Article

Demographic status of Komodo dragons populations in Komodo National Park

Biological Conservation (Impact Factor: 3.79). 02/2014; DOI: 10.1016/j.biocon.2014.01.017

ABSTRACT The Komodo dragon (Varanus komodoensis) is the world's largest lizard and endemic to five islands in Eastern Indonesia. The current management of this species is limited by a paucity of demographic infor-mation needed to determine key threats to population persistence. Here we conducted a large scale trap-ping study to estimate demographic parameters including population growth rates, survival and abundance for four Komodo dragon island populations in Komodo National Park. A combined capture mark recapture framework was used to estimate demographic parameters from 925 marked individuals monitored between 2003 and 2012. Island specific estimates of population growth, survival and abun-dance, were estimated using open population capture–recapture analyses. Large island populations are characterised by near or stable population growth (i.e. k $ 1), whilst one small island population (Gili Motang) appeared to be in decline (k = 0.68 ± 0.09). Population differences were evident in apparent sur-vival, with estimates being higher for populations on the two large islands compared to the two small islands. We extrapolated island specific population abundance estimates (considerate of species habitat use) to produce a total population abundance estimate of 2448 (95% CI: 2067–2922) Komodo dragons in Komodo National Park. Our results suggest that park managers must consider island specific population dynamics for managing and recovering current populations. Moreover understanding what demographic, environmental or genetic processes act independently, or in combination, to cause variation in current population dynamics is the next key step necessary to better conserve this iconic species.

0 Bookmarks
 · 
123 Views
  • Conservation Biology 01/1998; 12(3):516-520. · 4.36 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Tropical islands are species foundries, formed either as a by-product of volcanism, when previously submerged seabed is thrust upwards by tectonics, or when a peninsula is isolated by rising sea level. After colonisation, the geographical isolation and niche vacancies provide the competitive impetus for an evolutionary radiation of distinct species-island endemics. Yet the very attributes which promote speciation in evolutionary time also leave island endemics highly vulnerable to recent and rapid impacts by modern people. Indeed, the majority of documented human-driven extinctions have been exacted upon island endemics. The causes include over-exploitation, invasive species brought by people and destruction of island’s naturally constrained habitats. Imminent threats include inundation by rising sea levels and other adaptive pressures related to anthropogenic global warming. We review recent work which underscores the susceptibility of island endemics to the drivers of global change, and suggest a methodological framework under which, we argue, the science and mitigation of island extinctions can be most productively advanced.
    Biodiversity and Conservation 19(2):329-342. · 2.26 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: We describe recent developments in the POPAN system for the analysis of mark-recapture data from Jolly-Seber type experiments. The previous versions (POPAN-3 for SUN/OS workstations and POPAN-PC for IBM-PC running DOS or Windows) included general statistics gathering and testing procedures, a wide range of analysis options for estimating population abundance, survival and birth parameters, and a general simulation capability. POPAN-4 adds a very general procedure for fitting constrained models based on a new unified theory for Jolly-Seber models. Users can impose constraints on capture, survival and birth rates over time and/or across attribute groups (e.g. sex or age groups) and can model these rates using covariate models involving auxiliary variables (e.g. sampling effort).
    Journal of Applied Statistics. 02/1995; 22(5-6):785-800.

Full-text

View
179 Downloads
Available from
Jun 10, 2014