Summary1. Accurate and precise estimates of abundance are required for the development of management regimes for deer populations. In woodland areas, indirect dung count methods, such as the clearance plot and standing crop methods, are currently the preferred procedures to estimate deer abundance. The use of line transect methodology is likely to provide a cost-effective alternative to these methods. 2. We outline a methodology based on line transect surveys of deer dung that can be used to obtain deer abundance estimates by geographical block and habitat type. Variance estimation procedures are also described. 3.As an example, we applied the method to estimate sika deer Cervus nippon abundance in south Scotland. Estimates of deer defecation and length of time to dung decay were used to convert pellet group density to deer density by geographical block and habitat type. The results obtained agreed with knowledge from cull and sightings data, and the precision of the estimates was generally high. 4. Relatively high sika deer densities observed in moorland areas up to 300 m from the forest edge indicated the need to encompass those areas in future surveys to avoid an underestimate of deer abundance in the region of interest. 5. It is unlikely that a single method for estimating deer abundance will prove to be better under all circumstances. Direct comparisons between methods are required to evaluate thoroughly the relative merits of each of them. 6. Line transect surveys of dung are becoming a widely used tool to aid management and conservation of a wide range of species. The survey methodology we outline is readily adaptable to other vertebrates that are amenable to dung survey methodology.

No abstract

A database was constructed of tree-anchorage measurements from almost 2000 trees from 12 conifer species that were mechanically overturned on 34 sites in the United Kingdom between 1960 and 2000. Anchorage was compared among species, soil groups (freely-draining mineral, gleyed mineral, peaty mineral, and deep peat) and root depth classes (shallow, <40 cm; medium, 40–80 cm; and deep, >80 cm) using regressions of critical turning moment against stem mass. Sitka spruce (Picea sitchensis (Bong.) Carr.) was used as a benchmark because it formed the largest part of the database and was the only species with all soil-group and depth-class combinations. Anchorage of Sitka spruce was strongest on peat and poorest on gleyed mineral soils. Deep rooting increased critical turning moments by 10%–15% compared with trees of equivalent mass with shallower roots. Significantly better anchorage than Sitka spruce was found for grand fir (Abies grandis (Dougl. ex D. Don) Lindl.), with various rooting depths on freely draining and gleyed mineral soils and for Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) on medium-depth mineral soil. Lodgepole pine (Pinus contorta Dougl. ex Loud.) had poorer anchorage than Sitka spruce over a range of soil groups and root depth classes. Norway spruce (Picea abies (L.) Karst.) on shallow gleyed mineral soil, and Corsican pine (Pinus nigra subsp. laricio (Poir.) Maire) on medium depth mineral soil, also had poorer anchorage. Other combinations had similar anchorage to the equivalent Sitka spruce. These results are discussed with respect to the development of forest wind-risk models.

No abstract

No abstract