RT info:eu-repo/semantics/article
T1 Species Distribution Models at Regional Scale: Cymodocea nodosa Seagrasses
A1 Arbelo Pérez, Manuel Imeldo
A1 Casas Más, Enrique José
A1 Martín-García, Laura
A1 Hernández Leal, Pedro Alberto
A2 Física
K1 Cymodocea nodosa
K1 remote sensing
K1 species distribution models
K1 ensemble model
K1 invest
K1 ecosystem services
K1 monetary assessment
K1 habitat suitability models
K1 coastal ecosystems
K1 oceanographic variables
AB Despite their ecological and socio-economic importance, seagrasses are often overlooked in comparison with terrestrial ecosystems. In the Canarian archipelago (Spain), Cymodocea nodosa is the best-established species, sustaining the most important marine ecosystem and providing ecosystem services (ES) of great relevance. Nevertheless, we lack accurate and standardized information regarding the distribution of this species and its ES supply. As a first step, the use of species distribution models is proposed. Various machine learning algorithms and ensemble model techniques were considered along with freely available remote sensing data to assess Cymodocea nodosa’s potential distribution. In a second step, we used InVEST software to estimate the ES provision by this phanerogam on a regional scale, providing spatially explicit monetary assessments and a habitat degradation characterization due to human impacts. The distribution models presented great predictive capabilities and statistical significance, while the ES estimations were in concordance with previous studies. The proposed methodology is presented as a useful tool for environmental management of important communities sensitive to human activities, such as C. nodosa meadows.
YR 2022
FD 2022
LK http://riull.ull.es/xmlui/handle/915/36913
UL http://riull.ull.es/xmlui/handle/915/36913
LA en
NO https://doi.org/10.3390/rs14174334
DS Repositorio institucional de la Universidad de La Laguna
RD 29-may-2024