Understanding the population consequences of disturbance

Ecology and Evolution - Tập 8 Số 19 - Trang 9934-9946 - 2018
Enrico Pirotta1,2, Cormac Booth3, Daniel P. Costa4, Erica Fleishman5,6, Scott D. Kraus7, David Lusseau8, David Moretti9, Leslie New1, Robert S. Schick10,11, Lisa K. Schwarz12, Samantha E. Simmons13, Len Thomas10, Peter L. Tyack14, Michael J. Weise15, Randall S. Wells16, John Harwood10
1Department of Mathematics and Statistics Washington State University Vancouver Washington
2School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland
3SMRU Consulting New Technology Centre St Andrews UK
4Department of Ecology and Evolutionary Biology University of California Santa Cruz California
5Department of Environmental Science and Policy University of California Davis California
6Department of Fish, Wildlife and Conservation Biology Colorado State University Fort Collins Colorado
7Anderson-Cabot Center for Ocean Life New England Aquarium Boston Massachusetts
8School of Biological Sciences, University of Aberdeen, Aberdeen, UK
9Naval Undersea Warfare Center Newport Rhode Island
10Centre for Research into Ecological and Environmental Modelling, University of St. Andrews, St. Andrews, UK
11Duke University, Durham, North Carolina
12Institute of Marine Sciences University of California Santa Cruz California
13Marine Mammal Commission Bethesda Maryland
14Sea Mammal Research Unit, Scottish Oceans Institute, School of Biology, University of St Andrews, St Andrews, UK
15Office of Naval Research Marine Mammal & Biology Program Arlington Virginia
16Chicago Zoological Society's Sarasota Dolphin Research Program c/o Mote Marine Laboratory Sarasota Florida

Tóm tắt

Abstract

Managing the nonlethal effects of disturbance on wildlife populations has been a long‐term goal for decision makers, managers, and ecologists, and assessment of these effects is currently required by European Union and United States legislation. However, robust assessment of these effects is challenging. The management of human activities that have nonlethal effects on wildlife is a specific example of a fundamental ecological problem: how to understand the population‐level consequences of changes in the behavior or physiology of individual animals that are caused by external stressors. In this study, we review recent applications of a conceptual framework for assessing and predicting these consequences for marine mammal populations. We explore the range of models that can be used to formalize the approach and we identify critical research gaps. We also provide a decision tree that can be used to select the most appropriate model structure given the available data. Synthesis and applications: The implementation of this framework has moved the focus of discussion of the management of nonlethal disturbances on marine mammal populations away from a rhetorical debate about defining negligible impact and toward a quantitative understanding of long‐term population‐level effects. Here we demonstrate the framework's general applicability to other marine and terrestrial systems and show how it can support integrated modeling of the proximate and ultimate mechanisms that regulate trait‐mediated, indirect interactions in ecological communities, that is, the nonconsumptive effects of a predator or stressor on a species' behavior, physiology, or life history.

Từ khóa


Tài liệu tham khảo

10.1002/aqc.2393

10.1111/j.0021-8901.2004.00900.x

10.1016/j.ecolmodel.2017.02.002

10.1111/j.1365-2664.2005.01071.x

10.1093/conphys/cov001

10.3354/meps08888

10.1002/ece3.4180

10.1111/j.1748-7692.2009.00298.x

Caswell H., 2001, Matrix population models

10.1002/jwmg.836

10.1002/ecs2.1468

10.1111/conl.12166

10.3354/meps10163

10.1016/j.jembe.2014.05.014

10.1111/1365-2435.12200

10.1111/brv.12184

10.1086/671165

10.1121/1.1538248

10.1121/2.0000298

Costa D. P., 2017, Encyclopedia of marine mammals, 329

10.1007/978-1-4939-2981-8_19

10.1111/j.1600-0706.2012.00035.x

10.1111/mms.12171

10.1111/j.1461-0248.2007.01121.x

10.1890/07-1153.1

10.1111/1365-2435.13117

10.1242/jeb.071498

10.1098/rspb.2012.1700

10.1016/j.biocon.2006.05.019

10.3354/esr00727

10.1086/499438

10.1098/rsos.170629

10.3354/meps12457

10.1111/mms.12310

10.5751/ES-00404-060111

10.1016/0006-3207(95)00060-7

10.1016/S0006-3207(00)00002-1

10.1098/rspb.2014.1840

10.1007/s10531-017-1469-7

Grimm V., 2013, Individual‐based modeling and ecology

10.1046/j.1365-2664.2002.00713.x

10.1111/1365-2664.12955

10.1016/j.tree.2003.08.001

10.1111/j.1748-7692.2008.00277.x

10.1098/rspb.2011.2088

Houston A. I., 1999, Models of adaptive behavior: An approach based on state

10.1016/j.biocon.2006.04.022

10.1111/1365-2664.12911

10.1016/j.jembe.2015.07.016

10.1016/j.envsoft.2016.11.001

10.1046/j.1523-1739.2002.99290.x

10.1016/j.biocon.2007.04.014

10.1111/2041-210X.12411

10.1111/j.1365-2664.2005.01109.x

10.1578/AM.36.3.2010.239

10.2307/1313225

10.1111/j.1523-1739.2003.00054.x

10.1121/1.2229287

Mangel M., 1988, Dynamic modeling in behavioral ecology

10.1111/j.1523-1739.2011.01806.x

10.1016/j.biocon.2003.11.012

10.1016/j.dsr2.2007.11.002

10.1111/2041-210X.12701

10.3354/meps12041

10.1017/S0954102000000195

10.1046/j.1365-2656.2003.00685.x

10.1111/1365-2656.12611

10.1111/conl.12420

10.1111/ele.12133

10.1037/0735-7036.115.3.227

10.3354/meps09675

10.1016/j.dsr.2009.02.008

10.1111/1365-2664.12887

10.1371/journal.pone.0085064

10.1016/j.ecolmodel.2013.09.025

10.1111/conl.12563

National Academies, 2017, Approaches to understanding the cumulative effects of stressors on marine mammals

National Research Council, 2005, Marine mammal populations and ocean noise: Determining when noise causes biologically significant effects

10.1038/srep25539

10.3354/meps10547

10.1016/j.ocecoaman.2015.04.006

10.1111/1365-2435.12052

10.1371/journal.pone.0068725

10.1111/j.1748-7692.2010.00386.x

10.1016/j.anbehav.2016.07.019

10.3354/esr00699

10.1002/aqc.2668

10.1126/science.aan8677

10.1890/07-1131.1

10.3354/esr00800

10.1098/rspb.2015.2109

10.1086/695135

10.1016/j.biocon.2014.11.003

10.1016/j.ecolmodel.2014.03.009

10.1002/aqc.2892

10.1111/acv.12132

10.1016/j.biocon.2011.11.005

10.1016/j.biocon.2004.10.003

10.1098/rspb.2011.2429

10.3354/meps11547

10.1111/1365-2664.12678

10.1371/journal.pone.0064166

10.1111/1365-2656.12102

10.1111/j.1461-0248.2003.00560.x

10.3354/esr00777

10.1111/1365-2435.12434

10.1111/2041-210x.12002

10.1016/j.biocon.2008.06.026

10.1006/anbe.1998.0896

10.1111/j.1748-7692.2006.00092.x

10.1002/zoo.1430090507

10.1371/journal.pone.0017009

10.3354/esr00843

10.1890/ES15-00146.1

10.1111/1365-2656.12817

10.1007/s10393-004-0094-6

10.1242/jeb.161232

10.1890/0012-9658(2003)084[1083:AROTII]2.0.CO;2

10.1111/j.1365-2656.2006.01093.x

10.1016/j.tree.2005.10.018

10.1126/science.aao2740

10.1242/jeb.154245

10.1016/j.biocon.2006.06.010

10.1016/j.marpol.2016.04.023

10.1017/S0952836902000298

10.1111/cobi.12486

10.1111/1365-2664.12419