CHAD BISHOP University of Montana http://www.cfc.umt.edu/wbio/ One - PowerPoint PPT Presentation

CHAD ¡BISHOP University ¡of ¡Montana

http://www.cfc.umt.edu/wbio/

¨ One of three Programs of National Distinction at UM ¡ Consistently ranked as one of the top Wildlife programs in the nation ¨ 22 Faculty, 335 Undergraduate Students, and 47 Graduate Students ¨ 2/3 of Students from Out-of-State ¨ During past 2 years, faculty secured 6 multimillion dollar grants, 27 $100k - $1 M grants, and numerous small grants totaling $2.5 M ¨ Collaborating with >100 partner entities ¨ 2 Endowed Chairs

Service through Leadership Education Research

¨ Preservation of intact habitats and functioning ecosystems is essential if we are to conserve declining species and maintain healthy populations of other species ¨ Information is needed to guide future landscape management decisions for wildlife in light of development pressure, noxious weeds, climate change, water depletions, increased recreational use of public lands, disease, among others

¨ Unlike any time in the past, we now have the technological capacity to: ¡ collect detailed data on how animals use the landscape ¡ develop accurate vegetation and habitat data layers from satellite imagery ¨ This technology can help us learn more about wildlife populations at broad spatial scales than ever before and to forecast future population changes

¨ Wildlife data are collected by a host of state wildlife agencies, federal agencies, Universities, and NGOs ¨ There is a distinct need for transboundary, synthetic analyses of wildlife data

¨ UM can serve as a highly capable and unbiased bridge in facilitating synthetic data analyses among multiple entities ¨ Elements of successful integrated analysis collaborations: ¡ the intellectual data rights of contributors are recognized and valued ¡ contributors are brought together as collaborators to inform analyses ¡ statutory and other limitations which may restrict data use and distribution are respected

¨ Wildlife Biology at UM seeks to integrate wildlife population ecology, landscape ecology, and conservation genetics Remotely Sensed Data Partner-based Population Landscape Conservation Modeling Connectivity Strategies Conservation Genetics

Sage Grouse Initiative – Dave Naugle Wildlife conservation through sustainable ranching 1. Remove habitat-fragmenting threats to grouse while improving ranch sustainability 2. Implement enough of the right conservation in the right places to benefit populations 3. Assess effectiveness, quantify benefits and adapt program delivery

Improved rangeland health Conservation easements 1,129 ranchers enrolled, 6,000 mi 2 conserved in 5 years Equivalent to 2 Yellowstone National Parks Marked or moved ‘high risk’ fence Removed encroached conifer

• $211 million in NRCS base funding through 2018 • Four themes – State-based plans – Compliments partners – 4-year planning horizon – Achieves milestones

Donnelly ¡et ¡al. ¡ ¡ -­‑ Public ¡lands ¡and ¡private ¡waters: ¡scarce ¡mesic ¡resources ¡ structure ¡land ¡tenure ¡and ¡sage-­‑grouse ¡distributions ¡– Ecosphere ¡ ¡2016

Victoria Dreitz Mission to promote informed decision making based on ecological research – the collection, synthesis, and dissemination of knowledge for birds and their ecosystems – for conservation of natural resources . Objectives: 1. to conduct ecological research 2. to provide educational opportunities for students 3. to identify strategies for conservation delivery 4. and to assist with technical needs in using birds to make land management and policy decisions.

Elk ¡Population ¡Dynamics 1. Collect adult female elk survival and calf recruitment data across the Northwestern USA 2. Western Elk Research Collaborative (WERC) - ID, MT, WY, OR, CO, WA, UT 4. USGS – Coop unit funding key 5. Across our 45 study populations, we had data from 2746 individual adult female elk representing 9409 elk-years, with 1058 mortalities.

Elk ¡Population ¡Dynamics 1. Juvenile recruitment key to ungulate population dynamics 2. WERC lead 3. Calf:cow ratio - 23 years 1989 - 2012 - 101 elk management units - 1,512 unit-years 4. Climate (PRISM) and NDVI (growing season conditions)

Mule Deer and Sage-grouse Population Dynamics 1. Bayesian Integrated Population Models 2. Allow prediction in time and space with missing data 3. Provide a framework for wildlife managers to incorporate effects of variation in climate (PRISM) and NDVI (MODIS) on population management

Global ¡population ¡dynamics ¡and ¡climate ¡change Question: ¡ How ¡does ¡climatic ¡influence ¡vary ¡ across ¡a ¡species’ ¡range ¡and ¡globally ¡after ¡ accounting ¡for ¡biotic ¡interactions? Approach: ¡ Global ¡Population ¡Dynamics ¡Approach ¡ (Post ¡ et ¡al. ¡2009, ¡Bioscience) Methods: • Niche ¡Modeling ¡with ¡climate, ¡landuse, ¡fire • Population ¡dynamics ¡models ¡using ¡time ¡series ¡ models ¡with ¡climate ¡, ¡vegetation ¡indices, ¡biotic ¡ interactions • Link ¡population ¡and ¡niche ¡models ¡at ¡species ¡range ¡ scale

¨ Non-invasive Genetic Sampling ¨ eDNA ¨ Genomics

¨ Generalized for multiple species ¨ Customized for individual users ¨ User-Friendly Interface ¨ Supported by sophisticated, most up- to-date quantitative models available

THE OLD WAY… THE MODERN WAY.. ¨ Many standalone ¨ R leverages tools to programs that perform close the loop one task ¡ Repeatable and maintains data integrity ¡ Difficult to repeat a process and error prone

¨ Goals of PopR ¡ Facilitate data transfer from data bases to analysis engines ¡ Integrate data from many sources including biological survey data, remoting sensing data and social surveys ¡ Bring state-of-the-art statistical analysis to the fingertips of biologists ¡ Automate analysis ¡ Standardize reporting ¡ Catalog results for future use

¨ UM is presently positioned to expand its capacity for serving the needs of wildlife agencies and NGOs ¨ We propose a more direct integration of our ongoing efforts and collaborative partnerships ¨ What is needed? ¡ Dedicated servers to support ‘Big Data’ analyses and to increase capacity to work with partner agencies ¡ Additional Post-doc and Graduate Student support to accomplish analytical tasks tied to large collaborative efforts ¡ Faculty salary support to allow time toward these large, collaborative efforts ¡ Support to bring together collaborators

¨ Recognizing that implications of our scientific findings and proposed conservation actions affect others ¨ Valuing effective communication and learning from others ¨ Placing a high priority on building relationships and connections ¨ Committing to and finding a common purpose with others

¨ Our best conservation solutions are those that are effective and accepted by the very people who are impacted