REVISED ECOSYSTEM-BASED UNGULATE HABITAT MODELS FOR BOUNDARY TSA AND TFL 8
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1 REVISED ECOSYSTEM-BASED UNGULATE HABITAT MODELS FOR BOUNDARY TSA AND TFL 8 PREPARED BY Dennis L. Hamilton, RPBio Nanuq Consulting, Nelson, BC Steven F. Wilson, Ph.D, RPBio. EcoLogic Research, Gabriola Island, BC Kathleen McGuinness Touchstone GIS Services, Nelson, BC PREPARED FOR International Forest Products Limited Grand Forks, BC March 2009
2 Table of Contents Table of Contents... ii List of Figures... ii Appendices... ii Introduction... 4 Methods... 4 Study Area... 4 Field Data... 6 Revisions to Ecosystem-based Habitat Models... 6 Revisions to Map Database... 7 Results and Discussion... 8 Acknowledgements... 9 Literature Cited Appendices List of Figures Figure 1: Biogeoclimatic zones found in the Boundary TSA. and TFL Figure 2: 2004/05 and 2006/07 Ungulate Snow Track Count Survey Transects in Boundary TSA and TFL Figure 3: 2009 Ungulate Snow-track Count Survey Transects in Boundary TSA and TFL Figure 4: Bayesian belief network model for mule deer, elk and moose winter habitat suitability for Boundary TSA and TFL 8. The capability model was the same except that there were no nodes for Age, Structural Stage and Canopy (these were constant in the capability model).. 8 Appendices Appendix 1: Ecosystem-based Habitat Capability Map for Deer Appendix 2: Ecosystem-based Habitat Capability Map for Elk Appendix 3: Ecosystem-based Habitat Capability Map for Moose Appendix 4: Ecosystem-based Habitat Suitability Map for Deer Appendix 5: Ecosystem-based Habitat Suitability Map for Elk Appendix 6: Ecosystem-based Habitat Suitability Map for Moose ii
3 Introduction In support of their sustainable forest management planning framework, Interfor (formerly Pope & Talbot) adopted the ecosystem-based wildlife-habitat model approach (Resources Inventory Committee 1999) for mapping of ungulate winter habitats. This has led to development of species-habitat models for deer (Odocoileus hemionus), elk (Cervus elaphus) and moose (Alces alces) for the Boundary TSA and TFL 8 (Wilson and Hamilton 2008) and TFL 23 (Hamilton and Wilson 2002a) and for mountain caribou (Rangifer tarandus) on TFL 23 (Hamilton and Wilson 2002b). The Wildlife Habitat Ratings method is one of the few available that addresses both habitat suitability and capability (thereby providing the basis for future habitat supply modelling), captures broad knowledge, and can use empirical data (where available) to test and adjust ratings. In additional, subsequent maps can be updated easily when additional work warrants changes to base maps coverages or wildlife-habitat models. Both expert knowledge and recent empirical data from sample plot characteristics (Hamilton and Torrans 2008) and winter track encounter survey data (Stent and Hamilton, in prep.) were used in improving the wildlife habitat ratings. We used a revised methodology based on Bayesian Belief Network modelling to generate revised ratings tables, with the goal of making the generation of wildlife-habitat models more defensible and transparent. Methods Study Area Boundary TSA and TFL 8 are located in the Arrow-Boundary Forest District in south-central B.C. The TSA encompasses approximately 580,000 hectares and includes the communities of Grand Forks, Beaverdell and Greenwood. TFL 8 consists of 77,456 hectares of crown land and fresh water and in the Boundary Creek area north of Greenwood and the Trapping Creek and Carmi Creek drainages north of Beaverdell. Communities in the vicinity of TFL 8 include Grand Forks, Greenwood, Midway, Rock Creek, Westbridge and Beaverdell (Figure 1). The western portion of the TSA is the Northern Okanagan Highland ecosection which is drained by the Kettle River. This ecosection consists of a rolling highland with wide, deep, north-south valleys. In the eastern portion of the TSA, drained by the Granby River, is the Selkirk Foothills ecosection, which is characterized by subdued mountain terrain with wide, north-south valleys and trenches. The Southern Okanagan Highland ecosection consists of a narrow band along the Canada-US border. This ecosection is characterized by east-west valleys with rounded forested hillsides on north facing slopes and open grasslands on south slopes (Quesnel and Thiessen 1993, Meidinger and Pojar 1991). 4
4 Figure 1: Biogeoclimatic zones found in the Boundary TSA. and TFL 8. The climate is arid to sub-humid continental with warm summers and cool, snowy winters. In the past, natural forest fires were common. Large animals, notably mule and white-tailed deer, moose, elk and black bear are prevalent throughout the area, along with numerous smaller animals, reptiles, amphibians and birds. The area is ecologically diverse, with ecosystems ranging from low-elevation, dry rangelands in the south, to relatively wet, high-elevation Engelmann spruce-subalpine fir (ESSF) parkland forests. The forests are predominately mixtures of Douglas-fir, larch, lodgepole pine and ponderosa pine types at lower and mid elevations, and lodgepole pine, and spruce/balsam types at the higher elevations. Ecologically they occur primarily in the Montane Spruce (MS), Interior Douglas-fir (IDF), and Interior Cedar Hemlock (ICH) biogeoclimatic zones (Braumandl and Curran 2002). Annual precipitation in the vicinity of the TFL ranges from about 30 to 127 centimetres (increasing with elevation) with drought periods frequently as long as 80 days. The frost-free period may last from only 20 to 100 days. Because of low humidity, droughts, and frequent thunderstorms, the summer season is often characterized by extreme fire hazard. 5
5 Field Data Development of the original draft wildlife-habitat models for deer, elk and moose (Wilson and Hamilton 2008) was based on knowledge gained during two seasons of ungulate winter snow track count surveys (Stent and Hamilton 2007; Figure 2). This winter range distribution and use data were supplemented by summer field investigations of the habitat characteristics of ungulate winter range habitats identified from the snow track count surveys (Hamilton and Torrans 2008). Additional ungulate snow track count surveys were completed over a broader landscape in winter 2009 (Stent and Hamilton, in prep; Figure 3). Figure 2: 2004/05 and 2006/07 Ungulate Snow Track Count Survey Transects in Boundary TSA and TFL 8 Revisions to Ecosystem-based Habitat Models The development of the earlier wildlife-habitat ratings for deer, elk and moose on Boundary TSA an TFL 8 were based on Bayesian Belief Network models, using Netica 3.24 (Norsys Software Corp.) and are described in Wilson and Hamilton (2008). As reported, the structure of the wildlife-habitat models allow for new information to be incorporated more quickly, ensuring that management is always based on the most robust information available. This report incorporates new knowledge gained through additional field data attained from ungulate winter snow track count surveys, further analysis of data and additional knowledge gained from related winter and summer field sampling. 6
6 Figure 3: 2009 Ungulate Snow-track Count Survey Transects in Boundary TSA and TFL 8 Revisions were made to ratings for several non-forested site series; most importantly, ratings of site series associated with open range ecosystems, cultivated fields and clearings were adjusted to reflect the expected abundance of rooted forage. This increased the suitability of these areas for both deer and elk. Revisions to Map Database The map database was changed as follows: age class for shrub-dominated ecosystems and NSR (not sufficiently re-stocked) forest cover was adjusted to age class 1 to reflect the composition of the ecosystems; ICHdm1 was changed to ICHmk1 because of an assumed error in the ecosystem coverage (ICHdm1 does not exist); the following substitutions were made for BEC subzone variants without defined site series (R. Waterous, pers. comm.): o ICHdw2 used ICHdw site series o IDFxh4 used IDFxh1 site series o MSdm1a used ICHmk1 site series Several other site series were substituted for unknown map codes, based on site descriptions 7
7 Results and Discussion Inputs for the winter ungulate capability and suitability habitat models (Figure 4) included: biogeoclimatic subzone variant (BECLABEL; based on the provincial biogeoclimatic mapping, version 6) Site Identification (Braumandl and Curran 2002; Braumandl and Dykstra 2005) DBO TEM (Oikos Ecological Services 2000 and Biome Ecological Consultants 2004) DBO PEM (Timberline 2003) TSA forest cover VRI data from GeoBC (April 2008) TFL 8 forest cover (coverage from Randy Waterous) Slope and aspect grid (zonal majority processing by Tom Koftinoff) Basing the wildlife-habitat models for mule deer, elk and moose on Bayesian belief networks (Figure 4) has been described in detail as part of development of ungulate habitat models for Boundary TSA and TFL 8 by Wilson and Hamilton (2008) and for ungulate habitat models, including mountain caribou, for TFL 23 (Wilson and Hamilton 2007). Figure 4: Bayesian belief network model for mule deer, elk and moose winter habitat suitability for Boundary TSA and TFL 8. The capability model was the same except that there were no nodes for Age, Structural Stage and Canopy (these were constant in the capability model). Capability is defined as the ability of the habitat, under optimal natural (seral) conditions for a species to provide its life requisites, irrespective of the current condition of the habitat. It is an estimate of the highest potential value of a particular habitat for a particular species (RIC 1999). The ecosystem-based habitat capability maps for deer, elk and moose are found in Appendices
8 Suitability is defined as the ability of the habitat in its current condition to provide the life requisites of a species. It is an estimate of how current habitat conditions meet the specified life requisites for a specified species suitability is frequently less than the capability because of unfavourable seral conditions (RIC 1999). The ecosystem-based habitat suitability maps for deer, elk and moose are found in Appendices 4-6. The strengths of the more objective Baysian belief network basis for assigning habitat ratings to ecosystem units, compared to the tradition approach of manually populating wildlife habitat tables is also discussed in the habitat model reports by Wilson and Hamilton (2007, 2008) and others (McNay 2006, Nyberg et al 2006). In summary, the original intent of the wildlife-habitat ratings system was to capture expert knowledge, rather than to explicitly model relationships. In this respect, the manual approach is entirely justified. However, over time it has become evident that the ratings methodology must become more rigorous, transparent and repeatable if it is to be used to map wildlife habitat in relation to ecosystem maps. The Bayesian belief network models were still based on expert knowledge; however, they have the advantage of explicitly documenting the interactions among variables that were considered in developing the ratings. There is still room to improve the models; for example, forage capability in the deer, elk and moose models was still based entirely on an expert interpretation site series descriptions. This could be made more explicit by incorporating directly into models variables related to key forage species and correlates of their abundance. Acknowledgements Funding for the project was provided by the Forest Investment Account through Interfor, Grand Forks, BC. We thank Sandra Cheverie as contract manager. Randy Waterous provided ecosystem mapping files, assisted with interpretation of PEM mapping codes and provided review of an earlier draft. Tom Koftinoff processed slope and aspect grid data used in the mapping. 9
9 Literature Cited Biome Ecological Consultants TFL 8 BEC/PEM linework reconciliation project final report. Contract report for Pope & Talbot Ltd., Boundary Timber Division, Midway, BC. Braumandl, T. F., and M. P. Curran A field guide for site identification and interpretation for the Nelson Forest Region. BC Ministry of Forests Land Management Handbook Number 20. Braumandl, T. F., and P. R. Dykstra A field guide for site identification and interpretation for the Nelson Forest Region. Land Management Handbook 20, Supplement No. 1. Meidinger, D. and J. Pojar Ecosystems of British Columbia. BC Ministry of Forests, Victoria, BC. Special Report Series p. Oikos Ecological Services Ecosystem mapping Pope & Talbot, TFL 8. Final report, 30pp. McNay, R.S., B.G. Marcot, V. Brumovsky and R. Ellis A Baysian approach to evaluating habitat for woodland caribou in north-central British Columbia. Can. J. For. Res. 36: Nyberg, J.B., Marcot, B.G., and Sulyma, R Using Baysian belief networks in adaptive management. Can. J. For. Res. 36. Resources Inventory Committee British Columbia wildlife habitat rating standards. BC Ministry of Environment, Lands and Parks. Victoria. Stent, P., and D. Hamilton Ungulate winter range on Boundary TSA and TFL 8: summary of year-2 ungulate winter snow track count surveys and summer field sampling plan. Prepared for: Pope & Talbot Ltd., Midway, BC. Stent, P., and D. Hamilton. In prep. Summary of three years of ungulate winter track count surveys conducted on Boundary TSA and TFL 8. Prepared for International Forest Products, Grand Forks, BC. Torrans, D., and D. Hamilton Field sampling for ungulate winter range habitat attributes found on Boundary TSA and TFL 8. Prepared for Pope & Talbot and BC Timber Sales, Grand Forks, BC. Wilson, S.F., and D. Hamilton Ungulate winter habitat mapping of TFL8 and the Boundary TSA: Wildlife-habitat models for deer, elk and moose. Prepared for Pope & Talbot, Midway, BC. Wilson, S.F. and D. Hamilton Revised predictive ecosystem map and wildlife habitat models for TFL 23. Prepared for Pope & Talbot, Nakusp, BC 10
10 Appendices Appendix 1: Ecosystem-based Habitat Capability Map for Deer 11
11 Appendix 2: Ecosystem-based Habitat Capability Map for Elk 12
12 Appendix 3: Ecosystem-based Habitat Capability Map for Moose 13
13 Appendix 4: Ecosystem-based Habitat Suitability Map for Deer 14
14 Appendix 5: Ecosystem-based Habitat Suitability Map for Elk 15
15 Appendix 6: Ecosystem-based Habitat Suitability Map for Moose 16
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