توزیع فضایی استفاده تفرج کنندگان علمی با تاکید بر مدل تعیین کریدور وحوش زوج سم و پستانداران خشکی‌زی در مناطق حفاظت شده بیابانی

Extended Abstract
Our goal is identifying biologists suitability in Geno desert protected area that it is the most important protected area in Hormozgan according evaluation land by FAO models with identifying ecological and sub structural factors. In this research we use different map such as: slope, Dem, temperature, vegetation, soil, water resources and natural attraction (vegetation plant, kind of wild life and wild life density) and sub structural factors (roads and distance of city and facilities). Livestock grazing modals is entering modal for wildlife suitability modals and then finally tourism suitability determined. We use endemic plant suitability modal, vulnerable, Low risk and rare for vegetation landscape. Final results of tourism suitability in Geno show that 35.4% with high limitation (S3) and 64.6 % is not suitable (N). There isn’t any area with S1 and S2. Water resources, topography (Dem, slope) are limitation factors and Temperature, natural attraction, wild life and native, vulnerable and in danger plant diversity, proximity to city and service facilities are increasing factors.
Introduction
Coastal deserts, due to their special geography, close to the sea, plant and animal species are very adapted to those dry conditions, sultry weather and high temperature and humidity, which in other places, these species are not able to live. Therefore, many experts need to observe these different native species in their original habitat and habitat (Natz, 2020). Recreational assessment of the protected area determines the potential places for tourism in arid and semi-arid areas and leads to the preparation of infrastructure in accordance with the ecological potential of the area to prevent the destruction of natural ecosystems (Nikandish, 2020). Hormozgan has desert protected areas that have not yet been zoned for the use of experts and scientific practitioners, and it is necessary to do so. In this regard, determining the appropriate tourist locations by Ghorbanzadeh et al. (2019) by multi-criteria decision analysis with GIS and different methods have been used for weighting. Sur and Alamdarloo (2013) selected Poshtkuh lands suitable for tourism in Yazd province based on FAO evaluation method. Accordingly, among environmental and ecological parameters, temperature, slope, height and soil depth factors, and among infrastructure parameters, distance to the city and amenities are factors that increase the suitability and criteria of water resources, the value of vegetation attraction, distance to places and Attractions and roads and access routes were limiting factors for land suitability for tourism
Methods
In this study, ecological parameters and classification infrastructure were determined based on Makhdoom ecological model and the ecotourism competency model for GNU protected area was determined using FAO guidelines. The general structure of the tourism competency model and the effective parameters in this model are: environmental and ecological parameters (vegetation, slope, water resources, soil, area attractions, elevation map) and infrastructure parameters (distance to cities, access network such as roads and routes). In this study, ecological parameters and infrastructure were classified based on the servant ecological model and the ecotourism competency model for the GNU protected area was determined using FAO guidelines. The general structure of the tourism competency model and the effective parameters in this model are: environmental and ecological parameters (vegetation, slope, water resources, soil, area attractions, elevation map) and infrastructure parameters (distance to cities, access network such as roads and routes.
After vegetation typing, a representative area was considered in each vegetation type. Vegetation was sampled in each reagent area. Vegetation sampling was done by systematic random cutting and weighing by the authors. To measure plant species by the Minimal area method, the minimum plot area was determined and for tree and shrub species, a plot of 100 * 200 meters and for herbaceous and grass species, plots of 2 * 2 square meters were placed. The floristic list was measured in the designed forms and the production parameters, density, percentage of vegetation were measured and finally, after recording the plots, the vegetation information layer was prepared with GPS.
Results and discussion
In presenting the scientific tourism model of the region, information layers of ecological criteria and infrastructure criteria were prepared.Competency model of ecological or environmental parameters In presenting the competency model of ecological parameters, the information layers of ecological criteria with sub-models of natural gravity, biologists model were developed. To prepare the biodiversity competency sub-model, the carnivore competency map and the couple competency information layer were prepared separately. According to the results of the carnivorous competency model from the area of 44598 hectares, 5848.4 hectares (13.1%) in the 1S competency class, 22053.5 hectares (49.5%) in the 2S competency class and 16696 hectares (37.4%) in Competency class N is located. No area level was in the 3S competency category. According to the results of the competency model of cement couple or herbivores from 44598 hectares of area, 11877.8 hectares (26.6%) in 1S competency class, 7701.4 hectares (17.4%) in 2S competency class and 25018.8 hectares (56%) in Competency class N is located. No area level was in the 3S competency category.
Also in the wildlife species subspecies model, from the area of 44598 hectares of the region, 1959.279 hectares (44%) were in the 2S competency class, 25018.8 hectares (56%) were in the N competency class. No level was in the 1S and 3S competency categories. In presenting the scientific tourism model of the region, information layers of ecological criteria and infrastructure criteria were prepared.Competency model of ecological or environmental parameters.
In presenting the scientific tourism model of the region, information layers of ecological criteria and infrastructure criteria were prepared. Competency model of ecological or environmental parameters. The final model of scientific recreation. To prepare the final model of scientific recreation, the preliminary model of tourism is due to the combination of environmental parameters and infrastructure with each other in a restrictive way and theoretical combination was put together. Of the 44598 hectares in the region, 15870.6 hectares (35.4%) are in the 3S competency class and 28817.4 hectares (64.6%) are in the N competency class. In the protected area, no surface was located on floors class 1 or 2.
Conclusion