN M. 2007 http://dx.doi.org/10.1111/j.1474-919x.2007.00640.x https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1474-919X.2007.00640.x https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1474-919X.2007.00640.x en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Ibis volume 149, issue s1, page 102-111 ISSN 0019-1019 1474-919X journal-article 2007 crwiley https://doi.org/10.1111/j.1474-919x.2007.00640.x 2024-05-03T10:52:22Z Managers of wildlife reserves have a range of tools available to them when considering the best way to provide visitor access while avoiding as many of the negative effects of human disturbance as possible. However, managers lack guidelines as to whether conservation interests are best met by spreading visitors thinly throughout a reserve or by aggregating them in a small area. Here I describe how relationships between disturbance impact and disturbance pressure (the dose–response curve) can be used to address this issue. I generate a spatial simulation of two different models of visitor distribution (one more aggregated than the other) and explicitly model disturbance impact for a variety of dose–response curves. I show that the optimal visitor distribution is likely to depend on the sensitivity of the species and the overall visitor pressure. Importantly, I find that in certain circumstances optimal management can shift from one management option to the other if visitor numbers cross a certain threshold. I use published relationships predicting nesting success of Common Guillemots Uria aalge and Black‐legged Kittiwakes Rissa tridactyla to assess optimal management at three nature reserves in Scotland. Optimal management for Guillemots depends on the number of people and the distance between the people and the birds. At sites with high disturbance pressures, management should aim to aggregate visitors in as small an area as possible, whereas at sites with lower disturbance pressure, an even distribution of visitors is favoured. Kittiwake models were not generally accurate, and consequently only site‐specific guidelines could be generated, where an even distribution was favoured. Article in Journal/Newspaper rissa tridactyla Uria aalge uria Wiley Online Library Ibis 149 s1 102 111 |
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language |
English |
description |
Managers of wildlife reserves have a range of tools available to them when considering the best way to provide visitor access while avoiding as many of the negative effects of human disturbance as possible. However, managers lack guidelines as to whether conservation interests are best met by spreading visitors thinly throughout a reserve or by aggregating them in a small area. Here I describe how relationships between disturbance impact and disturbance pressure (the dose–response curve) can be used to address this issue. I generate a spatial simulation of two different models of visitor distribution (one more aggregated than the other) and explicitly model disturbance impact for a variety of dose–response curves. I show that the optimal visitor distribution is likely to depend on the sensitivity of the species and the overall visitor pressure. Importantly, I find that in certain circumstances optimal management can shift from one management option to the other if visitor numbers cross a certain threshold. I use published relationships predicting nesting success of Common Guillemots Uria aalge and Black‐legged Kittiwakes Rissa tridactyla to assess optimal management at three nature reserves in Scotland. Optimal management for Guillemots depends on the number of people and the distance between the people and the birds. At sites with high disturbance pressures, management should aim to aggregate visitors in as small an area as possible, whereas at sites with lower disturbance pressure, an even distribution of visitors is favoured. Kittiwake models were not generally accurate, and consequently only site‐specific guidelines could be generated, where an even distribution was favoured. |
format |
Article in Journal/Newspaper |
author |
BEALE, COLIN M. |
spellingShingle |
BEALE, COLIN M. Managing visitor access to seabird colonies: a spatial simulation and empirical observations |
author_facet |
BEALE, COLIN M. |
author_sort |
BEALE, COLIN M. |
title |
Managing visitor access to seabird colonies: a spatial simulation and empirical observations |
title_short |
Managing visitor access to seabird colonies: a spatial simulation and empirical observations |
title_full |
Managing visitor access to seabird colonies: a spatial simulation and empirical observations |
title_fullStr |
Managing visitor access to seabird colonies: a spatial simulation and empirical observations |
title_full_unstemmed |
Managing visitor access to seabird colonies: a spatial simulation and empirical observations |
title_sort |
managing visitor access to seabird colonies: a spatial simulation and empirical observations |
publisher |
Wiley |
publishDate |
2007 |
url |
http://dx.doi.org/10.1111/j.1474-919x.2007.00640.x https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1474-919X.2007.00640.x https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1474-919X.2007.00640.x |
genre |
rissa tridactyla Uria aalge uria |
genre_facet |
rissa tridactyla Uria aalge uria |
op_source |
Ibis volume 149, issue s1, page 102-111 ISSN 0019-1019 1474-919X |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1111/j.1474-919x.2007.00640.x |
container_title |
Ibis |
container_volume |
149 |
container_issue |
s1 |
container_start_page |
102 |
op_container_end_page |
111 |
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1800737443800940544 |