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Evaluating the usefulness of NDVI time series in modelling the distribution of priority reptiles of Greece
Tumukunde, Clarisse (2022) Evaluating the usefulness of NDVI time series in modelling the distribution of priority reptiles of Greece.
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| Abstract: | Biodiversity is a major public discussion topic, especially changes in biodiversity caused by human and natural processes. Sustaining biodiversity requires an awareness of its geographical distribution and pattern, as well as an understanding of the mechanisms that drive biodiversity at various scales. Greece is home to a large proportion of European species that are vulnerable on a European scale and thus bears considerable responsibility for protecting them within its borders. As a member of the European Union, Greece has pledged to prevent biodiversity loss and, like other EU members, will report every six years on the conservation status of its species. One of the potential approaches is to identify the key environmental variables that influence species distribution. Most early research that used species distribution models (SDM) at large spatial ranges (e.g., global, national, or regional) relied only on climatic/topographic predictors. Remotely sensed datasets are becoming more useful in SDM for identifying, characterising, and predicting animal habitats. In this study, species distribution modelling was carried out in Greece to evaluate the usefulness of using variables derived from the time-series of MODIS NDVI in models predicting the distribution of 42 priority reptiles in Greece. The modelling used data representing 7897 observations after data thinning, 42 species after removing the species with records below the number of explanatory variables, and 20 explanatory variables after removing correlated variables. Hyper-temporal NDVI and other environmental variables (e.g., climate, topography, geology) were used as biophysical features of the ecosystem. The three sets of models were built in Maxent (maximum entropy modelling), which are NDVI-based, commonly used, and combined. The discrimination power of these models was assessed by using the area under the receiver operating characteristic (AUC) and True skill statistic (TSS). The predictability of NDVI time series-based variables was investigated by comparing the commonly used and combined model performance. The results showed that MODIS NDVI-based metrics did not improve the model performance, however AUC and TSS slightly increased. Furthermore, the discriminating power measured by AUC showed that the NDVI-based model is a good predictor with a mean above 0.7, while TSS contradicts this with a mean of 0.35. Although NDVI-based metrics did not improve the model performance, it was among the four most important variables to 7 species, showing that it has valuable information to model certain reptiles. Precipitation of driest month and digital elevation model were the most important variables across many species. The findings of this research may contribute significantly to a better understanding of the ecological requirements of the species and may assist in setting priorities regarding conservation of reptiles in Greece. |
| Item Type: | Essay (Master) |
| Faculty: | ITC: Faculty of Geo-information Science and Earth Observation |
| Programme: | Geoinformation Science and Earth Observation MSc (75014) |
| Link to this item: | https://purl.utwente.nl/essays/107670 |
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