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Fig. 6 in The Eco-Physiological Status Of Hibernating Bats (Chiroptera) In The North Of The European Distribution Range

Fig. 6. Total WBC count and absolute numbers of each type of leukocytes in peripheral blood in bats. 1 - leukocytes 2 - monocytes, 3 - lymphocytes 4 - stab neutrophils, 5 - segmented neutrophils, 6 - eosinophils, 7 - basophils.

Fig. 2 in The Eco-Physiological Status Of Hibernating Bats (Chiroptera) In The North Of The European Distribution Range

Fig. 2. Species structure of hibernating bat populations (% of the total number of animals in the counts): A – Leningrad Region (Стрелков 1958), B – Tver Region (ГлуШкова et al. 2006), C – Samara Region (Смирнов et al. 2012), D – Finland (Siivonen & Wermundsen 2008), E – Karelia (own data), F – Arkhangelsk Region (Рыков 2008). 1 – M. dasycneme, 2 – M. daubentoni, 3 – M. brandtii/mystacinus, 4 – M. nattereri, 5 – P. auritus, 6 – E. nilssonii.

Fig. 5 in The Eco-Physiological Status Of Hibernating Bats (Chiroptera) In The North Of The European Distribution Range

Fig. 5. Differential WBC count in different bat species. 1 - monocytes, 2 - lymphocytes, 3 - band neutrophils, 4 - segmented neutrophils, 5 - eosinophils, 6 - basophils.

Fig. 3 in The Eco-Physiological Status Of Hibernating Bats (Chiroptera) In The North Of The European Distribution Range

Fig. 3. Distribution patterns of the hibernating northern bat, % of the total number of animals in counts: Finland (Siivonen & Wermundsen 2008), Karelia (own data), Ural region (Орлов 2000, БольШаков et al. 2005), Samara Region (Смирнов et al. 2008, Смирнов & Вехник 2009).

Fig. 1 in The Eco-Physiological Status Of Hibernating Bats (Chiroptera) In The North Of The European Distribution Range

Fig. 1. Locations of bat hibernacula in the Republic of Karelia. Legend: 1 – Lahdenpohja, 2 – Ruskeala, 3 – Sona, 4 – Shcheleyki, 5 – Medvezhjegorsk, 6 – Shunga.

Fig. 4 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity

Fig. 4. Time-course of Peformance Index (A) and chlorophyll concentration (B) in leaves of T. maritima plants grown in different substrates.

Fig. 7 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity

Fig. 7. Correlation between summary Na + K concentration and extract EC in leaves (A) and roots (B) of T. maritima plants.

Fig. 1 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity

Fig. 1. Effect of treatment type on soil electrical conductivity (A) and pH (B) after 8 weeks of cultivation.

Fig. 5 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity

Fig. 5. Time-course of Na+ (A), K+ (B) and Ca2+ concentration in leaves of T. maritima plants grown in different substrates.

Fig. 6 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity

Fig. 6. Effect of treatment type on Na+ (A) and K+ (B) concentration in roots of T. maritima plants after 8 weeks of cultivation.

Figure 2. Passion fruit species under different irrigation intervals. A. Passiflora gibertii with a 4 in Development and physiological aspects of three species of passion fruit submitted to water stress

Figure 2. Passion fruit species under different irrigation intervals. A. Passiflora gibertii with a 4-day interval; B. P. gibertii with a 8-day interval; C. P. gibertii with a 12-day interval; D. P. foetida with a 4-day interval; E. P. foetida with a 8-day interval; F. P. foetida with a 12-day interval; G. P. edulis with a 4-day interval; H. P. edulis with a 8-day interval; I. P. edulis with a 12-day interval. Bar = 30 cm.

Fig. 3 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures

Fig. 3. Image illustrating under water visibility at the beginning of the snorkeling excursion and the presence of tourists (Lima, 2008).

Fig. 1 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures

Fig. 1. Map showing the location of the study area: Sucuri River (C), município of Bonito area (B), Brazil (A). Adapted from Miranda & Coutinho (2004).

Fig. 8 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures

Fig. 8. Variation of behaviour patterns between before (8h00) and after (9h00) the first disturbance of tourists in the river (mean and SEM) for M. bonita; (a) Tourism and (b) No Tourism. Lighter bars = 8h00; darker bars = 9h00 (Mann-Whitney U-test). N = 70; * p <0.05; ** p <0.01.

Fig. 9 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures

Fig. 9. Variation (mean and SEM) of cortisol responses to restraining stress in Moenkhausia bonita individuals at the No Tourism and Tourism sites (Mann-Whitney U-test, N = 6; Z = -2.95; p <0.005).

Figure 5 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes

Figure 5. Effect of salinity stress on stomatal conductance (a), and transpiration rate (b) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Error bar shows standard error.

Figure 2 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes

Figure 2. Effect of salinity stress yield (a), and R:S (b) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Data labels represnts the level of significance for multiple comparison between all combination of treatments @ 0.05 probability level. Error bar shows standard error.

Figure 4 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes

Figure 4. Effect of salinity stress on crude protein content (a), Reducing sugars (b) and total carbohydrates (c) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Data labels represnts the level of significance for multiple comparison between all combination of treatments @ 0.05 probability level. Error bar shows standard error.

Figure 3 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes

Figure 3. Effect of salinity stress on proline content (a), lipid peroxidation (b) and H 2 O 2 (c) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Data labels represnts the level of significance for multiple comparison between all combination of treatments @ 0.05 probability level. Error bar shows standard error.

Figure 1 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes

Figure 1. Effect of salinity stress on SL (a) and RL (b) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Data labels represnts the level of significance for multiple comparison between all combination of treatments @ 0.05 probability level. Error bar shows standard error.