Managers, modelers, and measuring the impact of species distribution model uncertainty on marine zoning decisions

被引:6
作者
Costa, Bryan [1 ]
Kendall, Matthew [1 ]
McKagan, Steven [2 ]
机构
[1] NOAA, Natl Ctr Coastal Ocean Sci, Biogeog Branch, Silver Spring, MD 20910 USA
[2] NOAA, Natl Marine Fisheries Serv, CNMI, Saipan, CM USA
来源
PLOS ONE | 2018年 / 13卷 / 10期
关键词
BOOSTED REGRESSION TREES; CONSERVATION MANAGEMENT; HABITAT MODELS; RESERVE DESIGN; PREDICTION; BIODIVERSITY; LAGOON; CLASSIFICATION; ASSEMBLAGES; PROTECTION;
D O I
10.1371/journal.pone.0204569
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Marine managers routinely use spatial data to make decisions about their marine environment. Uncertainty associated with this spatial data can have profound impacts on these management decisions and their projected outcomes. Recent advances in modeling techniques, including species distribution models (SDMs), make it easier to generate continuous maps showing the uncertainty associated with spatial predictions and maps. However, SDM predictions and maps can be complex and nuanced. This complexity makes their use challenging for non-technical managers, preventing them from having the best available information to make decisions. To help bridge these communication and information gaps, we developed maps to illustrate how SDMs and associated uncertainty can be translated into readily usable products for managers. We also explicitly described the potential impacts of uncertainty on marine zoning decisions. This approach was applied to a case study in Saipan Lagoon, Commonwealth of the Northern Mariana Islands (CNMI). Managers in Saipan are interested in minimizing the potential impacts of personal watercraft (e.g., jet skis) on staghorn Acropora (i.e., Acropora aspera, A. formosa, and A. pulchra), which is an important coral assemblage in the lagoon. We used a recently completed SDM for staghorn Acropora to develop maps showing the sensitivity of zoning options to three different prediction and three different uncertainty thresholds (nine combinations total). Our analysis showed that the amount of area and geographic location of predicted staghorn Acropora presence changed based on these nine combinations. These dramatically different spatial patterns would have significant zoning implications when considering where to exclude and/or allow jet skis operations inside the lagoon. They also show that different uncertainty thresholds may lead managers to markedly different conclusions and courses of action. Defining acceptable levels of uncertainty upfront is critical for ensuring that managers can make more informed decisions, meet their marine resource goals and generate favorable outcomes for their stakeholders.
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页数:25
相关论文
共 73 条
  • [1] Practical solutions for making models indispensable in conservation decision-making
    Addison, Prue F. E.
    Rumpff, Libby
    Bau, S. Sana
    Carey, Janet M.
    Chee, Yung En
    Jarrad, Frith C.
    McBride, Marissa F.
    Burgman, Mark A.
    [J]. DIVERSITY AND DISTRIBUTIONS, 2013, 19 (5-6) : 490 - 502
  • [2] [Anonymous], R LANG ENV STAT COMP
  • [3] [Anonymous], 2001, ELEMENTS STAT LEARNI
  • [4] [Anonymous], 2011, J MAR BIOL, DOI DOI 10.1155/2011/940765
  • [5] Error and uncertainty in habitat models
    Barry, Simon
    Elith, Jane
    [J]. JOURNAL OF APPLIED ECOLOGY, 2006, 43 (03) : 413 - 423
  • [6] Battista T. A., 2007, 59 NOAA NOS NCCOS
  • [7] Battista T. A., 2007, 61 NOAA NOS NCCOS
  • [8] Battista TA, 2005, NCCOS8 NOAA NOS BIOG
  • [9] A stochastic approach to marine reserve design: Incorporating data uncertainty
    Beech, Talia
    Dowd, Michael
    Field, Chris
    Hatcher, Bruce
    Andrefouet, Serge
    [J]. ECOLOGICAL INFORMATICS, 2008, 3 (4-5) : 321 - 333
  • [10] Ben-Haim Y., 2001, INFORM GAP DECISION