Making better decisions about where to put stuff

David L Miller
NOAA Northeast Fisheries Science Center, Woods Hole, MA
converged.yt

NEFSC Webinar on Cetacean Spatial Analysis
8 February 2016

Disclaimer: this talk is about birds

Background

RI wanted to know what was in it’s waters
- Offshore energy development (windfarms)
- Block Island development
- “Area of mutual interest” w/ MA
OSAMP
- Ocean Special Area Management Plan
- NC/MA/NJ etc all have one
Basic question
- “where should we build a windfarm?”

A windfarm

The Danish Vindmølleindustrien Middelgrunden wind farm of the coast of Copenhagen CC BY-NC 2.0

Aerial line transect surveys

More species, more models
(More problems)

Density surface models

Modelling approach as SWFSC folks showed
Relate abundance or presence to smooth functions of covariates
Includes detectability, availability corrections
Produces spatially-explicit abundance estimates

Some uncertainty (CV)

Okay, so what do we do?

Combining information

Ecology and management are multidimensional
Not usually just one species to deal with
How can we combine information on multiple species?
Really want one number or one map to show folks

Spatial prioritisation

“Where can we put stuff?”
Take grid cells, say which are of “high value”
Use model output (predictions) get “value” of areas
Many options (Wintle, 2008 review)

Zonation

Put (prediction) maps together
Rank proportion of species lost per cell
- Maximise biodiversity rank
- Can weight by “conservation value”
- Can weight for connectivity
Software from Helsinki U (Moilenen et al, 2005)
http://cbig.it.helsinki.fi/software/zonation/
Maps don’t have to use the same model “types”

Figure 1 from Lehtomäki and Moilanen (2013) CC-BY 3.0

Zonation can answer the question:
“where should we do this?”
rather than just
“what happens if we do this here?”

Prioritization (weighted)

NOAA map 13205

http://www.charts.noaa.gov/OnLineViewer/13205.shtml

Winiarski et al (2012)

Shortcomings

If your model is garbage, your prioritization will be too
Abundance gives the most information
- Detection and availability corrected
Seasonal variation
No dynamics
Southern hemisphere competitor
- MARXAN: http://www.uq.edu.au/marxan/index.html
- Listed on the NOAA Digital Coast tools site

Acknowledgements

University of Rhode Island: Kris Winiarski (now UMass), Peter Paton, Scott McWilliams
Work was funded by grants from the US Department of Energy, the American Recovery and Reinvestment Act, and the State of Rhode Island

References

Lehtomäki, J and A Moilanen (2013). Methods and workflow for spatial conservation prioritization using Zonation. Environmental Modelling & Software 47, 128-137. http://dx.doi.org/10.1016/j.envsoft.2013.05.001.
Miller, DL, ML Burt, EA Rexstad and L Thomas (2013). Spatial Models for Distance Sampling Data: Recent Developments and Future Directions. Methods in Ecology and Evolution 4(11) : 1001–1010.
Moilanen, A, AMA Franco, RI Early, R Fox, B Wintle, CD Thomas (2005). Prioritizing multiple-use landscapes for conservation: methods for large multi-species planning problems. Proc. R. Soc. B 272 1885-1891; DOI: 10.1098/rspb.2005.3164.

References (continued)

Winiarski, KJ, DL Miller, PWC Paton, & SR McWilliams (2014). A spatial conservation prioritization approach for protecting marine birds given proposed offshore wind energy development. Biological Conservation, 169(C), 79–88. http://doi.org/10.1016/j.biocon.2013.11.004 http://converged.yt/papers/Zonation_ms_081613.pdf
Wintle, B.A. (2008). A review of biodiversity investment prioritization tools. A report to the Biodiversity Expert Working Group toward the development of the Investment Framework for Environmental Resources. http://www.inffer.com.au/wp-content/uploads/2011/06/biod_tools.pdf.