Balancing Airport Stormwater and Bird Hazard Management (2015)

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4C H A P T E R 2 Research Findings The research team reviewed documents on bird strike risk and stormwater BMP design and used factors identified in the research and from the research team’s experience to develop a draft Bird Strike Risk Analysis and Stormwater Management Decision Tool. As a result of the research, feedback from the case studies, project panel teleconference, and panel meeting, the research team identified the research findings described in the following paragraphs. Conclusions and recommendations from these findings are included in Chapter 3. Scope and Applicability Tool Use at Airports with Limited Data Because the tool provides a risk analysis based on bird haz- ard data from an airport, and the risk and mitigation options are species-dependent, airports without significant bird strike data or bird observation records may find the tool less pre- dictive. In addition, airports experiencing fewer operations and reporting few strikes, and airports without concerns about water as a bird attractant may find this tool less pre- dictive. Some airports may not possess the appropriate staff, knowledge, or funding to evaluate bird strike risk in regard to stormwater management. The tool is most effective when used by a team of airport personnel and/or consultants, ideally con- sisting of an airport engineer, airport wildlife biologist, and airport operations specialist. This may result in limited use of the tool among airports lacking significant bird hazard data, extensive stormwater management systems, or a large staff. The research team considered this limitation and identified ways to make the tool more functional to airports with these restrictions. To begin, the user must select species data and input strike data. If the user does not select a species of concern or does not enter any strike data for the airport, the user cannot proceed. The tool provides ranges to increase options when estimating factors such as distance to nearest water body, number of species observations, number of strikes, etc. While the tool provides a more accurate risk analysis when actual bird strike data from an airport are entered, these additional tool functions will expand the use of the tool to include air- ports that have limited bird strike data. Although users may select “Other” for bird species data, this can reduce the accu- racy of the risk assessment. The research team will emphasize that the quality of results depends on the quality of inputs in the guidance contained within the tool. It will be the respon- sibility of the user to input the most accurate and specific data available. Weighting Factors Weighting factors are one aspect of a risk assessment that can increase or decrease the influence a risk factor has on the math calculations. Originally, weighting factors ranged from 0 to 10 and the research team provided default weighting fac- tors for each risk factor in the risk matrix. For example, the “hazard ranking” of each species (or species selection) factor was given a default weighting factor of 10, while the “history of observations” factor was given a weighting factor of 2 and the “history of strikes” factor was given a weighting factor of 1. The rationale for the weighting of the species selection factor was that it is the most important factor when deter- mining bird strike risk, and, therefore, it was given the high- est weight. Based on research team experience with wildlife management, species selection was estimated to be 5 times as influential as the “history of observations” factor, therefore “history of observations” was assigned a default weighting factor of 2. The “history of observations” data is important, although it can be highly variable, and thus it was assigned a reduced weight. Species identification and corresponding hazard score was estimated to be 10 times as influential to risk as the “history of strikes” factor, therefore “history of strikes” was assigned a default weighting factor of 1. Although the Findings and Applications

5 strike data can be revealing, the shortage of species identi- fications in the database and the general absence of data for many airports can provide misleading information. The goal was to make the species identification and the corresponding relative hazard scores from DeVault et al. (2011) the most significant wildlife risk factor. Through discussions with the panel, the research team decided to change the approach for assigning importance to the species relative hazard score. As opposed to using the experience-based factor of 10, the tool now calculates an average of the severity factors other than hazard score, and then this score is averaged with the hazard score to estimate the overall severity. The weighting factors of 2 and 1 were retained to differentiate the relative importance of likelihood factors in estimation of the overall likelihood. The tool also originally allowed users to define additional weighting factors to be applied on top of the default weight- ing values to further adjust the importance of each risk fac- tor to severity or likelihood. Through discussions amongst the research team and with the project panel, the research team decided to replace this approach with confidence lev- els. Confidence levels allow users to adjust the relative influ- ence that individual wildlife risk factors have on the overall risk if they have particularly low confidence in the quality of a particular type of wildlife data. For example, if the user indicates low confidence in the quality or completeness of their strike data, then the history of strikes input will have less significance in determining the overall risk. To simplify user input, the user will simply select “High” or “Low” confidence, and factors that are associated with “Low” confidence will have their weighting values reduced by one-half compared to default weighting values. Factors with “High” confidence will retain the non-adjusted default weighting values. If the user has equal confidence in the quality of strike data, history (frequency) of observations, and proximity of bird sightings, they may select equal weighting for all three and keep the default weighting as originally designed. This approach sim- plifies a difficult concept for users to understand and allows the overall risk to be tailored to airport-specific data quality. Other Wildlife Hazards and Attractants The scope of this project was to develop a tool address- ing bird strike risk associated with stormwater, and explicitly excluded other wildlife (mammals and herpetofauna) and attractants not related to stormwater. This clearly represents only one component of wildlife hazards at an airport and, as such, the tool will not be able to provide an airport with an overall wildlife hazard risk assessment. While the research team recognizes the benefit of developing a risk assessment tool that addresses other wildlife species and non-stormwater related hazards, those are outside of the scope and budget of the current project. The research team recommends that these species and their attractants be further characterized as part of a separate research effort. Therefore, the species that may be analyzed in the tool are limited in accordance with the project scope. The research team will indicate in the guidance that the risk analysis is specific to water-dependent bird species and does not quantify all wildlife hazard risks or attractants. Assessment of Overall Risk The tool is designed to assess the wildlife attractant risk for bird species individually and does not provide a cumula- tive assessment of risk for all bird species of concern. The research team considered developing a calculation of cumu- lative risk, but determined that an overall assessment could prove more complicated than beneficial. If cumulative risk was calculated based on the average risk for all species con- sidered, high risk for an individual species might be masked by low risk for multiple other species or vice versa, potentially giving the user a false sense of risk. Additionally, mitigation measures are species-specific, and both risk and mitigation should be considered by airports on a species-specific basis. The research team intends that airport staff mitigate their stormwater designs based on their riskiest species. Species Definition and Birds Not Affected by Stormwater The initial list of species included in the tool was based on a list of 77 wildlife species gathered by DeVault et al. (2011) based on national wildlife strike data. The species listed are the most frequently reported wildlife species to cause damag- ing strikes to aircraft and/or cause a negative effect on flights (aka “adverse effect” strikes) from 1990 to 2009; however, not all of these species are birds or are attracted to stormwater BMPs. Per the scope, the risk assessment produced by the tool is focused on the attraction of birds to stormwater BMPs, and the tool allows users to mitigate for this risk by modifying the design of potential stormwater BMPs. At the case study visit, PMP staff identified the turkey vulture as a species of concern for their airport to be analyzed in the tool. Although turkey vultures are not attracted to stormwater, the inclusion of this and other non-water-dependent species in the tool suggested that changes to the stormwater BMP design would affect the species-specific bird strike risk, when this is not scientifically accurate. The initial and residual risks produced by the tool integrate species and stormwater characteristics. They cannot be analyzed independently of one another. As a result, the list of species included in the tool was modified to include only water-dependent birds that pose an aircraft strike risk (i.e., included on the list of 77 hazardous

6wildlife species). This will prevent users from selecting a bird not affected by stormwater and attempting to reduce bird strike risk through stormwater management decisions. The research team recognizes that many users may not be aware of which species are attracted to water and may be frustrated when they see that their species of concern is not on the list. See Appendix G for a list of species included in the tool with their associated hazard rankings. Cost and Other Non-Avian Decision Factors The research team was tasked with identifying other fac- tors, beyond bird strike risk, that may affect stormwater man- agement decisions at airports. The research team referred to their own stormwater management experience to develop a list of considerations that typically play a role in selecting an airport-specific stormwater management approach: • Construction cost • Operations and maintenance requirements • Performance and regulatory acceptance • Constructability • Footprint and space requirements In developing the list of these non-avian factors, the research team recognized that many of these factors are highly specific to each airport, the particular site selected for the BMP, and the associated regulatory requirements. The importance of these factors compared to each other and compared to the level of bird strike risk may vary depending on an airport’s resources, priorities, and other unique perspectives. Although the scope and budget of this project did not allow for the tool to provide the user with an assessment of these factors, it was important that the tool facilitate the user being able to perform these assessments based on outside resources. Thus, a BMP alter- natives analysis worksheet was incorporated into the tool to allow the user to document these assessments for each BMP alternative, rank the importance of the factors based on the air- port’s specific priorities, and select a BMP alternative that best meets the airport’s stormwater management objectives. Microsoft Excel 2010 The Bird Strike Risk Analysis and Stormwater Manage- ment Decision Tool is designed to allow users to enter and/ or read local information (e.g., FAA strike data, local storm- water BMPs) as an Excel spreadsheet does. Tool users are not expected to see or modify the software, and they will not have to purchase expensive software to use the application (other than basic Microsoft Office-type software). The research team was tasked with making the tool available to airport personnel with varying degrees of background in wildlife hazards and risk analysis, thus the Excel platform was determined to be the most appropriate for this project. Through the development of the tool, the research team decided to use dropdown selection lists in Excel to simplify input selection. The use of these particular dropdown lists is a feature of Microsoft Excel 2010 that does not convert to ear- lier versions of Microsoft Excel. The research team weighed the benefits enabled by the drop-down lists (streamlining inputs, reducing confusion, and prohibiting inappropriate inputs) with the potential limitation of the tool for users with older versions of Microsoft Excel. The research team deter- mined that most airports are likely currently using Microsoft Office 2010 or will be upgrading in the near future. Therefore, Excel 2010 is required to operate the tool. Bird Strike Risk Incorporating Airport-specific Strike Data The severity risk factors include the relative hazard score of an individual species, which was derived based on the num- ber of adverse effect strikes reported for that species within the airport environment (below 500 feet above ground level) (DeVault et al. 2011). The percentage of reported strike his- tory for water-dependent birds for a specific airport associ- ated with a specific species is included as a likelihood factor for each species and is titled, “Percentage of Total Airport Bird Strikes Associated with Species.” The “Percentage of Total Airport Bird Strikes Associated with Species” risk factor is a calculation of total strikes reported for that species divided by the total strikes reported for all water-dependent birds at the airport. Levels or “banding” is a common SMS risk assessment method and the research team developed five levels for each risk factor outlined in the risk matrix. The banding categories describing the “Percentage of Total Airport Bird Strikes Asso- ciated with Species” risk factor are listed in Table 2-1. Strikes that are not linked to a specific aircraft (e.g., car- cass recoveries) are often reported to the FAA Wildlife Strike Database and should be included in an airport’s strike history Likelihood Percentage of Total Airport Bird Strikes Associated with Species Frequent >75 Probable 50–75 Remote 10 to <50 Extremely Remote 5 to <10 Improbable <5 Table 2-1. Likelihood levels for percentage of total airport bird strikes associated with species.

7 when calculating the rate of overall strikes. Unfortunately, species data may be absent when only partial carcasses are recovered. If species data is known and reported, it is incor- porated into the above calculations. The comparison of total bird strikes per operation at an airport compared with the national average is also included as a likelihood factor titled, “History of Total Bird Strikes per Operations Compared to National Average.” This risk fac- tor is a calculation of the total strikes reported for all water- dependent birds at the airport divided by the total operations for the airport for the period of bird strike record compared with the national average airport strikes of water-dependent bird species per airport operation. The national averages were calculated using the number of strikes for water-dependent bird species per airport, from 1990 through 2012 (Dolbeer et al. 2013) and the total national aircraft operations for the same time period for airports with operations data reported in the FAA air traffic control database (ATADS 2014). The banding categories describing the “History of Total Bird Strikes per Operations Compared to National Average” likelihood factor are listed in Table 2-2. If the user’s airport has a strike rate within one standard deviation of the national average, the likelihood will be remote (Level 3) for this risk factor. If the user’s airport strike rate is greater than one stan- dard deviation from the national average, the likelihood will be either probable or frequent (Levels 4 or 5) for this risk fac- tor. If the user’s airport strike rate is less than one standard deviation from the national average, the likelihood will be either extremely remote or improbable (Levels 2 or 1) for this risk factor. Strikes that are not linked to a specific aircraft (e.g., car- cass recoveries) are often reported to the FAA Wildlife Strike Database and should be included in an airport’s strike history when calculating the rate of overall strikes. Unfortunately, species data may be absent when only partial carcasses are recovered. If species data is known and reported, it is incor- porated into the above calculations. For the two strike data factors, the user must enter the num- ber of strikes per species for each identified species of concern within a specified time period (e.g., 22 years or 5 years, etc.), the total strikes for other water-dependent bird species not identified as a species of concern, and the number of aircraft operations at the airport for the same time period. The tool will calculate the percentage of strikes associated with each species of concern at that airport for the “Percentage of Total Airport Bird Strikes Associated with Species” likelihood fac- tor, and the rate of strikes per operations to compare with the national average for the “History of Total Bird Strikes per Operations Compared to National Average” likelihood factor. Bird Strike Mitigation Measures The research team identified various mitigation measures that would reduce bird strike risk at an airport by managing the hazard itself. The SMS framework categorizes risk mitiga- tion measures by relative effectiveness at reducing risk. The research team decided to adopt the SMS framework or “Hier- archy of Controls” to reduce risk and organized the mitigation measures by each control. This is also a standard function of Failure Modes and Effects Analysis (FMEA) widely used in the safety profession to classify the effectiveness of controls (ISO 2009). The SMS Hierarchy of Controls or “defense in depth model” implies that additional levels of mitigation equate to an increase in risk reduction. However, there appears to be an intrinsic diminishing return on risk reduction with implementation of additional mitigation measures. That is, the risk reduction associated with implementing five measures is not the same as five times the risk reduction associated with implement- ing one measure. The research team determined that the tool needed to address the concept of decreased risk with increased mitigation while incorporating diminishing returns from implementing numerous mitigations. In order to account for diminishing returns for implementation of multiple mitiga- tion measures, the tool quantifies a risk reduction for zero, one, or more than one measure in each category. The research team recognizes there may be some additional risk reduction with implementation of additional mitigations, but that it would be less effective and difficult to quantify that risk. The research team decided to include the mitigation mea- sures described in Table 2-3, which are grouped by SMS catego- ries (categories are listed in decreasing order of effectiveness). Likelihood Strike Rate for Species in Question Compared to National Average Frequent > 2 standard deviations above national average Probable Between 1 and 2 standard deviations above the national average Remote Within 1 standard deviation of the national average Extremely Remote Between 1 and 2 standard deviations below the national average Improbable < 2 standard deviations below national average Table 2-2. Likelihood definitions for history of total bird strikes per operations compared to national average.

8The research team included the “Elimination” and “Sub- stitution” Hierarchy of Control categories here as concep- tual SMS components, but does not include realistic wildlife mitigation options. The user will not be permitted to select a mitigation option under these categories. The user may select a mitigation option under Engineering, Warnings, and/or Administrative controls. The research team further assessed the effectiveness of each mitigation measure by allowing the user to indicate whether the measure is ongoing or only con- ducted when a species is observed, i.e., upon sighting. If the measure is “ongoing,” the user receives a greater risk reduction than if the measure only took place “upon sighting.” Safety science literature outlined in International Standards Orga- nization (ISO) 31010 (2009) suggests that the level of risk will depend on the adequacy and effectiveness of existing and proposed controls. Factors to consider when addressing the efficacy of controls include: current mitigation options avail- able, whether the existing mitigation options have proven to reduce risk to a more tolerable level, whether the mitigation options are being implemented in the manner intended, and whether they can be continuously evaluated for effectiveness if required. These factors can only be satisfied with confidence if there are proper documentation and assurance processes in place (e.g., annually auditing a wildlife hazard control pro- gram). The level of effectiveness for a particular control, or suite of related controls, may be expressed qualitatively, semi- quantitatively, or quantitatively. It is valuable to express and record a measure of risk control effectiveness so that judg- ments can be made on whether effort is best expended in improving a current mitigation or implementing a different mitigation option. Numeric Definition of Risk Originally, the tool was designed so that the higher the risk output number, the lower the risk. For example, a Canada goose was assigned a hazard ranking of 2, while a swallow was given a hazard ranking of 5. The justification being that the SMS Hierarchy of Control Mitigation Measures Elimination Not Applicable (N/A) Substitution Not Applicable (N/A) Engineering Falconry Harassment with dogs Toxicants; fumigants Anti-perching devices Capture and lethally take Lethal take (shooting) Install wire grid across/around BMP Alter mowing regime Capture (trap) and relocate Dead bird effigies Install bird balls Pyrotechnics Nest destruction Other Warnings Bioacoustics (distress calls) Propane cannons Vehicle harassment Visual deterrents Warnings from ATC Other Administrative Maintain a wildlife management log (data collection) Signage Wildlife hazard management training WHA/site visit Wildlife strike reporting Wildlife control permits Wildlife patrols/inspections Wildlife hazard management plan Other Table 2-3. Bird strike mitigation measures.

9 hazard rankings were akin to mitigation/management priori- ties. A goose is a higher priority than a swallow, so it would be assigned a lower number (higher priority). Similarly, a risk score less than 10 was high risk (or red) and a risk level higher than 21 indicated low risk (or green). Throughout the case studies, it was determined that this approach was counter- intuitive for the user. The research team reversed the order so that a higher number indicates greater risk. Stormwater BMPs Definition of Stormwater BMPs The Amplified Research Plan specified that the tool would allow the user to select the size and type of stormwater man- agement options. The research team determined that there are many different types of BMPs. Different names are often used for similar BMPs which could lead to confusion if the user does not see the specific name for their BMP on the list. Also, for some BMP types, there could be wide varia- tions in the characteristics of a specific BMP that may greatly influence its attractiveness to birds, making a risk assess- ment based on a specific BMP type difficult. For example, a swale can have steep slopes or gradual slopes, a dry deten- tion pond can have vegetation or not, or an infiltration basin can be close or far from another water body in the area or from the air operations area (AOA). All of these characteris- tics are associated with varying risk levels, regardless of the BMP type. Assigning default characteristics to BMPs by type would ignore the variations in design approaches between airports, and would also limit the tool to a set list of BMPs that may not consider emerging approaches for stormwater management. To account for site-specific design variations and main- tain flexibility for a variety of BMP types, the research team decided to define the BMPs by the basic characteristics affect- ing their attractiveness to birds, potentially shared by several types of BMPs. Guidance is provided in the tool to inform the user on the characteristics with the potential to affect wildlife attraction, and recommended values for these char- acteristics. A copy of a list of recommended wildlife-resistant plants developed by USDA is also included with the tool as an example to help the user identify plant species for their BMP, although users are encouraged to consult with local resources for additional species that may be appropriate within their geographic region. The research team identified the follow- ing BMP characteristics related to wildlife attraction, which will require determination by the user based on their selected existing BMP, proposed BMP, or potential BMP modification: • Water exposure – Is water fully enclosed? – Does the BMP draw down water within 48 hours? • BMP geometry – BMP—perimeter irregularity – BMP—apparent slope to water’s edge – Is the length:width ratio (aspect ratio of the BMP) 3:1 or greater? • BMP Location – BMP—proximity of water bodies (from each other) – Proximity of BMP to airport movement areas – Is there less than 12 acres of combined standing water (6,500 feet) of the AOA? • BMP Vegetation – BMP—percentage of stormwater vegetation coverage – Do all vegetation species appear on the USDA recom- mended plant list? – Is BMP vegetation a monoculture? BMPs with no open water surface, such as underground detention, initially were not addressed in the tool calculations. Although they have no associated wildlife risk, the research team decided to include them (i.e., is water fully enclosed?) so that they could be evaluated based on the non-wildlife factors and compared with open-water BMPs in the overall assessment. Quantification of Stormwater BMP Risk Factors The research team used published literature as a starting point for which factors could most influence the severity risk (i.e., increase the size or numbers of birds attracted to the air- port) of a bird/aircraft strike in regards to stormwater man- agement systems or BMPs. Blackwell et al. (2008) studied the avian use of stormwater management ponds considering the following factors: pond surface area, ratio of the area of open water to area of emergent and woody vegetation, perimeter irregularity, and geographic isolation. Previous research also suggested that species richness increases in wetland com- plexes versus large, isolated wetlands (Brown and Dinsmore 1986) and also increases in those wetlands with an intermediate level of emergent cover (Gibbs et al. 1991). The research team deduced that an increase in species richness leads to an increase in strike risk (i.e., increasing diversity could lead to an increase in the size or number of birds attracted to the airport). Further, Blackwell et al. (2008) found two of the 30 ponds they surveyed to have a particularly high average of individuals utilizing the pond. Mean usage throughout the other 28 ponds in the study was 2.0 individuals with a standard deviation of 1.6 individu- als. The two outlier ponds had an average usage of 23.3 indi- viduals and 15.3 individuals, respectively. These averages are substantially higher than the overall average of 2.0 individuals. These ponds had two characteristics that were interesting to note: (1) they had little to no emergent vegetation and (2) they had a high perimeter irregularity. These results seem reason- able as this mimics what our team’s biologists often observe in

10 the field. Therefore, an intermediate level of vegetation was determined to be the most attractive to birds (i.e., the most risky, Level 5, Appendix A, Table A-2), while 100% vegeta- tive cover with no open water exposed was the least attractive (Level 1). No vegetative cover (Level 2) was determined only slightly more attractive than 100% coverage. In addition, Blackwell et al. (2008) illustrate that the more irregularly shaped a pond is, the higher the probability of use by birds. Therefore, having a perimeter greater than that of a perfect circle is more attractive (i.e., risky) than having a pond perimeter equal to that of a perfect circle (Level 1). With regards to the tool, if the ratio value of the pond perim- eter to the perimeter of a circle of equal area is less than 1.1, that implies a negligible level of risk. Conversely if the ratio value is greater than 6.4, we consider that to be most risky (Level 5) for that factor. The other levels fall between those two extremes and are based on demonstrated probabilities of use. Blackwell et al. (2008) also found that the more geo- graphically isolated a stormwater pond is, the lower the prob- ability of use by birds. Thus, being part of a wetland complex is more attractive (risky) than being an isolated pond as previ- ously concluded by Brown and Dinsmore (1986). Therefore, the research team incorporated geographic isolation into the tool. The probability of use is near zero when the water bodies are 8 km or greater from one another (Blackwell et al. 2008), therefore 8 km (approximately 5 miles) was determined the minimum for the least risky level of that severity factor. All of the findings in Blackwell et al. (2008) mirror the anecdotal observations biologists continuously see in the field. Regulatory Requirements for BMPs One of the objectives of the tool is to provide guidance on BMP selection to meet regulations while minimizing wildlife attraction in accordance with FAA requirements. Although there are a variety of BMP types to choose from (e.g., infiltra- tion basin, vegetated swale, detention basin, etc.), many of the BMP types have similar design features with the potential to contribute to their attractiveness to wildlife (e.g., vegetation, open water surface, side slopes, etc.). The team turned to indus- try guidance with consideration for what characteristics make BMPs more or less attractive to wildlife. FAA AC 150/5200-33B Hazardous Wildlife Attractants On or Near Airports identifies specific BMP design criteria that minimize the attraction of wildlife. These criteria include the exposure of the water sur- face (FAA recommends a 48-hour drawdown time with no standing water between storm events, or use of physical cov- ers such as bird balls), vegetation (FAA recommends elimi- nating vegetation), and length-to-width or aspect ratio (FAA recommends a “narrow” shape). Additional resources were used to further define these criteria, including the Washing- ton DOT Aviation Stormwater Manual and USDA vegetation guidance. Rather than evaluate these regulatory requirements with banding levels (like the risk factors outlined above), they were incorporated into the tool as priority impact fac- tors, which are input as answers to yes or no questions. The risk calculations are affected negatively or positively based on whether the design criterion complies with industry recom- mendations for minimizing the attraction of wildlife (where a “Yes” response indicates a design characteristic that complies with industry recommendations and leads to reduced strike risk). The tool originally included a factor for the linearity of the water surface edge, in accordance with BMP guidance in FAA AC 150/5200-33B Hazardous Wildlife Attractants On or Near Airports. However the research team removed this factor after it was determined that it may be redundant with the perimeter irregularity factor from DeVault et al. (2011). Both factors are assumed to represent the similarity of an irregular BMP perim- eter to a natural water body, which has the potential to increase wildlife attraction. Vegetation Attractiveness There are additional variables including climate (Zhao et al. 2006) and immigration accessibility (Daniels 1992) that can affect species richness; however, there is a general positive correlation between animal diversity and plant diversity, par- ticularly when comparing homogeneous habitats (MacArthur 1964; Recher 1969). Studies have shown that aquatic macro- invertebrate communities are at least as rich and diverse in highway stormwater retention ponds as surrounding ponds, suggesting that stormwater ponds can contribute to biodiver- sity on a regional scale and provide crucial landscape connec- tivity (Le Viol et al. 2009). For example, mean nesting success for red-winged blackbirds in highway stormwater ponds was found to be comparable to nesting success recorded in natu- ral wetlands (Sparling et al. 2007). Therefore, just because a stormwater BMP is man-made, does not mean that it neces- sarily lacks in diversity. Decreasing plant diversity in an air- port’s BMP will help facilitate an overall sterile environment. In the tool, the user’s risk is affected by his or her response to the question, “Is BMP vegetation a monoculture?” Although not all vegetation has the same attractiveness to birds, existing research does not definitively indicate that one plant species is better over another in every situation, and species vary significantly across the United States. For example, research shows that certain kinds of grasses are more attractive than others to Canada geese (Washburn and Seamans 2012), but this same information is not available for all hazardous wildlife species. The USDA has developed a recommended plant list for use on airports. Although origi- nally intended for use in Ohio, it is rather all encompassing, applicable across the country, and provides a long list of veg- etation options. USDA/FAA generally prefers to have BMPs

11 Application It is the research team’s intent that the tool be integrated into the overall BMP planning and selection process to help bring bird strike risk considerations to the forefront amongst competing BMP selection factors. When applied during the BMP planning phase, the tool may be useful to explore the bird strike risk associated with conceptual BMP design char- acteristics, and allow for changes to reduce risk with minimal project cost impacts. The tool may also be used to demon- strate the potential bird strike risk impacts of particular BMP regulatory requirements, therefore facilitating discussion and negotiation with regulators during the planning process. Out- reach materials associated with the tool will include a broad overview of the conflict between stormwater design and wild- life hazard management at airports, and provide guidance on how and when to most effectively use the tool to reduce risk. The outreach material will also provide brief instructions on how the tool works (conceptually). Ultimately, these materials, along with the tool, should be incorporated into the storm- water design process. The tool allows for documentation of potentially acceptable alternatives, and will prompt airports to incorporate these other non-wildlife factors to allow the selec- tion of a preferable alternative that meets airport constraints and priorities. The research team anticipates that the following entities are stakeholders in this project: • Airport planning departments • Airport safety managers • Airport engineering departments • Airport operations staff • Environmental compliance staff • Airport facilities managers • FBOs/airport tenants • Planning, engineering, and environmental consultants work- ing for airports • Airport wildlife biologists or managers • Local government representatives that manage/operate airports • Local, state, and federal government agencies that regulate stormwater design criteria on airports The tool developed as a result of this research project will be introduced to the aforementioned stakeholders through out- reach materials, webinars, and presentations designed for air- port personnel, wildlife regulators, stormwater regulators, and/ or the general public given at aviation associated conferences and/or committee meetings. constructed containing those species and considers them to reduce wildlife attractiveness. Greater vegetative diversity increases the diversity in wild- life species; however, there is no mathematical equation that relates plant diversity directly to animal diversity as there are additional factors influencing diversity (Zhao et al. 2006; Daniels 1992). That is, biologists cannot say that an increase by a factor of 10 in plant diversity translates to an increase by a factor of 2 in animal diversity, etc. The research team is also concerned with an airport’s ability to correctly identify and count all of the species in the BMP. Thus, the USDA plant list is included in the tool to assist users with identification of species, provide the user with a way to assess their confidence in the identification of their plant species, and as a recom- mendation of plant options that are less attractive to wildlife. Proximity of BMP to Movement Areas/Other Water Bodies The tool includes separate inputs for the proximity of the BMP to airport movement areas (a likelihood factor) and the proximity of water bodies to each other (a severity factor). The “proximity of water bodies” severity factor includes any other water body, lake, ocean, natural wetland, etc., and is not exclusive to only stormwater BMPs or only other water bodies within the AOA. There is research that suggests that the closer water bodies are located to one another, the more attractive those water bodies become to birds. This may appear counterintuitive; however, as noted above, research shows that “wetland complexes” are more attractive than single water bodies to birds (Brown and Dinsmore 1986). Also as previously mentioned, Blackwell et al. (2008) found that if the water bodies are farther than 8 km apart, the level of attractiveness (due to proximity) drops dramatically. [We converted 8 km to miles (approximately 5 miles) and defined 5 miles as a “negligible” severity level (Level 1)]. At the CLE site visit, the airport suggested adding a tool parameter that would account for the synergistic effect of having attractants located on opposite sides of the airfield, allowing potential bird flight paths to conflict with aircraft flight patterns due to an increased likelihood of birds crossing the runway to travel from one BMP to another. The research team acknowledged that there isn’t an easily-defined param- eter that would accurately assess this situation, which is extremely complex and unpredictable in nature. The research team decided that the current tool parameters indirectly address this risk and that the addition of another parameter could make the tool overly complex. As such, the research team did not add this additional parameter to the tool.