The present study was conducted in Magnesia Prefecture, central Greece, during the period May–June 2007. It aimed at the comparison between conventional and certified organic olive groves with regard to olive and olive oil production, diversity of plants (herbaceous and woody) and diversity and abundance of avifauna. Correlations between variables within herbaceous plants (linear regression) and woody plants (Principal Component Analysis), and the role of integration time of olive groves to the organic system were investigated. Also, finding easily measurable parameters indicating high bird diversity levels within organic and conventional management systems was a main target of the study. According to our findings, neither edible olive yield nor olive oil yield showed significant differences between conventional and certified organic olive groves. There is an increasing trend for alpha and beta diversity of herbaceous plant species, woody plant beta diversity, density and cover of woody plants, and density of breeding birds in certified organic olive groves (10 years) in comparison with conventional ones. The effect of time since the adoption of organic procedures is very important and produces benefits for the biodiversity. In the total olive groves 15 insectivorous, six granivorous and three insectivorous/granivorous birds species were recorded. Nine bird species distinguished by Ward's hierarchical clustering were identified as typical (indicator value, IndVal>50%) of specific farming systems. Among them, the Eurasian jay, associated with the 10-year certified organic olive groves, and the common cuckoo, Orphean warbler and Red-backed shrike, associated with the 6-year certified organic olive groves, should be regarded as characteristic species (IndVal>70%). Conclusively, organic farming favors some aspects of diversity of herbaceous and woody plants of olive grove ecosystems. On the contrary, similar effects on breeding bird diversity and density were not clearly recorded. However, breeding bird density proved a good indicator of their richness.

Olive cultivation (Olea europaea L.) is one of the most significant sources of income for agricultural areas in the Mediterranean basin, and the olive oil industry as well as the environmental protection are an important part of the Greek agricultural sector. Generalized Linear Models were applied in order to investigate the predictive strength of several biodiversity components and agro-environmental factors for yield and herbaceous plant diversity (species richness) in organic and conventional olive groves of Greece. Our study highlights an increase in yields of organic olive groves by increasing manure application and the earthworms’ density. In the conventional olive groves, yields increase by increasing soil organic matter and the application of inorganic fertilizer N. Also, the herbaceous plant species richness increases with increasing the Shannon diversity index of herbaceous plants, the field area, the application of organic fertilizer K and the manure in organic olive groves. As for the conventional ones, herbaceous plant species richness increases with the increase of the application of inorganic fertilizer N. Moreover, some plant species could be regarded as indicators of the differently managed olive groves. Conclusively, this study contributes to the integration of biodiversity conservation with ecologically sustainable agriculture and conservation of agroecosystem. Finally, it could be utilized as a decision and management tool to the scientific and agricultural community reinforcing the knowledge about the agro-environmental impact in olive grove management systems.

Strongly affected by the escalating impacts of climate change, wildfires have been increasing in frequency and severity around the world. The primary aim of this study was the development of specific territorial measures—estimating the optimal locations of firefighting resources—to enhance the spatial resilience to wildfires in the fire-prone region of Chalkidiki Prefecture in northern Greece. These measures focus on the resistance to wildfires and the adaptation of strategies to wildfire management, based on the estimation of burn probability, including the effect of anthropogenic factors on fire ignition. The proposed location schemes of firefighting resources such as vehicles consider both the susceptibility to fire and the influence of the topography on travel simulation, highlighting the impact of road slope on the initial firefighting attack. The spatial scheme, as well as the number of required firefighting forces is totally differentiated due to slope impact. When we ignore the topography effect, a minimum number of fire vehicles is required to achieve the maximization of coverage (99.2% of the entire study area) giving priority to the most susceptible regions (that is, employing 18 of 24 available fire vehicles). But when we adopt more realistic conditions that integrate the slope effect with travel time, the model finds an optimal solution that requires more resources (that is, employing all 24 available fire vehicles) to maximize the coverage of the most vulnerable regions within 27 min. This process achieves 80% of total coverage. The proposed methodology is characterized by a high degree of flexibility, and provides optimized solutions to decision makers, while considering key factors that greatly affect the effectiveness of the initial firefighting attack.

Forest fires are a natural phenomenon which might have severe implications on natural and anthropogenic ecosystems. Future projections predict that, under a climate change environment, the fire season would be lengthier with higher levels of droughts, leading to higher fire severity. The main aim of this paper is to perform a spatiotemporal analysis and explore the variability of fire hazard in a small Greek island, Skiathos (a prototype case of fragile environment) where the land uses mixture is very high. First, a comparative assessment of two robust modeling techniques was examined, namely, the Analytical Hierarchy Process (AHP) knowledge-based and the fuzzy logic AHP to estimate the fire hazard in a timeframe of 20 years (1996–2016). The former technique was proven more representative after the comparative assessment with the real fire perimeters recorded on the island (1984–2016). Next, we explored the spatiotemporal dynamics of fire hazard, highlighting the risk changes in space and time through the individual and collective contribution of the most significant factors (topography, vegetation features, anthropogenic influence). The fire hazard changes were not dramatic, however, some changes have been observed in the southwestern and northern part of the island. The geostatistical analysis revealed a significant clustering process of high-risk values in the southwestern and northern part of the study area, whereas some clusters of low-risk values have been located in the northern territory. The degree of spatial autocorrelation tends to be greater for 1996 rather than for 2016, indicating the potential higher transmission of fires at the most susceptible regions in the past. The knowledge of long-term fire hazard dynamics, based on multiple types of remotely sensed data, may provide the fire and land managers with valuable fire prevention and land use planning tools.

Wildfires are a natural phenomenon, which nowadays, due to the synergistic effect of increased human intervention and the escalation of climate change, are displaying an ever-increasing intensity and frequency. The underlying mechanisms present increased complexity, with the phenomenon itself being characterized by a significant degree of stochasticity. For the above reasons, machine learning models and neural networks are being implemented. In the current study, two types of neural networks are implemented, namely, Artificial Neural Networks (ANN) and Radial Basis Function Networks (RBF). These neural networks utilize information from the Fire Weather Index (FWI), Fosberg Fire Weather Index (FFWI), Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Moisture Index (NDMI), aiming to predict ignitions in a region of Greece. All indices have been developed through the Google Earth Engine platform (GEE). In addition, a new index is proposed named “Vegetation-Enhanced FWI” (FWIveg) in order to enhance the FWI with vegetation information from the NDVI. To increase the robustness of the methodology, a genetic algorithm-based approach was used in order to obtain algorithms for the calculation of the new index. Finally, an artificial neural network was implemented in order to predict the Mati wildfire in Attica, Greece (23 July 2018) by applying the new index FWIveg, aiming to assess both the effectiveness of the new index as well as the ability to predict ignition events using neural networks. Results highlight the effectiveness of the two indices in providing joint information for fire prediction through artificial intelligence-based approaches.

The role of breeding birds as indicators of sustainable management in olive groves was investigated. The data revealed significantly higher alpha diversity in organic and abandoned olive groves and maquis than in conventional ones. The highest beta diversity was found between the following pairs: organic olive groves–maquis, and abandoned olive groves–maquis. Breeding bird diversity, Heteroptera, Hymenoptera, Hemiptera and Coleoptera densities positively influenced bird species richness in organic olive groves and maquis, and additionally, manure application positively influenced bird species richness in organic ones. Bird species richness was negatively influenced by pesticide and inorganic fertilizer application in conventional ones. Moreover, isopod density was unimportant in explaining breeding bird richness in organic olive groves. Finally, our study suggests a difference in bird communities of various olive groves as a result of different management and practices, and concludes that birds might serve as indicators of overall olive grove health. Furthermore, these findings could be used as a tool for prediction of breeding bird species richness probability in different olive grove management systems and maquis. Finally, the results of the present study may contribute to highlighting some aspects of the effect of different farming practices on the dynamics of Mediterranean bird communities.