Benthos distribution modelling and its relevance for marine ecosystem management

Abstract

Marine benthic ecosystems are difficult to monitor and assess, which is in contrast to modern ecosystem-based management requiring detailed information at all important ecological and anthropogenic impact levels. Ecosystem management needs to ensure a sustainable exploitation of marine resources as well as the protection of sensitive habitats, taking account of potential multiple-use conflicts and impacts over large spatial scales. The urgent need for large-scale spatial data on benthic species and communities resulted in an increasing application of distribution modelling (DM). The use of DM techniques enables to employ full spatial coverage data of environmental variables to predict benthic spatial distribution patterns. Especially, statistical DMs have opened new possibilities for ecosystem management applications, since they are straightforward and the outputs are easy to interpret and communicate. Mechanistic modelling techniques, targeting the fundamental niche of species, and Bayesian belief networks are the most promising to further improve DM performance in the marine realm. There are many actual and potential management applications of DMs in the marine benthic environment, these are (i) early warning systems for species invasion and pest control, (ii) to assess distribution probabilities of species to be protected, (iii) uses in monitoring design and spatial management frameworks (e.g. MPA designations), and (iv) establishing long-term ecosystem management measures (accounting for future climate-driven changes in the ecosystem). It is important to acknowledge also the limitations associated with DM applications in a marine management context as well as considering new areas for future DM developments. The knowledge of explanatory variables, for example, setting the basis for DM, will continue to be further developed: this includes both the abiotic (natural and anthropogenic) and the more pressing biotic (e.g. species interactions) aspects of the ecosystem. While the response variables on the other hand are often focused on species presence and some work undertaken on species abundances, it is equally important to consider, e.g. biological traits or benthic ecosystem functions in DM applications. Tools such as DMs are suitable to forecast the possible effects of climate change on benthic species distribution patterns and hence could help to steer present-day ecosystem management.

High-Resolution Habitat Suitability Models for the Conservation and Management of Vulnerable Marine Ecosystems on the Louisville Seamount Chain, South Pacific Ocean

“…While our attempt to predict the distribution of VME habitat is currently defensible because no consensus exists about what density of corals is necessary to generate the structural and functional attributes of a VME, the lack of a robust density threshold-based definition of VME habitat potentially limits the acceptance of these maps for conservation and fisheries management purposes (see below). Nonetheless, the results of the present study are in line with the developments envisaged for habitat suitability modeling in order that predictive distribution maps can be better used for the spatial management of VMEs (Ross and Howell, 2013;Reiss et al, 2014;Rengstorf et al, 2014;Vierod et al, 2014;Robert et al, 2016). These improvements include our use of an abundance-based multimodel ensemble approach to produce high-resolution predictive distribution maps, and presentation of spatially explicit measures of model uncertainty for VME indicator taxa and VME habitat across a group of seamounts that are targeted by a specific fishery.…”

“…Habitat suitability modeling is being used increasingly to predict distribution patterns of VME indicator taxa in the deep sea, where data are particularly sparse, and such models are considered useful for marine ecosystem management (Ross and Howell, 2013;Reiss et al, 2014). Habitat suitability models have been produced for numerous deep-sea taxa (see review by Vierod et al, 2014), but the predicted distributions are dependent on how the models are constructed.…”

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

“…This contribution to the literature was written keeping this antinomy in mind, which can be summarized with a quote from Box and Draper (1987), who wrote that "essentially, all models are wrong, but some are useful, " and a subsequent quote by : "all spatial data are wrong, but some are useful." Despite their utility and their strong potential for clear and understandable communication, maps and models will always require scientific expert advice and interpretation (Reiss et al, 2015): we must be transparent with the mapping techniques and data, and recognize their respective limitations (Kindsvater et al, 2016). In addition, understanding the different trade-offs involved in the mapping process is critical when maps and models are used in marine conservation and management planning (Langford et al, 2009).…”

“…Biodiversity hotspots Bedulli et al, 2002;Allen, 2008 Ecosystem services Galparsoro et al, 2014;Outeiro et al, 2015 Uses of marine resources Buhl-Mortensen et al, 2015;Hossain et al, 2016 Threats to biodiversity Andersen et al, 2004;Harris, 2012 While the ability of maps and models to communicate relevant information about current and predicted states of the environment makes them ideal candidates in any attempt to (re)connect decision-making with science, how do we know that these spatial decision-support tools are conveying the right information? In fact, maps and models have downsides and their use in conservation and policy-making should be carefully examined (Reiss et al, 2015). In this contribution I ask, "What if the information extracted from such tools is misleading?"…”

What Is Marine Biodiversity? Towards Common Concepts and Their Implications for Assessing Biodiversity Status

“…(Bremner et al, 2006a,b;Cochrane et al, 2012) but these have not previously been the main focus of structural biodiversity; most methods have centered on the plethora of quantitative means of defining benthic community structure (Gray and Elliott, 2009). However, recognizing and measuring functional diversity within the benthos also has become of increasing importance from a management perspective (Reiss et al, 2015). A high biodiversity, including species richness, may enhance ecosystem processes and promote long-term stability by buffering, or insuring, against environmental fluctuations (Yachi and Loreau, 1999;Loreau, 2000).…”