Schlacher T.A., Schoeman D.S., Jones A.R., Dugan J.E., Hubbard D.M., Defeo O., Peterson C.H., Weston M.A., Maslo B., Olds A.D., Scapini F., Nel R., Harris L.R., Lucrezi S., Lastra M., Huijbers C.M., Connolly R.M.
School of Science and Engineering, The University of the Sunshine Coast, Q-4558 Maroochydore, Australia; Division of Invertebrates, The Australian Museum, Sydney, NSW 2010, Australia; Marine Science Institute, University of California, Santa Barbara, CA 93106-6150, United States; UNDECIMAR, Facultad de Ciencias, Igua 4225, PO Box 10773, 11400 Montevideo, Uruguay; Institute of Marine Sciences, University of North Carolina, Chapel Hill, Morehead City, NC 28557, United States; Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood, VIC 3125, Australia; Department of Ecology, Evolution and Natural Resources, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, NJ 08901, United States; Department of Biology, University of Florence, via Romana 17, 50125 Firenze, Italy; Department of Zoology, Nelson Mandela Metropolitan University, Port Elizabeth, 6031, South Africa; TREES-Tourism Research in Economic Environs and Society, North-West University, Potchefstroom, South Africa; Department of Ecology and Animal Biology, Faculty of Marine Science, University of Vigo, 36310 Vigo, Spain; Australian Rivers Institute, Coast and Estuaries, and School of Environment, Gold Coast Campus, Griffith University, QLD, 4222, Australia
Schlacher, T.A., School of Science and Engineering, The University of the Sunshine Coast, Q-4558 Maroochydore, Australia; Schoeman, D.S., School of Science and Engineering, The University of the Sunshine Coast, Q-4558 Maroochydore, Australia; Jones, A.R., Division of Invertebrates, The Australian Museum, Sydney, NSW 2010, Australia; Dugan, J.E., Marine Science Institute, University of California, Santa Barbara, CA 93106-6150, United States; Hubbard, D.M., Marine Science Institute, University of California, Santa Barbara, CA 93106-6150, United States; Defeo, O., UNDECIMAR, Facultad de Ciencias, Igua 4225, PO Box 10773, 11400 Montevideo, Uruguay; Peterson, C.H., Institute of Marine Sciences, University of North Carolina, Chapel Hill, Morehead City, NC 28557, United States; Weston, M.A., Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood, VIC 3125, Australia; Maslo, B., Department of Ecology, Evolution and Natural Resources, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, NJ 08901, United States; Olds, A.D., School of Science and Engineering, The University of the Sunshine Coast, Q-4558 Maroochydore, Australia; Scapini, F., Department of Biology, University of Florence, via Romana 17, 50125 Firenze, Italy; Nel, R., Department of Zoology, Nelson Mandela Metropolitan University, Port Elizabeth, 6031, South Africa; Harris, L.R., Department of Zoology, Nelson Mandela Metropolitan University, Port Elizabeth, 6031, South Africa; Lucrezi, S., TREES-Tourism Research in Economic Environs and Society, North-West University, Potchefstroom, South Africa; Lastra, M., Department of Ecology and Animal Biology, Faculty of Marine Science, University of Vigo, 36310 Vigo, Spain; Huijbers, C.M., Australian Rivers Institute, Coast and Estuaries, and School of Environment, Gold Coast Campus, Griffith University, QLD, 4222, Australia; Connolly, R.M., Australian Rivers Institute, Coast and Estuaries, and School of Environment, Gold Coast Campus, Griffith University, QLD, 4222, Australia
Complexity is increasingly the hallmark in environmental management practices of sandy shorelines. This arises primarily from meeting growing public demands (e.g., real estate, recreation) whilst reconciling economic demands with expectations of coastal users who have modern conservation ethics. Ideally, shoreline management is underpinned by empirical data, but selecting ecologically-meaningful metrics to accurately measure the condition of systems, and the ecological effects of human activities, is a complex task. Here we construct a framework for metric selection, considering six categories of issues that authorities commonly address: erosion; habitat loss; recreation; fishing; pollution (litter and chemical contaminants); and wildlife conservation. Possible metrics were scored in terms of their ability to reflect environmental change, and against criteria that are widely used for judging the performance of ecological indicators (i.e., sensitivity, practicability, costs, and public appeal). From this analysis, four types of broadly applicable metrics that also performed very well against the indicator criteria emerged: 1.) traits of bird populations and assemblages (e.g., abundance, diversity, distributions, habitat use); 2.) breeding/reproductive performance sensu lato (especially relevant for birds and turtles nesting on beaches and in dunes, but equally applicable to invertebrates and plants); 3.) population parameters and distributions of vertebrates associated primarily with dunes and the supralittoral beach zone (traditionally focused on birds and turtles, but expandable to mammals); 4.) compound measurements of the abundance/cover/biomass of biota (plants, invertebrates, vertebrates) at both the population and assemblage level. Local constraints (i.e., the absence of birds in highly degraded urban settings or lack of dunes on bluff-backed beaches) and particular issues may require alternatives. Metrics - if selected and applied correctly - provide empirical evidence of environmental condition and change, but often do not reflect deeper environmental values per se. Yet, values remain poorly articulated for many beach systems; this calls for a comprehensive identification of environmental values and the development of targeted programs to conserve these values on sandy shorelines globally. © 2014 Elsevier Ltd.