We present a new biodiversity monitoring tool in Google Earth Engine (GEE) to measure trends in species habitat suitability over time using ecological niche models (ENMs) with a time series of satellite products. Focusing on Montesinho Natural Park (MNP) in northeastern Portugal, the application uses MaxEnt to calculate species distribution models for amphibians, birds, mammals, vascular plants, and reptiles with data from six Moderate Resolution Imaging Spectroradiometer (MODIS) products from 2001 to 2023. Habitat suitability trends are estimated with the Mann-Kendall test. The main result is a map for each modelled species showing positive, negative, or null trends over time; a negative trend indicates a monotonic decrease in habitat suitability. The application allows users to select species, the temporal period, the number of model replicates, and the proportion of training and test records. Analyses run intuitively in less than a minute, displaying several results: the mean MaxEnt model over time, Mann-Kendall trends for the study area, species presences, significant pixels, and species presences in significant pixels, main MaxEnt outputs, including Area Under the Curve (AUC) values, variable contributions, plots of global predictor variable contributions over time, average trend values, and MaxEnt parameters. Decision-makers and conservation planners can use this application as a complementary tool for biodiversity monitoring and conservation.
The Montesinho Natural Park (MNP) is one of the largest protected areas in Portugal, covering an area of 74,225 hectares in the extreme northeast of the country. MNP hosts a wide range of endemic and highly threatened species and priority habitats such as oak forests, meadows, grasslands, and bushlands. However, human activities continue to pose a significant challenge to conservation. To address this challenge, the MontObEO project aims to implement an early warning system to identify changes in habitat suitability and species extinction risk over time and space in the MNP, using a time series of satellite remote sensing data and ecological niche models (SRS-ENMs). Herein, we compiled biodiversity data for five major taxonomic groups (flora-vascular plants, amphibians, reptiles, birds, and mammals) and yearly remote sensing products from MODIS sensors between 2000 and 2021. We conducted all the satellite data processing and modelling procedures in Google Earth Engine (GEE) platform using the MaxEnt algorithm. We measured trends in species’ habitat suitability with the Mann-Kendall test, a non-parametric test for monotonic trend detection in a time series. Those species with stronger decreasing trends will have higher extinction risks. Additionally, we developed a ready-to-use web geographic information system (Web GIS) to map individual species distributions with a high spatial resolution (1 km). This project provides tools for biodiversity conservation in the MNP to help in the decision-making process for conservation planning and could serve as a model for other national or international protected areas.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.