Traffic intensification, often in conjunction with habitat fragmentation, has caused frequent roadkill incidents, particularly among reptiles, amphibians, and other taxa. Herpetofauna species, which are slow moving and habitat dependent, are particularly susceptible to these incidents because they often use roads during thermoregulation. Lesvos, the eighth-largest Mediterranean island, boasts a biodiversity that surpasses most other Mediterranean islands of similar or larger size, with a plethora of herpetofauna species inhabiting its terrain. In recent years, new roads were constructed on Lesvos, which are considered to be one of the most important factors that negatively affect the island’s wildlife as they increase the non-natural mortality of animals, are obstacles to their mobility, and reduce the connectivity of populations by limiting their dynamics. In the present study, we examined the road mortality of amphibians and reptiles by analyzing (a) the temporal and seasonal patterns of such incidents, (b) the relationship between roadside habitats and road network characteristics with the roadkilled herpetofauna species, and (c) their spatial distribution on Lesvos during the years 2009–2012 and 2016–2019. To identify significant clusters of reptile and amphibian roadkills, we performed hotspot analysis by utilizing kernel density estimation and Getis Ord Gi* statistics. We recorded a total of 330 roadkills among 20 species, with the highest rates emerging among the European green toad (Bufotes viridis), the European glass lizard (Pseudopus apodus), the Rhodos green lizard (Lacerta diplochondrodes), and the snake-eyed lizard (Ophisops elegans). Spatial statistical analysis revealed that roads close to herpetofauna habitats exhibit statistically significant clusters of roadkills that intensify during the spring season. Regular monitoring and mapping of herpetofauna road mortality will enable the implementation of management strategies to mitigate the negative impact of this phenomenon.
Conservation of traditional olive groves through effective monitoring of their health state is crucial both at a tree and at a population level. In this study, we introduce a comprehensive methodological framework for estimating the traditional olive grove health state, by considering the fundamental phenotypic, spectral, and thermal traits of the olive trees. We obtained phenotypic information from olive trees on the Greek island of Lesvos by combining this with in situ measurement of spectral reflectance and thermal indices to investigate the effect of the olive tree traits on productivity, the presence of the olive leaf spot disease (OLS), and olive tree classification based on their health state. In this context, we identified a suite of important features, derived from linear and logistic regression models, which can explain productivity and accurately evaluate infected and noninfected trees. The results indicated that either specific traits or combinations of them are statistically significant predictors of productivity, while the occurrence of OLS symptoms can be identified by both the olives’ vitality traits and by the thermal variables. Finally, the classification of olive trees into different health states possibly offers significant information to explain traditional olive grove dynamics for their sustainable management.
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