Animal Adaptations: Evolution of Forms and Functions

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Avadh Saxena, the American Group Leader of Physics of Condensed Matter and Complex Systems Group (T-4) at Los Alamos National Laboratory Jaarsma, C. F., van Langevelde, F., Baveco, J. M., van Eupen, M. & Arisz, J. Model for rural transportation planning considering simulating mobility and traffic kills in the badger Meles meles. Ecol. Inform. 2, 73–82 (2007).

Sarkar, D. Lattice: Multivariate Data Visualization with R. (2008). Springer, New York. ISBN 978-0-387-75968-5. accessed 25 Mar 2019; https://lmdvr.r-forge.r-project.org/. The threshold traffic volume at which AVC probability was equal to probability of successful crossing ( P h = 0.5) varied for different species. Under present traffic heterogeneity, this threshold traffic for group living animals like chital, gaur and wild pig was 300–400 vehicles/h. This threshold traffic volume was higher for sambar (700 vehicles/h), and highest for tiger and leopard (1100–1300 vehicles/h). Across all simulated scenarios, traffic volumes of 200–300 vehicles/h decreased the chances of a successful crossing by half for gaur. For chital, this traffic volume lies above 400–500 vehicles/h in traffic composed of light vehicles (H 0, H 1, H 4, H 7). This threshold volume is higher for sambar (1100 vehicles/h) in traffic composed mostly of heavy vehicles (H 3, H 5, H 6). Hourly traffic volumes above 1000 vehicles/h posed a barrier to < 50% successful traverses for tiger and leopard at most traffic heterogeneity scenarios. The threshold traffic volume for solitary species was lowest (800 vehicles/h) at scenario H 3 which comprised of only MAVs. Beyond this threshold traffic volume, higher fatalities are expected to occur. At present, traffic on NH 44 may not present a barrier to movement of chital and wild pig as we frequently encounter chital and wild pig roadkill at present traffic volumes. Gaur and sambar, on the other hand, are more vulnerable to barrier effect through avoidance behaviour of roadside habitat that reflects a lower tolerance to traffic disturbance 39, 40. Rhodes, J. R., Lunney, D., Callaghan, J. & McAlpine, C. A. A few large roads or many small ones? How to accommodate growth in vehicle number to minimise impacts on wildlife. PLoS ONE 9(3), e91093 (2014).Mitigation of roadkill and barrier effects of rapidly expanding road networks requires identification of road sections that may cause animal mortalities and barriers to animal movement, and species most likely to be involved in AVCs 8. Studies that take into account road, traffic and landscape characteristics along with species presence, activity and movement characteristics 8, 25, 32 have been able to predict mortality and barrier hotspots across road networks. However, the interaction among risk factors contributing to roadkill and barrier effects to inform mitigation strategies is largely missing from such models. Moreover, mitigation for rapidly expanding road networks should also be informed by road and traffic characteristics such as road types, and projections of traffic growth 33 and traffic composition or ‘heterogeneity’ that is the proportion of different vehicle types in a traffic flow 8. Effect of morning injections of melatonin (aMT)) and 5-methoxytryptamine (MT), for 60 continuous days, on the seminiferous tubule diameter (μm) of testis in sham-operated (S0) and pinealectomized (Px) F. Pennanti exposed to natural daylength (NDL), long photoperiod (14L:10D) and short photoperiod (10L:14D) during the gonad active phase. Among the six study species, lowest AVC probabilities were observed for tiger and leopard, primarily because these are solitary fast moving species. Body size had negligible effect on AVC probability 23, but increase in group size increased the probability resulting in higher AVC probabilities for group living species. Among social species, lower group size of sambar translated to lower AVC probability than chital and wild pig, despite having similar maximum running speeds. Group size of gaur was similar to that of wild pig; yet gaur had the highest AVC probabilities across all heterogeneity scenarios as a result of its low running speed. Roads also cause some species to respond by avoidance of habitat near high traffic roads at peak traffic hours 6, 7. This avoidance of roadside habitat could result in the road becoming a barrier to animal movement 8. In addition to the risk of local species extinction 9, mortality and barrier effects together alter wildlife movement 10, 11 leading to isolation of populations 12, 13. With the global road network growth projected at more than 60% 14, and rampant increase in worldwide vehicle ownership 15, these impacts are set to accelerate in magnitude.

The untreated group of mice infected with the chloroquine sensitive strain, P. berghei recorded a significant (p<0.05) reduction in PCV, Hb, RBC, MCV and neutrophils observably from day 8-14 post infection ( Table 3, 4). While lymphocytes, WBC and platelets counts increased significantly (p<0.05) from day 8-14 postinfection in infected but untreated mice.Velmurugan, S., Errampalli, M., Ravinder, K., Sitaramanjaneyulu, K. & Gangopadhyay, S. Critical evaluation of roadway capacity of multi-lane high speed corridors under heterogeneous traffic conditions through traditional and microscopic simulation models. Journal of Indian Roads Congress (October–December 2010) 235–264 (2010). accessed 23 Mar 2019; https://www.crridom.gov.in/

When the aqueous extracts of A. boonei was administered at the different dosages 100, 200, 400 and 800 mg kg -1 to mice infected with P. berghei, it was observed that the net effect of this extracts was such that it appears to normalize hematological indices in the groups of mice infected and treated with the plant extract when compared with the data obtained for the experimental control groups of mice ( Table 3, 4). Table 1: Arasan, V. T. & Koshy, R. Z. Headway distribution of heterogeneous traffic on urban arterials. J. Inst. Eng. (India) 84, 210–215 (2003).Champion, H. G. & Seth, S. K. A Revised Survey of the Forest Types of India (Manager of Publications Govt. of India, New Delhi, 1968). Jhala. Y. V., Qureshi, Q. & Gopal, R. (eds.). The status of tigers, co-predators & prey in India 2014. National Tiger Conservation Authority, New Delhi & Wildlife Institute of India, Dehradun TR2015/021. (2015).