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Widespread attention continues to be drawn to the ecological effects of roads, especially as the road system continues to expand. Ecological conditions are not only affected by the construction of roads and road appurtenances but also by the traffic and by the increase in road density. Roads affect the abiotic components of landscapes including the hydrology, the mechanics of sediment and debris transport, water and air chemistry, microclimate and levels of noise, wind, and light adjacent to roadsides. Habitat fragmentation due to transport infrastructure is receiving growing concern among ecologists and civil engineers. Ecosystem structures and processes affected by a road in Northern Evia are examined and analysed. Future research must focus on types of road avoidance behaviors, and types of roads having great impact on population persistence.

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Habitat Fragmentation and habitat loss in Euboya Island

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Habitat Fragmentation and habitat loss in Euboya Island

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Widespread attention continues to be drawn to the ecological effects of roads, especially as the road system continues to expand. Ecological conditions are not only affected by the construction of roads and road appurtenances but also by the traffic and by the increase in road density. Roads affect the abiotic components of landscapes including the hydrology, the mechanics of sediment and debris transport, water and air chemistry, microclimate and levels of noise, wind, and light adjacent to roadsides. Habitat fragmentation due to transport infrastructure is receiving growing concern among ecologists and civil engineers. Ecosystem structures and processes affected by a road in Northern Evia are examined and analysed. Future research must focus on types of road avoidance behaviors, and types of roads having great impact on population persistence.

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Impact of roads on ecological conditions

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Widespread attention continues to be drawn to the ecological effects of roads, especially as the road system continues to expand. Ecological conditions are not only affected by the construction of roads and road appurtenances but also by the traffic

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Socioeconomic interactions of fishries and aquqculture in Greece: A case study og South Evoikos Gulp

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Socioeconomic interactions of fishries and aquqculture in Greece: A case study og South Evoikos Gulp

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Established in 1964, the IUCN Red List of Threatened Species has evolved to become the world's most comprehensive information source on the global conservation status of animal, fungi and plant species.

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Paeonia mascula (L.) Mill. 1768 subsp. mascula

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Alien Species in Europe that have been banned!

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Alien Species in Europe that have been banned!

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The EU Invasive Alien Species Regulation - Here, plants and animals, that have been banned

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A typical Trophic Pyramid in Euboya Island

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A typical Trophic Pyramid in Euboya Island

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As producers at first level can be plants such as stachys euboica,frillitaria enhartii,sideritis euboica,cholchicum euboeum
At First Level consumers(Herbivores) can be insects such as ditera,trichoptera,hymenoptera,Hemiptera(Beetles,Moths)
At second Level Consumers(carnivores) can be Chiroptera such as Myotis Nattereri ,Pipistrellus pipistrellus

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Τροφική Πυραμίδα

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Greece, is one of the most impacted countries, with more than 300 reported IAS. Although continuous monitoring is of great importance such efforts that involve scientists and research vessels, are very expensive and insufficient to ensure good spatial coverage, especially in a country like Greece with approximately 17,000 km of (60% of the Mediterranean coastline). Thus the inventory of IAS in Greece, as well as in other countries, is considered ambiguous, potentially jeopardizing the efforts for tackling the issue.

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On Septemer 2018 medicane Zorbas swept across the Greece.Euboya also hitted by its force.As a result a lot of damages and accidents happened!

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Medicane Zorbas is sweeping across Greece and leaves behind chaos: flooded towns and villages, swollen rivers and streams, collapsed bridges, damaged infrastructure, areas without electricity. Three people are reportedly missing on Sunday in North Evia, that was hit by torrential rains in the night form Saturday to Sunday.

Police and fire Service are searching for an elderly couple that was driving between Mantoudi and Metohi in North Evia short after Saturday midnight. Their car was found on Sunday in the area of Pyli.

Missing is also the driver of a vehicle that was swept away by rushing waters. The co-passenger, a woman was found to have climbed on a tree, and could not give information about the whereabouts of the 27-year-old motorist.

Due to heavy volume of rainwater in short time, river Kisseas swoll and flooded Mantoudi and passed through the village of Prokopi.
Mantoudi on Sunday morning - via evianews.
Homes and businesses were flooded and many residents went to roof tops for protection.

Between Mantoudi and Prokopi on Sunday morning.

Flooded businesses where the open bazaar is held on Sundays.

Short after Saturday midnight, south Fthiotida was also hit by torrential rainfalls, with flooded homes in Agios Konstantinos, Arkitsa and Atalanti.

Locals say they have never experienced such a situation and were expecting help.

In Malesina and Theologos, huge volumes of rainwater fell while gale force winds were striking the areas.

Traffic in the area was halted in the early morning hours and "the worst was avoided as many people who have summer houses in the area went to check if their properties were OK," deputy governor of Civil Protection in charge of the area Thanassis Karakantza told amna.

'They were trying to drive through the water to check their properties," he stressed.

Calls to evacuate motorists went through all night.

Firefighters have been working all night to pump waters, have reportedly evacuated hundreds of people from flooded homes.

The Fire Service has received form than 1,300 calls for help.

In one case, they evacuated a woman and her child, whose car engine went off when they were driving in the waters.

An elderly couple from USA was found in good condition in Chlomo by Atalanti. The couple had lost orientation amid the weather havoc and called the European Emergency Number <112> They could not say where exactly they were, a fire service team located the couple several hours later.

Halkida in Evia Saturday night

Medicane Zorbas hit first South-West Peloponnese and brought sea into the towns and villages. In Kalamata with winds reached a speed 103 km/h on Saturday morning. It moved to the East causing floods in Argos and Corinth. It swept further to the East, flooding areas in Kineta and Megara and later to Attica where it caused minor flooding and had traffic closed in many roads.

By 2 o' clock Sunday noon, the cyclone is striking the Sporades islands

Greece's Civil Protection is urging people to refrain from crossing streams, rivers and flooded roads.

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Three people missing in Evia as Medicane Zorbas is sweeping across Greece - Keep Talking Greece

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Medicane Zorbas is sweeping across Greece and leaves behind chaos: flooded towns and villages, swollen rivers and streams, collapsed bridges, damaged infrastructure, areas without electricity. Three people are reportedly missing on Sunday in North Evia, that was hit by torrential rains in the night form Saturday to Sunday.

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Common pipistrelle - Pipistrellus pipistrellus - (Schreber, 1774)

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Pipistrellus pipistrellus with the common name Common pipistrelle, belongs to the Mammals group

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Established in 1964, the IUCN Red List of Threatened Species has evolved to become the world's most comprehensive information source on the global conservation status of animal, fungi and plant species.

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Abstract

Ecologically-similar species were found to develop specific strategies to partition their resources, leading to niche differentiation and divergence, in order to avoid interspecific competition. Our study determines multi-dimensional differentiation of two sympatric top-predators, long-legged buzzards (LLB) and short-toed eagles (STE), which recently became sympatric during their breeding season in the Judean Foothills, Israel. By combining information from comprehensive diet and movement analyses we found four dimensions of differentiation: (1) Geographic foraging area: LLB tended to forage relatively close to their nests (2.35 ± 0.62 km), while STE forage far from their nest (13.03 ± 2.20 km); (2) Foraging-habitat type: LLBs forage at low natural vegetation, avoiding cultivated fields, whereas STEs forage in cultivated fields, avoiding low natural vegetation; (3) Diurnal dynamics of foraging: LLBs are uniformly active during daytime, whereas STEs activity peaks in the early afternoon; and (4) Food-niche: while both species largely rely on reptiles (47.8% and 76.3% for LLB and STE, respectively), LLB had a more diverse diet and consumed significantly higher percentages of lizards, while STE consumed significantly higher percentages of snakes. Our results suggest that this multidimensional differentiation allows the spatial coexistence of these two dense populations in the study area.

Introduction

Interspecific competition occurs when sympatric species consume or occupy a common limited resource essential for their survival or reproduction1. Interspecific competition has long been recognized as an important factor for shaping species distributions, and as an ecological force by which major modification in species communities can be shaped2. It can influence species abundance and distribution, habitat colonization rate, population size, species diversity, and even species extinction rate2,3,4. One strategy to avoid competition in sympatric species involves multidimensional niche differentiation5,6. Understanding the degree of niche overlap and the differences between coexisting species across multidimensional resources that include diet, space, and time is necessary to manage and preserve species' populations in general and, as we show here, raptor populations in particular7.

Diet similarity between species, coupled with limited supply of resources, has long been recognized as one of the essential conditions of competition8. While dietary overlap indicates a potential for interspecific competition6, conclusive evidence for competition is typically based on manipulative experiments9, which are, in most cases, not feasible when studying top predators in the wild10. Competition theory predicts that diet similarity should be reduced, in neighboring pairs of different species, which breed in the same habitat11, compared to non-neighboring pairs. Body size and trophic structure are among the factors that determine the size of prey captured12 and therefore have a major impact on the competitive strength of sympatric species13. Yet ecologically-similar species have been found to partition their use of resources, such as diet, leading to niche divergence14.

In addition to having similar diets, spatial overlap of foraging habitats by species may also indicate potential for competition15. Spatial divergence between co-existing species' foraging areas was observed as a mechanism to avoid competition for similar resources16,17,18. Foraging-habitat partitioning can be achieved by simple spatial differentiation at a landscape (geographic) scale, where each species utilizes different areas18,19. It can also be achieved at a small (patch) scale, where both species forage in the same geographic area but each forages in different sub-habitat (patch) type20. However, only a few studies have combined these two spatial dimensions when analyzing differentiation in foraging of coexisting species16,21.

Diel differences in activity time have been considered as the most important niche axis, apart from diet and habitat, along which organisms most frequently segregate16. Temporal partitioning may act either through exploitation competition, which presumes partitioning of other niche axes (mainly food and habitat), or through interference competition, which allows time to act as an independent niche dimension over which organisms may reduce the effects of agonistic interactions22. Thus, temporal segregation in foraging activity may be used as a mechanism of coexistence in sympatric species16,22.

Here, we present a study on the long-legged buzzard ( Buteo rufinus) (hereafter LLB) and the short-toed eagle ( Circaetus gallicus) (hereafter STE) - two diurnal, large-sized raptors occasionally sympatric throughout their breeding distribution23. In our study area, the Judean Foothills, Israel, these two species became sympatric during their breeding season recently, during the last two decades. It is assumed that this sudden change in community dynamics was a result of a LLBs' population shift into this area24. Each year these two species return from their wintering areas to their sympatric breeding grounds in order to nest. Their populations have a large temporally overlapping breeding season, sharing the same areas for their nesting territories and, in some cases, even alternating use of nests in consecutive years25. Hence, it was questioned how LLBs which recently shifted into the STEs' traditional nesting area coexist with each other? The goal of this study is therefore to determine the mechanism of coexistence for these two overlapping populations.

We investigate the possible mechanisms of resource partitioning that may explain the coexistence of these two sympatric top predators during their breeding season. Specifically, we aim to quantify the overlap between the two raptors along four dimensions: (a) large-scale foraging area, (b) small-scale foraging-habitat type, (c) diet, and (d) the diel timing of foraging. According to the niche-complementarity hypothesis, a high overlap in one dimension should be compensated by a low overlap in at least one other dimension26. We use this information to assess the likelihood of competition between the two species and to make recommendations for their management and conservation. We combine comprehensive diet analysis with GIS data analysis and high-frequency GPS animal-tracking data which provide millions of precise and reliable data points. Our study provides new insights into the spatial and temporal distributions and habitat preferences of coexisting animals27.

Results

Nest density and localization

The number of LLBs nests in the breeding area increased by 38% from 2007 to 2014, whereas the number of STE nests remained relatively stable (62 ± 1.5, mean ± SE) during the four study seasons (2011-2014, Fig. 1). We analyzed the average distance to the nearest neighboring nest, based on the 2013 breeding season. We found that the interspecific average distance between LLB to the nearest STE nest (1.44 ± 0.27 km, n = 37) and STE to the nearest LLB nest (1.30 ± 0.18 km, n = 63) were relatively similar. However, the intraspecific distance to nearest neighbor among LLB nests was significantly larger than that of STE nests (2.65 ± 0.29 km, n = 37 and 1.23 ± 0.16 km, n = 63, respectively, t = 4.2, P < 0.0001).

Figure 1: Number of nests located in the breeding area (215 km²) in the Judean Foothills, Israel.

Note that long-legged buzzards (LLBs) and short-toed eagles (STEs) were not sampled during 2009-2010 and 2007-2010, respectively.

Large-scale foraging area

All reported GPS locations for both species were within a 116 by 78 km area, within the semi-arid and Mediterranean ecosystems of the Northern Negev, Judean Foothills, Coastal Plains and Western Judean Mountains in Israel ( Fig. 2a,b). The average distance between the foraging areas of STE and its nest during the whole breeding season was 13.03 km (±2.20), and was 5.5 times greater than that of LLB ( Table 1, Figs 2b and 3). Therefore, while LLBs intensively wander relatively close to their nests, STEs typically forage relatively far away from their nests (note the red areas in Fig. 3a,b).

Figure 2

( a) Nest location of all tagged raptors (LLB n = 9, STE n = 8) at the entire study area. ( b) Foraging areas (defined by a 95% KDE with a constant smoothing factor of 500 m) of 5 STEs and 6 LLBs. Note that 10 of the nests (marked inside the small rectangle in a) were located close to each other and that LLBs tended to forage close to their nests (2.35 ± 0.62 km), while STEs used "flight corridors", represented by black arrows, to access their far foraging areas located at a mean distance of 13.03 km (±2.20) from their nests and at different geographical areas. These figures were generated by using GIS software - ArcGIS (ESRI. 10.1).

Table 1: Foraging area size and distance from their related nests, obtained by KDE (95%) analysis.

Figure 3: Point density analysis (smoothing factor of 500 m) of all movement data from one STE (#2186 a) and one LLB (#2181 b) during the entire breeding season.

Note that the total area of STE's movements was greater than LLB's. In addition, STEs use "flight corridors", of ~5-30 km, from their nests to their main foraging areas ( a), while LLBs tended to forage close to their nests ( b). These figures were generated by using GIS software - ArcGIS (ESRI. 10.1).

Consequently, the average foraging area of STEs during the whole breeding season was 3.5 to 4.2 times larger than that of LLBs, and depended on the value of the Kernel Density Estimator (KDE28) smoothing factor ( Table 1, Figs 2b and 3). The average foraging area of STEs during the shared breeding period was 2.5 to 3.0 times larger than that of LLBs, depending on the smoothing factor ( Table 1, Figs 2b and 3). The average Utilization Distribution Overlap Index (UDOI29) during foraging among STE individuals (0.16 ± 0.19) was significantly higher than among LLB individuals (0.01 ± 0.01). It was also larger than the interspecific average UDOI between individuals of the two species (0.03 ± 0.07, F 2.26  = 5.62, P = 0.01 followed by Bonferroni multiple comparison test, P < 0.05 on arcsin-sqrt transformed UDOI values).

A spatial cluster analysis on foraging locations showed that individuals' foraging locations clustered by species ( Fig. 4a, Supplementary Table S1). We identified five foraging clusters, two of which were nearly exclusively LLB (clusters A and D, Fig. 4a, Supplementary Table S1), another two which were exclusively STE (clusters C and E), and the fifth (cluster B) which was 75% STE.

Figure 4

( a) Clustering of individual birds' foraging locations. We have identified 5 significant foraging-locations clusters (dashed ellipses, labeled A-E). The foraging locations of each individual are marked by colored dots, with LLB individuals in "warm" shades (magenta-red-brown) and STE individuals in "cool" shades (violet-blue-grey). Nest location for each individual are marked by a triangle (LLB) or a square (STE). Cluster analysis to group foraging locations was conducted using the k-means function in MATLAB. ( b) Results of attraction-repulsion analysis of movement patterns between each pair of individual birds using MoveMine49. Individual bird IDs are listed and sorted by species. The figure is symmetric across the diagonal. Color marks the attraction index, varying from 0 (complete avoidance) through 0.5 (mutually random movement pattern) to 1 (complete attraction, coordinated, matching movement patterns). A white (blank) square indicates that these two individuals were never observed at the same year. Most individuals display neutral movement patters to each other, except three LLB individuals that display avoidance toward STE individual 2186, and one pair of LLBs (2183 and 2180) that show matching (attracted) movement patters. This figure was plotted using MATLAB (Mathworks, Natick, MA) version R2015b ( http://www.mathworks.com/products/matlab/).

Analysis of attraction/repulsion patterns in the movement data showed that most individuals where neutral to each other ( Fig. 4b), indicating that direct intra- and interspecific interactions between individuals are rare. The exception to this general observation of no direct interactions were one STE's (2186) movements that displayed slight repulsion toward three LLBs, and the movements of two LLBs (2180, 2183) that were highly synchronized and indicated attraction.

Small-scale foraging habitat type

Ordination of the habitat-type dataset indicated a pronounced and significant difference (stress value = 0.1) in the overall composition of the types of habitat used for foraging, with low overlap between species ( Fig. 5a). LLB over-utilized Mediterranean Garrigue and Batha (hereafter low natural vegetation), with this habitat comprising 41% of the full range of habitats used for foraging, even though it covered less than 12% of the study area. In contrast, LLB under-utilized cultivated fields (12% use versus 37% availability, Fig. 5b). STE exhibited the opposite pattern, over-utilizing cultivated fields (59% use versus 37% availability) and under-utilizing low natural vegetation (7% use versus 12% availability, Fig. 5b).

Figure 5

( a) Multi-dimensional scaling (MDS) plot of similarity in habitat type used for foraging by the two raptor species during the breeding season. Each point represents one individual. The habitat types of LLB and STE were significantly different from each other. The lines represent 40% and 60% similarity contours, so all samples inside each contour have a similarity above these two values, ( b) Box plot of habitat type used by each species in comparison (one sample t -test) to habitat type availability in the whole study area ("Actual" line). Box = 25th and 75th fractions; bars = min and max values; red lines = median; red dots = outliers. Note that each species foraged in different habitat types; LLB showed a clear significant preference to low natural vegetation, and significantly avoided cultivated fields, while STE showed an opposite behavior by significant preference of cultivated fields and significant avoidance of low natural vegetation. *= 0.01 < P < 0.05, **= 0.001 < P < 0.01, ***= P < 0.001, ns = not significant (P > 0.05).

Multi-dimensional scaling (MDS) plots of similarity in habitat type showed that there is minimal overlap in the habitat-type preferences of the two species, with only a single STE falling within 60% similarity cluster of LLB ( Fig. 5a). ANOSIM analysis confirmed the significance of the low degree of habitat type overlap between the two raptor species (Overall R = 0.44, P < 0.001). The average Bray-Curtis diet dissimilarity between the two raptor species was 49.7% ( Supplementary Table S2). SIMPER analyses confirmed that most of this difference was due to the opposite preferences of cultivated fields by STE and of low natural vegetation by LLB (24.3% and 19.2% contributions for dissimilarity, respectively). Individuals of STE were more similar to each other (average 63.9%) than those of LLB (average 59.7%). Cultivated fields were the most typical foraging habitat of STE, contributing 50.1% to the average resemblance within the species whereas low natural vegetation was the most typical foraging habitat of LLB (30.3%, Supplementary Table S2).

The observed low overlap in foraging-habitat types between the two raptor species (O jk = 0.24) was not significantly different than expected by chance under the null simulated values of randomization algorithms RA3 ( Supplementary Table S3). The observed overlap of foraging habitats between individuals within each raptor species (O jk = 0.39 for LLB and 0.38 for STE) was significantly higher than expected by chance by RA3 ( Supplementary Table S3).

Timing of foraging

Although the patterns of foraging time in both diurnal species were largely overlapping, the two species had significantly different patterns of daily foraging activity. LLBs demonstrated an almost uniform pattern of activity during daytime (between 07:00 and 19:00), while STEs exhibited a unimodal pattern with a clear midday peak (between 11:00 and 15:00) ( Fig. 6a). MDS ordination clearly (stress value = 0) separated the foraging activity pattern of the two species ( Fig. 6b) and overall R analysis confirmed significant differences between the two species (Overall R = 1.0, P < 0.05). SIMPER analyses demonstrated that the overall dissimilarity of foraging time between the two species is less than 18%, and most of this difference was due to the high and low activity of LLB and STE, respectively, in the early morning (between 07:00 and 08:00) and late afternoon (between 18:00 and 19:00, Supplementary Table S4). Both species demonstrated high intraspecific similarity in their foraging activity pattern with an average of 95.9% and 90.2% similarity in LLB and STE, respectively ( Supplementary Table S4).

Figure 6

( a) Daily foraging time activity during 07:00-19:00 of each raptor species. Note that LLB tended to forage during all day time while STE showed a unimodal pattern with a clear midday peak. ( b) Multi-dimensional scaling (MDS) plot of similarity in foraging time used by the two raptor species during the breeding season. Each point represents one individual. Although the patterns of the foraging time of both species largely overlap, these two species had different patterns of daily foraging activity.

The high observed Pianka's overlap index in foraging time between the two raptor species (O jk = 0.86) was similar to that expected by random chance, as simulated by the RA3 algorithm ( Supplementary Table S3). The high observed foraging-time overlap values between individuals within each raptor species (O jk = 0.98 for LLB and 0.96 for STE) were significantly higher than expected by random chance (using RA3 algorithm, Supplementary Table S3).

Diet

Based only on nests with a minimum of eight prey items, we identified a total of 1,416 and 1,239 prey items from 59 STE and 32 LLB nests, respectively, during three breeding seasons (2011-2013). The actual/observed prey-taxa richness found in LLB nests was higher than that of STE (49 and 34, respectively, Supplementary Table S5). Because the observed prey-taxa richness depends on sample size, we calculated Chao1 non-parametric estimators for the predicted prey-taxa richness. The curves for both species appear to be approaching the asymptote, indicating that the most common prey taxa were sampled. The rarefaction plots show that the Chao1-predicted prey-taxa richness of LLB is roughly 60% higher than that of STE (65.1 and 40.7, respectively, Fig. 7a) when taking into account the lower sample size (32 nests of LLB, see the vertical line in Fig. 7a). Dietary niche breadth of LLBs was 31% higher than that of STEs ( Bi  = 10.7 and 8.2, respectively).

Figure 7

( a) Expected species accumulation curves based on Chao1 estimate of prey taxa richness of LLB and STE. Average and bootstrapped SD are based on 1,000 permutations. The curves appear to be approaching asymptote, indicating that most prey taxa were sampled. The vertical line indicates that when taking into account a similar sample size (n = 32 nests) more prey taxa were found in LLB than in STE diets. ( b) Comparison (Independent sample t-tests) of the total fraction of each prey category (reptiles, birds, mammals and arthropods) between the two raptor species. *= 0.01 < P < 0.05, ***= P < 0.001, ns = not significant (P > 0.05). Box = 25th and 75th fractions; bars = min and max values; black lines = median; red dots = outliers. ( c) Comparison (Repeated measures ANOVA) between the consumption of lizards (Sauria) versus snakes (Ophidia) between the two raptor species. Box = 25th and 75th fractions; bars = min and max values; black lines = median; red dots = outliers. Note that LLB consumed higher percentages of lizards, while STE consumed much higher percentages of snakes. ( d) Multi-dimensional scaling (MDS) plot of similarity in dietary prey taxa of the two raptor species during the breeding season. Each point represents one nest. The diets of LLB and STE were significantly different, indicating that each species selected different proportions of prey items. The lines represent a 15% and 30% similarity contours, so all samples inside each contour have a similarity above these two values.

Although the two raptor species share 30 prey items ( Supplementary Table S5) the proportions of prey categories in their diet differ significantly, as indicated by the higher fraction of birds in LLB diets and the higher fraction of reptiles and arthropods in STE diets ( Fig. 7b). No significant difference was found with regard to the fraction of mammals in the diets of the two species ( Fig. 7b). Further analysis focusing on the composition of reptiles in the diet showed that LLB consumed a higher percentage of lizards (Sauria), while STE consumed a higher percentage of snakes (Ophidia) (Repeated Measures ANOVA, F 1,1 = 161.3, P < 0.001, Fig. 7c).

Ordination of the dietary data set indicated a pronounced and significant difference (stress value = 0.19) in the overall composition of the diets of the two species with low overlap ( Fig. 7d). Nonparametric MDS indicated that only two LLB nests fall within 30% similarity cluster of STE and three STE nests fall within 30% similarity cluster of LLB ( Fig. 7d). ANOSIM confirmed the significantly low degree of dietary overlap between the two raptor species (Overall R = 0.77, P < 0.001). The average Bray-Curtis diet dissimilarity between the two species was high (71%, Supplementary Table S6). SIMPER analyses showed that two snake taxa (large whip snake, Dolichophis jugularis, and an unidentified large Colubridae) contributed most to this difference (15.7%), followed by pigeons ( Columba livia domestica) and other unidentified birds (14.9%) and schneiders skink ( Eumeces schneideri, 7.0%). Other prey types contributed 2-6% each to dietary dissimilarity. Individuals of STE were slightly more similar to each other (average 52%) than those of LLB (average 48%). Large whip snake was the most common prey item of STE, contributing 30.4% to the average resemblance within the species whereas roughtail rock agama ( Stellagama stellio) and schneiders skink were the most common prey items of LLB (20.2% and 18.0%, respectively, Supplementary Table S6).

The observed medium dietary-niche overlap between the two raptor species was significantly higher than expected by random chance during two of the three years and for all years combined (RA3 simulation, O jk = 0.48 Supplementary Table S3). The observed diet overlap between individuals within each raptor species ( O jk = 0.85-0.94 for LLB and 0.91-0.94 for STE) were significantly higher than expected by random chance for both species (RA3 simulation, Supplementary Table S3).

Discussion

We present data suggesting a multi-dimensional niche partitioning between two raptor species which recently became sympatric within a small area of 215 km ² in the Judean Foothills during their breeding season. The nest density of STE, the veteran inhabitant of the area, is higher than reported in other areas in the world30,31 and is probably the highest in their entire breeding distribution. The nesting density of the LLB, which first arrived in this area twenty years ago, is probably the highest in their entire breeding distribution as well32,33,34,35. In some parts of our study area we recorded only 100-200 m between the nests of the two species. Furthermore, it appears that nest densities of both species are still increasing.

Because both species are top predators, both are active at daytime, and are similar in body type and activity patterns, it is expected that their new geographical overlap in the Judean area will create also an overlap over food, foraging areas, foraging habitats and foraging time. Furthermore, the close proximity of nests of the two species is particularly peculiar considering that LLB is known as an aggressive and territorial species, which is sensitive to interspecific and intraspecific intruders36. Here we demonstrated that the two species ecologically segregate across four niche dimensions: foraging area, foraging habitats, foraging timing and diet ( Table 2).

Table 2: Multidimensional differentiation between long-legged buzzards (LLBs) and short-toed eagles (STEs).

GPS tags which operated more than two years showed high fidelity of both species to their nesting territories and foraging areas. Despite their high breeding densities and sympatric nesting sites, the GPS tags revealed a clear spatial pattern of interspecific segregation between the foraging areas of the two species. LLBs tended to forage relatively close to their nests. STEs intensively foraged relatively far from their nest, and used larger foraging areas than LLBs. Both species maintained low overlap among individuals' foraging areas. Each species thereby segregates intra-specifically as well. Analysis of patterns of attraction-repulsion movements revealed that most individuals, regardless of species, were neutral to each other. Both intra- and interspecific interactions among individuals were thus rare.

STEs tended to use long "flight corridors" to reach their foraging areas. These corridors had never before been documented in this species' breeding movement ecology. The furthest STE foraging point was sampled at a distance of 35.63 km from its nest.

Our results show that these two species spatially segregate at two distinct scales ( Table 2). They choose geographically distinct foraging areas, and within each foraging area, each species targets a different land-cover type (habitat-type). Land cover is considered an important component in determining raptors' foraging preferences20,24,37. LLB mainly foraged in low natural vegetation habitats, whereas STE mainly foraged in cultivated fields. However, in areas without LLBs, STEs are assumed to forage in low natural vegetation habitats38 and therefore, one possible explanation for the habitat segregation in our study area can be derived from a STE's strategy to avoid competition in their sympatric foraging areas. On the other hand it can also be derived from interspecific differences in their visual attributes. Visual information is necessary to detect prey items against the background and track them visually until capture39. Thus, vision-related differences between the two species such as visual field configuration, the degree of eye movement, the size of the binocular and blind areas should affect the two species' prey-searching strategies in each habitat type39, and thus affect their prey specialization (see below).

We found that the low observed overlap in foraging habitats between the two raptor species ( O jk = 0.24) was lower (but not significant) than expected by chance under the null simulated values of RA3 algorithm. This may indicate that the types of habitats, rather than the number of habitat types, reduced the ecological similarity between the two species. On the other hand, as expected, both species showed a higher intraspecific similarity than expected by chance in their habitat type preferences, which were also higher than the value of their interspecific similarity. This pattern of non-random foraging in available habitat types exhibited by the two species may emerge from interspecific competition, but may also be a natural consequence of other differences between the species, such as morphological differentiation and prey specialization.

Differences in timing of foraging may also be an important mechanism reducing interspecific competition among avian species16,22,40. There was a large overlap in foraging hours between the two species, and within each species, as both are diurnal raptors. However, foraging patterns clearly differed between these two species as indicated by the highly significant overall R and by the MDS ordination. LLBs were equally active during each hour of daytime whereas STEs showed a rather unimodal pattern.

It is unknown whether this temporal segregation is a direct consequence of a mechanism to reduce interspecific interaction22, an outcome of the different environmental conditions required by each species, or an outcome of the differences in diet and temporal availability of prey throughout the day. For example, high wing-loading species41 such as STEs may wait for thermal currents to develop in early mornings in order to fly to their foraging areas. On the other hand, better soaring conditions are typically available during midday and early afternoon, especially for high wing-loading species41. Therefore, species with lower wing-loadings, such as LLBs, are able to exploit weaker thermals and are expected to expand their activity time in the early morning and late afternoon. However, the temporal segregation between the two species may reflect the temporal activity pattern of their main prey items. For example, reptiles, the main prey of STE, are mainly active at midday, while birds, which are the main prey of LLB, are active throughout the entire day. Regardless of its direct cause, this timing segregation is clearly an important factor that influences the potential interactions between these two species.

As expected, the observed diet similarity between the two species was much lower than the observed diet niche overlap within each species. All these values were significantly higher than expected by chance and may indicate that the type, rather than the number, of dietary items increased dietary niche overlap not only within species, but also between the two species. However, these results may reflect the fact that the RA3 analysis assumes that all dietary categories were equally available to both consumers.

A possible explanation for the higher observed dietary niche overlap within STEs than within LLBs is that STEs display a low degree of reversed sexual dimorphism, which may be linked to its more specialized diet3, while LLBs display much higher degrees of reversed sexual dimorphism, were females are much larger than males, and thus their diet is more diverse within the population.

We found that LLB is more opportunistic than STE, as indicated by its wider dietary niche breadth and higher observed and predicted prey-taxa richness. The overall diet analysis showed a significant difference in the proportions of prey categories in the two species' diets, as indicated by a significantly higher percentage of birds in the LLB diet and much higher percentage of reptiles and arthropods in STE diets. However, although the diet of both species largely rely on reptiles, we found that LLBs consumed significantly higher percentages of lizards, while STEs consumed significantly higher percentages of snakes. Hence, there is a clear segregation not only among prey categories but also in the composition of their reptile diet.

It is unclear whether this diet segregation derives from a niche shift process, which responds to interspecific competition, or from the morphological differences and hunting techniques used by these two species. For example, LLB is known to be an aggressive and rapid raptor, which dives to attack its prey diagonally42 and catches it by surprise, and thus can prey on flying birds and quick lizards36. STE is known to be a slower and cumbersome raptor, which dives to its prey vertically, sometimes with several aerial midair stopovers.

We propose that the diverse and rich diet of LLBs may facilitate its successful colonization in new breeding areas, as is the case in recent years in the Judean Foothills24. Such diet plasticity influences the ability to occupy new habitats43, as was documented in other raptors10,44 in which their plasticity in behavior and life history facilitates their expansion to new areas.

Although, STE is known as a specialist predator of snakes30,38,45, our results suggest that the diet of STEs in our study area is more diverse and expansive than it is in other breeding areas, with snakes comprising only 54.5% of its total diet. This may fit the predictions of competition theory11, and can lead to the assumption that in their former allopatric stage their diet similarity was higher but prey diversity was lower and similar to other areas where STE is a specialist predator. However, in their current sympatric stage, their diet similarity is reduced and their dietary-niche diversity is expanded. Thus, recent LLB population shifts and their increasing population density may have led to a decrease in STE prey availability, forcing them to add alternative prey to their diet.

The n-dimensional niche theory predicts that even minor segregations along several different dimensions can lead to a significant overall segregation40. Indeed, our study shows that the two raptor species significantly segregate on each of the four dimensions analyzed ( Table 2). Despite nesting in close proximity, the two species demonstrated a clear spatial segregation in their foraging areas. Furthermore, multiplying the Bray-Curtis similarity values of the other three axes of differentiation (0.50 habitat type X 0.83 foraging active hours X 0.29 diet = 0.12), shows a clear niche segregation between these two species. Therefore, it seems that the two species could coexist in the same area.

Our results suggest a combination of four dimensions of segregation between two sympatric populations with similar ecology that had been allopatric during their entire history in the Judean area. However, it is impossible to rule out an alternative hypothesis - that pre-existing dissimilarity in these top predator niches, due to physiological differences, ghost of competition past, or any other long-term evolutionary driver, is the cause rather than the effect of the successful sympatric coexistence. Nonetheless, this study provides important insights on the ecological mechanisms which allow coexistence of two dense populations of top predators.

Methods

Study area and species

The study was conducted during three breeding seasons (2011-2013). The total study area (9,048 km ² of foraging area and 215 km ² of breeding area) comprised the Judean Foothills, the Western Judean Mountains, the Coastal Plain and Northern Negev, while the breeding area comprised several parts of the Judea region, Israel. The Judea mountainous region rises up to 800 m above sea level and is dissected by several streams flowing west to the Mediterranean Sea or east to the Dead Sea. On the west, the mountains border the Coastal Plain or Judean Foothills - a region of undulating low hills ranging in height between 150-450 m above sea level, where the natural plant community is comprised of Mediterranean Garrigue and Batha formations (hereafter "low natural vegetation"), as well as scattered trees ( Quercus calliprinos, Pistacia lentiscus and Ceratonia siliqua). The valleys between these hills are mostly cultivated. For a full description of the two studied species, see Supplementary Methods.

Nest localizations and nest visits

During the three breeding seasons we systematically located active nests of LLBs' and STEs' by following the breeding pairs and by systematically searching and inspecting all suitable nesting trees and cliffs within the study area. The majority of pairs did not nest in the same nest each year25, thus we needed to locate their new nests every year. By doing so, we have found 100 LLBs' nests and 182 STEs' nests total. We calculated the mean distance to the nearest neighbor between LLBs' and STEs' nests (interspecific) and within each species (intraspecific), by using the ESRI ArcGIS 10.1 'Near'-function. We analyzed the average distance between nearest neighboring nests for 2013 breeding season only, because this was the year with the largest number of observed STE nests (n = 63) and LLB nests (n = 37). Each one of the 282 active nests was visited and monitored at least twice throughout each breeding season: during the chick-rearing period (~30 days after hatching) and again two weeks after fledging.

GPS tagging and tracking

Between 2011 and 2013, we trapped and tagged with GPS tags (E-Obs GmbH; Munich, Germany) 13 breeding LLBs (five regular and eight solar powered) and 11 breeding STEs (eight regular and three solar powered). The two types of GPS tags were assigned at random to each individual, regardless of species. Tags were fitted at the center of their back using special Teflon harness, and were programmed to sample one GPS fix (data point) at five minute intervals (for the solar tags) and 90 minute intervals (for the regular tags). Each fix provided date, hour, longitude, latitude, elevation, ground speed and heading azimuth. In addition, each tag included a specific UHF-signal (pinger) to facilitate tagged individual detection. These tags accumulated and stored GPS data until the data was downloaded through UHF communication. After the data were downloaded successfully, the tag continued to store new data until the next download. LLBs and STEs are diurnal raptors and thus these tags were programmed to work in a 12 h duty cycle (06:55-19:05) with 147 fixes per day (11 solar GPS tags, track duration: ~730 days: 2,697-39,592 fixes per individual for two breeding seasons: many of these fixes occurred outside foraging hours) or 4-10 fixes each day, mostly during foraging hours around midday (13 regular GPS tags, track duration: 75-450 days: 244-1,081 fixes per individual for one breeding season) due to battery and storage limitations. Therefore, both types of GPS tags provided comparable sample sizes for the analysis of foraging area.

The actual number of tagged individuals included for further analyses was eight STEs and nine LLBs, as we excluded individuals that did not achieve the chick-rearing phase (i.e. eggs didn't hatch) or those with less than 51 data points in their home range polygons (see below). GPS locations where uploaded to ArcGIS 10.1 software and to movebank.org46 for further processing and archiving. The movement data used in this study are archived at movebank.org, study name "Movements of long-legged buzzards and short-toed eagles", and are available through the Movebank Data Repository47.

All bird handling work were conducted according to relevant national and international guidelines, and were approved by the Israel Nature and Parks Authority (research permit # 2011/38319).

Large-scale foraging area

Foraging area for each tagged adult was defined by a 95% Kernel Density Estimator (KDE28) during each breeding season. We used the utilization distribution (UD) approach28, with a constant smoothing factor of 500 m. To assess the sensitivity of our results to the smoothing factor, we repeated the analysis using two additional smoothing factors, 250 m and 1000 m. We pre-processed the data in ArcGIS (ESRI. 10.1) and calculated the UD in R using the adehabitat package48. A foraging data point was defined as a point in which the ground speed was less than 4 m/s (hereafter "standing point"; Supplementary Fig. S7). A point-density analysis was used to identify foraging areas with high density of standing points. Using this method, all "flights corridors", from the nest to the foraging areas, were excluded from the foraging area analysis. Our observations demonstrated that most of the activity in a radius of <0.15 km and <1.5 km from nests of LLB and STE, respectively, were dedicated to social interactions and not foraging; thus, were not included in the foraging-area analysis. For each individual we calculated the average distance between its nest and all the data points in its foraging area polygon.

Quality control for our analysis was composed of the following steps: (1) Polygons that contains less than 51 data points were excluded. (2) Tagged individuals that didn't achieve the chick-rearing phase (i.e. eggs didn't hatch) were excluded. (3) An average foraging area between two consecutive years was made for tagged individuals whose tag has been working throughout two consecutive breeding seasons (e.g. solar tags) and had similar foraging area during these two years ( Supplementary Fig. S8).

LLBs tend to start incubating roughly three weeks prior to STEs, and complete their nesting approximately six weeks before STEs. Therefore, we analyzed our data in two separate time frames: (a) the entire breeding season from early incubation until one month after fledging for each species; and (b) the overlapping period (shared) within the breeding season of both species, i.e., from STEs' early incubation until the end of LLBs' post fledging phase (i.e. ~March 25 th - July 15 th).

Pairwise attraction-repulsion relationships between each pair of birds in the nesting site was conducted using the MoveMine49 software. MoveMine determines the relationship by comparing the expected meeting frequency, as predicted using permutation of the observed tracks, with the actual meeting frequency in a pair of tracks50, where meeting is defined using proximity in space and time. Cluster analyses were conducted on known foraging points for individuals breeding in close proximity to one another. The k-means method of clustering, from the software MATLAB 2015a using the "kmeans" function, was utilized to classify foraging locations to spatially coherent groupings, assuming 5 clusters and an Euclidian distance function.

Small-scale foraging habitat type

After determining the foraging areas, we identified and compared the foraging habitat types of the two raptor species within their foraging areas. We used the most current Israeli land cover GIS layer (KKL-JNF- Land cover survey of Israel, dataset 5, 2012). This dataset contains 15 categories of habitats within the study area; the four most common were: (1) Mediterranean rocky area, (2) Mediterranean Garrigue and Batha (hereafter low natural vegetation), (3) cultivated fields (e.g. all types of agricultural field crops: wheat, lucerne, potato etc.), and (4) uncultivated land (e.g. low vegetation leafy fields across the foothills valleys, sparse vegetation near dirt roads, exposed areas, etc.). The other 11 categories included: constructed land, quarries, breached areas, sandy areas, chaparral and forests 2-6 m height (dense, medium and sparse densities) and chaparral and forests 6-12 m height (dense, medium and sparse densities). The proportions of land cover of each of the 15 habitat types over the entire study area were determined using GIS. We identified the respective land cover type underneath each foraging standing point using GIS operations. This yielded a statistical distribution of habitat types in the foraging area, which is less prone to bias than a simple overlay of the entire KDE polygon on the land cover map.

Timing-of-foraging analysis

We quantified and compared the foraging time for the two raptor species within their foraging areas. We monitored the time of foraging activity of each tagged individual of both species based on the timing of the position fix within their foraging area. We used only tagged individuals that achieved the chick-rearing phase and wore a solar tag, as their sampling frequency was sufficiently high to evaluate the timing of foraging in a consistent manner. Thus, timing of foraging was calculated for two and six individuals of STE and LLB, respectively. For each of these individuals we calculated the proportion of fixes during each daytime hour between 07:00-19:00.

Diet analysis

All food remains and pellets were collected from each nest twice a year during three breeding seasons (2011-2013). In total we collected food remains from 182 nests of STE and 100 of LLB. The most widely used method for investigating raptors' diet includes the analysis of both pellets and prey remains left at the nest51. We used a combination of these two methods to achieve a complete and reliable picture of the entire breeding diet52. All food remains and pellets were identified to the lowest possible taxonomic level. To prevent bias, we underestimated prey items as we considered all remains of one taxon that were found in one pellet as a single prey item52. Groups of feathers, fur or scales were recorded as a single prey item for each pellet or prey remain.

In total, 2,861 prey items were identified and categorized into 53 taxa, most of them to the species level ( Supplementary Table S5). The identification of the reptile class was carried out by making a comprehensive scale index for most reptiles found in the Judean Foothills. By using this index, we were able to identify a species using a single dorsal scale. Mammals were identified by their bones, teeth, fur and nails while birds were identified by their feathers, bones, claws and legs. Arthropods were identified by their cuticles or the morphology of specific body parts.

In order to prevent bias we excluded all nests with samples which contained fewer than eight prey items during a breeding season. We have found that the two raptor species are monogamous and that pairs return to the same territories each year ( Supplementary Fig. S8). To avoid pseudo-replication of nests among years we calculated the average number of each prey taxon per year for each nest. Consequently, all diet analyses were based on the average number of prey taxon of 32 and 59 nests for LLB and STE, respectively. For further calculations and statistical analyses we used either the frequency or the proportion of each prey taxa.

Data analyses

We calculated foraging area overlaps within and between individuals of the two species based on the Utilization Distribution Overlap Index (UDOI)29 using R Package 'adehabitat'48. For the comparison of the (1) habitat type within foraging area, (2) foraging timing, and (3) overall diet compositions of the two raptor species, data on (1) the proportions of habitat type used, (2) foraging time activity, and (3) prey taxa proportions, respectively were subjected to classification and ordination (PRIMER v6.2; www.primer-e.com)53. Analysis of similarity (ANOSIM)54, with the Global-R statistic was employed to test the null hypothesis of no difference between habitat type within foraging area, foraging timing and overall diet compositions of the two raptor species. We evaluated the interspecific niche overlap between the two species, and the intraspecific overlap among individuals within each raptor species with regard to habitat type use within their foraging area, foraging time and diet by using Pianka's index55. To evaluate whether the pattern of the observed Pianka's niche overlap diverged significantly from a random distribution (absence of overlap) we tested significance of the overlap by comparing the observed frequency of habitat type use, foraging timing and dietary prey taxa using randomization algorithms (RA3) by the ECOSIM 7 software56. We used rarefaction analysis to estimate the predicted total prey taxa richness in the diet of each of the two raptor species based on the frequency of prey taxa57. The dietary-niche breadth of each of the two raptor species was calculated by Levin's index ( B i). For full description of the above data analyses methodologies see Supplementary Methods.

Data availability

The movement data used in this study are available on Movebank (movebank.org, study name "Movements of long-legged buzzards and short-toed eagles") and are published in the Movebank Data Repository47.

Additional Information

How to cite this article: Friedemann, G. et al. Multidimensional differentiation in foraging resource use during breeding of two sympatric top predators. Sci. Rep. 6, 35031; doi: 10.1038/srep35031 (2016).

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Acknowledgements

This research was supported by the Keren Kayemeth LeIsrael (KKL-JNF), the Ministry of Science and Technology (Israel), Smaller-Winnikow Foundation, Israel Nature and Parks Authority (INPA), Hoopoe Foundation (SPNI), Rieger Foundation (USA), Raptor Research Foundation (RFF), the International Center for the Study of Bird Migration at Latrun (Israel) and Kfar-Etzion field school (Israel). GB and KMM were supported in part by NASA grant #NNX11AP61G, US National Science Foundation grant #IOS-1145952 and the Jacob and Lena Joels Memorial Foundation Visiting Professor Award. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We thank many people for their useful advises and helpful analysis, including O. Spiegel, R. Harel, Y. Orchan, R. Nathan, Y. Bartan, and S. Rotich (Movement Ecology Lab-HUJI); R. Rabinovich, and R. Biton (HUJI); Y. Nissan, R. Talmor, A. Sherman (KKL); F. Kuemmeth and W. Heidrich (E-Obs GmbH); We are grateful to D. Brand, Y. Rozental, H. Mazar, D. Alon, N. Leader, Y. Malichi, O. Hatzofe, for their generous logistical support and research permits. We thank our accompanying committee: U. Motro, A. Lotem, and G. Katzir for their useful guiding. We are grateful to many people who helped during fieldwork, including U. Kaizer, Y. Ben-Ari, O. Sulimani, D. Gad, Y. Miller, G. Perlman, Y. Perlman, Y. Kiat, J. Meyrav, D. Oz, A. Saieg, Y. Motro, D. Oberman, I. Eitan, I. Ben-Dov, Y. Milo, G. Milo, R. Izraeli, Y. Friedemann, B. Porat, D. Gavish, G. Kali, B. Rinat, A. Naor, Y. Sela, E. Haklai, A. Ben-Gigi, N. Laufer, Y. kaufman, E. kaufman, Y. Siman-Tov, U. Levin, D. Ashkenazi, O. Ben-Shabat, T. Levi, D. Barel, A. Goldfarb, I. Shifman, Y. Shamir, H. Ben-Yaakov, B. Trooper, and R. Milgalter. This paper is dedicated to the memory of R. Trabelsy.

Author information

Affiliations

1. Department of Zoology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Israel

Guilad Friedemann

, Yossi Leshem

& Lior Kerem

2. National Natural History Collections, The Hebrew University of Jerusalem, Israel

3. Department of Biology and Environment, University of Haifa at Oranim, Kiryat Tivon, Israel

4. Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA

Krystaal M. McClain

& Gil Bohrer

5. Department of Evolutionary and Environmental Biology, Faculty of Natural Sciences, University of Haifa, Israel

Contributions

G.F., Y.L. and I.I. conducted, analyzed and collected the data for the study and wrote this manuscript. L.K assisted with nest climbing. B.S. assisted with the diet analysis. A.B.-M. analyzed the KDEs and timing of foraging. K.M.M. and G.B. analyzed the MoveMine and Cluster sections, and participated in the writing of the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Guilad Friedemann.

Supplementary information

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Multidimensional differentiation in foraging resource use during breeding of two sympatric top predators

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Ecologically-similar species were found to develop specific strategies to partition their resources, leading to niche differentiation and divergence, in order to avoid interspecific competition. Our study determines multi-dimensional differentiation of two sympatric top-predators, long-legged buzzards (LLB) and short-toed eagles (STE), which recently became sympatric during their breeding season in the Judean Foothills, Israel.

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Booted eagle and Eurasian Eagle owl are 2 predator birds that live and breed on Euboya Island!They do have the same  eating habits and behaviours.Theyusually select obvious topographic features such as rocky pinnacles, stark ridges and mountain peaks to use as regular song posts.
They both eat Small and medium-sized birds, from small passerines to pigeons, gamebirds, domestic fowl and corvids; also mammals, including mice

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Booted Eagle

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The booted eagle ( Hieraaetus pennatus, also classified as Aquila pennata) is a medium-sized mostly migratory bird of prey with a wide distribution in the Palearctic and southern Asia, wintering in the tropics of Africa and Asia, with a small, disjunct breeding population in south-western Africa.

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The Eurasian eagle-owl is a very large bird, smaller than the golden eagle ( Aquila chrysaetos) but larger than the snowy owl, despite some overlap in size with both species. It is sometimes referred to as the world's largest owl, although Blakiston's fish owl ( B.

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Ecological Niche of Common toad bufo bufo

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Ecological Niche of Common toad bufo bufo

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Common toad videos, photos and facts - Bufo bufo | Arkive

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The common toad (Bufo bufo) is surrounded by a wealth of folklore and superstition. It can alter the tone of its skin to suit its surroundings; the upper surface may be brown, greenish or grey, and...

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As other toads, B. bufo is active mainly in twilight. The activity in light time, common for the toads of the Bufo viridis group, is rare in the Common Toad. The toads hibernate singly or in groups from September - beginning of November to March - June, depending on the altitude and latitude. Hibernation occurs on land and occasionally in streams and springs. Usually, the hibernation is finished in April - May. Reproduction occurs from March - June (usually late April - May). Amplexus is pectoral. A few males often clasp one female, and in many instances several males try to clasp the same female, and large "balls" consisting of numerous toads may be observed. The smallest males are forced out by larger individuals. Therefore, assortative (by body size) mating takes place. Embryonic and larval development takes usually 1.5-2.5 months.

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Ecological niche of two characteristic animals

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Ecological niche of two characteristic animals

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Sometimes distinct species, in different parts of the world, share very similar functions within the ecosystems they inhabit. This is especially true among species belonging to the same genus, such as pipits. There are 44 different species of pipit. They are around 20 cm in size and can be found all over the world. They are all very similar and perform the same functions in their environments, although they cannot mate with each other. However, there are also totally distinct species that perform similar functions in their ecosystems, such as the woodpecker and the aye-aye. But before we talk about them, let's define a couple of important concepts:

The ecological niche of a species

The function or set of interrelations that an organism maintains within the ecosystem where it lives is known as an ecological niche. We can say that it is a way of life of the species, which includes its conditions, the resources it uses and the way it interacts with the environment and the other species within it.

For example, emperor penguins have bodies adapted to hunting in water at very low temperatures (where they live most of the time). They feed mainly on fish, crustaceans and squid, so are predators. At the same time they are prey to larger animals, such as killer whales. These characteristics, combined with many others, define the emperor penguin's ecological niche. But what if two species share the same ecological niche in the same geographical area?

The same ecological niche in the same geographical area

Well, they have a problem, and a serious one. Two organisms with the same ecological niche cannot survive in the same habitat in the long term. In fact, when this happens (for example, by introducing invasive species), when competing for the same resources, one of the two species will eventually disappear. We call this the principle of competitive exclusion. Even so, there are species in a given ecosystem with only partly overlapping niches that manage to coexist.

When there is competitive exclusion, if one of the species is able to adapt and evolve to find another ecological niche to survive, we say that there is a partition of resources, allowing both species to coexist.

What if two different species share an ecological niche in different habitats?

Vicarious species or vicariants and the concept of dispersion

When we think of very similar species that inhabit geographically opposite places (such as the monkeys of the old world and those of the new world or the various species of apes), a question arises: How is it possible for such similar animals to live in opposite and isolated places?

There are two hypothetical answers to this question:

Dispersalism

This theory suggests that species can overcome geographic barriers or obstacles that limit their territory (such as mountain ranges or oceans) by colonising a second territory. Therefore, part of species "A" could cross a chain of mountains and evolve over time into species "B", different and isolated from the first.

Vicariance

Vicariance, supported by the discovery of tectonic plates, shows that the same phenomenon can occur in another way: species "A" occupies an extensive territory, which is divided by the appearance of a geographical barrier that separates them. In this case, the same species will evolve into two different ones: "B" and "C", isolated by this barrier.

In fact, both of these mechanisms can happen simultaneously, for example when the Strait of Gibraltar was created, which separated Africa and the Iberian Peninsula. Terrestrial species may have experienced vicariance and dispersalism simultaneously. Let's look at some examples:

Elephant birds, moas, ostriches, emus, cassowaries, rheas, tinamous and kiwis

Let's consider all the species present in this image. They're all representatives of different orders (the first two extinct), which form a single superorder: paleognaths. This means that they all have a common ancestor. At some point, because of the effects of dispersalism and/or vicariance, they were separated, evolving into the 50 species that form the superorder. Each one inhabits a different part of the planet (although there is some evidence and opposing hypotheses about their origin).

But do they share an ecological niche?

The rhea and the ostrich, or even the emu and the cassowary could be described as sharing an ecological niche. They have similar characteristics, eat similar types of food and face similar predators. But in the case of the tinamous and kiwis, their physiognomy and characteristics place them in very different niches, despite having evolved from a common ancestor.

The woodpecker and the aye-aye

As I said at the beginning, two species can share an ecological niche without being alike. They don't even need to belong to the same class. This is the case of the aye-aye, a rare primate endemic to Madagascar, and the woodpecker.

The aye-aye has a special finger that's thinner, longer and more flexible than the others. They use their big ears to listen to activity under the tree bark, their specialised teeth to puncture it and their finger to extract insect larvae lodged inside.

The woodpecker does something very similar, hitting the bark with his beak repeatedly to pierce it and reach the larvae that hide there.

This and other characteristics related to each of the ecosystems in which they live means that they share similar ecological niches, even though they have evolved in completely different places.

Conclusion

There are many species that share an ecological niche in different territories. Some are similar to each other, such as brown bears and polar bears or cows and bison, who share common ancestors. In other cases, these species are very different, such as kangaroos, whose niche is similar to that of cows and bison, despite having different evolutionary origins. The difference between both forms is down to the effects of dispersalism and vicariance, or simply by a similar adaptation to the environment in unrelated species.

References:

I'm a photographer, designer and future zoologist. I write about wildlife and do the artwork for Zoo Portraits and other creative projects.

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What's an ecological niche? Different species and their place within nature

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Sometimes distinct species, in different parts of the world, share very similar functions within the ecosystems they inhabit. This is especially true among species belonging to the same genus, such as pipits. There are 44 different species of pipit. They are around 20 cm in size and can be found all over the world.

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Two Examples of parasitic organisms are 1)Lice 2)ticks
1)How many times as a kid you find lices on your hair?These insects breed on your blood!
2)Ticks is another annoying category of insects which are glued on the skin of animals e.g.dogs and suck blood!

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The program Natura 2000 is a network of areas / zones for the ecosystem protection throughout the European Community. The aim is to ensure the survival of Europe's most valuable and threatened species in our ecosystem ( fauna & flora ) and general biodiversity .

Evia  island has several zones covered by Natura 2000.

Some of them are:

· Mount Ochi - Campos Karystou - River - Cape Kafirefs

· Dirfys : Narrow Forest - Delphi

· Mount Kandylis - Valley Prokopios - Delta Kirea

· Large & Small Livari - Delta Xirias

· Forest St. Nicholas

· Telethrion - Lihada - Gialtra

·

The region contains over 700 different plant species. Some are rare, endemic or protected.

Rare plants in the area

It is not only the local endemic plants that are interesting from a botanical point of view. There are also many plants that are endemic only to Evia or only to Greece. Some are rare, that is, they can be found only in small numbers, or they grow in few areas.  Ochi is the southernmost point at which some species will grow, while others are simply valued as decorative plants.

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τουριστικοί πράκτορες στην εύβοια

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ξενοδοχεία στην εύβοια

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ευβοια ξενοδοχεια 5 αστερων

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ενοικιαζομενα δωματια ευβοια

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ξενωνες ευβοια

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ευβοια παραλιες

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ξενοδοχεια all inclusive στην ευβοια

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ενοικιαζομενα δωματια ευβοια

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ελευθερο καμπινγκ ευβοια

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παραλιες για ελευθερο καμπινγκ στην ευβοια

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παραλίες εύβοια

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ευβοια φωτογραφιες

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παραλιες νοτια ευβοια

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βορεια ευβοια παραλιες

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φθηνοι προορισμοι στην  εύβοια

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καλοκαιρινοι προορισμοι στην  εύβοια

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xειμερινοι προορισμοι εύβοιας

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Goevia.com is the official tourism web site for Evia and Skyro, with information on the main tourist destinations with highlights and happenings

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2 Examples of Animals with a Predator-Prey Relation

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2 Examples of Animals with a Predator-Prey Relation

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1 Example:Bat and Mosquito Relation!Bats breed on mosquitos which reposit their eggs in the water.That s why you find more bats near lakes,river shores,sea shores
2 Example:Eagle and Snake Relation!Eagle is a perdator bird which is stated at the top of the trophic pyramid!Snake is referred as the usual victim of eagle!

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The arrival of Zika virus in America has triggered widespread alarm and a search for mosquito control remedies. It is carried by mosquitoes belonging to the genus Aedes that appear to be active both night and day. As in the control of other mosquitoes, a variety of options should be considered.

Existing chemical pesticides typically cause more long-term problems than they solve. Chemical poisons kill natural mosquito predators more effectively than mosquitoes. Over time, predators of mosquitoes such as fish, other insects, and bats (with much smaller populations and slower reproductive rates), die out while mosquitoes develop resistance, multiplying in ever larger numbers in a losing battle often referred to as "the pesticide treadmill." ¹ As resistance develops, larger quantities or increased toxicity are required, eventually threatening environmental as well as economic and human health.

Bats are primary predators of the vast numbers of insects that fly at night, and some species consume large numbers of mosquitoes when they are available. However, mosquito control is a complex problem that rarely can be solved by a single approach.

For many years biologists debated whether or not predators, including bats, could help reduce mosquito abundance. Some pointed out that, overall, mosquitoes comprised only a small fraction of prey found in bat stomach and fecal analyses. This is true. But no allowance was made for the fact that studies were often conducted at times and places where mosquitoes were either rare or absent. When mosquitoes are abundant (the only times when we're concerned!), even some of America's largest, seemingly unlikely bat species have been found consuming large numbers in a single meal. ²

Biologists at the University of Michigan were the first to conduct an experimental assessment of the imA little brown myotis (Myotis lucifugus) in flight in Wisconsin. One bat can catch up to 1,000 mosquito-sized insects in a single hour.pact of bats on mosquitoes. They documented that bats can significantly reduce numbers of ovipositing mosquitoes and suggested that "bat predation on mosquitoes could help regulate disease vectors." 3 Claims that bats are irrelevant to pest control typically come from those who benefit from sales of chemical alternatives or bat exclusion services.

Individuals of some bat species can capture up to 1,000 mosquitoes in a single hour, ⁴and large colonies can consume amazing quantities. For example, a Florida colony of 30,000 southeastern bats was calculated to capture 50 tons of insects annually, including over 15 tons of mosquitoes, ⁵ and from 77.4% to 84.6% of little brown bats living in the northern U.S. and Canada eat mosquitoes. 6,7 Because mosquitoes do not take evasive action, and are exceptionally easy to capture, bats sometimes appear to prefer them over larger prey. 8,9 Bats can be attracted to live in bat houses, 10 and nursing mothers can eat up to their body weight in insects nightly. ¹¹

Nevertheless, despite the numbers of mosquitoes that bats eat, simple provision of additional roosts should not be promoted as more than one potentially helpful step toward solving mosquito problems. In some cases bat houses may help and in others, they may not. Bats are one of several groups of animals that naturally prey on mosquitoes. Their relative importance varies from none to high in different locations.

Where human activities have greatly simplified once diverse habitats, predators of pests may decline to the point of irrelevance. For example where single crops cover large areas there may be too few alternative prey between crops to feed insectivorous animals. Loss of biodiversity threatens whole ecosystems, which cannot be restored by simply providing bat houses. Mosquito-eating bats may also die out in some areas due to loss of suitable hibernation caves. Finally, over use of pesticides may preclude help from natural predators in general.

No single approach to mosquito control is appropriate for all locations. However encouraging natural predators should be an important priority in long-term planning. Anything that can be done to facilitate mosquito predation by aquatic insects, fish, or bats may prove helpful.

In areas like Chautauqua, New York, where bats apparently have traditionally played a valuable role, all possible precautions should be taken to ensure their continued presence. And where bats are known to have declined, their recovery should be encouraged.

Putting up bat houses may be quite helpful in places where appropriate bats can be attracted, but even successful bat houses do not always attract a species that feeds heavily on mosquitoes. Some bat-house-dwelling species prefer moths or beetles and may prove more helpful in protecting your yard or garden. Either way, bat houses can be beneficial, and attracting bats is far safer than applying toxic chemicals.

It is unrealistic to even attempt total control of mosquitoes. In most cases, this is impossible for more than brief periods, though mosquito numbers can be substantially reduced. Poisoning will only exacerbate long-term problems. 12,13 First lines of defense should always include elimination of as much temporary standing water as possible, and can be as easy as regularly emptying (or changing) water from flower pots, bird baths, clogged rain gutters or other water-holding containers. Such simple approaches can work wonders in reducing mosquitoes. Finally, introducing mosquito-eating fish into permanent ponds and providing roosts for bats can further aid in success. Responsible mosquito reduction typically requires a multifaceted approach.

Bat houses are most likely to succeed where bats are already known to use old buildings. Such roosting habitat is gradually being replaced by structures that are unsuitable for bats, forcing them to find new roosts or die. All American bats are beneficial in keeping the vast numbers of night flying insects in balance, though their primary diets vary considerably.

Building bat houses is an especially good and timely idea quite aside from any hoped for impacts on mosquito control. Millions of American bats have recently been killed by an accidentally introduced fungus, Pseudogymnoascus destructans. ¹⁴ It causes white-nose syndrome (WNS). You can help survivors rebuild populations by providing summer homes. Our bats are worth billions of dollars annually in agricultural protection alone. ¹⁵

Plans for building several kinds of artificial roosts are readily available, including structures capable of housing from dozens to thousands of bats. ¹⁶ If you'd prefer to buy a bat house, beware of cheap imitations that fail to meet bat needs. The best bat houses will be caulked, tightly sealed and securely put together with screws. All landing and roosting area surfaces will be roughened to provide secure footing for bats (ideally with cross-cut grooves about 1/16 th-inch deep). Roosting spaces will be approximately 3/4-inch wide (no less than 1/2 nor more than 1-inch), and the overall external dimensions ideally should be at least 24 inches tall by 14 inches wide. All houses should have a roughened landing area extending 4-8 inches below the entry.

Both single and multi-chamber houses can be quite successful, though four-chamber houses have proven most attractive for nursery colonies. All houses, prior to mounting, should receive at least three coats of paint to ensure long-lasting weather resistance. Bats do not like drafty or leaky homes. Black houses are best in the coolest climates, ranging from light or medium brown in the hottest. Bats like to have roosting options, so those who put up at least two to three houses, on average double their probability of success.

Location of mounting is also important. The most successful houses are located within a quarter mile of a lake, pond or stream and are at least 10-15 feet above ground. In areas where average day to night temperature fluctuations in summer are less than 20 degrees F, houses can be mounted on poles in back-to-back pairs, facing north-south or east-west. Where day to night temperature fluctuations exceed 20 degrees, they should be mounted only on buildings (which serve as thermal heat sinks). All houses should receive at least six hours of direct daily sun (even in hot climates). In general, more is better. Bats like amazingly warm homes, though in all but the coldest climates bat houses should be equipped with ventilation slots in either the front or sides, approximately 6-8 inches above the entry to prevent over-heating. Houses mounted on or too near trees are least successful, because they are often too shaded and may also be too vulnerable to predators.

Single chamber houses may hold up to 50 bats, usually less, while multi-chamber houses are more likely to attract nursery colonies of up to 200. Exceptionally large artificial roosts have attracted up to 250,000 or more bats. We are happy to provide the most up-to-date advice on these and varied additional options and welcome reports of unusual successes or failures. Contact Merlin at MerlinTuttle.org or John here at jchenger@batmanagement.com

References

Spooner, A.M. Environmental Science for Dummies. http://www.dummies.com/how-to/content/the- dangers-of-pesticides-in-the-environment.html

Whitaker, J.O., Jr., C. Maser and L.E. Keller. 1977. Food habits of bats in western Oregon. Northwest Sci., 51:46-55.

Reiskind, M.H. and M.A. Wund. 2009. Experimental assessment of the impacts of northern long-eared bats on ovipositing Culex (Diptgera: Culicidae) Mosquitoes. J. Med. Entomol. 46(5):1037-1044.

Rydell, J. 1990. The northern bat of Sweden: Taking advantage of a human environment. Bats, 8 (2):8- 11.

Zinn, L., and S.R. Humphrey. 1976. Insect communities available as prey and foraging of the southeastern brown bat. Proc. 7th Annual North American Symposium on Bat Research, unpubl. paper presented at symposium.

Anthony, E.L.P, and T.H. Kunz. 1977. Feeding strategies of the little brown bat, Myotis lucifugus, in southern New Hampshire. Ecology, 58:775-786.

Fascione, N., T. Marceron, and M.B. Fenton. 1991. Evidence of mosquito consumption in M. lucifugus. Bat Res. News, 32(1):2-3.

Kalko, E.K.V. 1995. Insect pursuit, prey capture and echolocation in pipistrelle bats (Microchiroptera). Animal Behavior, 50:861-880.

Rydell, J., D.P. McNeill, and J. Eklof. 2002. Capture success of little brown bats (Myotis lucifugus) feeding on mosquitoes. J. Zool., London, 256:379-381.

Tuttle, M.D., and M. Kiser and S. Kiser. 2004. The bat house builder's handbook. Bat Conservation International, Austin, Texas, 35 pp. Revised 24 July 2006

Kurta, A., G.P. Bell, K.A. Nagy, and T.H. Kunz. 1989. Energetics of pregnancy and lactation in freeranging little brown bats Myotis lucifugus. Physiol. Zool., 62:804-818.

1. 2012. Aerial spraying public health hoax. PEEReview, Fall, pp. 1&12.

2. Howard, J.J., and J. Oliver. 1997. Impact of Naled (Dibrom 14@) on the mosquito vectors of Eastern Equine Encephalitis Virus. Journal of the American Mosquito Control Association, 13(4):315-325.

3. USGS National Wildlife Health Center http://www.nwhc.usgs.gov/disease_information/white- nose_syndrome/

4. Boyles, J.G., P.M. Cryan, G.F. McCracken and T.H. Kunz. 2011. Economic importance of bats in agriculture. Science, 332(6025):41-42.

5. Tuttle, M.D., M. Kiser and S. Kiser. 2005. The bat house builder's handbook. Univ. Texas Press, Austin, 35 pp. https://www.amazon.com/Builders-Handbook-Completely-Revised- Updated/dp/0974237914

All text and images protected by copyright. Contact Merlin Tuttle's Bat Conservation
Article date 8/29/16 - Reprinted by Bat Conservation and Management with permission

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By Merlin Tuttle Merlin Tuttle's Bat Conservation The arrival of Zika virus in America has triggered widespread alarm and a search for mosquito control remedies. It is carried by mosquitoes belonging to the genus Aedes that appear to be active both night and day.

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 Come up with possible reasons for the decision to reintroduce grey wolves into the National Park. From the three options below, select the reason you find most likely

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 Come up with possible reasons for the decision to reintroduce grey wolves into the National Park. From the three options below, select the reason you find most likely

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3.The wolves were brought in because the increased elk population was overgrazing the deciduous, woody species such as aspen and cottonwood.

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On a quiet spring morning, a resounding "Slap!" reverberates through the air above a remote stream leading to Lake Yellowstone. Over much of the past century, it has been a rarely heard noise in the soundscape that is Yellowstone National Park, but today is growing more common-the sound of a beaver slapping its tail on the water as a warning to other beavers.

When the grey wolf was reintroduced into the Greater Yellowstone Ecosystem in 1995, there was only one beaver colony in the park, said Doug Smith, a wildlife biologist in charge of the Yellowstone Wolf Project.

Today, the park is home to nine beaver colonies, with the promise of more to come, as the reintroduction of wolves continues to astonish biologists with a ripple of direct and indirect consequences throughout the ecosystem.

A flourishing beaver population is just one of those consequences, said Smith.

A Yellowstone Beaver's Tale of Elk

What happened, said Smith, is that the presence of wolves triggered a still-unfolding cascade effect among animals and plants-one that will take decades of research to understand.

"It is like kicking a pebble down a mountain slope where conditions were just right that a falling pebble could trigger an avalanche of change," Smith mused.

So how did this avalanche of change work out for the beaver?

To answer that, you have to go back to the 1930s, when the wolf was killed off in Yellowstone. Even though Yellowstone elk were still preyed upon by black and grizzly bears, cougars and, to a lesser extent, coyotes, the absence of wolves took a huge amount of predatory pressure off the elk, said Smith. As a result, elk populations did very well-perhaps too well. Two things happened: the elk pushed the limits of Yellowstone's carrying capacity, and they didn't move around much in the winter-browsing heavily on young willow, aspen and cottonwood plants. That was tough for beaver, who need willows to survive in winter.

Healthier Willow Stands in Yellowstone

This created a counterintuitive situation. Back in 1968, said Smith, when the elk population was about a third what it is today, the willow stands along streams were in bad shape. Today, with three times as many elk, willow stands are robust. Why? Because the predatory pressure from wolves keeps elk on the move, so they don't have time to intensely browse the willow.

Indeed, a research project headed by the U.S. Geological Survey in Fort Collins found that the combination of intense elk browsing on willows and simulated beaver cuttings produced stunted willow stands. Conversely, simulated beaver cutting without elk browsing produced verdant, healthy stands of willow. In the three-year experiment, willow stem biomass was 10 times greater on unbrowsed plants than on browsed plants. Unbrowsed plants recovered 84 percent of their pre-cut biomass after only two growing seasons, whereas browsed plants recovered only 6 percent.

With elk on the move during the winter, willow stands recovered from intense browsing, and beaver rediscovered an abundant food source that hadn't been there earlier.

As the beavers spread and built new dams and ponds, the cascade effect continued, said Smith. Beaver dams have multiple effects on stream hydrology. They even out the seasonal pulses of runoff; store water for recharging the water table; and provide cold, shaded water for fish, while the now robust willow stands provide habitat for songbirds.

"What we're finding is that ecosystems are incredibly complex," he said. In addition to wolves changing the feeding habits of elk, the rebound of the beaver in Yellowstone may also have been affected by the 1988 Yellowstone fires, the ongoing drought, warmer and drier winters and other factors yet to be discovered, Smith said.

Yellowstone Wolf Trophic Cascade

Biologists are often faced with the grim task of documenting the cascade effects of what happens when a species is removed from an ecosystem, by local extirpation or even extinction. In Yellowstone, biologists have the rare, almost unique, opportunity to document what happens when an ecosystem becomes whole again, what happens when a key species is added back into the ecosystem equation.

"In the entire scientific literature, there are only five or six comparable circumstances," Smith said. "What we're seeing now is a feeding frenzy of scientific research."

Scott Creel, an ecology professor at Montana State University, is hip-deep in that feeding frenzy.

"My research has been in the Gallatin Canyon," said Creel, where elk inhabit four drainages. Wolves come and go, he said, enabling him to study what elk do in the presence and absence of wolves.

"Elk have proven to be pretty adaptable," Creel said. "When wolves are around, they're more vigilant and do less foraging."

Elk move into heavy timber when wolves are around, Creel added, but return to the grassy, open meadows when wolves go away. Creel and other researchers are still working out what that means in terms of the elk's diet and whether there are costs associated with this behavior.

Rather surprisingly, elk herd size breaks up into smaller units when wolves are around, said Creel, who had expected herd size to get bigger as a defense mechanism. "I think they're trying to avoid encounters with wolves," he said, by being more vigilant, moving into the timber and gathering in smaller herd units.

Yellowstone Wolves are Food Distributors

Researchers have also determined that wolves, in the recent absence of hard winters, are now the primary reason for elk mortality. Before wolf reintroduction, deep snows were the main determinant of whether an elk was going to die.

Researchers from the University of California at Berkeley determined that the combination of less snow and more wolves has benefited scavengers both big and small, from ravens to grizzly bears.

Instead of a boom and bust cycle of elk carrion availability-as existed before wolves and when winters were harder-there's now a more equitable distribution of carrion throughout winter and early spring, said Chris Wilmers in the on-line journal Public Library of Science Biology. He added that scavengers that once relied on winter-killed elk for food now depend on wolf-killed elk. That benefits ravens, eagles, magpies, coyotes and bears (grizzly and black), especially as the bears emerge hungry from hibernation.

"I call it food for the masses," said Ed Bangs, wolf recovery coordinator for the U.S. Fish and Wildlife Service. He said he was genuinely surprised by the vast web of life that is linked to wolf kills. "Beetles, wolverine, lynx and more," he said. "It turns out that the Indian legends of ravens following wolves are true-they do follow them because wolves mean food."

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On a quiet spring morning, a resounding "Slap!" reverberates through the air above a remote stream leading to Lake Yellowstone. Over much of the past century, it has been a rarely heard noise in the soundscape that is Yellowstone National Park, but today is growing more common-the sound of a beaver slapping its tail on the water as a warning to other beavers.

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1200px-Εκκλησάκι_Προφήτη_Ηλία_στο_Τελέθριο_όρος,_Εύβοια

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The ecological niche of Vipera ammodytes meridionalis 

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The ecological niche of Vipera ammodytes meridionalis 

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The common name sand viper is misleading, as this species do not occur in really sandy areas.[11] Mainly, it inhabits dry, rocky hillsides with sparse vegetation. Not usually associated with woodlands, but if so it will be found there around the edges and in clearings. Sometimes found in areas of human habitation, such as railway embankments, farmland, and especially vineyards if rubble piles and stone walls are present. May be found above 2000 m at lower latitudes

This species has no particular preference for its daily activity period. At higher altitudes, it is more active during the day. At lower altitudes, it may be found at any time of the day, becoming increasingly nocturnal as daytime temperatures rise.[4]

Despite its reputation, this species is generally lethargic, not at all aggressive, and tends not to bite without considerable provocation. If surprised, wild specimens may react in a number of different ways. Some remain motionless and hiss loudly, some hiss and then flee, while still others will attempt to bite immediately.[4]

V. ammodytes hibernates in the winter for a period of 2 to 6 months depending on environmental conditions.
Primarily feeds on small mammals and birds. Juveniles apparently prefer lizards. Feeding behavior is influenced by prey size. Larger prey are struck, released, tracked, and swallowed, while smaller prey is swallowed without using the venom apparatus. Occasionally, other snakes are eaten.[4] There are also reports of cannibalism.
Before mating, the males of this species will engage in a combat dance, similar to adders.[4] Mating takes place in the spring (April–May), and one to twenty live young are born in late summer or fall (August–October). At birth, juveniles are 14–24 cm (5.5–9.4 in) in total length.[7] This species is ovoviviparous

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Vipera ammodytes (other common names include horned viper , long-nosed viper, nose-horned viper, sand viper) is a viper species found in southern Europe through to the Balkans and parts of the Middle East. It is reputed to be the most dangerous of the European vipers due to its large size, long fangs (up to 13 mm) and high venom toxicity.

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Μεγάλο_Λιβάρι_Ιστιαία

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Eagle vs. Toxic Snake | World's Deadliest

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MOUNT OCHI - PLAIN OF KARYSTOS - RIVER - CAPE KAFIREFS - COASTAL SEA ZONE GR2420001

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MOUNT OCHI - PLAIN OF KARYSTOS - RIVER - CAPE KAFIREFS - COASTAL SEA ZONE GR2420001

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The site is located in the southern part of the island of Evvoia. It contains two distinct areas: The "Kampos Karystou" plain and the mountain Ochi with the coastal areas of Cape Kafirefs and Potami. Kampos Karystou is a coastal plain lying west of Karystos, with extensive cultivated fields, small freshwater lakes, intermittently flowing streams and freshwater marshes, which are characterized by the presence of the plant species Typha latifolia, Salix sp. and Phragmites australis (a habitat type not included in Annex I, described in Corine 91 by code 53.2). Ochi mountain (1398 m) is located NE of Karystos. The most remarkable characteristics of this part of the site are: the extensive area with phrygana and sclerophyllus shrubs (especially Quercus coccifera), the many green valleys with Platanus orientalis, the small chestnut forest near the highest peak, and the rivers in which the dominant species are Vitex agnus-castus and Nerium oleander. The marine area of the site is characterized by the existence of posidonia beds, mainly in deep waters (>20 m) and by reefs (along Cape Kafirefs). Both of these ecosystems are in excellent condition. NOTES 1. In Kampos Karystou area there are extensive crops, not described by any habitat type of Annex I. 2. Habitat type 9320 describes areas with Olea europaea and Pistacia lentiscus shrubs. 3. On Ochi mountains there are extensive patches of Pteridium aquilinum. 4. There are Erica manipuliflora heathlands, a habitat type not included in Annex I.
Characteristic Habitats |
Valuable Plants
| Anthemis cretica cretica
Armeria johnsenii
Campanula celsii carystea
Cerastium candidissimum
Cerastium runemarkii
Cirsium heldreichii euboicum
Crocus sieberi atticus
Erysimum senoneri senoneri
Fritillaria ehrhartii
Paeonia mascula hellenica
Sideritis euboea
Stachys euboica
Viola euboea
Valuable Mammals | Lutra lutra
Monachus monachus (Meditteranian Seal)

Valuable Amphibians-Reptiles |
bufo bufo
Chalcides ocellatus ocellatus
Elaphe quatuorlineata quatuorlineata
Emys orbicularis
Hyla arborea arborea
Malpolon monspessulanus insignitus
Mauremys caspica rivulata
Ophisaurus apodus thracius
Podarcis erhardii amorgensis
Testudo hermanni hermanni
Vipera ammodytes meridionalis

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EuboeaNative name:

Εύβοια

Geography
Coordinates | 38°30′N 24°00′E
Archipelago | Aegean Islands
Area | 3,684 km ² (1,422 sq mi)
Highest elevation | 1,743 m (5,719 ft)
Highest point | Dirfi
Administration
Greece

Region | Central Greece
Regional unit | Euboea
Municipality | Εύβοια
Capital city | Chalcis
Demographics
Population | 191,206 (2011)
Pop. density | 54 /km ² (140 /sq mi)

Euboea or Evia[1]; Greek: Εύβοια, Evvoia, pronounced [ˈevia]; Ancient Greek: Εὔβοια, Eúboia, [eúboja]) is the second-largest Greek island in area and population, after Crete. The narrow (only 40 meters (130 ft) at its narrowest point)[2] Euripus Strait separates it from Boeotia in mainland Greece. In general outline it is a long and narrow island; it is about 180 kilometres (110 mi) long, and varies in breadth from 50 kilometres (31 mi) to 6 kilometres (3.7 mi). Its geographic orientation is from northwest to southeast, and it is traversed throughout its length by a mountain range, which forms part of the chain that bounds Thessaly on the east, and is continued south of Euboea in the lofty islands of Andros, Tinos and Mykonos.
It forms most of the regional unit of Euboea, which also includes Skyros and a small area of the Greek mainland.