Distinguishing Marine Habitat Classification Concepts for Ecological Data Management

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Distinguishing Marine Habitat Classification Concepts for Ecological Data Management Vol. 397: 253–268, 2009 MARINE ECOLOGY PROGRESS SERIES Published December 17 doi: 10.3354/meps08317 Mar Ecol Prog Ser Contribution to the Theme Section ‘Conservation and management of deep-sea corals and coral reefs’ OPENPEN ACCESSCCESS Distinguishing marine habitat classification concepts for ecological data management Mark J. Costello* Leigh Marine Laboratory, University of Auckland, Box 349, Warkworth, Northland 0941, New Zealand ABSTRACT: Including ecology in biodiversity data management systems requires classifications of habitat terms that provide standard definitions and indicate their relationships. In addition to data- bases, a wide range of intergovernmental, conservation and fishery organizations require classifica- tions of habitats and ecosystems to enable comparisons between areas and organize information in maps and reports. However, all of the terms used to describe habitats are concepts whose definition is context-dependent. This paper reviews the key concepts and ecological perspectives involved in classifying marine ‘habitats’ and ‘biotopes’ (habitat plus its associated species) so as to advise how they may be used in data management systems. Classifications of biotopes provide practical mea- sures of biodiversity at the ecosystem level. As an example the habitat of a benthic invertebrate is very different in spatial scale to that of a parasite, plankton, tuna or whale. Habitats can be geophys- ical and/or biogenic, and may operate at different spatial scales. For example, aggregations of deep- sea coral colonies <1 m in diameter may form km-scale reefs which contain other habitats (e.g. sedi- ments, sponges). An ecosystem can be physiographically defined as a lagoon, seamount, estuary, abyssal plain or entire ocean. Different sampling methods will define different regions, such as satel- lite images of ocean colour, acoustic maps of the seabed, in situ sampling of water or sediment cores and maps derived from analyses of species distributions that may define biogeographic regions. Because they are sampled (and thus defined) by different methods and can operate at different spa- tial scales, separate classifications are recommended for (1) nekton, plankton and benthos and (2) regions (defined to suit political, geographic or management areas), seascapes (defined by topogra- phy or water mass), biotopes and guilds (e.g. based on body size, diet or sampling method). Further- more, it is recommended to record the measurable features used to describe biotopes (e.g. depth, dominant species, substratum) and to avoid imposing a classification hierarchy where the concepts and methods of defining them are different. Indeed, one can let users create the most parsimonious classification for their purposes. KEY WORDS: Methods · Biogeography · Ocean · Biotope · Seascape · Eco-informatics · Biodiversity Resale or republication not permitted without written consent of the publisher INTRODUCTION characteristic species, their benthic or pelagic nature, intertidal zonation, substratum, salinity, wave action, Habitat classifications are required for reporting, depth and light penetration, and proposed a classifica- mapping and comparative analysis of ecological data. tion from the seashore to abyssal plain off the west Since the early 19th century, they have been devel- coast of Ireland. Such classifications permit: habitats oped for local and regional surveys to help organise and marine resources (e.g. shellfish beds) to be and describe the environment and associated assem- mapped at different spatial scales to visualise their dis- blages of species in a consistent manner (e.g. Pérès & tribution and manage their harvest; ecosystem pro- Picard 1964, Connor et al. 2004, 2006, Valentine et al. cesses and services to be quantified in space and time; 2005). Southern (1915) reviewed 14 publications since species to be grouped according to their habitat for 1832 that distinguished marine habitats based on their ecological data analysis; and prediction of species *Email: [email protected] © Inter-Research 2009 · www.int-res.com 254 Mar Ecol Prog Ser 397: 253–268, 2009 occurrence from physical environmental data (e.g. The Group on Earth Observations (GEO) is a partner- Southern 1915, Zacharias et al. 1999, Costello et al. ship of over 80 countries that plan to create a Global 1990, 1999, Costello 1992, Connor et al. 2004, Andre- Earth Observation System of Systems (GEOSS) that will fouet et al. 2005, Costello & Emblow 2005, Cattrijsse & require a method of classifying marine ecosystems (An- Hempel 2006, Redfern et al. 2006, Mumby et al. 2008). drefouet et al. 2008). However, to make these data eco- Different habitats will require different sampling logically relevant requires classifying the species or their methods, so habitat classifications also provide a basis locations according to their environment. Classifications for designing monitoring programmes to assess envi- derived from local studies may not be suitable for appli- ronmental quality (Diaz et al. 2004). cation to studies from other geographic areas and/or Environmental management and conservation re- which used different sampling methods. Thus it has been quires standardised classifications and terminology for unclear how globally applicable databases should clas- habitats to enable consistent mapping of the environ- sify their data ecologically. This paper describes the key ment across all possible habitats. This aids ranking of concepts and considerations in designing marine habitat areas for conservation management, such as in select- classifications, including a short review of terminology. It ing locations for Marine Protected Areas (MPAs) so then outlines how such data can be organised using exist- they are representative of the habitats of the country or ing geographic classifications and how each datum could region. In this instance, habitats are used as a surro- be labelled according to standard habitat descriptors. gate for biodiversity because it is impractical to sample and map all species distributions in a region. However, as most ecological studies are local to regional in scale, KEY CONCEPTS AND TERMINOLOGY the scope and structure of their classifications have been specific to their study areas. The terms habitat, biodiversity, ecosystem and eco- The classification of biological species creates a phy- tone are concepts, and thus can only be defined in a logenetic hierarchy that represents a species’ evolu- certain context. This context depends upon the species tionary history. In contrast, there is no common con- of interest and the sampling methods, thus different ceptual framework to provide a standard definition methods will provide different definitions of each term. and classification of habitats, ecosystems and related concepts (Jax 2006). They are variously defined by fea- tures such as geography, topography, sediment grain Habitats from perspectives of nekton, plankton and size, nutrients, salinity, temperature and/or species benthos composition. Thus, to develop a global classification that covers all marine biodiversity, benthic and It is generally agreed that a habitat is defined as the pelagic, shallow and deep sea, at a variety of spatial physical and chemical environment in which a species scales, is challenging. lives. Researchers considering free-swimming and wide- During this decade, an increasing amount of marine ranging animals such as birds, mammals, turtles and fish species distribution data has been published online (nekton) are likely to have different perspectives on (Costello & Vanden Berghe 2006). For example, the habitat than those studying plankton and benthos. These Ocean Biogeographic Information System (OBIS) pub- 3 different perspectives also involve completely different lishes about 19 million records of over 100 000 species methods of observation and sampling. Furthermore, from 600 data sets (www.iobis.org, Costello et al. 2007). these species vary in their spatial distribution on very dif- The Global Biodiversity Information Facility (GBIF) ferent time scales. Nekton may move significant dis- contains all the data from OBIS with similar mapping tances within minutes, whereas plankton move little but tools, plus additional data (http://data.gbif.org). One within a moving water mass, and benthic fauna and flora of the largest contributors to OBIS, OBIS-SEAMAP, may never move within their lifetime (O’Dor et al. 2009). enables exploration and analysis of marine mammal, Both the environmental conditions and spatial area will bird and turtle distributions (Halpin et al. 2006, Best et be different for these different biota. Thus to combine the al. 2007), while FishBase provides all kinds of informa- 3 perspectives of nekton, plankton and benthos within a tion on fish (Froese & Pauly 2009). Another OBIS con- single habitat classification seems unnecessary and is tributor, Hexacorallia, provides a world database on potentially misleading about their relationships. sea anemones with tools for mapping species against environmental data (Guinotte et al. 2006), and Aqua- Maps provides predicted and editable species range Ecosystems maps (Kaschner et al. 2008). However, at present none of these resources has a habitat classification to place Ecosystems are the combination of one or more habi- these species distribution data in an ecological context. tats with communities of species that can be consid- Costello: Marine habitat classification 255 ered a functional unit (Jax 2006). They are connected marine and freshwater
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