Man-made barriers to salmonid migration include road /stream crossings, irrigation diversions and dams. Road /stream crossings are extremely numerous and often cross multiple road ownerships within a watershed. Passage impediments and delays in migration affect both adult and juvenile fish. Given the magnitude and severity of the problem, reconnecting isolated stream habitat has become an important priority for the restoration of impaired anadromous salmon and steelhead stocks. A comprehensive CDFW fish passage program is vital towards identifying, prioritizing, and treating migration barriers so that unimpeded migration of California''s salmonid populations is achieved. By coordinating resources with CDFW fisheries engineers, the Fisheries Restoration Grant Program and in conjunction with the Fish Passage Forum, a comprehensive program will aid in the recovery and de-listing of salmon and steelhead, in California. In 2008, the California departments of Fish and Game (now California Department of Fish and Wildlife (CDFW)) and Transportation (Caltrans) met with staff from the Assembly committees on Natural Resources and Transportation to discuss joint agency collaboration on prioritizing and remediating fish barriers to salmon and steelhead migration. This was in response to Senate Bill 857 requiring the California Department of Transportation to complete an assessment of potential barriers to anadromous fish prior to commencing any project using State or Federal transportation funds. In addition to the expectation that both agencies would develop a mutual list of priority barriers occurring along transportation corridors, a request was made to CDFW to provide a statewide list of priority barriers based on significance to fish migration and independent of who manages or is responsible for the stream crossing. CDFW developed its first list in 2011 and the point features mapped in this dataset represent the barrier locations from this list. CDFW has a more comprehensive list of barriers to salmon and steelhead migration; these barriers represent our effort to demonstrate and emphasize barrier priorities across both Coastal and Central Valley watercourses. As such, this spatial dataset presents the top priorities in each twenty-four Coastal and Central Valley counties for fish passage improvement. This list is a result of compilation and review by CDFW Regional biologists and supervisors (Regions 1-5) and by the Fisheries Branch. The prioritization process considered the following criteria: 1) high likelihood to improve migration for anadromous species; 2) availability of recent data of fish and habitat; 3) willing partners and land access; 4) known political support at a local, State or national level; 5) the site is a barrier to a federal recovery plan "Core" population; 6) the watercourse is an eco-regional significant watershed; 7) CDFW is committed to monitoring before, during and after any barrier improvement project is undertaken; and 8) the site is considered to be a "keystone barrier", meaning the barrier was the lower-most in that river or creek. Visit http://www.calfish.org/tabid/420/Default.aspx to view the 2019 CDFW datasheet that the creation of this spatial dataset was based on. Compare the point locations found in this dataset to point locations with matching PAD_IDs in the California Fish Passage Assessment Database to get detailed information such as each barriers current barrier type, passage status, treatment status, and year removed (if applicable).

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CDFW divides the state into six administrative Regions. CDFW staff in each Region identified linear segments of infrastructure that currently present barriers to wildlife populations in their jurisdiction. In doing so, the Regions used all available empirical information in their possession, including existing connectivity and road crossing studies, collared-animal movement data, roadkill observations, and professional expertise. The dataset represents the ten highest priority barriers identified in each region. This dataset represents CDFWs initial effort to identify priority wildlife movement barriers across the state. Currently, increasing attention is being directed toward wildlife habitat connectivity as a mechanism of maintaining biodiversity in the face of population growth and climate change. Listing priority wildlife barrier locations will help focus limited financial resources where the highest need has been identified to improve wildlife movement. This is complementary to CDFW''s fish passage barrier priorities that have been identified for anadromous fish. Like the fish passage priorities, the wildlife barrier priorities list will be periodically updated to reflect new information and barrier removal successes.Most of the barriers identified are highway segments, but the list also includes a local road, a high speed rail segment, and a concrete water conveyance canal.Additional information can be found in this report: https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=178511.Wildlife Movement Barriers - CDFW [ds2867] represents a comprehensive dataset of all barriers identified to date, including those which have been remediated since 2020.

하천에 물고기 등의 이동을 곤란 또는 불가능하게 하는 방해물이 있을 때 그 이동목적을 달성시킬 수 있도록 만들어진 수로 또는 장치인 어도에 관한 정보

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The project leads for the collection of these data were David Casady (CDFW) and Heiko Wittmer (Victoria University of Wellington). Black-tailed deer (65 adult females) from the Mendocino/ Clear Lake/ Alder Springs herd complex (herafter: Mendocino herd) were captured and equipped with store-onboard GPS collars (Lotek Wireless models 3300 and 4400 M, Telonics model TGW-3500), transmitting data from 2004-2013. An additional 24 female black-tailed deer were captured from the Mendocino herd and fit with Lotek Iridiumtrack M GPS collars, transmitting data from 2017-2021. The project lead for this overlapping dataset was Josh Bush (CDFW). Mendocino mule deer exhibit variable movement patterns and strategies. This population includes traditional seasonal migrants, full-time residents, and multi-range migrants (i.e., deer with long-term spring and/or fall stopovers). Full-time residents were excluded from the analysis, but individual deer exhibiting any type of directed movement between high-use ranges were considered a migrant and included. Based on this analysis, the portion of the population that migrates between seasonal ranges does so from a multitude of lower elevation areas within the mountainous Mendocino National Forest in winter to higher elevation summer ranges. Migrants vary in their movements from shorter (2 km) to longer (25 km) distances. While this analysis clearly demonstrates certain movement corridor areas with higher concentrations of migrating deer, with a larger dataset, local biologists predict high-use winter ranges throughout valley bottoms in Mendocino National Forest, and possible high fidelity to summer range sites for individual deer in the area. Numerous black-tailed deer papers have been published as a result of this data collection effort (Casady and Allen 2013; Forrester et al. 2015; Lounsberry et al. 2015; Marescot et al. 2015; Bose et al. 2017; Bose et al. 2018; Forrester and Wittmer 2019).GPS locations were fixed between 1-13 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual deer is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of winter ranges and the identification and prioritization of migration corridors. Brownian Bridge Movement Models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 50 migrating deer, including 125 migration sequences, location, date, time, and average location error as inputs in Migration Mapper. The dataset was divided into four overlapping subgroups (i.e., north, central, south, east) and analyzed separately, but visualized together as a final product. The average migration time and average migration distance for deer was 7.43 days and 11.22 km, respectively. Corridors and stopovers were prioritized based on the number of animals moving through a particular area. Corridors were best visualized using a 200 m buffer around the lines due to large Brownian motion variance parameters per sequence. Winter ranges and stopovers were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours and a fixed motion variance of 400. Winter range analyses were based on data from 45 individual deer and 65 wintering sequences. Winter range designations for this herd may expand with a larger sample, filling in some of the gaps between winter range polygons in the map. Large water bodies were clipped from the final outputs.Corridors are visualized based on deer use per cell, with greater than or equal to 1 deer, greater than or equal to 3 deer (10% of