Assessing tiger population dynamics using photographic capture-recapture sampling

Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, "robust design" capture-recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of gamma" = gamma' = 0.10 +/- 0.069 (values are estimated mean +/- SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 +/- 0.051, and the estimated probability that a newly caught animal was a transient was tau = 0.18 +/- 0.11. During the period when the sampled area was of constant size, the estimated population size N(t) varied from 17 +/- 1.7 to 31 +/- 2.1 tigers, with a geometric mean rate of annual population change estimated as lambda = 1.03 +/- 0.020, representing a 3% annual increase. The estimated recruitment of new animals, B(t), varied from 0 +/- 3.0 to 14 +/- 2.9 tigers. Population density estimates, D, ranged from 7.33 +/- 0.8 tigers/100 km2 to 21.73 +/- 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.     

Spatial heterogeneity influences native and nonnative plant species richness

Spatial heterogeneity may have differential effects on the distribution of native and nonnative plant species richness. We examined the effects of spatial heterogeneity on native and nonnative plant species richness distributions in the central part of Rocky Mountain National Park, Colorado, USA. Spatial heterogeneity around vegetation plots was characterized using landscape metrics, environmental/topographic variables (slope, aspect, elevation, and distance from stream or river), and soil variables (nitrogen, clay, and sand). The landscape metrics represented five components of landscape heterogeneity and were measured at four spatial extents (within varying radii of 120, 240, 480, and 960 m) using the FRAGSTATS landscape pattern analysis program. Akaike's Information Criterion adjusted for small sample size (AICc) was used to select the best models from a set of multiple linear regression models developed for native and nonnative plant species richness at four spatial extents and three levels of ecological hierarchy (i.e., landscape, land cover, and community). Both native and nonnative plant species richness were positively correlated with edge density, Simpson's diversity index and interspersion/juxtaposition index, and were negatively correlated with mean patch size. The amount of variation explained at four spatial extents and three hierarchical levels ranged from 30% to 70%. At the landscape level, the best models explained 43% of the variation in native plant species richness and 70% of the variation in nonnative plant species richness (240-m extent). In general, the amount of variation explained was always higher for nonnative plant species richness, and the inclusion of landscape metrics always significantly improved the models. The best models explained 66% of the variation in nonnative plant species richness for both the conifer land cover type and lodgepole pine community. The relative influence of the components of spatial heterogeneity differed for native and nonnative plant species richness and varied with the spatial extent of analysis and levels of ecological hierarchy. The study offers an approach to quantify spatial heterogeneity to improve models of plant biodiversity. The results demonstrate that ecologists must recognize the importance of spatial heterogeneity in managing native and nonnative plant species.     

Flow of chemical energy in Alwar jheel of Yamuna basin near Allahabad

The water quality, rate of energy transformation, chemical composition of producers and flow of chemical energy were studied in both feeding river Yamuna and Alwar jheel near Allahabad. As the river Yamuna had high value of alkalinity (210.0 mgl(-1)), conductance (518.0 micromhos), dissolved solids (260.0 mgl(-1)), hardness (162.0 mgl(-1)) and chloride (54.6 mgl(-1)) jheel also showed high values of these parameters. The rate of energy transformation from kinetic radiant energy to chemical energy was very high in the jheel 32,315 Cal m(-2) day(-1) of which 25,620 Cal m(-2) day(-1) was contributed by aquatic plants. Out of 11,764 x 10(4) Kcal ha(-1) yr(-1) total energy fixed in the system, producers stored 7,154 x 10(4) Kcal ha(-1) yr(-1) and the rest was lost as heat of respiration. The pattern of storage of energy was different in two groups of producers and thus most of the energy fixed by phytoplankton was stored as protein (56.2%) and less as carbohydrate (11.7%) while aquatic plants stored more energy as carbohydrate (40.8%) than protein (23.2%). The chemical energy obtained from the system was 1,85,000 Kcal ha(-1) yr(-1) and thus only 0.260% of the chemical energy stored by producers was harvested. The potential chemical energy resource in the jheel was 81.4 x 10(4) Kcal ha(-1) yr(-1) of which only 22.6% was harvested in the jheel and there is enough scope for further enhancement.     

The use of ultra filtration in trace metal speciation studies in sea water

During this work, size fractionation technique "ultra filtration" is used in speciation studies of trace elements in the coastal sea water. Filtration is the most commonly used method to fractionate trace metal species, but often only "dissolved" and "particulate" fraction. The purpose of the present study is to determine colloidal and suspended particulate concentrations of Fe, Zn, Cu, Ni, and Mn in sea water. Suspended particulate matter were separated in three different size groups namely (>2.7 microm, <2.7->0.45 microm and <0.45->0.22 microm) by suction filtration using cellulose acetate and nitrate filter membranes. Thereafter to concentrate the solution with colloidal particle <0.22 microm-1.1 nm (0.5 k Nominal Molecular Weight cut-off Limit {NMWL}), the solution obtained from filtration through <0.22 microm, is sequentially passed through the ultra-filtration membranes having pore diameters of 14 nm (300 k NMWL), 3.1 nm (50 k NMWL), 2.2 nm (30 k NMWL), 1.6 nm (10 k NMWL) and 1.1 nm (0.5 k NMWL) by using Stirred Ultra-filtration Cells, operating in concentration mode. The concentration of Fe, Zn, Cu, Ni, and Mn were measured in suspended and dissolved fraction by ion chromatography, ICP-AES and Atomic Absorption Spectrometer. The salinity of the solution in various dissolved fractions of sequential filtration varies between 30.89-34.22 parts per thousand. The maximum concentrations of colloidal Zn, Cu, Ni and Mn in dissolved fraction were in <2.2->1.6 nm fraction. In case of Fe, colloidal fractions <2.2->1.6 nm and <1.6-<1.1 nm shows higher concentration. The concentration of Zn, Cu, Ni and Mn increase with decrease in size in suspended particulate matter, while the reverse is observed in case of Fe. This size separation data that specifies the partitioning of metals between dissolved and suspended solid phases is necessary for developing physically based models of metal transport in aquatic system.     

Treatment of fluoride-contaminated water. A review

Environmental Chemistry Letters - Delivering the right amount of fluoride to drinking water protects the&nbsp;teeth from decay and reduces the risk of cavities. Nonetheless, fluorosis has been...     

Role of microbes,metabolites and effector compounds in host–microbiota interaction: a pharmacological outlook

Environmental Chemistry Letters - Microbial cells react with intestinal surfaces and produce enzymes and metabolites that influence&nbsp;human health, host metabolism and immunity. Gut...     

Nanocarriers for drug delivery applications

Environmental Chemistry Letters - Nanobiotechnology research has recently provided numerous basic and applied advances in the health sector. Nanocarriers have been developed for efficient drug...     

Phosphorus adsorption by functionalized biochar: a review

Environmental Chemistry Letters - Phosphorus is essential element for agricultural production, yet phosphorus ore resources are non-renewable and become depleted. Moreover, phosphate release from...