Webinar #4 in WREN Environmental Webinar Series
August 27, 2015
Summary
Please join the webinar scheduled for Thursday August 27, 2015 from 3 to 4:30 pm UTC (8:00 am PT/11:00 am ET) developed as part of International Energy Agency’s Wind Task 34 (also known as WREN - Working Together to Resolve Environmental Effects of Wind Energy). This webinar series supports WREN’s goal to facilitate international collaboration that advances global understanding of environmental effects of offshore and land-based wind energy development. The topic of this webinar is Avian Sensitivity Mapping and Wind Energy Projects as presented by Julia Robinson Willmott of Normandeau Associates, Sinead Cummins of BirdWatch Ireland, and Roel May of the Norwegian Institute for Nature Research (NINA). The speakers will present on tools they have developed to assess the potential vulnerability of birds to wind energy development (WREN Introductory Slides).
Julia Robinson Willmott is a core member of Normandeau’s avian team, working directly with the technology team to design, test, and deploy innovative technology systems for remote monitoring of wildlife. She has over 20 years of experience designing, managing, and conducting ornithological and ecological projects in 23 countries. Julia’s utility and wildlife experience includes avian risk assessment and impact studies, literature review, field studies, data analysis and interpretation, transmission line impacts, and guideline documents. She is also skilled in field observation and visual/acoustic identification of birds, avian blood sampling and microscope surveys, avian surveys and data analysis, population monitoring, and ecological risk analysis.
Bird Sensitivity Mapping for Wind Energy Developments in Ireland
Sinead Cummins has worked at BirdWatch Ireland for over 12 years initially as a Senior Conservation Officer and since 2012, as Species Policy Officer. Sinéad led on the initial scoping study for the Bird Sensitivity Mapping Tool for Wind Energy Developments in the Republic of Ireland in 2010, and retained an active role in the Bird Sensitivity Mapping Tool project development engaging with many stakeholders in the Renewable Energy sector in Ireland over the past 5 years.
Avian Sensitivity Mapping and Wind Energy: GIS-based wind turbine micro-siting tool
Roel May is a Senior Research Scientist at the Norwegian Institute for Nature Research (NINA). His current research interest lies in the interface between science and conservation, and centers on impacts of renewable energy on wildlife and on spatial ecology. He has coauthored 24 peer-reviewed journal articles and over 60 technical reports. He received his Master of Science degree in Forestry/Ecology at the Wageningen University, the Netherlands, in 1996. He received his PhD degree on "Spatial Ecology in Wolverines in Scandinavia" at the Norwegian University of Science and Technology (NTNU) and NINA in 2007. He has worked in the Netherlands, Scotland and Norway.
Questions and Answers
Questions for: Julia Willmott
Is global population size (GPS) intrinsically the net result of Threat (the smaller GPS, the higher TR) and Adult Survival (the lower AS, the higher GPS)? So can GPS serve as the sole factor? And the Atlantic Outer Continental Shelf (AOCS) on the map seemed to be limited to the American east coast. How about the European / African west coast? Do you have to include global sub-populations (e.g. like American and European Eel as in Global Eel population)?
You are right that there is often a correlation between population size and threat ranking with Bermuda Petrel being an extreme case in point. However, the threat ranking also considers the status within the US regardless of the global population size. You could have a species that has healthy populations worldwide and is listed as threatened or endangered in the US. This usually relates to some of the population belonging to a subspecies. We did consider some recognized subspecies; the rufa red knot for example. In this case the threat ranking is raised by the USFWS listing this subspecies as threatened. Adult survival for red knot on the other hand, is not high-scoring, so for such instances we couldn’t exclusively use the global population size. The geographic scope of the AOCS is the politically recognized continental shelf of the USA. There are several planning areas for the U.S to use for offshore energy and those areas defined our scope. Though taking on more species and a larger area would be interesting.
Was there any investigation into comparative impacts or risk levels from other stressors (not wind turbines) to the species examined? If so, how do these stressors compare in significance to the impacts from wind?
No there wasn’t. We had a fixed scope, but expanding to consider other stressors would be a useful thing to do. Some of the boat and helicopter disturbance data came from offshore oil platforms... and from biological survey teams! That being said, metrics that we calculated for population sensitivity are not specific to wind farms and could applied to other forms of disturbance. Some of the displacement sensitivity metrics might be useful in other applications as well.
Are there mapping elements related to the report?
Great question, because it is something that we really want to do but haven’t had the funding to do it. Using the USGS data (BOEM compendiums for seabirds and shorebirds), modeling species’ distributions (Generalized Additive Models), and relating those data with our relative vulnerability indices could show hotspots where species could be the most vulnerable, and would be relatively easy to do. We could also apply this approach to the Gulf of Mexico, where we would need to update some of the population sensitivity metrics... lots of good ideas but we’d have to try to find funding to do it.
Ecologically sensitive areas also tend to be ideal for (Offshore) Wind Farms. Furthermore, in the many EIAs there is nothing like the Best Ecological Alternative (BEA). How do the presenters feel about designing preventive and mitigating measures in lay-out and (technical) design of Wind Farms based on the existing knowledge rather than wait for the final conclusive scientific proof or the perfect model? By the way, often Wind Farms are necessary to be able to research for the scientific proof and validate the model(s). In other words how could existing knowledge support decision making for the BEA of wind farms (OWFs included)?
These are true statements. Our sensitivity method is one way to support decision making using existing knowledge, which was the reason BOEM wanted such an index. Taking this to the next level as suggested in the previous question could be a consideration.
Questions for: Sinead Cummins
I wonder whether external consultation is no more than an averaged subjectivity of the scoring. It does not provide a higher degree of evidence, rather an averaged expert opinion with higher and lower limits. How do you consider this?
In responding to this question, it is probably useful to provide some detail, by way of background, on the Irish sensitivity mapping tool for wind energy developments which was finalized in March 2015. The process by which bird species were to be considered for inclusion in the tool involved the calculation of a Species Sensitivity Score (SSS). This was calculated by putting each species through a ‘Species Sensitivity Model’ based on a number of factors considered to make a species vulnerable to wind farm infrastructure. These included the risk of birds colliding with turbines, being displaced by the wind farm and associated infrastructure, being subject to barriers to movement or migration or being affected by habitat loss. Each factor was scored on a scale of 0 to 4, with higher scores increasing the ultimate vulnerability score.
As outlined in the webinar, an Internal BirdWatch Ireland Species Expert Group assessed the scores by consulting with external expertise and published evidence. In total, 22 bird species were selected for inclusion. Research on the potential impacts of windfarms on birds and other wildlife is a relatively recent albeit expanding field of research, with the first windfarm in Ireland built in 1992. Certain groups of species, such as geese and raptors, have been the subject of numerous wind farm related studies while information on other potentially vulnerable species may be lacking. In addition to the bulk collection of data, novel means of monitoring are increasingly utilized. These include radar tracking of bird migratory routes and flight heights (Desholm 2006; Hüppop et al. 2006), night vision and thermal imaging (Everaert & Stienen 2007; Krijgsveld et al. 2009) and GPS tagging and tracking of flock location and movements (Nygård et al. 2010). The cost of such measures, however, regularly limits their adoption.
Decision-making in relation to flight vulnerability attributes of species for example and whether they are relevant/important with regards wind energy developments can be more subjective in nature, depending on the information available. That is why it was so important to engage with not just an internal expert group, but to go through the process of wider consultation. While recognizing the caveats of this approach and the existence of data gaps, this map is considered an iterative tool and is using the best available information for vulnerability at this time. Only existing data were used to inform this tool, however, it is envisaged that the map will evolve as new data become available. As new research is published on how species are/can be affected by wind energy developments the species vulnerability scores can be adjusted accordingly. Similarly, a change in the conservation status of a species would result in a corresponding change in the species’ vulnerability score.
Therefore the rationale behind this external consultation phase was to facilitate a wider input from a variety of experts into the scoring process and also to receive information on studies in the grey literature or those as yet unpublished. A similar exercise was employed in relation to North Sea wind energy developments (Garthe & Hüppop 2004).
Ecologically sensitive areas also tend to be ideal for (Offshore) Wind Farms. Furthermore, in the many EIAs there is nothing like the Best Ecological Alternative (BEA). How do the presenters feel about designing preventive and mitigating measures in lay-out and (technical) design of Wind Farms based on the existing knowledge rather than wait for the final conclusive scientific proof or the perfect model? By the way, often Wind Farms are necessary to be able to research for the scientific proof and validate the model(s). In other words how could existing knowledge support decision making for the BEA of wind farms (OWFs included)?
The Irish example, as presented in the webinar, is very much using existing knowledge to help inform the final mapping tool, albeit it is restricted to land and not sea. Obviously in the offshore environment, it is more difficult and costly to gather the data necessary to support and produce a similar mapping tool, given the obvious data gaps that exist. However, with advances in technology, it should now be possible to do so (albeit a more expensive process as collection of tracking information for seabirds, for example, is not without its associated costs) as highlighted by Julia’s presentation.
Questions for: Roel May
Why not test the model with the existing information on fatalities from Smøla?
So far we have only worked on the development of the tool, but are considering doing this. However, the island of Smøla where the wind-power plant is located is relatively flat. Any major orographic effects can therefore not be expected. Likely any ground-truthing will consist of a combination of comparing modelled avian risk areas with locations of recorded fatalities, and correlating relocations of GPS-equipped white-tailed eagles with avian risk areas not only on Smøla but also on the neighboring island of Hitra which also has a wind-power plant and is much more rugged in nature.
Do you also work on Offshore Wind Farm siting and risk assessment?
We have so far focused on micro-siting for onshore situations. However we already see that this model could be extended also to include offshore phenomena generating updrafts or other avian risk areas.
Could terrestrial structures be translated into OWF geometric structures (like corridors and wind turbines)?
I am unsure whether I understand the question correctly. The model assesses potential avian risk sites given the surrounding landscape (topography, vegetation etc.) in a pre-construction situation. Based on its outcomes, coupled with optimization of wind capture, the result is a specific design of a wind farm. What the question seems to suggest is whether existing offshore wind farms could be interpreted as a pseudo-topography which may affect e.g. updrafts?! Interesting question (if this was the meaning of the question) for which I have no answer.
Ecologically sensitive areas also tend to be ideal for (Offshore) Wind Farms. Furthermore, in the many EIAs there is nothing like the Best Ecological Alternative (BEA). How do the presenters feel about designing preventive and mitigating measures in lay-out and (technical) design of Wind Farms based on the existing knowledge rather than wait for the final conclusive scientific proof or the perfect model? By the way, often Wind Farms are necessary to be able to research for the scientific proof and validate the model(s). In other words how could existing knowledge support decision making for the BEA of wind farms (OWFs included)?
This question relates very much to the current practice of wind farm development. I think that following the prioritized Mitigation Hierarchy is crucial to reach the least impact on the environment per kWh. This means that pre-construction foremost sensitive areas should be avoided, thereafter impacts minimized through micro-siting. Following the precautionary principle would thereby mean that lack of knowledge or uncertainty about the exact impact should benefit the environment. However this also means that appropriate mechanisms be put in place to reach consensus on balancing energy production with environmental concerns. How can we best to reach “no-net-loss”? Impact assessments executed on a purely project-by-project basis however do not enable proper evaluation of impacts at larger regional scales and over longer timeframes.
A video recording of the webinar has been posted below:
Past Events
- WREN Webinar #3: Understanding Avian Collision Rate Modeling and Discussing what this Means in a Population Context at Land-Based and Offshore Windfarms, Online, 2 April 2015 15:00-16:30 UTC
- WREN Webinar #2: Attraction and Interaction of Marine Mammals and Seabirds to Offshore Wind Farms Webinar, Online, 9 December 2014 16:00-17:30 UTC
- WREN Webinar #1: Bats and Wind Energy Webinar, Online, 3 September 2014 15:30-16:30 UTC
Comments
(No subject)