Modelling distribution and fate of coralligenous habitat in the Northern Adriatic Sea under a severe climate change scenario

被引:4
作者
Vitelletti, Maria Letizia [1 ]
Manea, Elisabetta [1 ]
Bongiorni, Lucia [1 ]
Ricchi, Antonio [2 ,3 ]
Sangelantoni, Lorenzo [3 ,4 ]
Bonaldo, Davide [1 ]
机构
[1] CNR Consiglio Nazl Ric, ISMAR Ist Sci Marine, Venice, Italy
[2] Univ Aquila, Dept Phys & Chem Sci, Laquila, Italy
[3] Univ Aquila, Ctr Excellence Telesensing Environm & Model Predic, Laquila, Italy
[4] Fdn Ctr Euro Mediterraneo Cambiamenti Climatici CM, Climate Simulat & Predict CSP, Bologna, Italy
关键词
coralligenous conservation; habitat suitability modelling; climate change; random forest; MaxEnt; machine learning; SPECIES DISTRIBUTION MODELS; GENERAL-CIRCULATION; CHANGE IMPACTS; RANDOM FOREST; EURO-CORDEX; ECOSYSTEM; BIODIVERSITY; SHIFTS; ASSEMBLAGES; COMMUNITIES;
D O I
10.3389/fmars.2023.1050293
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Due to their well-acknowledged capability in predicting habitat distributions, Habitat Suitability Models (HSMs) are particularly useful for investigating ecological patterns variations under climate change scenarios. The shallow coastal regions of the Northern Adriatic Sea, a sub-basin of the Mediterranean Sea, are studded with coralligenous outcrops recognized as important biodiversity hotspots exposed to the effects of climate change. In this research, we investigate the distributions of the Northern Adriatic Sea coralligenous habitats characterized by diverse species assemblages differently influenced by environmental factors, and provide a projection of how these might be impacted by climate change. Two models (Random Forest and MaxEnt), populated with occurrence data gathered from previous publications, environmental parameters' from online databases (CMEMS, Bio-Oracle), and a set of dedicated ocean model simulations, are applied in recent past conditions and under a future severe climate change scenario (RCP 8.5). The model performance metrics confirm the ability of both approaches for predicting habitat distribution and their relationship with environmental conditions. The results show that salinity, temperature, and nitrate concentration are generally the most relevant variables in affecting the coralligenous outcrops distribution. The environmental variations projected under climate change conditions are expected to favour the spreading of opportunistic organisms, more tolerant to stressful conditions, at the expense of more vulnerable species. This will result in a shift in the distribution of these habitats, with a consequent potential loss of biodiversity in the Northern Adriatic Sea.
引用
收藏
页数:19
相关论文
共 50 条
[41]   Present and future habitat shifts of the most important commercial fish species in the Black Sea under climate change [J].
Gul, Serkan ;
Ceylan, Yusuf ;
Dalgic, Goktug .
ENVIRONMENTAL SCIENCES EUROPE, 2025, 37 (01)
[42]   Habitat distribution modelling to identify areas of high conservation value under climate change for Mangifera sylvatica Roxb. of Bangladesh [J].
Akhter, Sayma ;
McDonald, Morag A. ;
van Breugel, Paulo ;
Sohel, Shawkat ;
Kjaer, Erik Dahl ;
Mariott, Ray .
LAND USE POLICY, 2017, 60 :223-232
[43]   Modelling potential distribution of Tuta absoluta in China under climate change using CLIMEX and MaxEnt [J].
Zhao, Jinyu ;
Ma, Li ;
Song, Chengfei ;
Xue, Zengsheng ;
Zheng, Ruirui ;
Yan, Xizhong ;
Hao, Chi .
JOURNAL OF APPLIED ENTOMOLOGY, 2023, 147 (10) :895-907
[44]   The Potential Distribution of Tree Species in Three Periods of Time under a Climate Change Scenario [J].
Antunez, Pablo ;
Ernesto Suarez-Mota, Mario ;
Valenzuela-Encinas, Cesar ;
Ruiz-Aquino, Faustino .
FORESTS, 2018, 9 (10)
[45]   GEOSPATIAL DISTRIBUTION VARIATION OF THE PARIS POLYPHYLLA (MELANTHIACEAE) IN CHINA UNDER CLIMATE CHANGE SCENARIO [J].
Hong-Qun, Li ;
Xiao-Long, Peng ;
Peng, Jiang ;
Xie-Ping, Sun ;
Ligang, Xing .
PAKISTAN JOURNAL OF BOTANY, 2024, 56 (03) :1067-1074
[46]   Modelling the current and future distribution of Kigelia africana under climate change in Benin, West Africa [J].
Guidigan M.L.G. ;
Azihou F. ;
Idohou R. ;
Okhimamhe A.A. ;
Fandohan A.B. ;
Sinsin B. ;
Adet L. .
Modeling Earth Systems and Environment, 2018, 4 (3) :1225-1238
[47]   Modelling the potential distribution of two tropical freshwater fish species under climate change scenarios [J].
de Jesus Sauz-Sanchez, Jonathan ;
Rodiles-Hernandez, Rocio ;
Andrade-Velazquez, Mercedes ;
Mendoza-Carranza, Manuel .
AQUATIC CONSERVATION-MARINE AND FRESHWATER ECOSYSTEMS, 2021, 31 (10) :2737-2751
[48]   Deep-sea lobster shifts in distribution and population connectivity under future climate change [J].
Roach, Christopher J. ;
Jeffs, Andrew G. ;
van der Reis, Aimee L. ;
de Souza, Joao Marcos Azevedo Correia ;
Behrens, Erik .
NEW ZEALAND JOURNAL OF MARINE AND FRESHWATER RESEARCH, 2025,
[49]   Predicted scarcity of suitable habitat for alpine plant communities in northern Japan under climate change [J].
Amagai, Yukihiro ;
Oguma, Hiroyuki ;
Ishihama, Fumiko .
APPLIED VEGETATION SCIENCE, 2022, 25 (04)
[50]   Species Distribution Modelling predicts habitat suitability and reduction of suitable habitat under future climatic scenario for Sclerophrys perreti: A critically endangered Nigerian endemic toad [J].
Nneji, Lotanna M. ;
Salako, Gabriel ;
Oladipo, Segun O. ;
Ayoola, Adeola O. ;
Onadeko, Abiodun B. ;
Adedeji, Babatunde E. ;
Omotoso, Olatunde ;
Ugwumba, Adiaha Alda A. ;
Adeola, Adeniyi C. .
AFRICAN JOURNAL OF ECOLOGY, 2020, 58 (03) :481-491