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Analysis of the Long-Term Dynamics of Ungulates in Sikhote-Alin Zapovednik, Russian Far East

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Analysis of the Long-Term Dynamics of Ungulates in Sikhote-Alin Zapovednik, Russian Far East Analysis of the long-term dynamics of ungulates in Sikhote-Alin Zapovednik, Russian Far East P.A. Stephens, O.Yu. Zaumyslova, G.D. Hayward and D.G. Miquelle Collaborators: Sikhote-Alin State Biosphere Zapovednik Wildlife Conservation Society University of Wyoming USDA Forest Service Analysis of the long-term dynamics of ungulates in Sikhote-Alin Zapovednik, Russian Far East A report to the Sikhote-Alin Zapovednik and USDA Forest Service Philip A. Stephens* Department of Zoology and Physiology, University of Wyoming, Laramie, WY 82071, USA Olga Yu. Zaumyslova Sikhote-Alin State Biosphere Zapovednik, Terney, Terneiski Raion, Primorski Krai, Russia Gregory D. Hayward Department of Zoology and Physiology, University of Wyoming, Laramie, WY 82071, USA; USDA Forest Service, Rocky Mountain Region, PO Box 25127, Lakewood, CO 80225, USA Dale G. Miquelle Wildlife Conservation Society, Russian Far East Program, Vladivostok, Primorye Krai, Russia 2006 * Present address: Department of Mathematics, University of Bristol, University Walk, Bristol, BS8 1TW, UK; [email protected] EXECUTIVE SUMMARY Study and findings 1. The winter transect count involves monitoring game species by counting tracks of animals that intersect with a stable network of transects, surveyed during periods of snow cover. It is the main method of estimating the number of many game animals in the Russian Federation. For over four decades, this approach has been used consistently to monitor a variety of species in Sikhote-Alin Zapovednik (SAZ), Russian Far East. Hitherto, this extensive data set has not been rigorously analysed to assess trends and ecological relationships in a variety of species, or to assess its potential and limitations with regard to informing management of SAZ. We present such an analysis, focused on six of the larger game species occurring in SAZ: red deer (Cervus elaphus), wild boar (Sus scrofa), roe deer (Capreolus pygargus), musk deer (Mochus moschiferus), sika deer (Cervus nippon) and moose (Alces alces). 2. The principle objectives of this work were to examine spatial pattern in the occurrence of the species of interest; to investigate methods for estimating population densities from the track encounter data; to assess factors underlying temporal changes in populations of the more abundant species; to analyse the survey protocol and recommend practices whereby it might be improved; and to determine the likely impact of Amur tigers (Panthera tigris altaica) on potential prey species. Through these analyses, we aimed to inform understanding of the distribution and dynamics of the ungulates within SAZ, to aid ongoing efforts to manage the area for the benefit of the endangered Amur tiger, and to integrate the disparate Russian and English language literatures on estimating animal abundance from indirect sign, thereby contributing to this important yet contentious field. 3. Comparisons of track encounter rates among forest types and drainages suggested few consistent patterns of animal distribution beyond those already recognised by accepted divisions of SAZ into three broad habitat zones (the coastal, oak-birch zone; the central belt, dominated by mixed Korean pine and deciduous forests; and the north-western, higher altitude areas, dominated by spruce and fir forests). Within the oak-birch zone, however, sika deer show pronounced differences in their use of the coastal oak forests and mixed birch and aspen forests further inland. Though less marked, the data suggested that other species may also show differences in their use of these areas. Consequently, we recommend that, in future, the oak-birch zone should be divided into two separate survey units, recognising the existence of four (rather than three) broad habitat zones for survey purposes. 4. Three methods for estimating ungulate absolute population densities from track counts were compared, including a correction factor based on the relationship between track counts and total counts of deer in experimental plots; the established Formozov- Malyeshev-Perelshin (FMP) formula based on records of animal daily movement distances; and a computationally-intensive simulation approach based on two- dimensional records of animal daily movements. The simulation and FMP approaches gave very similar estimates, supporting the existing belief in Russia that the FMP formula is theoretically sound and generally robust to the different movement patterns of ungulate species. The correction factor tended to overestimate densities but this is unsurprising, i given that data used to develop the correction factor came from other study areas, where animal movements may be very different. 5. We stress that no method for estimating density from indirect sign is robust to violations of underlying assumptions. In particular, no method can fully compensate for biases arising from a survey network that does not adequately represent the area of interest. All methods based on indirect sign also require independent validation, ideally using monitoring based on direct sightings. Specific recommendations for enhancing the validity of the track count surveys are given below. 6. Two of the methods for estimating ungulate abundance from track encounter rate depend on good data on animal 24-hour movements. These data are currently limited for SAZ but preliminary analyses indicated that movement distances may be affected by time of year and group size (for red deer and roe deer), and a combination of habitat type and time of year (for wild boar). Understanding how travel distances are affected by different conditions is essential for improving the accuracy of density estimation and we urge further collection of these data in a range of conditions. 7. Differences between ungulate densities in the three major habitat zones of SAZ are pronounced and we assumed that data would always be stratified at this level, at the very least. Finer levels of stratification, including stratification by drainage basin and by forest formation were compared. These different types of stratification seldom had strong effects on estimates. However, analyses indicated that stratification by forest formation could be vulnerable to outliers and, consequently, stratification by drainage basin is recommended. It remains to be seen whether this will be necessary, if a four zone approach to the surveys is adopted (see further below). 8. Non-parametric bootstrapping was used to derive confidence intervals around estimates of ungulate densities. This method is free from many of the assumptions required by other suggested methods for estimating confidence intervals about estimates derived using the FMP formula. Using non-parametric bootstrapping also avoids the requirement for estimates of parameters such as average group size and average crossing rate for the paths of individual animals, both of which can be very difficult to obtain. 9. Overall, densities of ungulates tend to be highest in coastal areas and lowest in the spruce-fir, montane forests. Red deer were the most abundant species (1.5 to 3.0 km-2 throughout SAZ), followed by roe deer (1 to 2.5 km-2). At present, sika deer occur only in the oak-dominated forests on the coast but their population appears to be growing rapidly (now exceeding 1 km-2 in that area). Less is known about musk deer daily movements but analyses indicated that this species shows the opposite trend to the other ungulates in SAZ, with the highest densities in montane, spruce-fir forests, and the lowest densities towards the coast. Overall, mean musk deer density throughout SAZ is approximately 1 km-2. Wild boar show substantial fluctuations throughout the coastal and central areas but are at generally low abundance in both, seldom exceeding 0.1 to 0.5 km-2. Finally, moose tracks are encountered too rarely to analyse. That moose track encounters have virtually ceased since 1980, suggests that this species (which is at the southern extent of its range in SAZ) may have shifted northward in response to increasing temperatures. 10. Analyses of changes in track encounter rates within years suggested that encounters of the tracks of several species (including red deer, roe deer and musk deer) show ii pronounced declines from early to late winter. Although this results partly from changes in travel distances as winter progresses, it is also possible that species distributions shift throughout winter. Survey routes that accurately represent the entire area of interest are essential if this phenomenon is to be understood (see further below). 11. In spite of the rigour with which SAZ is surveyed, the track data are prone to census error and resultant estimates of density are noisy. This leads to difficulties in determining the major factors dictating the dynamics of each species. Nevertheless, evidence for density dependent processes was found in several populations. Additionally, climate, competition, quality of mast crops and protection from poaching all influence the studied populations. Dynamics of the red deer and sika deer populations are currently best understood. There is evidence for competition between these species and, also, for climate effects acting in different directions. In particular, increasing temperatures appear to have a positive effect on the sika deer population but a negative effect on red deer populations in the coastal and central zones. By contrast, red deer in the spruce-fir zone are positively affected by increasing temperatures, suggesting that the species may be shifting its distribution northwards
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