Preparing for the Emerald Ash Borer in the City of Ithaca, NY

Transcription

1 Preparing for the Emerald Ash Borer in the City of Ithaca, NY Ryan T. Hicks, Master of Regional Planning Candidate 2012 College of Architecture, Art, and Planning Cornell University 12/9/2010 Prepared for the City of Ithaca, NY and CRP 5080 Introduction to Geographic Information Systems

2 1 Contents Contents... 1 Introduction... 2 Methods... 5 Maps and Analysis... 7 Conclusion/Findings Bibliography... 30

3 2 Introduction The Emerald Ash Borer (EAB), Agrilus planipennis, is an invasive green beetle native to Eastern Russia, Northern China, Japan and Korea. It is one of the most destructive pests ever to affect a particular type of tree, comparable in the scale of its damage to Dutch Elm Disease, or the Chestnut Blight, which caused massive extinction of the once widespread American Chestnut tree. While most pests and diseases affecting trees only affect a single species, the EAB poses a threat to the entire Fraxinus Genus. Since being accidentally introduced to North America in the 1990s, and its discovery in 2002 in Canton, Michigan (US Forest Service, 2010), it has spread to fourteen US states and parts of Canada, and is thought to have killed 50 to 100 million ash trees thus far (USDA Forest Service/Michigan State University/Purdue University/Ohio State University, 2010). Fig. 1 A Green Ash tree killed by the Emerald Ash Borer The adult EAB nibbles on ash foliage but causes little real damage. The immature larvae, however, feed on the inside of ash trees, damaging the xylem and phloem, which together are responsible for nutrient take-up and transfer in trees. After their discovery in Michigan, the EAB was subsequently found in Ohio (2003), Indiana (2004), Illinois and Maryland (2006), Pennsylvania and West Virginia (2007), Wisconsin, Missouri, and Virginia (2008), Minnesota, New York, and Kentucky (2009), and Tennessee (2010). It is thought to have cost various parties tens of millions of dollars in damage (USDA Forest Service/Michigan State University/Purdue University/Ohio State University, 2010) Recently, it has been reported as close to the City of Ithaca as Bath, NY, a mere 60 mile drive to the west. Since the City of Ithaca s most recent tree inventory shows 383 Ash trees, all of which are potentially susceptible to the Emerald Ash Borer, it may be necessary to pre-treat a number of Ashes in Ithaca s urban forest. Ithaca is commonly known as the Forest City, and the health and protection of its urban forest is one of the City s highest priorities. However, because pre-treating Ash trees to protect them from the EAB is expensive, it may be necessary to determine criteria for prioritizing trees, and to perform an analysis to help determine which trees should be the City s highest priority to save. I discussed what such a priority system should look like with Jeanne Grace, Forestry Technician for the City of Ithaca, and we came up with the following guidelines:

4 3 All trees classified in the Ithaca Tree Inventory as in poor, fair, or cull condition should be categorically excluded from pre-treatment. Only excellent or good quality trees should be considered for pre-treatment because we want to prioritize attractive, healthy trees. All trees listed as close to high voltage power lines should be categorically excluded from pretreatment, because they are at high risk of being indiscriminately and haphazardly mangled by the electric companies. Trees with lawn widths listed as five feet or less should be categorically excluded from pretreatment because their growth is likely to be impeded and/or they are likely to encroach upon sidewalks and other urban infrastructure. Trees along certain busy vehicular corridors (Meadow St., Fulton St., Old Elmira, Green St., and Seneca St.), as well as those located in parks and recreational areas, should be given special weight/consideration for saving. Different types of trees should be weighted differently for prioritization. White Ashes/Fraxinus Americana (for their aesthetic qualities/beauty) and the one Blue Ash/Fraxinus Quadrangulata in Ithaca (for its novelty/rarity in Ithaca) should be the first tier, European Ashes/Fraxinus Excelsior should be second tier, and all other ashes (Green Ash/Fraxinus Pennsylvanica and Flowering Ash/Fraxnius Orcus) will fall into a third priority tier. We would like to ideally end up with distribution of pre-treated trees that looks roughly like this in relation to DBH (Diameter at Breast Height): o 50% trees with inch DBH o 25% trees with <10 inch DBH o 25% trees with >10 inch DBH In addition to the above, analysis of the cost of treatment should be considered in the recommendations of which trees should be singled out for pre-treatment. The City of Ithaca would prefer to see those Ash Trees which are saved dispersed relatively evenly in the different neighborhoods/areas of the city. However, the above criteria are considered to be more important towards determining what trees to save. At the very least, it will be helpful to see the distribution of trees by neighborhood in the eventual scenarios. Fig. 2 An adult EAB.

5 4 Fig. 3 Locations of confirmed EAB infestations in New York State (New York State Department of Environmental Conservation, 2010)

6 5 Methods I received a shape file of Ithaca City Trees from Ruth Aslanis, the GIS Administrator of the City of Ithaca. This shape file contains attributes of 13,157 trees in Ithaca s urban forest, and 31 different attribute fields, the majority of them containing data for each and every tree. Since my project only deals with Ash trees, with the exception of showing a base map of the City of Ithaca s entire urban forest, I immediately exported a shape file of only trees in the Fraxinus genus. I then exported a shape file from the Ash-trees-only shape file of only trees that were not in poor, fair, or cull condition, were not near highvoltage power lines, and were not on lawns of less than five Fig. 4 EAB Larvae, the cause of tens of millions of Ash tree deaths. feet in width. All the shape files I used to create the maps for this project, apart from those derived from the City of Ithaca tree inventory shape file, were either among those already available in the Geddes Lab at Cornell, or ones I downloaded from the CUGIR (Cornell University Geospatial Information Repository) website. All but two or three were already set in the New York Central StatePlane projection, and those that were not had no difficulty being projected on-the-fly in line with the other maps and vectors. After creating an Fraxinus-only shape file, the two next things I needed to do in order to ultimately create a weighting system for EAB pre-treatment prioritization was to divide trees based on significance / non-significance, as well as to separate different species of Ash Trees. Our definition of significant contained trees along a few major thoroughfares decided by Jeanne Grace at the City of Ithaca, and any trees located inside parks or recreational areas. I initially intended to use a buffer in order to locate all the trees along specific roads, but as I examined the locations of Ash trees and roads closely, I realized this would not work. The reason for this was that there were some trees that were located as far as 40 feet from some roads, particularly wider roads like more semi-suburban stretches of Route 13, but that were clearly associated with that road and that road only. However, in the more dense central areas of Ithaca, there were many trees much closer than 40 feet to roads, yet far closer still to another road. If had used a buffer, I would have ended up selecting some trees associated with the incorrect road. Since the roads we picked out were very limited, I simply picked out trees along them manually, did the same with trees in parks and recreational areas, and created a new field in the attribute table to separate out significant trees from those that were not. I entered the number 1 in cells of significant trees, and 2 of non-significant ones.

7 6 In order to divide the trees into different priority tiers by species, I simply created a new field and assigned all White Ashes (Fraxinus Americana) and Blue Ashes (Fraxinus Quadrangulata) a 1, all European Ashes (Fraxinus Excelsior) 2, and Green (Fraxinus Pennsylvanica) and Flowering Ashes (Fraxinus Ornus) 3. Since in the case of both the significance field, and the tier field, the most desirable Ash Trees for pre-treatment had the lowest numbers, I then created a third new field containing the sums of the other two fields. The newly created numbers in this field ranged from two to five. Those trees with a two, I refer to throughout the report as Highest priority, those with a three, High priority, those with a four, Moderate priority, and those with fives, Low priority. In addition to creating maps showing all the different sets of trees that could be pre-treated depending on what priority level was used on as a cut-off point, I also created maps showing neighborhood overlays (based on City of Ithaca designated tree management areas, which I received a separate shape file for from Ruth Aslanis), since Jeanne Grace wanted a sense of how trees to be saved might end up distributed spatially throughout the City. I also inserted tables showing how many trees to be pre-treated were in each neighborhood. Fig 5. White Ash leaves (School of Forest Resources and Conservation at the University of Florida, 2010) Since Jeanne Grace and I ideally wanted to pre-treat a set of trees with a particular distribution of sizes (25% of DBH less than 10 inches, 50% 10 to 20 inches, and 25% greater than 20 inches), I extracted the data of the quantity of trees falling into those respective size ranges from the attribute tables in each of the four pre-treatment scenarios, and created a new map based on an alternate way of creating a set of trees. Finally, I plugged the DBH data for each of the four scenarios I d created into Purdue University s Emerald Ash Bore cost calculator website, and generated charts and tables showing estimated costs, both for individual years and cumulatively.

8 7 Maps and Analysis

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21 20 DBH (Diameter at Breast Height) in Scenario 1 DBH # of trees to be treated Percentage of trees in scenario Less than 10 Inches 2 40% 10 to 20 Inches 2 40% More than 20 Inches 1 20% DBH (Diameter at Breast Height) in Scenario 2 DBH # of trees to be treated Percentage of trees in scenario Less than 10 Inches % 10 to 20 Inches % More than 20 Inches 3 6.7% DBH (Diameter at Breast Height) in Scenario 3 DBH # of trees to be treated Percentage of trees in scenario Less than 10 Inches % 10 to 20 Inches % More than 20 Inches % In my discussion with Jeanne Grace, we decided that we ideally wanted about one quarter of pretreated trees to have DBH s below 10 inches, about one half between 10 and 20 inches, and the remaining quarter to be over 20 inches. Clearly, based on the exclusions and criteria we decided on, the trees that were determined to be of highest priority for pre-treatment skew heavily towards those with smaller diameters. However, I wanted to create an alternative to the above scenarios in which, hopefully, the distribution by diameter was closer to what Jeanne Grace and I had envisioned. Accordingly, I decided to look at the distributions of different priority levels based on the three categories of DBH we d decided to use. DBH by Weighted Pre-Treatment Priority Distribution (# of Trees) Highest Priority High and Above Moderate and Above Low and Above Less than 10 Inches to 20 Inches More than 20 Inches It takes only a few moments looking at this chart to see that there s only one possible way to arrange a new scenario that comes close to the 25/50/25 DBH categorical distribution for which we d hoped. This scenario would be to pre-treat all trees with DBH under 10 under the highest and high categories, and for the other two DBH categories to simply treat all trees not initially excluded from pre-treatment.

22 21 DBH (Diameter at Breast Height) in Alternate Scenario DBH # of trees to be treated Percentage of trees in scenario Less than 10 Inches % 10 to 20 Inches % More than 20 Inches %

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25 24 Cost Analysis I used an Emerald Ash Borer cost calculator (Purdue University, 2008) to determine how much the pretreatments might cost in the various scenarios above. I first entered data regarding the set of trees from Scenario 1, in which only Highest priority Ash trees are treated. The data generated shows estimated costs per year if pre-treatment is done annually over a period of 25 years (with the steady increase in cost due to the projected growth of trees, based on their sizes) and cumulative costs after x years. Here were the results: (Purdue University, 2008)

26 25 Here were the results for scenario 2: (Purdue University, 2008)

27 26 Scenario 3: (Purdue University, 2008)

28 27 And the Alternate DBH-Based Scenario: (Purdue University, 2008)

29 28 The following is a table showing estimated pre-treatment costs for the first five years (both per individual year and cumulative): Year 1 Year 2 Year 3 Year 4 Year 5 Scenario 1 (Individual Year) $228 $235 $242 $248 $255 Scenario 1 (Cumulative) $228 $463 $704 $953 $1208 Scenario 2 (Individual Year) $1473 $1534 $1596 $1657 $1719 Scenario 2 (Cumulative) $1473 $3007 $4603 $6261 $7979 Scenario 3 (Individual Year) $2826 $2953 $3080 $3207 $3334 Scenario 3 (Cumulative) $2826 $5779 $8859 $12066 $15399 Alt Scenario (Individual Year) $4662 $4887 $5112 $5338 $5563 Alt Scenario (Cumulative) $4662 $9549 $14662 $19999 $25562 Here is the same table, with the dollar figures normalized by the number of trees in each particular scenario: Year 1 Year 2 Year 3 Year 4 Year 5 Scenario 1 (Individual Year) $46 $47 $48 $50 $51 Scenario 1 (Cumulative) $46 $93 $141 $191 $242 Scenario 2 (Individual Year) $33 $34 $35 $37 $38 Scenario 2 (Cumulative) $33 $67 $102 $139 $177 Scenario 3 (Individual Year) $30 $32 $33 $34 $36 Scenario 3 (Cumulative) $30 $62 $95 $130 $166 Alt Scenario (Individual Year) $54 $57 $59 $62 $65 Alt Scenario (Cumulative) $54 $111 $170 $233 $297

30 29 Conclusion/Findings Most of what I found in working on this project doesn t lead to simple, clear-cut recommendations on what should be done by the City of Ithaca to address the problems of EAB. One reason for this is that I have little knowledge of the budgetary constraints and vagaries of the City of Ithaca s government and any other relevant actors. My main goal was to simply process some already existing data into a product that would give the City information with which to make a better informed decision in the near future regarding protecting their Ash trees. I think that the analysis I offer does provide a very useful starting point for thinking about how this might be done. Based on what I know, I strongly believe Ash tree protection is an issue that needs to be addressed quickly, for based on the speed with which the EAB has moved (or has been moved) from place to place in the past, it seems unfortunate but inevitable that the pest will reach the City of Ithaca at some point in the near future. Clearly, the priority system that I use, while based on many of the relevant concerns regarding Ash tree pre-treatment, is only something of a rough draft, and may need to be tweaked quite a bit when it comes to actually moving forward with decision-making on which Ashes to treat. Although I provide multiple scenarios for pre-treating varying numbers of Ash trees, it may be the case that the amount of funds that are appropriable for such use is somewhere between two of the scenarios (or more than any of them), and a new one may need to be devised. Perhaps it will be decided that another variable is equally as important as ones that I use for prioritization, or that one of the variables I use is less relevant to EAB pre-treatment than had been previously thought. Additionally, the weighting system I used was rather simplistic, and more precise ways of weighting the variables I used may be necessary. The cost estimates that I generate using the Purdue University online EAB Treatment Cost Calculator should be taken with a grain of salt, as when I delved deeper, I found dramatically different cost estimates for both the chemicals used to pre-treat for EAB, and for the differences in suggestions as to how much should be used per-dbh inch depending on the range of trees sizes. Additionally, the regional differences in cost of chemicals used for EAB pre-treatment seem even more wildly variable than one would expect. For these reasons, I simply use the default cost settings on the online cost calculator. I would welcome the opportunity to redo the cost analysis at some point based on what the City determined was a definitive cost estimate for EAB pre-treatment per DBH-inch according to various size ranges. It would also be valuable to do further analysis and research which also incorporates the costs of replacement and removal in lieu of pre-treatment, as well as a STRATUM or similar analysis estimating a quantifiable benefit of each tree.

31 30 Bibliography New York State Department of Environmental Conservation. (2010). Emerald Ash Borer. Retrieved December 2010, from NYS Dept. of Environmental Conservation: Purdue University. (2008). Emerald Ash Borer Cost Calculator. Retrieved December 2010, from Emerald Ash Borer in Indiana from Purdue Entomology: School of Forest Resources and Conservation at the University of Florida. (2010). Florida 4-H Forest Ecology. Retrieved December 2010, from Florida 4-H Forest Ecology: US Forest Service. (2010). Emerald Ash Borer, USFS. Retrieved December 2010, from Northeastern Area State & Private Forestry - USDA Forest Service: USDA Forest Service/Michigan State University/Purdue University/Ohio State University. (2010). Emerald Ash Borer. Retrieved December 2010, from Emerald Ash Borer Information Network: