Population abundance using Mark Recapture Techniques

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The Stock Assessment of Crayfish (Astacus leptodactylus Eschscholtz, 1823) in the Keban Dam Lake

The Stock Assessment of Crayfish (Astacus leptodactylus Eschscholtz, 1823) in the Keban Dam Lake

which require that ma rk-recapture techniques be emp loyed, are available in the literature (Krebs, 1989). Mark-recapture studies have been proven useful for obtaining information on the migration, growth, population size and morta lity rates of many aquatic anima l species. This estimat ion method requires a methodology designed to assess the population size within a known area. It can be carried out either in terms of re lative abundance using catch per unit effort data, absolute abundance using census methods or mark-recapture techniques (Bolat, Mazlu m, De mirci, & Koca, 2011; Pollock, Nichols, Brownie, & Hines, 1990).
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Photo Identification Methods Reveal Seasonal and Long Term Site Fidelity of Risso’s Dolphins (Grampus griseus) in Shallow Waters (Cardigan Bay, Wales)

Photo Identification Methods Reveal Seasonal and Long Term Site Fidelity of Risso’s Dolphins (Grampus griseus) in Shallow Waters (Cardigan Bay, Wales)

A photo-identification study on Risso’s dolphins was carried out off Bardsey Island in Wales (July to September, 1997-2007). Their local abundance was estimated using two different analytical techniques: 1) mark-recapture of well-marked dolphins using a “closed-population” model; and 2) a census technique based on the total number of iden- tified individual dolphins sighted over the study period. The mark-recapture estimates of 121 (left sides; 64 - 178, 95% CI; CV 0.24) and 145 dolphins (right sides; 78 - 213, 95% CI; CV 0.24) closely matched the census technique estimates (population size of 90 - 151). It was found that the dolphins showed a degree of long-term and seasonal site-fidelity. A first long-distance match was made for Risso’s dolphins (319 km) between Bardsey Island and Cornwall, confirming they can be wide-ranging animals. This study demonstrates that the combination of systematic and opportunistic photo-ID studies has complementary value as a population assessment tool in generating the first local abundance esti- mate for Risso’s dolphins in UK waters. From the conservation perspective, these studies confirm the regular presence of Risso’s dolphins in these waters and the presence of calves shows breeding. Bardsey Island may be part of a network of localities that are important habitats to this species where it may take advantage of prey abundance in shallow waters. As such, results of this study may provide assistance to include the Risso’s dolphin in future regional conservation strategies including the envisaged marine protected areas.
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Exploring the Estimability of Mark-Recapture Models with Individual, Time-Varying Covariates using the Scaled Logit Link Function

Exploring the Estimability of Mark-Recapture Models with Individual, Time-Varying Covariates using the Scaled Logit Link Function

Wildlife conservation has become a worldwide task in the past decades. A lot of research and fieldwork have been done to help with wildlife management and protection. In wildlife re- search, one is often interested in the abundance or survival of an animal population. Since it is unrealistic to count or observe all individuals in the population, one first conducts experi- ments to study the population of interest. Statistical models are then developed to analyze the data from the experiment. Over the past century, capture-recapture (CR) methods have been widely used to estimate the abundance (i.e., the total number of animals in a population) or other demographic parameters (e.g., survival probability). This CR method is also the basis of other more complex models, which can obtain some auxiliary information (e.g., individual co- variates) to estimate relevant parameters more accurately. Many statistical and computational techniques can be applied to these models to deal with more complicated cases and improve the accuracy of the parameter estimation, which is an active research area.
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Open population mark recapture models including ancillary sightings : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Statistics at Massey University

Open population mark recapture models including ancillary sightings : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Statistics at Massey University

Robson ( 1969) introduced a model that allowed marking to have a short-term (usu­ ally lasting 1 capture period) effect on survival probabilities. Independently Manly ( 1971b) developed a similar model. Pollock ( 1 975) extended Robson's ( 1 969) model to include a short term effect on capture probabilities. In the Jolly-Seber model the population is divided into two groups of animals: marked and unmarked, with the assumption that all animals, whether marked or unmarked, have the same time­ specific capture and survival probabilities. This assumption allows inference to be made about the population. Robson (1969) and Pollock ( 1 975) consider the popu­ lation immediately after each sample as comprising three groups: unmarked, newly marked, and previously marked. �ewly marked is usually taken as first marked at the most recent sample, with the response lasting just one sampling period, how­ ever a longer-lasting response is also possible under their model. The assumption that the trap-response "wears off:' after the short term (i.e. capture and survival probabilities for previously marked and unmarked animals are equal) means that inference can still be made about the population based on the sample of marked animals.
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Estimating Detection Probabilities for Terrestrial Salamanders in Great Smoky Mountains National Park

Estimating Detection Probabilities for Terrestrial Salamanders in Great Smoky Mountains National Park

General amphibian surveys have been initiated for 3 primary purposes: (1) to establish baseline data and techniques for long-term monitoring programs conducted to periodically assess community or ecosystem status (Gibbons et al. 1997; Corn 2000; Dodd et al. 2000; Hyde and Simons 2001), (2) to compare historical to current distributions (Fisher and Shaffer 1996; Shaffer et al. 1998; Corser 2001) and (3) to identify areas of high species richness and diversity for protection (Akani and Luiselli 2001). Two important sources of variation, spatial variation and detectability, constrain the inferences drawn from these types of surveys (Yoccoz et al. 2001; Pollock et al. 2002). Studies often make inferences about large areas by collecting information from sample units selected by some probability sampling technique (e.g., stratified random sample). Additionally, because not all species are detected in a sampled area, monitoring programs must incorporate methods for estimating or removing effects of variations in species detection probabilities (Pollock et al. 2002). Species detection probability is defined as the probability of detecting at least one individual of a given species during a particular sampling occasion, given that individuals of the species are present in the area (Boulinier et al. 1998; MacKenzie et al. in press). Although some salamander studies incorporate a spatial design (e.g. Hyde and Simons 2001), we know of no previous study that has estimated species detection probability. Most amphibian studies use a variety of sampling methods to document species occurrence and record the total number of
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Modelling the tuberculosis epidemic population using bayesian techniques

Modelling the tuberculosis epidemic population using bayesian techniques

For this purpose, the model that has been considered is Bayesian proportional hazards. Three different kinds of prior distribution has been assigned to baseline cumulative incidence and unknown coefficients of covariates. For the baseline cumulative incidence, Gamma prior was assumed because the variables that have been considered for the study follows the Poisson distribution which also facilitates the computation of conjugated distribution. By using the Markov Chain Monte- Carlo (MCMC) methods the estimates of the parameters and the posterior distribution (as well as hyper parameters) is obtained. The confidence intervals that have been calculated for the incidence rates of tuberculosis on the assumption of the Poission distribution with the Gamma prior.
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Local dispersal of palaearctic Culicoides biting midges estimated by mark release recapture

Local dispersal of palaearctic Culicoides biting midges estimated by mark release recapture

The directions that the Culicoides took may be related to the topography of the landscape (rivers, valleys etc.), but we did not explore this due to low recapture rates. Culicoides did not appear to disperse towards farms with larger numbers of livestock present and indeed were trapped on one premise containing no livestock. The red- marked Culicoides recaptured on farms to the northwest of the release farm may have been aided by wind dispersal, with the wind during the day of release heading north- westerly. Similarly the red-marked individuals trapped on a farm easterly from the release site at 2 days post-release may have been influenced by the easterly wind recorded a day following their release. The same cannot be said for the blue dust-marked individuals found in the east and south-east, with the wind heading northwest on the day of release before changing to the southwest, highlighting that these individuals flew upwind. These findings may be ex- plained by Sedda et al . [6] who considered that during the European BTV-8 outbreak, upwind midge flight may be a response to wind acting as a carrier of host semio- chemicals, while downwind movement of midges was due to wind transporting the midges themselves. It is import- ant to note, however, that our wind direction data are 24 hr averages and do not provide the temporal resolution to examine wind directions at night only, when Culicoides flight is most likely. Large changes in wind direction may also be caused by complex topography, such as that found in the study site, therefore the wind direction and speed at the release site may vary significantly from that in other areas of the field site.
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Estimating demographic parameters for capture recapture data in the presence of multiple mark types

Estimating demographic parameters for capture recapture data in the presence of multiple mark types

In mark-recapture studies of open biological populations a number of simplifying assumptions are often made. These include no loss of marks from individuals; all identifying marks are unique; marks are never mis-read so that animals are always correctly identified; and the sample is representative of the population. Unfortunately, some (or all) of these assumptions are not always valid and these aspects are often of particular interest. For example, in the case where individual marks may be lost, the probability of losing a mark is often of interest in itself. Alternatively, recapture prob- abilities are typically assumed to be homogeneous over individuals, however, this may not generally be the case, particularly where different marking methods are applied to different individuals. We consider the case where there are multiple methods for marking individuals. In some cases, individuals may carry more than one mark type; when this is the case, we assume that individuals can be cross classified across marks. For the particular application considered, these are brands, tags and photo-identifica- tion. Ignoring the different mark types and assuming that recapture probabilities are homogeneous over mark type can potentially lead to biased results. We develop an integrated approach where we simultaneously analyse all available data, modelling explicitly the effect of mark type on the recapture probability of an individual. In particular, we allow the recapture probability to vary with respect to the mark type applied to the individual, but assume that the recapture probability is homogeneous over individuals with a given mark type. We note that this approach is similar to that of Lebreton et al. (1992) who adopt a stratified CJS-type model where groups are distinguished by mark type; and Pledger et al. (2003) who propose mixture models to allow for heterogeneity amongst different individuals for both recapture and sur- vival probabilities but where group membership is not known for individual animals. Within our approach the mixture component that each individual belongs to is known, corresponding to the type of mark applied to the animal for unique identifiability. We consider reparameterisations of the model (and additional sub-models) to repre- sent interpretable biological parameters of interest, including relative mark recapture (efficiency) rates and mark-loss probabilities.
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Study design and mark-recapture estimates of dispersal: A case study with the endangered damselfly Coenagrion mercuriale

Study design and mark-recapture estimates of dispersal: A case study with the endangered damselfly Coenagrion mercuriale

The number of recaptured individuals may affect dispersal estimates in one of two ways. First, while capable of larger movements, many individuals may be sedentary through lack of necessity for dispersal. Thus finding individuals that fulfil their dispersal potential may require sampling of larger number of individuals. Secondly, there may be a proportion of individuals that are pre-disposed to philopatry and a proportion that are dispersive, leading to a bimodal distribution of dispersal distance. Sampling from the dispersive individuals requires greater sample sizes which, in turn, provide better estimates of dispersal. Estimates of philopatry in odonates vary markedly between species, from 1.5% recaptures to 90.2% recaptures (Beirinckx et al. 2006), while this study found a recapture rate of 29.0% (Rouquette and Thompson 2007). Philopatry is also present in mammals (Waser and Jones 1983) and birds, where a review of passerine birds showed levels of philopatry between 0% and 39.7% (Weatherhead and Forbes 1994). A wide variety of factors have been implicated in affecting the extent to which odonates disperse. These include body size (Anholt 1990; cf. Conrad et al. 2002; Thompson 1991) a pattern which is seen across taxa (Jenkins et al. 2007) immune activity (Suhonen et al. 2009), ectoparasitic mite burden (Conrad et al. 2002), sex (Beirinckx et al. 2006; Conrad et al. 2002) and age {Michiels, 1991 #1340}. This age-dependent dispersal tendency could potentially result in increased dispersal later in the season. However, we find no evidence of this in the present study. Female polymorphisms (Bots et al. 2009), proximity to range margins (Hassall and Thompson 2008b) and landscape structure (Taylor and Merriam 1995) have also been suggested as factors affecting flight ability via changes in morphology.
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MICROGEOGRAPHIC AND TEMPORAL GENETIC DIFFERENTIATION IN NATURAL POPULATIONS OF DROSOPHILA SUBOBSCURA

MICROGEOGRAPHIC AND TEMPORAL GENETIC DIFFERENTIATION IN NATURAL POPULATIONS OF DROSOPHILA SUBOBSCURA

Spatial dzferences: Using mark-release-recapture experiments and genetic analysis of flies collected from different areas, several investigators have found differences in h[r]

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Open population maximum likelihood spatial capture recapture

Open population maximum likelihood spatial capture recapture

model and model with moving activity centers is shown in Figure 3. Table 1 shows the maximum likelihood estimates from both models. There is a remarkable difference in the estimated mean abundance: a 40% reduction in the estimated abundance when activity centers are assumed to be stationary. Furthermore, the stationary model estimates survival to be 10% lower and activity range to be 60% larger. The substantial effect the assumption of stationary activity centers has on the resultant inference makes clear that this assumption must be validated for any application of open population models. Moving activity centers, when present in the survey but unaccounted for in the model, leads to two problems. First, as individuals are seen over a wider range over the entire survey compared to within each occasion, the stationary model compensates for this by overestimating activity range and underestimating encounter rate; this ultimately leads to an overestimation of detection probability and, in this case, a substantially underestimated density. The second problem is while the model with movement is able to account for reduced detectability due to movement, the stationary model cannot and tends to explain this reduced detectability by lowering survivial probability: individuals that move out of detectable range are best explained by having failed to survive. One question is whether there is evidence that population density has changed over time. To investigate this, one can consider the estimated rate of change in density between occasions: ∆ k = (D k+1 − D k )/∆t k where ∆t k is the time between occasions k and
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Estimating Key Largo woodrat abundance using spatially explicit capture–recapture and trapping point transects

Estimating Key Largo woodrat abundance using spatially explicit capture–recapture and trapping point transects

Table 1. The number of woodrat capture events, with the number of unique woodrats captured given in parentheses, and the area of habitat (in hectares) for each of three habitat strata during the spatially explicit capture-recapture survey. A total of 33 grids were set for the 3 primary sessions (spring, summer, and winter). Row totals (i.e., by strata) for the number of woodrats caught are not a direct summation of each row, as some woodrats were caught across multiple sessions.

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Site-specific assessments of the abundance of three inshore dolphin species to inform conservation and management

Site-specific assessments of the abundance of three inshore dolphin species to inform conservation and management

The value of long-term data to support conservation and adaptive management of wildlife populations is well-recognized (e.g., Clutton-Brock and Sheldon, 2010; Cheney et al., 2014), and recent expert-led prioritization exercises have emphasized the need for long-term studies of population dynamics of inshore dolphins in northern Australia (Department of the Environment, 2013a, 2015). They encourage multi-year, multi- disciplinary studies at appropriate reference sites (representing a range of levels of human impact), including data on abundance and habitat use, to facilitate: detecting trends in the abundance of local populations; the investigation of natural variability in characteristics of populations (e.g., abundance and habitat use) and their relationship to environmental stochastic events (e.g., cyclones); collecting life history data to inform assessments of population viability; and, developing a greater understanding of threatening processes and mitigation options (Department of the Environment, 2015). Such long-term studies will require considerable planning and investment, and existing data are of great value to inform the selection of suitable sites. To this end, our results provide an indication of the suitability of several candidate sites. Specifically, the abundance and accessibility of snubfin dolphins within Roebuck Bay present a scientifically suitable and relatively cost-effective candidate for long-term study (see recommendations). Roebuck Bay is subject to moderate levels of human activity, including: a growing adjacent township, port facilities, and considerable recreational vessel traffic in some areas (Department of Parks and Wildlife, 2015), presenting opportunities for the study of impacts from threatening activities. Furthermore, the imminent establishment of a 788 km 2 multi-use Marine Protected Area (MPA) within Roebuck Bay, which aims to conserve a range of natural, cultural and recreational values, can provide the necessary management framework to facilitate such an ongoing study (Department of Parks and Wildlife, 2015).
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Local dispersal of palaearctic Culicoides biting midges estimated by mark-release-recapture

Local dispersal of palaearctic Culicoides biting midges estimated by mark-release-recapture

Methods: The dispersal of Obsoletus Group members was studied on 19 farms around Bala, north Wales. Field-collected Culicoides were trapped in a black-light (OVI) trap and self-marked in the collecting vessel, using micronized fluorescent dust. Culicoides were released at a central farm and OVI traps set on 18 surrounding farms, at distances of 1 to 4 km. The study was repeated using six colours of fluorescent dust over an 18 day period. Results: An estimated 61,062 (95% CI = 56,298-65,830) marked Culicoides were released during the study and 12 (0.02%) Culicoides were recaptured. Of the females recaptured, six were C. obsoletus/scoticus, two C. dewulfi, two C. pulicaris and one C. festivipennis. The male was C. obsoletus. Recaptures occurred 1 – 2.5 km from the release site, with greatest numbers at 2.5 km. Most recaptures were 2 nights post-release; none were more than 3 nights post-release. Two females were recovered at 1.5 km on the night of release and one male at 1 km two nights post-release. The mean distance travelled (MDT) for males was 1 km, females was 2.21 km, and all recaptured Culicoides was 2.15 km. Recaptures were made both downwind and upwind of the prevailing wind direction during the trapping periods, highlighting possible passive and active dispersal of Culicoides between farms.
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Estimating density of ship rats in New Zealand forests by capture- mark-recapture trapping

Estimating density of ship rats in New Zealand forests by capture- mark-recapture trapping

sites that will not yield density estimates. In 2003, only one of our six trapping arrays yielded more than 20 individual rats; only this site had enough captures for us to fit a spatial model and estimate D at that site. At two sites, fewer than 10 rats were caught, but these data could be combined for analysis with data from the other sites. A form of adaptive sampling may be advisable, to minimise the effort expended on a group of trapping arrays unlikely to yield enough data for combined analysis. A potential rule is: if few rats are captured in 3 days on three arrays that are to be pooled for analysis, cut your losses and move to the next location instead of continuing to trap for 5 days. In order not to bias the overall conclusions of the study, these results must not be discarded but should be recorded as ‘density apparently low’. The adaptive cluster-sampling approach proposed by Thompson (1990, 1991) may also be useful, whereby when the number of captures at a location exceeds some limit, nearby locations are also sampled. However, this algorithm will not be helpful if high-density patches of rats are smaller than c. 100 ha, unless very small, high-intensity trapping arrays are used. An alternative or additional approach would be simply to sample at more locations in strata (e.g. forest types) with more captures in preliminary surveys. This strategy assumes that strata likely to have different densities of ship rats can be identified in advance. Although ship rats are highly cosmopolitan, forest composition (King et al. 1996; King & Moller 1997), structure (Harper et al. 2005), and elevation (because ship rats are relatively scarce at high elevations and are not found above treeline; Innes 2005) may be useful strata for stratified sampling of their population density. The best sampling design will depend on the scale and objectives of the study. Even preliminary results may help to improve the design of subsequent studies, and will substantially add to our knowledge of spatial patterns in the distribution and abundance of an important introduced forest predator.
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Abundance Annex: Ape Population Abundance Estimates

Abundance Annex: Ape Population Abundance Estimates

Guislain, P. and Reinartz, G.E. (2010–11). Means of verification report of wildlife indicators to CARPE. CBFP SLS landscape no. 8. Milwaukee, WI: Zoological Society of Milwaukee. Unpublished report to US Agency for International Development (USAID) Central Africa Regional Program for the Environment (CARPE). Hakizimana, D. and Huynen, M.-C. (2013). Chimpanzee (Pan troglodytes schweinfurthii) population density and

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Double observer line transect methods : levels of independence

Double observer line transect methods : levels of independence

Distance sampling (Buckland et al., 2001) is widely used for estimating animal abundance. In line transect sampling, an observer travels along each of a number of lines, laid out according to some randomised (usually systematic random) scheme, and records each detected animal, together with its perpendicular distance from the line. One of the key assumptions of the method is that animals on the line are certain to be detected. A number of authors have considered so-called double-observer or double- platform methods to extend line transect sampling to the case that not all animals on the line are detected (e.g., Buckland and Turnock, 1992; Palka, 1995; Alpizar-Jara and Pollock, 1996; Manly et al., 1996; Quang and Becker, 1997; Chen, 2000; Innes et al., 2002). The double-observer data can be regarded as two-sample mark-recapture. However, heterogeneity in detection probabilities generates bias in abundance estimates, just as heterogeneity in capture probabilities generates bias in mark-recapture estimates of abundance. Authors have attempted to minimize this bias, for example by modelling the effects of covariates (Borchers et al., 1998a,b; Borchers, 1999; Schweder et al., 1999; Laake and Borchers, 2004; Borchers et al., 2006), or by assuming independence in the detections of instantaneous cues (such as whale blows) rather than of animals (Skaug and Schweder, 1999; Schweder et al., 1999).
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Recommendations for photo identification methods used in capture recapture models with cetaceans

Recommendations for photo identification methods used in capture recapture models with cetaceans

images and data used in photographic capture-recapture studies used to estimate the abundance of cetaceans... Examination of variation in methods used across laboratories and researchers[r]

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A continuous time version and a generalization of a Markov-recapture model for trapping experiments

A continuous time version and a generalization of a Markov-recapture model for trapping experiments

The estimate of the unknown population size is based on the assumption of a closed population and a simple Markov model in which the rates of marking, capture, and recapture are assumed [r]

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An assessment of the suitability of captive bred founders for lizard restoration projects using Duvaucel's geckos (Hoplodactylus duvaucelii) : a thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in Conservation

An assessment of the suitability of captive bred founders for lizard restoration projects using Duvaucel's geckos (Hoplodactylus duvaucelii) : a thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in Conservation Biology, Massey University, Albany, New Zealand

TABLE 2.1: THE AVERAGE WEIGHT ± STANDARD ERROR (SE) AND THE WEIGHT RANGE FOR MALE AND FEMALE HOPLODACTYLUS DUVAUCELII FROM EACH ORIGIN, I.E. CAPTIVE-BRED, KORAPUKI-SOURCED AND STANLEY-SOURCED, DURING THE QUARANTINE PERIOD PRIOR TO TRANSLOCATION IN FEBRUARY 2013……26 TABLE 2.2A (APPENDIX): LIST OF ALL HOPLODACTYLUS DUVAUCELII RADIO TRACKED DURING THE FIRST RADIO TRACKING PERIOD (FEBRUARY TO MAY 2013), INCLUDING THEIR WEIGHTS (G) WITH AND WITHOUT THE TRANSMITTERS ATTACHED…………………………………………………………………………………………………………………………134 TABLE 2.2B (APPENDIX): THE AVERAGE WEIGHT (G) ± STANDARD ERROR (SE) AND THE WEIGHT RANGE FOR HOPLODACTYLUS DUVAUCELII BEFORE AND AFTER TRANSMITTER ATTACHMENT (SOPR-2038) AND THE EQUIVALENT INCREASE IN BODY WEIGHT PERCENTAGE (%)………………………………………………………………………135 TABLE 2.2C (APPENDIX): LIST OF ALL HOPLODACTYLUS DUVAUCELII RADIO TRACKED DURING THE SECOND RADIO TRACKING PERIOD (SEPTEMBER TO DECEMBER 2013), INCLUDING THEIR WEIGHTS (G) WITH AND WITHOUT THE TRANSMITTERS ATTACHED…………………………………………………………………………………………………135 TABLE 2.2D (APPENDIX): THE AVERAGE WEIGHT (G) ± STANDARD ERROR (SE) AND THE WEIGHT RANGE FOR HOPLODACTYLUS DUVAUCELII BEFORE AND AFTER TRANSMITTER ATTACHMENT (PIP3 AG393) AND THE EQUIVALENT INCREASE IN BODY WEIGHT PERCENTAGE (%)………………………………………………………………………136 TABLE 3.1 (APPENDIX): THE NUMBER OF DOUBLE-ENDED G-MINNOW FUNNEL TRAPS SET WITHIN AND OUTSIDE OF EACH OF THE MONITORING SITES DURING THE 2013 AND 2014 MARK-RECAPTURE
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