1 Animal Conservation (2003) 6, The Zoological Society of London DOI: /S Printed in the United Kingdom Science deficiency in conservation practice: the monitoring of tiger populations in India K. Ullas Karanth 1, James D. Nichols 2, John Seidensticker 3, Eric Dinerstein 4, James L. David Smith 5, Charles McDougal 6, A. J. T. Johnsingh 7, Raghunandan S. Chundawat 7 and Valmik Thapar 8 1 Wildlife Conservation Society (International Programs), 2300, Southern Boulevard, Bronx, New York 10460, USA 2 US Geological Service, Patuxent Wildlife Research Center, Laurel, Maryland 20708, USA 3 Smithsonian National Zoological Park, Washington DC 20008, USA 4 World Wildlife Fund US, 1250 NW 24th Street, Washington DC 20037, USA 5 University of Minnesota, Department of Fisheries and Wildlife, 200, Hodson Hall, 1980, Folwell Avenue, St. Paul, Minnesota 55108, USA 6 Tiger Tops, PO Box 242, Kathmandu, Nepal 7 Wildlife Institute of India, Dehradun, Uttaranchal , India 8 19, Kautilya Marg, New Delhi , India (Received 7 January 2002; resubmitted 4 July 2002; accepted 4 November 2002) Abstract Conservation practices are supposed to get refined by advancing scientific knowledge. We study this phenomenon in the context of monitoring tiger populations in India, by evaluating the pugmark census method employed by wildlife managers for three decades. We use an analytical framework of modern animal population sampling to test the efficacy of the pugmark censuses using scientific data on tigers and our field observations. We identify three critical goals for monitoring tiger populations, in order of increasing sophistication: (1) distribution mapping, (2) tracking relative abundance, (3) estimation of absolute abundance. We demonstrate that the present census-based paradigm does not work because it ignores the first two simpler goals, and targets, but fails to achieve, the most difficult third goal. We point out the utility and ready availability of alternative monitoring paradigms that deal with the central problems of spatial sampling and observability. We propose an alternative sampling-based approach that can be tailored to meet practical needs of tiger monitoring at different levels of refinement. INTRODUCTION Conservationists generally agree with the proposition that conservation practices should be based on sound science. For example, understanding the population dynamics of a species in decline is known to be central to implementing appropriate recovery practices (Burgman, Ferson & Akçakaya, 1993; Lancia, Nichols & Pollock, 1994). In reality, however, conservation measures are often initiated on the basis of sparse data and incomplete knowledge. Theoretically, these lacunae are subsequently addressed through the absorption of advancing scientific knowledge into conservation practice. Methods, data and practices of conservation are all supposed to get continually refined through an adaptive feedback process that involves the process of scientific peer-review and publication (Walters, 1986; Nichols, Johnson & Williams, 1995; Pulliam, 1995). However, in practice, the pace at which conservation practitioners All correspondence to: K. Ullas Karanth, 26 2, Aga Abbas Ali Road (Apt: 403), Bangalore, Karnataka , India. Tel: ; Fax: ; absorb new scientific knowledge may be too slow to assist species recovery. In this paper, we examine the above issue in the context of the conservation of the tiger (Panthera tigris) in India. Reliable estimation and effective monitoring of demographic parameters in wild tiger populations are of central concern to conservationists (Karanth & Nichols, 1998, 2002; Seidensticker, Christie & Jackson, 1999). Indian tiger monitoring efforts provide a unique opportunity to examine to what extent new scientific advances influence conservation practices, for the following reasons. First, Indian tiger conservation has involved 30 years of serious official commitment leading to sporadic recovery of tiger populations (Mountfort, 1981; Thapar, 1999; Karanth, 2001). Second, Indian officials have used a single approach called the pugmark census method to monitor tiger populations throughout the above period (Choudhury, 1970, 1972; Panwar, 1980; Singh, 1999). Third, new knowledge about tiger ecology (Schaller, 1967; Sunquist, 1981; Seidensticker & McDougal, 1993; Smith, 1993; Karanth & Sunquist, 1995, 2000; Karanth & Nichols, 1998, 2000; Chundawat, Gogate & Johnsingh, 1999; Miquelle et al., 1999), as well
2 142 K. U. KARANTH ET AL. as development of new methodologies of animal population monitoring (Seber 1982; Thompson, 1992; Lancia et al., 1994; Thompson, White & Gowan, 1998; Williams, Nichols & Conroy, 2002), both advanced greatly during the same period. In this paper, we describe a statistical framework that underpins modern animal population sampling methods (Thompson, 1992; Lancia et al., 1994; Thompson et al., 1998; Williams et al., 2002). We then evaluate the biological and statistical bases of the pugmark census method. Based on our analysis, we propose an array of alternative tiger monitoring methods within the statistical framework described by us. A REVIEW OF TIGER POPULATION MONITORING ISSUES The analytical framework Most modern methods of animal population sampling/ estimation come under a general statistical framework that deals with two central concerns: spatial sampling and observability (Thompson, 1992; Lancia et al., 1994; Thompson et al., 1998; Williams et al., 2002). Spatial sampling concerns the frequent inability of animal survey methods to cover the entire area of interest. In such cases, we representatively survey some subset of that area, and then use these results to draw inferences about the entire area. Observability concerns the typical inability to detect and count all animals (or their sign) in the surveyed area, requiring us to estimate the underlying detection probabilities from our sample counts. Using this framework, Lancia et al. (1994) described the following general estimator for the number of animals in a population: Nˆ = C /αˆ pˆ, where Nˆ = estimated number of animals in the population within the total area of interest, C = count statistic, or the number of animals counted during the survey, αˆ = estimated proportion of the total area which was actually covered during the survey, pˆ = estimated proportion of animals occurring in the surveyed area that were counted. In a true animal census, by definition, the entire area of interest is assumed to be covered by the survey, and all animals in the area are assumed to be counted. There are strong assumptions in a census that α = 1 and p = 1, so that C = N in the above general estimator. If either of these major assumptions is invalid, the survey cannot be considered a true census (Lancia et al., 1994; Thompson et al., 1998). However, because biologists realize that true censuses that ensure α = p = 1 are rarely feasible in the field, they employ sample surveys in which α and p are modelled, estimated and then combined with the count statistic C to derive estimates of population size (Nˆ ) (Thompson et al., 1998; Williams et al., 2002). Under this approach, several plausible models that generated the sample can be tested against the field data, to select the most appropriate model using objective criteria (Burnham & Anderson, 1998). Even when estimates of absolute animal abundance Nˆ cannot be derived because of practical constraints, the above sampling framework can be used to generate indices for comparing the relative abundances of animals at two points in time or space. In such cases, the investigator hopes to establish at least a monotonic relationship between count C and true animal abundance N by standardizing the survey protocols to ensure that values of α and p are similar between surveys. Even where direct counting of animals is not feasible, and only their sign, such as tracks or scats can be recorded, this sampling framework can still be employed to estimate probabilities of detecting sign, thereby enabling the investigator to estimate relative abundance or habitat occupancy with greater rigour (Thompson et al., 1998; Mackenzie et al., 2002; Williams et al., 2002). The pugmark census approach to monitoring tigers The pugmark census was invented in 1966 by Indian forester S. R. Choudhury (Choudhury, 1970, 1972). In this census, during a 1 2-week period, thousands of forestry department personnel simultaneously fan out across India to search for tiger tracks. They are expected to locate the tracks and obtain plaster casts (or tracings) of the imprints of the left hind paws of nearly all the tigers in the entire country. The pugmarks collected are later compared to identify individual tigers relying on perceived differences in shape, other measurements and ancillary local knowledge. These individual tiger identifications are then refined through cross-comparisons among census blocks, reserves and larger regions to obtain what are claimed to be reliable estimates of wild tiger numbers in India. The protocol for conducting pugmark censuses has been described repeatedly in the grey literature but not in peer-reviewed journals (Choudhury, 1970, 1972; Panwar, 1980; Singh, 1999). In this paper we examine only this particular method and not the general use of tiger track surveys for monitoring. For 30 years, this method has been exclusively used to derive tiger numbers in individual parks and larger regions, and on a country-wide basis. It is claimed that the pugmark censuses yield accurate results in a cost-effective and practical manner (Panwar, 1980; Singh, 1999). However, because the objective is censusing rather than sampling tiger populations, the practitioners do not record the field effort invested or try to derive estimates of α and p within any kind of estimation framework. Instead, they assume, without any evidence, that α = p = 1. Biological basis of the pugmark census The pugmark census method assumes that adult female and male tigers spatially exclude same-sex conspecifics. Choudhury (1970, 1972) even suggests that tigers live in pairs. Panwar (1979) opines that transient tigers reside in marginal habitats away from core breeding areas. Singh (1999) adds that tiger populations at higher densities have a relatively lower proportion of transient tigers. On the basis of such conjectures, the census method assumes that probability of tracks of the same individual being found
3 Science deficiency in tiger conservation 143 in different counting units is negligible, thus avoiding multiple counts (Singh, 1999). The above premises can be examined in light of scientific data on tiger ecology (Schaller, 1967; Sunquist, 1981; Karanth & Nichols, 1998). These data show that tigers are polygynous animals that do not form pair bonds (Smith, McDougal & Sunquist, 1987; Smith, 1993). Although breeding tigers may occupy exclusive ranges in some high-density areas, same travel routes are intensively used by neighbours (Sunquist, 1981; Smith, 1993). In other areas, the overlap between individuals is considerable (Karanth & Sunquist, 2000). In low tiger density areas, even breeder ranges show large overlaps (Miquelle et al., 1999). More importantly, adult male ranges spatially overlap ranges of two to six breeding females (Sunquist, 1981; Smith et al., 1987; Smith, 1993; Chundawat et al., 1999). Both male and female transient floaters also move back and forth across breeding territories (Smith, 1993; Karanth & Sunquist, 2000). Tiger populations at higher densities have higher proportions of transient individuals (Karanth & Nichols, 1998, 2000). Karanth (1987, 1988) has pointed out additional inconsistencies in census results: the lack of correlation between reported prey densities and tiger densities, as well as unrealistic long-term population growth rates over large regions. Thus, ecological data on tigers from field studies do not support the major biological assumptions as well as results generated from pugmark censuses. Statistical basis of the pugmark census Choudhury (1970, 1972) and Panwar (1980) claim that a total (or nearly total) count of all tigers in an area can be reliably obtained by the census. Singh (1999) concedes the possibility of some undercounts, but not of any overcounts. This means the term α p 1, but never > 1. Therefore, the following assumptions must hold true for the pugmark method to be statistically valid: 1. The entire potential tiger habitat in India is effectively covered during the pugmark census. 2. All the four paw prints of every individual tiger in the surveyed area are detected during the censuses. 3. The same hind pugmark of each one of these individual tigers is lifted from suitable and comparable substrates or from standardized soil track-plots. 4. The shape of each pugmark lifted is recorded without distortion by thousands of census personnel involved in the operation. 5. Supervisory officials are subsequently able to segregate the pugmarks of each individual tiger correctly, based on footprint shape, track measurements, and prior local knowledge. They are expected to do so using either subjective skills (Singh, 1999) or multivariate statistical approaches (Sharma, 2001). We note that all the above conditions must be satisfied if the pugmark census is to work at all. Furthermore, failure of assumptions 1 and 2 would lead to under-counts (α p < 1), failure of assumptions 3 and 4 would lead to overcounts (α p > 1), and failure of assumption 5 could lead to either undercounts or overcounts. Therefore, the pugmark census depends on several complex, unstated statistical assumptions. Failure of these assumptions can potentially influence the magnitude of both α and p to vary from 0 to > 1, with the result that the count C may have no predictable relationship with the true tiger population size N. In the following section, using ecological data, experimental evidence and our own field observations, we show how several underlying assumptions are violated during pugmark censuses. Violations of the assumptions Surveying the entire area Potential tiger habitat in India extends over 300,000 km 2 area (Wikramanayake et al., 1998). In reality, only an unknown fraction of this area is searched intensively during censuses (Karanth, 1999). For example, about 300 km 2 out of the total 3000 km 2 Namdapha Tiger Reserve were covered in the 1996 census. In reserves like Nagarahole and Bandipur, census teams of three to four persons who walk about km/day are unrealistically assumed fully to search blocks of km 2. In reality, logistical constraints (e.g. in Namdapha, Sundarban), security concerns (e.g. in Nagarjuna Sagar, Indravati and Manas reserves) or staff shortages (almost everywhere) restrict the proportion of the area covered by field teams (Karanth, 1999). Locating the tracks of every individual tiger The probabilities of finding the tracks of each individual tiger in the surveyed area are low, except in a few reserves with high road density and suitable substrates. Over most of India, particularly in the Western Ghats and Northeastern hills, difficult substrate conditions and terrain hinder the finding of tiger tracks. For example, in Nagarahole reserve, which has a high tiger density of 12 tigers/100 km 2 (Karanth & Nichols, 1998), tracks were impossible to detect along many tiger travel routes because of inappropriate substrates although radiotelemetry and camera trapping showed intensive tiger movements along them. Selecting the appropriate footprint Lifting footprints from a firm substrate overlaid with dust or sand is an essential precondition to obtaining accurate pugmarks. Admittedly, prints lifted from loose or muddy soil invalidate the identifications by distorting track shapes (Choudhury, 1972; Panwar, 1980; Singh, 1999). However, such ideal soil conditions do not occur in most areas, thereby forcing census personnel to lift prints from inappropriate substrates (Karanth, 1987, 1988). Laying down artificial track-plots (called Pug Impression Pad s), is advocated as a solution to the problem of unsuitable substrates (Panwar, 1980; Singh, 1999). However, track-plots often do not work because of practical problems: lack of suitable soil in the vicinity,
4 144 K. U. KARANTH ET AL. logistical problems in transporting soil, and the effects of rain, wind or animal movement. For example, the trackplots observed in Namdapha during the 1996 pugmark census were made from the wrong soil type. Although the 2600 km 2 delta of Sundarban Tiger Reserve obviously lacks the appropriate substrate, track-plots are not employed because of logistical difficulties (K. U. Karanth, pers. obs.) Unless clear impressions of all the four paws on the right substrate are detected for each individual tiger, it is impossible to pick the same hind pugmark of each individual for comparisons, as prescribed by the pugmark method (Choudhury, 1970, 1972; Panwar, 1980; Singh, 1999). In reality, census personnel often do not find clear prints of all four paws, and consequently lift prints of the different paws of the same animal from different localities. Recording and recognizing tiger tracks The shape of the same tiger footprint traced by different persons may vary considerably (Choudhury, 1972; Sharma, 2001). This variation can be reduced by using well-trained persons in controlled trials (Sharma, 2001), but not in field censuses involving thousands of personnel with varying levels of skills. The pugmark method assumes that supervisory officials can identify and segregate tracks of each individual tiger from the pugmarks brought in by field teams. However, Karanth (1987) demonstrated through a blind test involving footprints from captive tigers obtained from varying substrates that even experienced census personnel failed to segregate individual animals correctly. More recent validation tests done in captivity on standardized substrates (Riordan, 1998; Sharma, 2001) suggest that the ability of experts (or multivariate statistical tests) to discriminate individual tracks improves somewhat if there are less than 12 individual tigers involved in the comparisons. The crucial point at issue here is not whether the prints of the same paw obtained from standard substrates and compared among a small number (< 12~17) of individual tigers can lead to the correct identification of a high proportion of individuals (Riordan, 1998; Sharma, 2001). Such controlled studies simply do not address other serious problems with large-scale field censuses we have described above. Moreover, how the probabilistic individual tiger identifications derived from statistical track-discrimination can be used for population estimation in a general sampling framework (Thompson et al., 1998; Williams et al., 2002) remains unexplored. CONSERVATION IMPLICATIONS Utility of pugmark census for monitoring tiger populations We emphasize that while tiger monitoring methods must be practical, they should also be scientifically defensible. Invalid data inhibit progress towards potential solutions, whereas lack of data might actually encourage such progress (Karanth, 1999). We identify the following three critical goals (Karanth, 1999; Karanth & Nichols, 2002) relevant for monitoring wild tiger populations in India: (1) periodic measures of the expansion or contraction of distribution of tiger populations based on geo-referenced habitat occupancy data on a country-wide basis; (2) annually derived indices of relative abundance that reflect changes in tiger numbers in important reserves, at least in terms of detecting increases, declines or stability; (3) measures of absolute abundance or densities of tigers at highpriority sites. Although an elaborate record-keeping protocol has been prescribed for the pugmark censuses (Choudhury, 1972; Panwar, 1980; Singh, 1999), this protocol essentially ignores the fundamental need for mapping and geo-referencing the tiger signs that are detected by field personnel. As a result, even after 30 years of pugmark censuses, large-scale, country-wide maps of tiger spatial distribution are not available. Because the effort expended by the field teams in terms of search routes, distances covered and time spent looking for tiger tracks has not been recorded or replicated over successive pugmark censuses in the past, it is not possible now to use the raw counts of tracks obtained even to derive simple indices that can possibly detect changes in tiger abundance or habitat occupancy over time. In fact, the pugmark census method (Choudhury, 1970; Panwar, 1979; Singh, 1999) does not even consider the above two simple monitoring goals that are adequate for most management purposes. It primarily addresses the third and most difficult goal, that of measuring the absolute abundance of tigers, on a country-wide basis. Because the pugmark census fails to attain its unrealistic goal, three decades of tiger monitoring has basically failed in India, despite being backed by massive investments and the best of intentions. This failure has, inevitably, led to poor conservation practices. For example, field managers initially reported an increase in tiger population in 1994, despite mounting evidence of deteriorating reserve protection and increasing poaching pressure (Thapar, 1999; Karanth, 2001). In response, the authorities of Project Tiger arbitrarily reduced census tally by 750 tigers, to instil a sense of crisis among field officials. Although the situation has not improved greatly thereafter, recent pugmark censuses are once again reporting increasing tiger numbers. Possible alternative approaches to monitoring tigers In a brief review of this nature, it is not possible to describe all possible approaches to monitoring tigers based on the sampling framework we proposed earlier. Some of us, and other workers, have tried to do so elsewhere (Karanth, 1988, 1999; Karanth & Nichols, 1998, 2002; McDougal, 1999; Miquelle et al., 1999). We briefly reiterate below a few alternative approaches that can meet tiger monitoring needs at different levels of resolution. (1) As tiger habitats become fragmented and degraded
5 Science deficiency in tiger conservation 145 local populations may be extirpated. On the other hand, if conservation measures are successful, habitats may get reconnected or restored, establishing new or larger populations. Therefore, at the national level (> 300,000 km 2 of tiger habitat) it is critical to document annually the spatial distribution (presence or absence) of tigers. This goal can be met by modifying the present large-scale, labour-intensive pugmark censuses into surveys of tiger sign that involve merely recording the presence of tiger tracks and other signs under a statistically rigorous sampling design. Such surveys will necessarily involve recording the sampling effort and proper geo-referencing of survey data, but they will not involve the impossible task of individually trying to identify all wild tigers from track prints under field conditions. (2) At the level of individual reserves, managers need to keep track of annual population trends of tigers to evaluate the effectiveness of conservation interventions. Although desirable, it may not always be possible to obtain rigorous estimates of tiger densities because of lack of material resources or skills. However, even under resource constraints, indices of relative densities of tigers can be derived annually using encounter rates of tiger sign (e.g. number of tiger track sets or scats encountered per 10 km walked, the proportion of 1 km trail segments in which tiger tracks were detected, number of fresh tiger tracks crossing the path of a boat or vehicle). Although such quantitative indices of tiger abundance may not necessarily calibrate accurately to absolute tiger abundance (Karanth & Nichols, 2002), with sufficient survey effort, establishing a monotonic relationship between the index value and tiger abundance may be still feasible. Such standardized, quantitative index surveys of tiger signs will be non-subjective and replicable. (3) At a few priority sites ecological parameters such as absolute densities of prey and tigers may need to be estimated. In such cases, there is no escape from employing advanced equipment and techniques, and skilled personnel. Such techniques will include line transect surveys of prey densities and camera-trap capture recapture surveys of tigers (Karanth & Nichols, 1998, 2000, 2002). The central challenge involves identification of the relevant level of resolution required for tiger monitoring, and then deploying available material and manpower resources within the rigorous population-sampling framework we elaborated earlier. We estimate that during 1999 alone, the central and state governments in India spent about 10 million dollars on tiger-related conservation measures, with non-governmental donors contributing an additional 1.75 million dollars (Thapar, 1999). In the absence of reliable tiger population monitoring, it is impossible to judge the effectiveness of such conservation investments, thus highlighting the urgent need for addressing the deficiencies pointed out in this paper. Acknowledgements We thank P. Jackson, two reviewers and the editor for useful comments on earlier drafts of this paper. REFERENCES Burgman, M. A., Ferson, S. & Akçakaya, H. R. (1993). Risk assessment in conservation biology. New York: Chapman and Hall. Burnham, K. P. & Anderson, D. R. (1998). Model selection and inference: a practical information theoretic approach. New York: Springer-Verlag. Choudhury, S. R. (1970). Let us count our tigers. Cheetal 14: Choudhury, S. R. (1972). Tiger census in India. Cheetal 15: Chundawat, R. S., Gogate, N. & Johnsingh, A. J. T. (1999). Tigers in Panna: preliminary results from an Indian tropical dry forest. In Riding the tiger: tiger conservation in human-dominated landscapes: Seidensticker, J., Christie, S. & Jackson, P. (Eds). Cambridge: Cambridge University Press. Karanth, K. U. (1987). Tigers in India: a critical review of field censuses. In Tigers of the world: the biology, biopolitics, management, and conservation of an endangered species: Tilson, R. L. & Seal, U. S. (Eds). Park Ridge, NJ: Noyes Publications. Karanth, K. U. (1988). Analysis of predator prey balance in Bandipur Tiger Reserve with reference to census reports. J. Bombay Nat. Hist. Soc. 85: 1 8. Karanth, K. U. (1999). Counting tigers with confidence. In Riding the tiger: tiger conservation in human-dominated landscapes: Seidensticker, J., Christie, S. & Jackson, P. (Eds). Cambridge: Cambridge University Press. Karanth, K. U. (2001). The way of the tiger: natural history and conservation of the endangered big cat. Stillwater, MN: Voyageur Press. Karanth, K. U. & Nichols, J. D. (1998). Estimating tiger densities in India from camera trap data using photographic captures and recaptures. Ecology 79: Karanth, K. U. & Nichols, J. D. (2000). Ecological status and conservation of tigers in India. Final Technical Report to the US Fish and Wildlife Service and Wildlife Conservation Society, New York. Bangalore: Centre for Wildlife Studies. Karanth, K. U. & Nichols, J. D. (Eds). (2002). Monitoring tigers and their prey: a manual for researchers, managers and conservationists in tropical Asia. Bangalore: Centre for Wildlife Studies. Karanth, K. U. & Sunquist, M. E. (1995). Prey selection by tiger, leopard and dhole in tropical forests. J. Anim. Ecol. 64: Karanth, K. U. & M. E. Sunquist. (2000). Behavioural correlates of predation by tiger (Panthera tigris), leopard (Panthera pardus) and dhole (Cuon alpinus) in Nagarahole, India. J. Zool. (Lond.) 250: Lancia, R. A., Nichols, J. D. & Pollock, K. N. (1994). Estimation of number of animals in wildlife populations. In Research and management techniques for wildlife and habitats: Bookhout, R. (Ed.). Bethesda: The Wildlife Society. McDougal, C. (1999). You can tell some tigers from their tracks with confidence. In Riding the tiger: tiger conservation in humandominated landscapes: Seidensticker, J., Christie, S. & Jackson, P. (Eds). Cambridge: Cambridge University Press. Mackenzie, D. I., Nichols, J. D., Lachman G. B., Droege, S., Royale, J. A. & Langtimm, C. A. (2002). Estimating site occupancy rates when detection probabilities are less than one. Ecology 83: Miquelle, D. G., Smirnov, E. N., Merrill, T. W., Myslenkov, A. E., Quigley, H. B., Hornocker, M. G. & Schleyer, B. (1999). Hierarchical spatial analysis of Amur tiger relationships to habitat and prey. In Riding the tiger: tiger conservation in humandominated landscapes: Seidensticker, J., Christie, S. & Jackson, P. (Eds). Cambridge: Cambridge University Press. Mountfort, G. (1981). Saving the tiger. London: Michael Joseph. Nichols, J. D., Johnson, F. A. & Williams, B. K. (1995). Managing North American waterfowl in the face of uncertainty. Ann. Rev. Ecol. Syst. 26:
6 146 K. U. KARANTH ET AL. Panwar, H. S. (1979). Population dynamics and land tenures of tigers in Kanha National Park. Indian Forester (special issue) 1979: Panwar, H. S. (1980). A note on tiger census technique based on pugmark tracings. Cheetal 22: Pulliam, H. R. (1995). Providing the information that conservation practitioners need. In The ecological basis of conservation: heterogeneity, ecosystems and biodiversity: Pickett, T. A., Ostfield, R. A., Shack, M. & Likens, G. (Eds). New York: Chapman and Hall. Riordan, P. (1998). Unsupervised recognition of individual tigers and snow leopards from their footprints. Anim. Conserv. 1: Schaller, G. B. (1967). The deer and the tiger. Chicago: University of Chicago Press. Seber, G. A. F. (1982). The estimation of animal abundance and related parameters (2nd. edn). New York: Macmillan. Seidensticker, J., Christie, S. & Jackson, P. (1999). Preface. In Riding the tiger: tiger conservation in human-dominated landscapes: xv xix. Seidensticker, J., Christie, S. & Jackson, P. (Eds). Cambridge: Cambridge University Press. Seidensticker, J. & McDougal, C. (1993). Tiger predatory behaviour, ecology and conservation. Symp. Zool. Soc. Lond. 65: Sharma, S. (2001). Evaluation of pugmark census technique. MSc dissertation, Saurashtra University, Rajkot, India. Singh, L. A. K. (1999). Tracking tigers: guidelines for estimating wild tiger populations using the pugmark technique. New Delhi: World Wide Fund for Nature India. Smith, J. L. D. (1993). The role of dispersal in structuring the Chitwan tiger population. Behaviour 124: Smith, J. L. D., McDougal, C. & Sunquist, M. E. (1987). Female land tenure system in tigers. In Tigers of the world: the biology, biopolitics, management, and conservation of an endangered species: Tilson, R. L. & Seal, U. S. (Eds). Park Ridge, NJ: Noyes Publications. Sunquist, M. E. (1981). Social organization of tigers (Panthera tigris) in Royal Chitawan National Park, Nepal. Smithsonian Contrib. Zool. 336: Thapar, V Tragedy of the Indian tiger: starting from scratch. In Riding the tiger: tiger conservation in human-dominated landscapes: Seidensticker, J., Christie, S. & Jackson, P. (Eds). Cambridge: Cambridge University Press. Thompson, S. K. (1992). Sampling. New York: Wiley. Thompson, W. L., White, G. C. & Gowan, C. (1998). Monitoring vertebrate populations. New York: Academic Press. Walters, C. J. (1986). Adaptive management of renewable resources. New York: Macmillan. Wikramanayake, E. D., Dinerstein, E., Robinson, J. G., Karanth, K. U., Rabinowitz, A. R., Olson, D., Mathew, T., Hedao, P., Conner, M., Hemley, G. & Bolze, D. (1998). An ecology based method for defining priorities for large mammal conservation: the tiger as a case study. Conserv. Biol. 12: Williams, B. K., Nichols, J. D. & Conroy, M. J. (2002). Analysis and management of animal populations. San Diego: Academic Press.
Scientific Monitoring of Tiger Populations and Habitats John Seidensticker Conservation Ecology Center Smithsonian Conservation Biology Institute GTRP Stocktaking New Delhi May 16, 2012 Tiger Monitoring
Did You Know? 1. Tigers now occupy 7 percent of their historical range, and in the past decade, the area occupied by tigers has decreased by as much as 41 percent, according to some estimates (Dinerstein
MINISTRY OF FORESTRY OF REPUBLIC OF INDONESIA Global Tiger Initiative National Consultations the Road to the Tiger Summit National Tiger Recovery Program INDONESIA July, 10 Template to describe a Summary
Bitterroot Mountain Lion Project Report January 2014 Background Wildlife managers need reliable methods to monitor mountain lion population abundance in order to manage harvest, minimize conflicts with
Harvesting Paradigms Sustained Yield Harvesting Paradigms Net-Annual Increment Paradigm The Myth of MSY How should we consider them? The logistic paradigm obviously arises from logistic model. Says that
1 The Set of Candidate Models Formulation of critical hypotheses and models to adequately reflect these hypotheses is conceptually more difficult than estimating the model parameters and their precision.
Ecology, 83(8), 2002, pp. 2248 2255 2002 by the Ecological Society of America ESTIMATING SITE OCCUPANCY RATES WHEN DETECTION PROBABILITIES ARE LESS THAN ONE DARRYL I. MACKENZIE, 1,5 JAMES D. NICHOLS, 2
STATEMENT OF RESEARCH for Kevin McGarigal September 2002 Goals and Philosophy The goals of my research program are as follows: develop a diverse and productive research program in landscape ecology, provide
Biology 103 A Method of Population Estimation: Mark & Recapture Objectives: 1. Learn one method used by wildlife biologists to estimate population size of wild animals. 2. Learn how sampling size effects
Biodiversity Concepts WHAT IS BIODIVERSITY? Biodiversity is the variety of life on Earth. For any kind of animal or plant each individual is not exactly the same as any other; nor are species or ecosystems.
Project ID: 35019 Title: Develop and Implement a Pilot Status and Trend Monitoring Program for Salmonids and their Habitat in the Wenatchee and Grande Ronde River Basins. Response to ISRP Comments A. This
Techniques and Tools for Monitoring Wildlife on Small Woodlands Fran Cafferata Coe, Cafferata Consulting, Hillsboro, OR Monitoring wildlife can provide many unique insights into the health and productivity
9.3.7 Advice December 2014 ECOREGION STOCK Widely distributed and migratory stocks European eel Advice for 2015 The status of eel remains critical and ICES advises that all anthropogenic mortality (e.g.
State Comprehensive Wildlife Conservation Support Program Application for Funds I. APPLICANT INFORMATION Organization (intended recipient): Northeast Association of Fish & Wildlife Agencies Street: c/o
Developing a Methodology for In situ Soil Quality Assessment for the Function of Biodiversity Support MSc Thesis Summary by Laura A Edwards: September 2008 Supervisors: Dr Nick Voulvoulis and Dr Martin
Removal fishing to estimate catch probability: preliminary data analysis Raymond A. Webster Abstract This project examined whether or not removal sampling was a useful technique for estimating catch probability
JoTT Co m m u n ic a t i o n 4(2): 2370 2380 Population and prey of the Bengal Tiger Panthera tigris tigris (Linnaeus, 1758) (Carnivora: Felidae) in the Sundarbans, Bangladesh M. Monirul H. Khan Department
Key Stage 1 & 2 Aims and Objectives Understand what a habitat is Understand the important role of plants and animals within a habitat Focus on issues that cause habitats to decline Establish how we can
Design and Analysis of Ecological Data Conceptual Foundations: Ec o lo g ic al Data 1. Purpose of data collection...................................................... 2 2. Samples and populations.......................................................
CHAPTER 2: APPROACH AND METHODS APPROACH Given Hawaii s biological uniqueness on a global scale, the Comprehensive Wildlife Conservation Strategy (CWCS) recognizes the importance of protecting all native
Occupancy estimation & modeling Many interesting questions and applied problems in ecology and conservation require data from large spatial scales through a number off years Often it is not possible to
Appendix A. The Marine Life Protection Act (MLPA) THE PEOPLE OF THE STATE OF CALIFORNIA DO ENACT AS FOLLOWS: SECTION 1. Chapter 10.5 (commencing with Section 2850) is added to Division 3 of the Fish and
FOCUS ON INDIA The Family-Friendly Workplace Model Helping Companies Analyze the Benefits of Family-Friendly Policies Today, women make up 40 percent of the global workforce, and they are becoming an increasingly
Fisheries and Oceans Canada Species at Risk Act Listing Policy and Directive for Do Not List Advice DFO SARA Listing Policy Preamble The Fisheries and Oceans Canada (DFO) Species at Risk Act (SARA) Listing
RK University (Pre-registration coursework for PhD program) Program PhD (Environmental Science) Concerned Dean Dr. T. R. Desai (email firstname.lastname@example.org) Sr. No. Subject Contents Method of evaluation 1.
COMPLETE CASE STUDY 4.3 - TRENDS IN SIGNIFICANT SPECIES AND COMMUNITIES - SOUTH AUSTRALIA Mallee emu-wren Stipiturus mallee Description The mallee emu-wren is one of Australia s smallest birds, weighing
1 Standard 14: Produce a long-term financial plan to support strategies and measures, implementation, further data development, and analyses. Case Study: A Financial Modeling,, Implementation and Tracking
Rocky Mountain Wolf Recovery 2009 Interagency Annual Report A cooperative effort by the U.S. Fish and Wildlife Service, Nez Perce Tribe, National Park Service, Montana Fish, Wildlife & Parks, Idaho Fish
Annexure-IV PROPOSED TERMS OF REFERENCE 1.0 Proposed Scope of Work for EIA Study The components of the EIA study include: Detailed description of all elements of the project activities (existing and proposed
4 Year Historically Asian Colleges and Universities (Alphabetical List of Colleges) COLLEGE CONTACT MAJORS Boston University 121 Bay State Road Boston, Massachusetts 02215 (14%) Asian Office of (617) 353-3590
Introduction to Landscape Ecology By Kevin McGarigal Disclaimer: Some of the material in this document was borrowed from Turner et al. (2001) and Dean Urban s Landscape Ecology course notes, Duke University.
OIKOS 105: 117/124, 2004 Patterns in the species/environment relationship depend on both scale and choice of response variables Samuel A. Cushman and Kevin McGarigal Cushman, S. A. and McGarigal, K. 2004.
Getting the Most from Demographics: Things to Consider for Powerful Market Analysis Charles J. Schwartz Principal, Intelligent Analytical Services Demographic analysis has become a fact of life in market
J. Sci. Trans. Environ. Technov. 2009, 2(3), 2009 2(3): 139-144 139 Population distribution and conservation of the four-horned antelope (Tetracerus quadricornis) in the tropical forest of Southern India
ANNUAL MEETING HANDOUT Social Media Case Study: Give Ten for Tigers Learn how the Woodland Park Zoo raised $149,000 in two weeks through an integrated social media and e-mail campaign, Give Ten for Tigers,
Sustainability and Wildlife Conservation Updates: the Malaysian Perspectives MPOC Reach & Remind Friends of the Industry Seminar: Challenges and Opportunities in 2012 Royale Chulan Hotel 16 January 2012
1 Proposed Terms of Reference for EIA studies Base line data collection will be collected for the Post-Monsoon season 2016 (September to November 2016) in study area and 10 kms radius from project site.
Wan-yu Shih, John Handley, Iain White (PhD Student Wan-yu Shih, School of Environment and Development, the University of Manchester, Manchester, United Kingdom, Wan-yu.Shih@postgrad.manchester.ac.uk) (Professor
Current and probable past wildlife fatality hotspots on the Thousand Islands Parkway, Ontario, Canada E. Eberhardt 1, S. Mitchell 2, and L. Fahrig 3 1 Parks Canada, Ecological Integrity Branch, National
Revising the Nantahala and Pisgah Land Management Plan Preliminary Need to Change the Existing Land Management Plan Throughout the Plan 1. There is a fundamental need for the revised plan to address how
Past and Current Research on Natural Resource Issues in the Blue Mountains Recreation, Hunting, Access Livestock Production (and Wild Ungulate Ecology) Restoration Timber Harvest, Production Biodiversity,
POPULATION DYNAMICS Zoo 511 Ecology of Fishes Today s goals Understand why and how population dynamics are important in fisheries ecology Gain experience in a variety of mark-recapture methods What are
SAMPLING AND STATISTICAL METHODS FOR BEHAVIORAL ECOLOGISTS This book describes the sampling and statistical methods used most often by behavioral ecologists and field biologists. Written by a biologist
Regional Transport in Canterbury Health Impact Analysis Dynamic Simulation Model Final Report for Environment Canterbury David Rees and Adrian Field 11 June 2010 CONTENTS 1. Background 2. Model Structure
Integration of Forestry & Wildlife Management By Ken Negray Regional Certification Manager, NewPage Corp & member of the KY SIC Committee Abstract: Kentucky SIC (Sustainable Forestry Initiative Implementation
, Selection and Preference ESRM 450 Wildlife Ecology and Conservation Habitat any area offering the resources and conditions that promote occupancy by a species any area offering the resources and conditions
Oregon Juniper and Biomass: Status and Proposed Approach For Consideration in Conjunction with the AOC Juniper-Use Project Inquiry Revised DRAFT November 9 2011 Status There is general agreement that overstocked
January 2004 1 Center for Urban Ecology Strategic Plan Science and Service through Partnerships Mission The Center for Urban Ecology is an interdisciplinary team that provides scientific guidance, technical
NIMAL ARK OR INKING SHIP? Photo Charles Smith, United States Fish and Wildlife Service Photo Dr Joseph Tobias, University of Oxford July 2007 At least 5,624 species of vertebrate animals are threatened
Integrative Zoology 2010; 5: 285-299 was declared endangered in 1969, yet in this Year of the Tiger: 2010 2011, it is distressing to witness that wild tigers are still being annihilated. The decline of
July 2012 Endangered Species: TIGERS Bulletin Board Resources for CFs by the Office of Sustainability Simply cut and paste! Tips for a More Sustainable Bulletin Board: Created by: Amelia Evans Use newspaper
Required and Recommended Supporting Information for IUCN Red List Assessments This is Annex 1 of the Rules of Procedure IUCN Red List Assessment Process 2013-2016 as approved by the IUCN SSC Steering Committee
THE DIMINISHING TROPICAL RAIN FORESTS: CAUSES, SYMPTOMS AND CURE First Asia Head of Research Councils (Asia HORCs) Joint Symposium on Biodiversity, Characteristics Conservation and Sustainable Use July
M O N T G U I D E MT 9516 Agriculture A Rancher s Guide for Monitoring Elk, Deer and Pronghorn Antelope Populations by James E. Knight, Extension Wildlife Specialist Much emphasis is put on the positive
Florida Panther In spite of many, many attempts, I have not been able to discover let alone photograph a majestic Florida panther in the wild. The tawny cat is an endangered species. The panthers I have
Analysis of Butterfly Survey Data and Methodology from San Bruno Mountain Habitat Conservation Plan (1982 2000) 1. Status and Trends Travis Longcore Christine S. Lam John P. Wilson University of Southern
I. introduction Definition Current extinction Genetic drift Extinction; Lecture-8 II. 3 types of extinction 1. background 2. mass 3. stochastic III. 5 periods of mass IV. human caused 1. on land and in
The Obama Administration s Progress on Federal Policies for Wildlife Corridor and Ecological Connectivity Conservation January 2009 through December 2012 R o b A m e n t S e n i o r C o n s e r v a t i
Estimating Asian Elephant Population in Dindugul, Kodaikanal and Theni Forest Divisions, Western Ghats Tamil Nadu A. Kumaraguru 1, K. Karunanithi 2, S. Asokan 2 and N. Baskaran 3 1 CCMB, Mayiladuthurai,
17 BIODIVERSITY MONITORING IN CANADA S YUKON: THE COMMUNITY ECOLOGICAL MONITORING PROGRAM Charles J. Krebs Lesson # 1. Construct a food web for the system under study. Lesson # 2. You cannot do everything
Visitor management strategy Introduction Protected areas attract people. Sometimes the protected area management is glad about people who are interested in their work and activities, sometimes protected
Statewide Monitoring of the Florida Manatee Presentation for the Marine Mammal Commission 2015 Annual Meeting Leslie Ward-Geiger, Marine Mammal Research Program Leader Florida Fish and Wildlife Conservation
Kaleidoscope Volume 11 Article 70 July 2014 POPULATION DYNAMICS OF THE AFRICAN LION (Panthera leo L.) WITHIN THE MAASAI MARA REGION OF SOUTHERN KENYA Richard Hatfield Follow this and additional works at:
Analyzing Wildlife Habitat with Google Earth Left: Sharon Lovell; Right: Dawn Tanner by Dawn Tanner Habitat loss is the most significant threat to wildlife around the world and a driving force behind the
policy q&a December 2012 Produced by The National Bureau of Asian Research for the Senate India Caucus healthcare in india A CALL FOR INNOVATIVE REFORM As India seeks to become a global power, there is
EUROPEAN COMMISSION Better Regulation "Toolbox" This Toolbox complements the Better Regulation Guideline presented in in SWD(2015) 111 It is presented here in the form of a single document and structured
Prioritizing Riparian Restoration at the Watershed, Reach and Site Scales Richard R. Harris University of California, Berkeley Cooperative Extension Issues Riparian communities provide multiple benefits
PPENDIX C: F APPENDIX C: FOREST MANA ANAGEMENT CERTIFICA ERTIFICATION TION PROGRAMS Forest Management and Forest Product Certification In the past 10 years, forest management monitoring has been extended
Guiding Principles for the Management of Hoofed Game in Austria s National Parks Preamble Based on the objectives and visions of the Austrian National Park Strategy the present Guiding Principles for the
AVIAN CENSUS TECHNIQUES: Why count birds? Descriptive Studies = asks what types of birds occur in a particular habitat? - Provides gross overview of bird occurrence and perhaps a crude estimate of abundance
ECOLOGICAL A MEANS OF CONSERVING BIODIVERSITY AND SUSTAINING LIVELIHOODS RESTORATION The Society for Ecological Restoration International (SER) is a non-profit organization infused with the energy of involved
This PDF is a selection from a published volume from the National Bureau of Economic Research Volume Title: Fiscal Policy and Management in East Asia, NBER-EASE, Volume 16 Volume Author/Editor: Takatoshi
Overview of Water Utility Benchmarking Methodologies: From Indicators to Incentives Sanford Berg and Julie C Padowski email@example.com Public Utility Research Center (www.purc.ufl.edu) University
Pledge Supporting NJ Wildlife Action Plan 10 Points 10 Points The Wildlife Action Plan Pledge is a community s first step in recognizing the important role that wild animals play in healthy, sustainable
Importance of Wildlife The wildlife comprises all living organism (plants, animals, microorganisms) in their natural habitats which are neither cultivated or domesticated nor tamed. But in its strictest
Newsflash, June 2012 Marianne Leone In this issue: Fondation Segré Website revamp Wildlife health monitoring 2011 update from WCS 2011 update from Phoenix Fund 2011 update from ZSL Thank you Helsinki Zoo!!