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 Research Education

¨ Preservation of intact habitats and functioning

ecosystems is essential if we are to conserve declining species and maintain healthy populations

• f 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

• f 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

Partner-based Conservation Strategies Remotely Sensed Data Landscape Connectivity Conservation Genetics Population Modeling

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 Removed encroached conifer Conservation easements Marked or moved ‘high risk’ fence

1,129 ranchers enrolled, 6,000 mi2 conserved in 5 years Equivalent to 2 Yellowstone National Parks

• $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

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.

Victoria Dreitz

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…

¨ Many standalone

programs that perform

• ne task

¡ Difficult to repeat a

process and error prone

THE MODERN WAY..

¨ R leverages tools to

close the loop

¡ Repeatable and

maintains data integrity

¨ 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