Economic mapping and assessment of Cymodocea nodosa meadows as nursery grounds for commercially important fish species. A case study in the Canary Islands

IF 1.8 Q3 ECOLOGY One Ecosystem Pub Date : 2021-09-03 DOI:10.3897/oneeco.6.e70919
E. Casas, Laura Martín-García, F. Otero-Ferrer, F. Tuya, R. Haroun, M. Arbelo
{"title":"Economic mapping and assessment of Cymodocea nodosa meadows as nursery grounds for commercially important fish species. A case study in the Canary Islands","authors":"E. Casas, Laura Martín-García, F. Otero-Ferrer, F. Tuya, R. Haroun, M. Arbelo","doi":"10.3897/oneeco.6.e70919","DOIUrl":null,"url":null,"abstract":"Cymodocea nodosa seagrass meadows provide several socio-economically ecosystem services, including nurseries for numerous species of commercial interest. These seagrasses are experiencing a worldwide decline, with global loss rates approaching 5% per year, mainly related to coastal human activities. Cymodocea nodosa, the predominant seagrass in the Canary Archipelago (Spain), is also exposed to these threats, which could lead to habitat loss or even local disappearance. In this case study, we estimated the potential economic value of Cymodocea nodosa seagrass meadows for local fisheries at an archipelago scale. Habitat suitability maps were constructed using MAXENT 3.4.1, a software for modelling species distributions by applying a maximum entropy machine-learning method, from a set of environmental variables and presence and background records extracted from historical cartographies. This model allows characterising and assessing the C. nodosa habitat suitability, overcoming the implicit complexity derived from seasonal changes in this species highly dynamic meadows and using it as a first step for the mapping and assessment of ecosystem services. In a second step, value transfer methodologies were used, along with published economic valuations of commercially-interesting fish species related to C. nodosa meadows. We estimate that the potential monetary value of these species can add up to more than 3 million euros per year for the entire Archipelago. The simplicity of the proposed methodology facilitates its repeatability in other similar regions, using freely available data and hence, being suitable for data-scarce scenarios.","PeriodicalId":36908,"journal":{"name":"One Ecosystem","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"One Ecosystem","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3897/oneeco.6.e70919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 7

Abstract

Cymodocea nodosa seagrass meadows provide several socio-economically ecosystem services, including nurseries for numerous species of commercial interest. These seagrasses are experiencing a worldwide decline, with global loss rates approaching 5% per year, mainly related to coastal human activities. Cymodocea nodosa, the predominant seagrass in the Canary Archipelago (Spain), is also exposed to these threats, which could lead to habitat loss or even local disappearance. In this case study, we estimated the potential economic value of Cymodocea nodosa seagrass meadows for local fisheries at an archipelago scale. Habitat suitability maps were constructed using MAXENT 3.4.1, a software for modelling species distributions by applying a maximum entropy machine-learning method, from a set of environmental variables and presence and background records extracted from historical cartographies. This model allows characterising and assessing the C. nodosa habitat suitability, overcoming the implicit complexity derived from seasonal changes in this species highly dynamic meadows and using it as a first step for the mapping and assessment of ecosystem services. In a second step, value transfer methodologies were used, along with published economic valuations of commercially-interesting fish species related to C. nodosa meadows. We estimate that the potential monetary value of these species can add up to more than 3 million euros per year for the entire Archipelago. The simplicity of the proposed methodology facilitates its repeatability in other similar regions, using freely available data and hence, being suitable for data-scarce scenarios.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
作为重要商业鱼类苗圃的伞形草甸的经济制图与评价。加那利群岛的案例研究
结状Cymodocea nodosa海草草甸提供多种社会经济生态系统服务,包括许多具有商业价值的物种的苗圃。这些海草正在世界范围内减少,全球损失率接近每年5%,主要与沿海人类活动有关。加那利群岛(西班牙)的主要海草Cymodocea nodosa也面临这些威胁,这可能导致栖息地丧失甚至当地消失。在本案例研究中,我们估计了在群岛尺度上,结状Cymodocea nodosa海草草甸对当地渔业的潜在经济价值。利用MAXENT 3.4.1(物种分布建模软件),基于历史地图学中提取的环境变量、存在和背景记录,采用最大熵机器学习方法构建生境适宜性图。该模型可用于描述和评估石竹的生境适宜性,克服了该物种高度动态草甸的季节变化所带来的隐性复杂性,并将其作为绘制和评估生态系统服务的第一步。在第二步中,使用了价值转移方法,并公布了与C. nodosa草甸有关的具有商业价值的鱼类物种的经济估值。我们估计,这些物种的潜在货币价值每年可以为整个群岛增加300多万欧元。所提议的方法的简单性有助于其在其他类似区域的可重复性,使用可免费获得的数据,因此适合于数据匮乏的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
One Ecosystem
One Ecosystem Environmental Science-Nature and Landscape Conservation
CiteScore
4.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
期刊最新文献
CH4 and N2O emissions and their potential control by rice biomass biochar: The case of continuously flooded paddy fields in Indonesia - A review The influence of naturalness of the landscape structure on children’s connectedness to Nature in north-eastern Italy Historical reconstruction of the invasions of four non-native tree species at local scale: a detective work on Ailanthus altissima, Celtis occidentalis, Prunus serotina and Acer negundo As green infrastructure, linear semi-natural habitats boost regulating ecosystem services supply in agriculturally-dominated landscapes Practical framework for cultural ecosystem service in urban landscape design
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1