Climate change vulnerability assessment of forest plants in the Credit River watershed: An application of NatureServe's CCVI tool

By Madaleine Sansom

A capstone submitted in conformity with the requirements for the degree of Master of Forest

Conservation

Daniels Forestry

University of Toronto

January, 2020

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Executive Summary

Climate change is the most important conservation challenge of our lifetime. Conservation organizations and researchers can no longer assume stable climate averages and need to account for climate vulnerabilities when planning management and conservation activities. Climate vulnerability assessments allow for fine-scale information on species natural history and functional traits to be considered. The three pillars of this type of assessment are 1) exposure to climate change, 2) sensitivity to these changes, and 3) the adaptive capacity of a species or system. There are several methods for assigning climate vulnerability, among which the NatureServe Climate Change Vulnerability Index (CCVI) is the most widely used. In the present study, I used the NatureServe CCVI to assess 30 forest plant species in the Credit River watershed including forbs, ferns, shrubs, and trees. Credit Valley Conservation (CVC) is responsible for protecting and managing approximately 1000 km2 of land in southern Ontario. The land within CVC’s jurisdiction is largely fragmented and encompasses several municipalities and major cities. As climate change becomes a real issue, CVC needs a way to understand its effects on the natural heritage that exists within its watershed.

My objectives were to: 1) conduct a climate change vulnerability assessment of forest plants within the Credit river watershed, using the CCVI tool; 2) identify the key factors contributing to species’ vulnerabilities; 3) use existing bioclimatic envelope models for several tree species within the Credit River watershed and rankings from other CCVI projects in nearby areas, to support or dispute species ranks; and 4) weigh the benefits and limitations of the CCVI tool, and provide recommendations on how it could be used by organizations like CVC in the future.

Future climate conditions under Representative Concentration Pathway (RCP) 4.5 indicate overall drying from 38-58 mm as indicated by the Hamon (AET:PET) moisture metric, and a 3°C increase in mean annual temperature by 2050. Upon ranking each species, 13% are “less vulnerable”, 43% are “moderately vulnerable”, 37% are “highly vulnerable” and 7% are “extremely vulnerable”. The factors that contributed most to vulnerability were historical and physiological hydrological niche, history of pathogens or natural enemies, dispersal and movement capabilities, history of genetic bottlenecks, and genetic variation, consecutively.Theses results align with previous CCVI assessments in nearby geographic regions including the Ontario Great Lakes basin, Michigan, and West Virginia. Additionally, the rankings generally agree with bioclimatic envelope modelling for tree species in the Credit River watershed under climate change.

Moving forward, I recommend that CVC: 1) Conduct more detailed assessments using the CCVI, and work with other organizations on larger-scale assessments; 2) Develop a plan for assisted migration of species with more southerly seed zones, and Carolinian species; 3) Conduct a study to determine whether phenological mismatch is affecting spring ephemerals; and 4) Develop public education campaigns centred around climate change impacts on natural heritage.

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Acknowledgments

I would like to thank Dr. Laura Timms (CVC) for bringing this project to my attention and

for her support and confidence through its duration. Thanks to CVC for providing me with the

opportunity to pursue my work as an intern. I would also like to thank Dr. Sandy Smith for

providing invaluable advice and continually challenging me as I worked through the many

phases of the project. Lastly, I would like to thank Dr. Danijela Puric-Mladenovic for her

involvement in the later stages of this project, and for lending her expertise in climate change

modelling and working within the complex framework of conservation in southern Ontario.

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Table of Contents Executive Summary ....................................................................................................................................... 2

Acknowledgments ......................................................................................................................................... 3

Introduction .................................................................................................................................................. 6

Literature review .......................................................................................................................................... 7

NatureServe CCVI ...................................................................................................................................... 9

Making use of multiple methods ............................................................................................................ 10

Objectives ................................................................................................................................................... 12

Methodology .............................................................................................................................................. 12

Study area ............................................................................................................................................... 12

Species selection ..................................................................................................................................... 14

Species occurrence maps ........................................................................................................................ 15

Climate data ............................................................................................................................................ 15

Species life history information .............................................................................................................. 16

Mapping vulnerability of dominant tree species in ELC communities ................................................... 16

Results......................................................................................................................................................... 16

Historic and future climate exposure ..................................................................................................... 16

CCVI rankings .......................................................................................................................................... 17

Factors most affecting vulnerability ....................................................................................................... 19

CCVI rankings and other assessment areas ............................................................................................ 19

Mapping vulnerability by ELC type ......................................................................................................... 21

Discussion ................................................................................................................................................... 21

Climate results and uncertainty .............................................................................................................. 21

Factors affecting vulnerability/ rankings ................................................................................................ 22

Comparing results to previous work ....................................................................................................... 25

Mapping vulnerable communities .......................................................................................................... 26

Benefits and limitations .......................................................................................................................... 27

Recommendations ..................................................................................................................................... 28

Future vulnerability assessments ........................................................................................................... 28

Other work .............................................................................................................................................. 28

Conclusion .................................................................................................................................................. 28

References .................................................................................................................................................. 30

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Appendix A: Figures ................................................................................................................................... 36

Appendix B: Tables ..................................................................................................................................... 38

Appendix C: List of references used to obtain CCVI rankings ................................................................... 42

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Introduction

The Credit Valley Conservation (CVC) Authority manages and protects the Credit River watershed in southern Ontario, an area of approximately 1000 km2 (CVC, 2009). The watershed encompasses portions of the regions of Peel, Halton, Wellington, and Dufferin and contains many different vegetation communities. The most significant physiographic features in the Credit River Watershed are the Niagara Escarpment, the Oak Ridges Moraine, and the Lake Ontario Shoreline. Because of its location, and position within Ontario’s busiest cities, including Mississauga, the watershed is largely fragmented in its Southern regions which poses many threats to the health of the riparian ecosystems and surrounding forests.

The three zones of the watershed include this most southern portion, or lower watershed, extending as far north as Norval (Fig. 1; CVC, 2009). The central watershed extends from Inglewood to Georgetown and encompasses part of the Oak Ridges Moraine and Niagara Escarpment. The landscape in this area is especially diverse and includes many wetlands and forests and has historically been used primarily for agriculture, with a few smaller cities and conservation areas. The upper watershed extends as far as Orangeville and is largely dominated by mixed coniferous-deciduous forests and farms. As the level of development and infrastructure increases from North to South water quality of the river and streams in the watershed also declines (CVC, 2009).

The challenges that face the Credit River watershed are not far different than those faced by other urban-rural watersheds in

southern Ontario. The existing Natural areas are generally restricted to the middle and upper watershed, and closely follow the Credit River (Fig. 1). As a result, the watershed management differs across the CVC due to distribution of natural heritage and land use types, as well as due

Figure 1: Land-use in the three section of the Credit River watershed (source: Chapter 3, Credit River Watershed Report, 2012. Retrieved from https://cvc.ca/watershed-science/watershed-monitoring/credit-river-watershed-health-report/chapter

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to different priorities that municipalities in the watershed have. Cumulative effects of habitat fragmentation, pollution, and climate change put the pressure on the remaining natural areas. Despite long-term monitoring, restoration, and local engagement, that all contribute to a better understanding of the watershed and surrounding ecosystems and help improve existing environmental (CVC, 2009), watershed management needs to account for climate change adaptation. Conservation authorities like CVC need tools to incorporate climate change threats into both short and long terms management.

CVC works in close partnership, and receives funding from various municipalities including Peel Region, Halton Region, and the Cities of Mississauga, Brampton, and Caledon. As the neighbouring watershed to the TRCA’s jurisdiction, CVC also collaborates with the TRCA on larger scales initiatives. Some of the most recent examples of this type of work can be seen in the Climate Trends and Future Projections in Peel Region report (Auld et al., 2016) and the Natural Systems Vulnerability to Climate Change in Peel Region (Tu et al., 2017). This work was carried out by Peel Region, with the help of representatives from the TRCA, the Ontario Climate Consortium (OCC), and CVC. These two reports have set the stage to understand the impacts of climate change at a regional scale and are useful in that Peel Region covers approximately half of CVCs jurisdiction.

Literature review Natural resources management and conservation groups are faced with one of the most

important challenges climate change. Its effects are not isolated to specific regions and species and it can amplify and worsen the effects of human activities already putting stress on natural systems (Akbari et al., 2001; Greene & Millward, 2016). Climate was once considered to be a constant and its impact predictable on most systems, however it has now become one of the greatest uncertainties (Stein et al., 2014). Adaptation and mitigation are two ways in which society can respond to climate change (Glick et al., 2011). Current conservation policy and planning has turned focus towards adaptation since that the threats of climate change are better understood (Glick et al., 2011; Pearson & Dawson, 2003). This requires managers to have an in-depth understanding of what species, habitats or ecosystems are most susceptible to the effects (Füssel & Klein, 2006; Stein et al., 2014), and thus highlights the need to develop tools to assess where intervention may be needed.

The study of climate change has commonly focused on the impact assessments as they enable

evaluate what effects different climate scenarios are likely to have on natural systems (Füssel &

Klein, 2006). The ability to narrow down effects due to specific CO2 concentrations and levels of

warming may have on water resources, crops, and other life-supporting systems allows for

identification of threats. However, this approach does not deal with adaptation to those threats

(Feenstra et al., 1998; Moriondo et al., 2011). Impact assessments are useful in raising

awareness about the degree of climate change and the potential long-term effects (Pearson &

Dawson, 2003), and helping to inform and creating new policies. That is not to say that impact

assessments should not be used, alone however they do not provide sufficient information on

how to respond to changing climate and should be used in conjunction with other methods

including vulnerability assessments (Füssel & Klein, 2006; Jones, 2001).

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Species vulnerability assessment (VA) is an effective way to identify how and why certain species, based on their life history and niche requirements, may be more vulnerable than others to climate change (Young & Hammerson, 2016). The common metrics for VAs include evaluating exposure to changes in climatic factors (i.e., mean annual temperature, seasonal precipitation, and growing season length), the sensitivity of the species/ system to changes, and its adaptive capacity (Glick et al., 2011). These three characteristics act as pillars for vulnerability assessments and can be applied across spatial scales and different ecosystem types (Stein et al., 2014; Young & Hammerson, 2016). Though vulnerability assessments provide important insight in the future and what climate change could bring, it should not be used alone, but rather in combination with other methods and tools informing conservation prioritization for climate change adaptation (Stein et al., 2014). There are different VA methods that range from species distribution modelling, to frameworks and various tools that give species ranks.

Species distribution models (SDMs) are generally the most commonly used modelling

approach in VAs (Sinclair et al., 2010; Willis et al., 2015). These models usually assume that thee

existing species’ distribution is at equilibrium with the environment and do not include the

species potential for adaptation or dispersal limitations (Austin et al., 2011). SDMs also tend to

assume that correlation between species’ range changes and changing climatic factors is a

causative relationship, which is another flaw (Sinclair et al., 2010). The method also requires an

in-depth understanding of modelling approach and can be inaccessible to many people (Austin

et al., 2011). Additionally, predictive models can be developed based on different approaches

which makes comparing results across different applications challenging (Sinclair et al., 2010).

Trait-based assessments (TVAs) are also frequently-used for VA and involve the use of tools or frameworks to rank species or habitat vulnerability based on a set of traits (Glick et al., 2011). Generally, TVAs require less technical and modeling knowledge, making their use more accessible. inputs include information on species’ functional traits and habitat requirements. Their output is a score or ranking that indicates how vulnerable a given species is to the effects of climate change. TVAs assessment can be conducted based on four tools developed: the United States Environmental Protection Agency (EPA) released the “Framework for categorizing the relative vulnerability of threatened and endangered species to climate change” in 2009, a document which outlines four modules used to determine overall vulnerability and the confidence of a given score (EPA, 2009). The United States Forest Service System for Assessing the Vulnerability for Species to climate change (SAVS) was released in 2011 (Bagne et al., 2011). The Climate Change Sensitivity Database (CCSD) was released in 2012 in collaboration between the University of Washington and the Nature Conservancy. The NatureServe Climate Change Vulnerability Index (CCVI) tool was released for the first time in 2011, with the most recent Canadian-specific version released in 2015 (Appendix B, Table 1 provides details on each VA method).The SAVS and CCSD are both online tools that are openly accessible whereas the CCVI is formatted in a MS Excel workbook that can be downloaded for free as well.

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NatureServe CCVI The CCVI is one of the most widely-used TVA tools as it can be applied to a range of

taxonomic groups, from aquatic to terrestrial, and from plants to animal species (Pacifici et al., 2015; Stein et al., 2014; Young & Hammerson, 2016). The CCVI’s widespread use has been also attributed to its ability to rapidly assess a large number of species and produce a confidence score for each ranking (Pacifici et al., 2015). The CCVI was designed to help managers screen large numbers of species and identify which ones are the most vulnerable and what factors contribute most to that vulnerability (Young et al., 2016). As such, it has become a popular tool used by government, non-profit, and academics (Young et al., 2015). A recent survey revealed that the CCVI is now the most common method being used by state agencies to assess the impacts of climate change on wildlife as part of federally-mandated revisions to their state wildlife action plans (AFWA, 2012).

A review conducted in 2015 ( Young et al., 2015 ) surveyed previous users and identified challenges and different approaches to using the tool (Young et al., 2015). The most common reason for using CCVI was to “generate a broad understanding about climate change”, and “to address species management decisions” (Young et al., 2015). All studies were targeted at managers or scientists directly involved in species management decisions. In most cases, the CCVI was the only method considered, however in three cases the CCVI was used in conjunction with other methods (distribution models/ scenario-based spatial analysis). The main strengths identified were that the CCVI was easy to use, had detailed guidelines, the ability to screen multiple species from variety of taxa, a consistent and repeatable framework, and ability to compare confidence in scores among species (Young et al., 2015).

Specific USA and Canadian CCVI versions have been created in response to feedback from users (Young et al., 2015) and have been released in 2016. The tool is regularly updated, and the newest release of the Canadian version has several improvements. This included a means to “assess climate effects in overwintering areas of migratory species when they are not present within the assessment area” (Young et al., 2015), two more interspecific factors (sensitivity to pathogens/natural enemies and sensitivity to competition from native/non-native species), and a new factor that considers plant reproductive systems (Young et al., 2015). The tool developers have been quick to make improvements based on feedback from the users. As the tool has grown in popularity, also more studies citing the CCVI are being published, often in the form of reports for specific areas or groups of species. Several studies have used Nature Serve tool for breeding birds in Alaska (Liebezeit et al., 2012), rare plant species in California (Anacker et al., 2013), the Lake Simcoe watershed (Brinker & Jones, 2012), and the entire Great Lakes basin (Brinker et al., 2018).

Brinker et al. (2018) and Ontario Ministry of Natural Resources and Forestry (OMNRF) conducted a TVA using the Canadian release of the CCVI for species in the Ontario Great Lakes basin. They selected species based on their susceptibility to climate change, whether they were habitat specialists or keystone species, species of conservation concern (provincially or globally rare), those which inhabit the southern or northern limits of their suitable range, and those which have sufficient data available to conduct an assessment (Brinker et al., 2018). One of the main limitations that Brinker et al., 2018 noted is that the tool does not allow for the

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assessment of conservation threats unrelated to climate change. They suggested that it be used in conjunction with other status assessments, such as NatureServe Conservation Status ranking (Brinker et al., 2018).

To cope with the uncertainty of the effects of climate change, and the discrepancies in scoring at different spatial scales, Griffis-Style et al. (2018) took a slightly different approach than most studies using the CCVI to assess the vulnerability of desert herpetofauna. They used spatial at data from the “conterminous United States and the southwestern desert regions” (Griffis-Kyle et al., 2017) to calculate exposure. Climate data from the Coupled Model Intercomparison Project (CMIP) for four different emissions scenarios were used to determine future climates. Each species was ranked using both sets of spatial data and each climate change scenario, then scores were averaged to represent the overall response of the species (Griffis-Style et al., 2018). While this novel approaches to VA can be taken by CCVI tool-users to suit their own needs it causes some discrepancies when attempting to compare scores from a wide range of studies.

Making use of multiple methods Both SDMs and TVAs have their limitations and uncertainties, however these can be

reduced, or cross-validated when both methods are employed in one assessment. Willis et al.

(2015) outline the need to compare SDMs and TVAs and used a case study of two African bird

species to show the different results that they produce. The results of this showed that SDMs

do not consider a species’ ability to migrate and barriers that might impede migration under

climate change. Even if the results show that species will have good habitat in the future, if they

cannot access that habitat due to dispersal limitations, then they may be more vulnerable than

the model indicates. As TVAs are so accessible and easy-to-use, SDMs are often not done or

overlooked, which is a critical flaw in vulnerability assessments since simple is not always the

best solution (Willis et al., 2015).

Information from SDMs can be incorporated into TVAs, as was done by Anacker et al.

(2013) by including species’ modelled response to climate change in the CCVI tool assessment.

This is an optional field within the tool which is useful, should information be available. They

used both the Nature Serve CCVI to determine general categories of vulnerability, and then

Maxent (Phillips, 2017) to run SDMs to determine if and how each species range might be

reduced under climate change and if the new range overlaps with the historical range (Anacker

et al., 2013). The CCVI score excluding the SDM resulted in different species in the top five most

vulnerable species list. They indicate that, due to the variability in modelled results based on

model type and parameters used, quantitative modelling alone does not provide enough

consistency to predict the fate of rare species under climate change. Overall, they conclude that

using multiple methods can provide a broader picture of climate change vulnerability but that

index-based methods are an excellent place to start (Anacker et al., 2013).

Similarly, Still et al. (2015) used CCVI and Maxent to conduct a vulnerability assessment of

rare plants in the western United States. Unlike Anacker et al. (2013), they did not include

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modelled response in the CCVI score to compare SDM and index results without overlap. Some

species not scored as vulnerable under the CCVI proved to be highly vulnerable using the SDM

method. Overall, their results indicate that the CCVI and SDM can be used to compliment each

other and to further prioritize species for management. The two approaches can cross-validate

results and decrease uncertainty leading to greater confidence in results and more informed

decision-making (Still et al., 2015).

The need to conduct binational assessments that transcend political boundaries has been acknowledged as a key issue in VAs. This is of particular concern when assessing climate change vulnerability because if a species’ range is expected to shift, this usually means it will shift into different jurisdictional boundaries. A 2017 study (Rempel & Hornseth, 2017) evaluated the effectiveness of using the CCVI with SDMs to assess the vulnerability of migratory birds in the US and Canadian Great Lakes Basin. Three focal species were selected and overall, the CCVI allowed for a basic assessment of vulnerability. Gaps in data and monitoring across jurisdictions did, however, prove to be a challenge and required the authors to extrapolate some information (Rempel & Hornseth, 2017).

The NatureServe CCVI is quickly becoming the most widely-used TVA tool as it has used by

government departments. For example, it has been mandated for use in the revision of state

wildlife action plans in the US (AFWA, 2012). It has also been used by the OMNRF for two

studies (Brinker et al., 2018; Brinker & Jones, 2012). Although Credit Valley Conservation has

not used the the CCVI, they do use provincial status ranks produced by the Natural Heritage

Information Centre using the NatureServe Conservation Status tool. This pairs well with the

CCVI as the results can be added to the spreadsheet model and help provide more information

about a species. Based on CCVI’s wide use, as well as its ability to produce rapid assessments of

a large number of species, I will be using the tool to evaluate its use to CVC and aid in

communicating results to a wide audience that could lend to improved collaboration in future

projects. Collaboration in climate change planning and mitigation is key, and a more concerted

effort to do so is necessary.

The present study is a pilot project for CVC, to evaluate the CCVI and determine whether is

a useful tool to assist in climate change planning at a regional scale. Through this work, I expect

to obtain rankings of vulnerability for a set of the selected species. To achieve this and have

enough data, I have deliberately not chosen extremely rare species that may have limited

information in the published literature. Lastly, I anticipate that this work will enhance the

results of the Natural Systems Vulnerability in Peel Region report (Tu et al., 2017) since they did

not include such fine-scale traits in their assessment. In time, it would be beneficial for the work

to be expanded to include more species and taxonomic groups.

Through my research, I will provide recommendations on how CVC can contribute to

climate change research in southern Ontario. I will outline where this work might fit within

existing jurisdictions, and what roles different municipal tiers, and organizations have in

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implementing climate change knowledge in practice. As CVC is currently working on a forest

management plan, it is pertinent to understand how to account for climate change in a more

concrete way, to ensure that a “business as usual” approach to management is not taken.

Objectives

The specific objectives of this project are to:

1. Conduct a climate change vulnerability assessment of forest plants within the Credit River watershed, using the CCVI tool;

2. Identify the key factors contributing to species’ vulnerabilities; 3. Use existing bioclimatic envelope models for several tree species within the Credit River

watershed and rankings from other CCVI projects, to support or dispute species ranks; and 4. Weigh the benefits and limitations of the CCVI tool to provide recommendations on how it

could be used by organizations like CVC in the future (i.e., by using existing Ecological Land Classification data to map vulnerable communities).

Methodology

The methodology used for the project was developed by NatureServe for the Canadian version 3.0 of the CCVI tool (Young et al., 2016). See Figure 2 for the process of conducting a VA using the CCVI. The CCVI framework includes direct and indirect climate exposures that contribute to an overall ranking (Fig. 3). The MS Excel (Microsoft, 2017) spreadsheet contains a total of 23 factors and one must score at least 13 of them in order to obtain a ranking (Young et al., 2016). The factors are distributed among four sections including; A) exposure to local climate change, B) indirect exposure to climate change, C) sensitivity and adaptive capacity, and D) documented or modelled response to climate change (optional). Each factor was ranked based on how it is expected to contribute to a species’ vulnerability (e.g. greatly increase, increase, somewhat increase, neutral). The CCVI is also meant to provide a starting point for identifying knowledge gaps related to climate change, as well as factors that contribute to species’ vulnerability.

Study area It is important to identify a discrete geographic area for an assessment using the CCVI

because climate raster data must be clipped to a specific geographic area in order for exposure scores to be calculated. The study area used to test the tool was defined as being any land within CVC’s jurisdiction (Fig. 1). The area of the Peel Region, that extends beyond CVC watershed, was not included due to limitations of data requirements on species occurrences.

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Define geographic assessment area

Acquire species distribution data

Acquire or Calculate downscaled climate projection models

Compile species-specific sensitivity and life history

data

Perform GIS analyses to spatially overlay individual

species range files and spatially explicit climate

projection models

Assess life history data for required CCVI factors

Complete the CCVI excel worksheet

Interpret vulnerability score and class results

Figure 3. Direct and indirect climate exposure variables including sensitivity factors used to generate overall vulnerability scores in the Climate Change Vulnerability Index (Young et al., 2010)

Figure 2. The process of conducting a climate change vulnerability assessment using the NatureServe CCVI tool (modified from Glick et al., 2017)

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Species selection As plants are primary producers, and drivers of community structure and composition, for

the purposes of this project, forest plants (trees, shrubs, grasses, forbs, ferns) were the focal taxonomic group. This was decided based on consultation with CVC staff and program directors, they need to have a better knowledge on how climate change could affect plant species and thus future forest management, restoration projects, and climate change mitigation actions.

Several different approaches were considered for species selection. In a recent study of species in the Ontario Great-Lakes basin (Brinker et al., 2018), species were selected based on several factors including habitat specialists or keystone species, species of conservation concern, and those which are at the southern or northernmost extremes in their range within the study area. Other studies have focused solely on at-risk species which poses an interesting issue. That is, rare and at-risk species can be vulnerable to climate change; however common species and those that are dominant in the ecosystem may also be vulnerable. The Ecological Land Classification (ELC) has been applied to characterize and map communities within CVC’s boundaries. ELC is based on the dominant vegetation and site (soil moisture and origin).

To select species that are representative of the ecological diversity that exists within the Watershed, several “filters” were applied. First, the dominant species in the ten most common, and ten least common Ecological Land Classification (ELC) vegetation types for forests and treed swamps were selected. This selection was based on which ELC types occupied the greatest or least area within the watershed boundaries. Additionally, any ELC types that were listed as provincially rare (S1-S3) by the NatureServe conservation status ranking system were included. This list was verified using data from the Integrated Watershed Monitoring Program (CVC, 2019), on species that occurred in 50% or more of sample plots within the watershed.

Species identified as “low-occurrence” with ten or fewer known occurrences in the watershed, were also included to represent more regionally rare species. To make the list more relevant for urban areas, data from the City of Mississauga OpenData (Mississauga, 2019) was used to determine the most abundant species of city-owned trees (street trees and those in city parks). Characteristic Carolinian tree species were also added, as they represent a small portion of the diversity in the lower watershed and have the potential to increase in abundance as the climate warms. Lastly, important invasive species were added to the list as CVC is interested in whether or not they will be favoured under future climate change.

A list of 124 species was compiled, and further reduced to 87 species based on feedback from individuals involved with the project. Those 87 species were then prioritized by how many selection filters applied to each. For example, a species may be present in one of the ten most common forest communities, be a dominant street tree in Mississauga, and be found in over 50% of the monitoring plots. The top 30 (Table 1) were chosen for the CCVI assessment.

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Table 1. The list of species selected for CCVI assessment in the Credit watershed.

Species occurrence maps Species occurrence maps were created

in ArcMap 10.6.1 (ESRI, 2018) with assistance

from CVC’s Information Management division.

Data from CVC’s Natural Heritage database

(CVC, 2019), Bill McIlveen’s Dataset (2016),

Mississauga Natural Areas Assessment (NAS)

database (Mississauga, 2018), TEMO database

(CVC, 2019), and wetland database (CVC, 2019)

were used to create occurrence maps for each

species. All species occurrences, represented as

a point file, were projected to Universal

Transverse Mercator (UTM) points and further

used to map species occurrences. In addition to

these, species occurrences that had no specific

point location (no X and Y coordinates) were

identified by using the ELC polygons in which

the occurrence was documented. For these ELC

polygons, a centroid was identified and its

coordinates (in UTM projection) were used. All

observations were included to create an

accurate representation of the area of the

watershed in which a species can grow. Many

species have been observed in the entire

watershed; however, a few have only been

observed in the lower regions.

Climate data The dataset recommended by the CCVI guidelines is the ensemble of 15 general

circulation models (GCMs) from the International Panel on Climate Change (IPCC) 5th report.

The recommended data from the ClimateNA database is available through AdaptWest

(AdaptWest Project, 2015). In this case, the files were obtained from Bruce Young, of

NatureServe. The required raster data for this assessment includes future projections of annual

temperature change (in °C), and climate moisture deficit (Hamon AET:PET) for the 2050s with a

baseline period of 1961-1990. Secondly, historic data on temperature variation (in °C), and

mean annual precipitation (in mm), is required to determine past exposure to climate variation

within the watershed. The datasets are downscaled to 1-km resolution to encompass as much

Taxa Scientific Name Common Name

Fern Onoclea sensibilis Sensitive fern

Forb Allaria petiolate Garlic mustard

Arisaema triphyllum Jack-in-the-pulpit

Circaea canadensis Broad-leaved Enchanter's Nightshade

Glyceria Striata Fowl mannagrass

Impatiens capensis Spotted jewelweed

Rubus pubescens Dewberry

Shrub Cornus alternifolia Alternate-leaf dogwood

Cornus sericea Red-osier dogwood

Prunus virginiana Chokecherry

Rhamnus cathartica Common buckthorn

Tree Abies balsamea Balsam fir

Acer rubrum Red maple

Acer saccharum Sugar maple

Betula alleghaniensis

Yellow birch

Betula papyrifera Paper birch

Celtis occidentalis Common hackberry

Fagus grandifolia American beech

Fraxinus americana White ash

Fraxinus nigra Black ash

Fraxinus pennsylvanica

Green ash

Juglans nigra Black walnut

Ostrya virginiana Eastern hop-hornbeam

Prunus serotina Black cherry

Quercus rubra Red Oak

Sassafras albidum Sassafras

Thuja occidentalis Eastern white cedar

Tilia Americana American basswood

Tsuga canadensis Eastern hemlock

Ulmus americana American elm

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fine-scale variation as possible. This raster data was then clipped to the watershed boundary,

using ArcMap 10.6 (ESRI, 2018), to determine historic and future exposure of species within its

boundary to changes in climate.

Species life history information Detailed life history information is required for each species which was obtained

through several sources. For most species, the US Forest Service Fire Effects Information

System (USDA, various dates), Silvics of North America (Burns & Honkala, 1990), Trees in

Canada (Farrar, 1995), and the Lady Bird Johnson Native Plant Database (Lady Bird Johnson

Wildflower Centre) were used. See Appendix C for a list of references that were used to provide

information that determined ranks for each species. The detailed guidelines (Young &

Hammerson, 2016) for the tool clearly outline how to rank each factor based on the species’

traits and should be followed closely in future assessments at CVC.

Mapping vulnerability of dominant tree species in ELC communities An example of a map that displays ELC communities dominated by species with differing

levels of vulnerability was created in ArcMap 10.6.1 (ESRI, 2018). The species selected to

illustrate this potential application of results were sugar maple, red oak, paper birch and balsam

fir. This was done after rankings were obtained for all selected species and represents

moderate, high, and extreme vulnerability. Should this type of mapping be done for the entire

watershed, one could then identify areas that have higher concentrations of vulnerable

communities and could prioritize management in those areas.

Results

Historic and future climate exposure The future climate conditions in the Credit River Watershed, and surrounding area

indicate an increased overall drying as indicated by positive values for the Hamon moisture

metric between 39-57 mm by 2050, compared to the baseline period (1961-1990) (Appendix A,

Fig. 1A). Net drying is expected to be greater in the southeastern portion of the watershed. An

increase in mean annual temperature between 3- 3.2 °C is also predicted (Appendix A, Fig. 1B).

Overall, the variation in predicted temperature increase is low within the study area, largely

due to the small spatial scale.

The data for RCP 4.5 to the 2050s shows that the Credit River Watershed, and

surrounding area has experienced moderate variation in precipitation (according to CCVI

guidelines) from 785-995 mm during the baseline period (1961-1990) (Appendix A, Fig. 1C).

Additionally, a mean seasonal temperature variation between 26.3-27.5 °C has been

experienced (Appendix A, Fig. 1D). Lower levels of precipitation have been observed in the

southeastern watershed, similar to the trend in predicted future drying. Similarly, slightly higher

17

temperature variation has also been recorded in the southernmost regions adjacent to Lake

Ontario (Appendix B, Table 2 shows detailed climate exposure scores for each species).

CCVI rankings Rankings of climate change vulnerability were derived from the CCVI for all species in

the assessment (Fig. 4, Table 3). There was enough information in the published literature and

plant guides to input at least 13 criteria for each species, excluding section D

(Documented/modeled response to climate change). The guidelines for the CCVI Canada V3.0

were closely followed to rank each factor based on the criteria described for each section.

Species ranked as “extremely vulnerable” include balsam fir, Eastern white cedar (Table

2). Species ranked “highly vulnerable” include jack-in-the-pulpit (Arisaema triphyllum [Linnaeus]

Schott), yellow birch (Betula alleghaniensis Britton), paper birch (Betula papyrifera Marshall),

American beech (Fagus grandifolia Ehrhart), white ash (Fraxinus americana Linnaeus), black ash

(Fraxinus nigra Marshall), fowl mannagrass (Glyceria striata [Lamarck] Hitchcock var. striata),

spotted jewelweed (Impatiens capensis Meerburgh), sensitive fern (Onoclea sensibilis

Linnaeus), Eastern hemlock (Tsuga canadensis [Linnaeus] Carrière), and American elm (Ulmus

americana Linnaeus). Species ranked “moderately vulnerable” include red maple (Acer rubrum

Linnaeus), sugar maple (Acer saccharum Marshall), alternate-leaved dogwood (Cornus

alternifolia Linnaeus f.), red-osier dogwood (Cornus s)ericea Linnaeus), green ash (Fraxinus

pennsylvanica Marshall), black walnut (Juglans nigra Linnaeus), Eastern hop-hornbeam (Ostrya

virginiana [Miller] K. Koch), black cherry (Prunus serotina Ehrhart), chokecherry (Prunus

EV7%

HV37%

MV43%

LV13%

Figure 4 proportions (%) of vulnerable species as ranked by the NatureServe CCVI tool (n=30). “LV” = less vulnerable, “MV” = moderately vulnerable, “HV” = highly vulnerable, and “EV” = extremely vulnerable

18

Table 2 Vulnerability rankings for each species, organized from most- to least- vulnerable.

RANKING CONFIDENCE COMMON NAME LATIN NAME

EXTREMELY VULNERABLE

Very high Balsam fir Abies balsamea

Low Eastern white cedar Thuja occidentalis

HIGHLY VULNERABLE

High Jack-in-the-pulipt Arisaema triphyllum

Very high Yellow birch Betula alleghaniensis

Very high Paper birch Betula papyrifera

Low American beech Fagus grandifolia

Very high White ash Fraxinus americana

Low Black ash Fraxinus nigra

Low Fowl mannagrass Glyceria Striata

High Spotted jewelweed Impatiens capensis

Low Sensitive fern Onoclea sensibilis

Very high Eastern hemlcok Tsuga canadensis

Very high American elm Ulmus americana

MODERATELY VULNERABLE

Very high Red maple Acer rubrum

High Sugar maple Acer saccharum

Very high Alternate-leaved dogwood Cornus alternifolia

High Red-osier dogwood Cornus sericea

Very high Green ash Fraxinus pennsylvanica

Moderate Black walnut Juglans nigra

Moderate Eastern hop-hornbeam Ostrya virginiana

High Black cherry Prunus serotina

Very high Chokecherry Prunus virginiana

Very high Red oak Quercus rubra

Moderate Dewberry Rubus pubescens

Very high Sassafras Sassafras albidum

Very high Basswood Tilia americana

LESS VULNERABLE

Very high Garlic mustard Allaria petiolata

Moderate Common hackberry Celtis occidentalis

Very high Broad-leaved enchanter’s nightshade

Circaea canadensis

Very high Common buckthorn Rhamnus cathartica

virginiana Linnaeus), red oak (Quercus rubra Linnaeus), dewberry (Rubus pubescens

Rafinesque), sassafras (Sassafras albidum [Nuttall] Nees), and basswood (Tilia americana

Linnaeus). Lastly, species ranked “less vulnerable” include garlic mustard (Alliaria petiolata [M.

Bieberstein] Cavara & Grande), common hackberry (Celtis occidentalis Linnaeus), broad-leaved

19

enchanter’s nightshade (Circaea canadensis [Linnaeus] Hill), and common buckthorn (Rhamnus

cathartica Linnaeus).

Factors most affecting vulnerability Similar to Brinker et al. (2018), I identified several factors contributed more to

vulnerability scores than others (Fig.5). Hydrological niche (both historical and physiological)

contributed to vulnerabilities in 93% and 33% of species, respectively. The presence or

anticipated presence of large-scale effects of pathogens or natural enemies (pests) was the

third most prevalent vulnerability factor at almost 27%, followed by species’ dispersal

capabilities (13%). The remaining factors listed affected the vulnerability of 6% and 3% of

species. Detailed rankings for each factor input into the CCVI can be found in Appendix B, Table

3.

CCVI rankings and other assessment areas Since the CCVI is an internationally-applicable tool, it makes it possible to compare and

apply results for species across multiple jurisdictional boundaries, creating a larger picture of

how vulnerability varies across a landscape. Several species that occur in the watershed and

that were ranked using the CCVI, have also been included in vulnerability assessments at larger

scale; the Ontario Great Lakes Basin (Brinker et al., 2018), and regions of West Virginia (Byers &

0 10 20 30 40 50 60 70 80 90 100

Historical hydrological niche

Physiological hydrological niche

Pathogens/ natural enemies

Dispersal/movement capabilities

Genetic bottleneck

Anthropogenic barriers

Physiological thermal niche

Genetic variation

Phenological response

percent of species affected (n=30)

CC

VI f

acto

r

Figure 3. Percentage contribution of factors to increased (“greatly increase”, “increase”, and “increase/somewhat increase”) climate change vulnerability of assessed species (n=30) in the Credit River watershed.

20

Table 3. CCVI rankings from this assessment and other studies in nearby geographic areas as well as species distribution modelling conducted for the Credit River Watershed. Green colouring indicates results that agree with what was found in the present study, orange indicates results that somewhat agree, red indicates results that do not agree.

Latin name

CCVI ranking

Brinker et al. (2018),

Penskar, 2014

Byers & Norris, 2011

Malcolm et al., 2008

Eastern hemlock (Tsuga canadensis) HV MV HV . Loser

sugar maple (Acer saccharum) MV LV . MV Stayer N

American beech (Fagus grandifolia) HV . HV . Stayer N

black ash (Fraxinus nigra) HV MV . . Loser

red maple (Acer rubrum) MV . . PS Stayer N

black cherry (Prunus serotina) MV . . MV Stayer

red oak (Quercus rubra) MV . . PS Stayer

Sassafras (Sassafras albidum) MV LV . . Winner

balsam fir (Abies balsamea) EV . . . Loser

Eastern white cedar (Thuja occidentalis) EV . EV . .

yellow birch (Betula alleghaniensis) HV . . . Loser

paper birch (Betula papyrifera) HV . . . Loser

American elm (Ulmus Americana) HV . . . Stayer

black walnut (Juglans nigra) MV . . .

Winner N/ Stayer S

basswood (Tilia Americana) MV . . . Stayer N

garlic mustard (Allaria petiolata) LV . . IL .

common hackberry (Celtis occidentalis) LV . . . Winner

Norris, 2011) and Michigan (Penskar, 2014). A study was also commissioned by CVC in 2007 to

create user-friendly mapping of tree species distribution changes under future climate

conditions for the Credit River Watershed (Malcom et al., 2008). Fifteen tree species overlap

with those in this assessment (Table 3). "losers"= species that were modelled to be currently

widely distributed in the Credit River Watershed, but whose habitat was projected to become

rare or absent in the future, "winners"= species that were modelled to be currently rare or

absent in the Credit River Watershed, but whose habitat was projected to become widely

21

distributed in the future, “stayer”= species that were projected to remain widely distributed in

the Credit River Watershed.

Mapping vulnerability by ELC type Once species vulnerability is assessed based on CCVI, I was able to map vegetation

community types dominated by four tree species, using data provided by CVC (2019) (Appendix

A, Fig. 2). Two areas are highlighted as they indicate higher concentrations of community types

dominated by vulnerable species. Additionally, the abundance of Sugar maple-dominated

communities is made apparent in the yellow-coloured ELC polygons which occur over a large

portion of the Watershed. Overall, sugar maple-dominant communities are abundant in the

watershed, occurring through the majority of the upper and middle watershed with some

presence in the lower. Red oak occurs in small pockets in the upper watershed, and in the lower

watershed close to Lake Ontario. Balsam fir and paper birch are both restricted to the upper

watershed and only in very small areas, as indicated by the inset map (Appendix A, Fig. 2).

Discussion

Climate results and uncertainty The results presented in the climate data provided by NatureServe align with those

projected for Peel Region in Auld et al. (2016), though the data were downscaled using slightly

different methods. However, the climate data provided by NatureServe provide a finer spatial

resolution (1 km) compared to the data for Peel Region (10 km) Auld et al. (2016). Regionally-

specific data at 1 km resolution are not widely available in Canada, although projects like

AdaptWest (AdaptWest Project, 2015) and ClimateData.ca (Canadian Centre for Climate

Services, 2019) are working to make it more accessible.

In addition to the uncertainty associated with different climate data sources, common

practice in work related to climate change is to consider multiple emissions scenarios (Deser et

al., 2012; Griffis-Kyle et al., 2018). In the case of this assessment only one, more conservative

scenario (RCP 4.5) was used to determine species’ future climate change exposure (IPCC, 2014).

The argument has been made that RCP 4.5 and the two more severe emissions scenarios (RCP

6.5 & 8.5) do not diverge until after 2050, which is the time frame used in this assessment

(Brinker et al., 2018; Young & Hammerson, 2016). However, to better account for the

uncertainty associated with climate change, a method more closely resembling that adopted by

Griffis-Kyle et al. (2018) should be adopted. The study compensated for the lack of accessible

data by calculating their own using downscaled CIMP5 data for monthly average surface air

temperature, potential evapotranspiration, and actual evapotranspiration, and three emissions

scenarios (RCP 2.6, RCP 6.0, and RCP 8.5) (Griffis-Kyle et al., 2018). Unfortunately, the required

22

data to replicate this methodology is not readily available in Canada, and thus, limited the

scope of this assessment.

On key example of why multiple scenarios and time periods should be used is because

some species may show relatively little response to changes in bioclimatic variables in most

scenarios, until one discrete time period that shows a sharp decline. Puric-Mladenovic et al.

(2011) assessed the vulnerabilities of terrestrial vegetation cover to climate change in the Lake

Simcoe Watershed using ecological niche modelling based on data from the “Canadian Climate

Model Version 2 climate scenarios for three time periods (2011-2040, 2041-2070 and 2071-

2100)”. Of several tree species assessed, sugar maple showed little response to climate change

in the 2020s and 2050s, however by the 2080s, shows a sharp decline in abundance across

most of southern Ontario (Puric-Mladenovic et al., 2011). Although the methodologies between

the aforementioned study and this CCVI assessment are different, it is important to consider

the potential overlap and to use both as indicators of species’ responses to climate change.

Factors affecting vulnerability/ rankings Several factors weighed more heavily in terms of affecting species’ vulnerability in the

watershed. This is to be expected as some were not as relevant for plant species, such as

dependence on ice or snow, uncommon geographic features, or diet. It is useful to understand

these factors when moving forward with further climate change-related studies as one can

begin to frame how to think about managing species for traits that will respond more

favourably to changes in climatic conditions. Several species were vulnerable due to a number

of factors. The vulnerability of blasam fir, for example, was increased due to its limited dispersal

abilities, low drought tolerance, and the impacts of two major pests (Appendix B, Table 3). In

addition, this species is at the southernmost portion of it’s range it the assessment area, further

decreasing it’s ability to adapt to changing conditions in the Credit River watershed. Some

species showed lower vulnerability including common buckthorn and garlic mustard. These two

invasives show impressive adaptive capacity through long-distance dispersal, their ability to

thrive in a variety of site conditions, and allelopathic properties that make them effective

competitors (Appendix B, Table 3). In general, factors that affect a species’ ability to thrive in

drought conditions, the effects of pathogens and pests, and the dispersal and movement

abilities of seeds greatly contribute to overall vulnerability.

Hydrological niche - Hydrological niche, both historical and physiological largely determine

where a species has been able to grow in the past and will continue to thrive into the future

(Silvertown et al., 2015). The CVC watershed has not experienced much variation in

precipitation compared to the baseline period, increasing the vulnerability of plants, according

to the CCVI guidelines, therefore vegetation communities may be more sensitive to drying in

the future. Because the remaining natural areas in the watershed are largely in riparian zones

and areas fed by groundwater, the vegetation is dominated by plants that are either dependent

on moist environments, or those that can tolerate wetter conditions in the event of flooding.

Eastern white cedar, American elm, ash species, balsam fir, Jewelweed, and Sensitive fern are

23

all examples of such species. Although it is difficult to generalize all of them, these species

typically show a preference for moist soil conditions and may be hydrologically sensitive to

drying (Burns & Honkala, 1990). Even though groundwater-fed ecosystems may be more

resilient in the face of climate change because they are likely to remain cooler, overall drying

will reduce the total area that has access to the water (Kundzewicz & Doll, 2009; Kurylyk et al.,

2013).

Pathogens and diseases - Several pathogens and diseases have already had a devastating impact

on plant species in Southern Ontario and the rest of Canada. Dutch Elm disease [Ophiostoma

ulmi (Buisman) Nannf.], Emerald ash borer [Agrilus planipennis Fairmaire], beech bark disease

(Neonectria faginata), and Hemlock woolly adelgid [Adelges tsugae Annand] have all worked to

weaken or completely extirpate natural populations of many tree species (Brunet & Guries,

2016; Eschtruth et al., 2006; NRCAN, 2016; Stephanson & Coe, 2017). Trees experiencing stress

from disease or pests are less likely to be able to withstand additional stressors associated with

climate change (Sturrock et al., 2011). The CCVI tool also accounts for diseases or pests that are

likely to reach the assessment area by the 2050s, which is important to consider, especially in

planning future tree planting activities in response to climate change. For example, Oak wilt

[Ceratocystis fagacearum (Bretz) Z.W. de Beer, Marinc., T.A. Duong and M.J. Wingf] has been

found in Michigan and is likely to reach southern Ontario despite best efforts to quarantine

contaminated wood and machinery (Jagemann, 2018; OFAH/OMNRF, 2012). This increases the

vulnerability of oak species, for example Pin oak [Quercus ellipsoidalis Hill] more southern-

adapted species. that may otherwise be relatively less vulnerable to climate warming. Similarly,

Laurel wilt [Raffaelea lauricola Harr., Fraedrich & Aghayeva] has impacted populations of

Sassafras in the United States and although it has not been found in regions that border

Ontario, warmer temperatures will likely expand the range of its vector, the Redbay ambrosia

beetle [Xyleborus glabratus Eichhof] (Formby et al., 2018). A commonly discussed option to

manage forests for climate change resilience is to increase planting of these more southerly-

adapted and Carolinian species (Almas & Conway, 2016; Taylor et al., 2006). It will be

increasingly important to take into consideration the diseases and pests that affect such species

in their native ranges, to develop proactive integrated pest management (IPM) programs.

Dispersal/ movements - The dispersal and movement capabilities of a species is something that

is unlikely to change and is related to the structure and quantity of seeds produced by a plant,

and method of seed dispersal (Young & Hammerson, 2016). This inherent dispersal ability is,

however, an important aspect of species that can contribute to their ability to migrate and

colonize new areas under future climate change (Young & Hammerson, 2016). Species that rely

on abiotic factors for dispersal, such as tree species that produce winged seeds that are wind-

dispersed, are generally scored less vulnerable in this category than those that rely on a small

group of species for dispersal (Young & Hammerson, 2016). These types of seeds, however, do

not typically travel more than 100 m from the source, unless carried in an updraft above the

forest canopy which is a highly unpredictable activity (Horn et al., 2001). In contrast, species

24

that have propagules that are carried by small mammals or birds can be found over 1 km from

the source (Conlisk et al., 2012). This phenomenon has been attributed to the population

persistence of Engelman oak [Quercus engelmannii Greene] in California and will likely

contribute to the persistence of Oak species in southern Ontario (Conlisk et al., 2012). The main

concern with plants that rely on a small number of species for dispersal is that if those

dispersers also experience population declines related to climate change, habitat loss and

fragmentation, or other factors. Thus vulnerability of dispersers and their ability disperse plants

in fragmented landscapes can have negative impacts on plant dispersal (Pearson & Dawson,

2005; Travis et al., 2013). In general, plants that can disperse greater distances will likely be

more resilient in the face of climate change as populations are not as isolated as those with

more limited dispersal abilities (Travis et al., 2013).

Genetic variation - The genetic variation of natural populations of any organism, including plants

contributes to the potential adaptive capacity of that species (Young et al.,2016). Since climate

change pushes systems beyond thresholds which they have previously experienced, forests

with greater genetic diversity will respond better to changes in abiotic conditions outside the

range that species are naturally adapted to (Alfaro et al., 2014). Phenotypic plasticity can only

go so far to allow individuals to respond to changes in climatic factors, and long-term health of

populations will rely on the ability of a species to adapt and migrate (Alfaro et al., 2014).

Several species in this assessment have reportedly low genetic variation including balsam fir,

spotted jewelweed, sensitive fern, eastern hemlock, and eastern white cedar (Klekowski &

Lloyd, 1968; Pandey & Rajora, 2012; Potter et al., 2012; Shes & Furnier, 2002; Toczydlowski &

Waller, 2019). Eastern white cedar reportedly shows much lower genetic variation than other

closely-related species Thuja plicata Donn and T. orientali Linnaeus, due to high rates of selfing

via vegetative reproduction (Pandey & Rajora, 2012). A similar observation has been made in

Balsam fir populations where the genetic variability is lower than most other conifers (Shes &

Furnier, 2002), and Eastern hemlock which has experienced large-scale inbreeding (Potter et al.,

2012).

Groups of interest

Spring ephemerals - Spring ephemerals are species of wildflower that bloom early in the spring,

before the forest canopy has closed, prior to leaf-out of many dominant tree species (Meier et

al., 1995). Jack-in-the pulpit was the only spring ephemeral species assessed in this project

however a recent study shows that this group of species may have already experienced 40%

decline in the last decade (Heberling et al., 2019). By measuring first leaf-out date (FLD) of the

canopy, and first flowering date (FFD) of jack-in-the-pulpit and comparing results to similar data

collected in Concord, Massachusetts in the late 1800s, they were able to quantify changes in

phenology. It was found that FLD has responded to increased spring temperatures by occurring

earlier in the spring, whereas FFD has been less responsive, thus narrowing the window of time

during which the spring ephemerals can photosynthesize. This has likely reduced the carbon

25

budget of these wildflowers to the tune of approximately 25%, leading to projected declines in

population of 10-48% (Heberling et al., 2019). Similar studies have not been conducted in

Ontario, however it could be hypothesized that similar impacts could be observed if measured.

This example of phenological mismatch has not been studied until recently and highlights a

larger issue in climate change science that is, it is nearly impossible to understand the

widespread effects of climate change on all taxonomic groups and we are likely missing many

fine-scale details about how phenology of forest plants is affected.

Invasive species - Understanding the impacts of climate change on invasive species will be a

crucial part of management planning (IUCN, 2017; Panda et al., 2018). Garlic mustard and

Common buckthorn were both ranked “LV” in this assessment which does not provide a very

encouraging view of the future condition of natural areas under climate change. Of course, the

exact characteristics that make these species invasive, those that allow them to rapidly colonize

new areas, and to withstand a variety of microclimatic conditions, also prove to be useful when

faced with increased temperature and droughts (Ren et al., 2009). One factor that could pose a

threat to invasive species in general is low genetic variation due to founder effects whereby a

small subset of a population is introduced to a new area, effectively reducing the genetic

variation of that “founding” population (Mullarkey et al., 2013). The origins of Garlic mustard

and Common buckthorn into North America show evidence of multiple introductions (Durka et

al., 2005; Kurylo & Endress, 2012; Meekins et al., 2001), therefore the species may be less

affected and have relatively higher genetic variation in local populations. In forests already

experiencing stress from climate change, disease, and fragmentation, invasive species may

become more prolific as we see changes in the forest canopy (Dukes et al., 2009).

Comparing results to previous work The results from the three studies as previously indicated in Table 3 that also used the

CCVI in relatively nearby geographic regions both agree and disagree with those found in this

assessment. Surprisingly, every species that overlapped with Brinker et al. (2018) were ranked

one step higher (more vulnerable) in the current assessment. It is likely the case that

vulnerability is scale-dependent- a result of different exposure scores at different scales. It is

also possible that variation in the literature review portion of the assessment and the individual

creating the rankings causes individual differences in species ranks. In this case it is more likely

the difference in spatial scale because when the exposure scores from that study were input

into the rankings for this assessment (everything else being the same), Sugar maple was ranked

“LV”, the same as in the Great Lakes study. This shortcoming of CCVI has been noted by other

researchers using the tool and has been addressed by using occurrence data at different spatial

scales and averaging the numeric scores for vulnerability (Griffis-kyle et al., 2018).

Three species overlapped with a study conducted in Michigan (Penskar, 2014) including

American beech, Eastern white cedar, and hemlock. All three rankings were the same as those

in this assessment which is encouraging as the study areas are not adjacent, however closely

26

related in terms of climate. The study that took place in West Virginia, however, did not

produce results that were unanimously in agreement (Byers & Norris, 2011). This is not

surprising as the geographic area is farther southwest than the Credit River Watershed.

The results of bioclimatic envelope modelling for the watershed conducted by Malcolm

et al. (2008), ranked species according to how the suitable habitat is expected to change under

future climate conditions, according to data from the third Coupled Intercomparison Project

(CIMP3), though since the time of this study new models have become available ( e.g. CIMP5 is

available). This does not take away from the fact that the ranges of several species are expected

to shift farther North and become reduced in the watershed (Malcolm et al., 2008). The species

that are deemed “losers” in Malcolm et al (2008) include Eastern hemlock, black ash, balsam fir,

paper birch, and yellow birch- all species that were ranked “HV” or “EV” in this assessment.

Generally, those ranked as “stayers” were scored “MV” which is interesting as the ranges may

not be expected to change much, although functional traits and future climate exposure may

work reduce the fitness of those species in the Watershed.

Mapping vulnerable communities The results of ELC mapping do not, by any means, provide a comprehensive enough idea of

the distribution of vulnerable communities. This will, however, prove to be useful contingent

Figure 6 Density of Lake Ontario Basin species found to be extremely or highly vulnerable to climate change as part of an assessment of the Ontario Great Lakes Basin (Brinker et al., 2018).

27

upon more detailed assessments in the future. In Ontario, Brinker et al. (2018), mapped the

density of vulnerable species across watersheds within the Great Lakes Basin (Fig. 6). This

approach is useful as it illustrates potential areas of concern and focus for further planning.

Since the study area was small for the current assessment, and CVC is a unique entity with its

own objectives and data, I was able to map vulnerability of four dominant tree species utilizing

information from the ELC. Should a similar process be adopted for all dominant vegetation, a

more comprehensive picture of how species vulnerability is distributed across the landscapes

could be developed.

Benefits and limitations Through testing and using the tool, I have been able to develop a list of benefits and

limitations of the CCVI and its use in broader applications (Table 4). These align closely with

what other users have identified (Young et al., 2015), and should be considered when moving

forward with future assessments at CVC, and other organizations in southern Ontario.

Table 4. Summary of the benefits and limitations of the Climate Change Vulnerability Index (CCVI) tool.

Benefits Limitations

✓ Accessible ✓ Easy-to-use ✓ Allows for rapid assessment of many

species ✓ A good first step to incorporate climate

change into natural heritage management

✓ Repeatable methodology that can be applied at various spatial scales

o Allows for communication across jurisdictional boundaries

✓ Allows for the expansion of projects to cover multiple taxa

✓ Can be used to identify areas of higher vulnerability when combined with spatial data

o Use in restoration planning ✓ Integration with species distribution

models is possible

▪ Provides simplified picture of climate change

o Only accounts for two bioclimatic variables

o Does not account for periodically wetter conditions due to increases in flooding

▪ Difficult to assess species under multiple climate change scenarios

o NatureServe can only provide climate data for RCP 4.5 in Canada

▪ Does not provide accommodation for species with multiple niches

▪ Results can be taken “at face value” without further analysis

▪ Gives the illusion of “doing something” but may not actually lead to implementation

▪ Susceptible to personal bias as criteria and rankings can seem arbitrary at times

o I am not an expert!

28

Recommendations

Future vulnerability assessments 1. Rank each species under multiple climate change scenarios- this is dependent on the

accessibility of downscaled climate data and may not be possible, however it should be

done. It is important to at least acknowledge the need to do so and indicate that the

required data is not available yet.

2. Conduct more detailed assessments based on groups of species- continuing the work

of mapping ELC communities according to vulnerability. This would also allow for a more

comprehensive study of vulnerable traits within each and to determine what species

may be good candidates for restoration and introduction. It would also create better-

organized reports and could be interpreted more easily by readers.

3. Work with other organizations- to identify roles and responsibilities in implementing

climate change into planning in southern Ontario. The MNRF should likely assume the

role of conducting larger-scale VAs and work with smaller organizations including

conservation authorities to implement targeted plans, or smaller-scale assessment.

Other work 4. Develop a plan for assisted migration of species with more southerly seed zones and

introducing more Carolinian species into natural areas to increase biodiversity. This is

imperative to ensure that decreased regeneration of native populations that can be

anticipated by climate change does not result in reduced overall canopy. There is a real

chance that invasive species will become more prevalent in the future as they are able

to take advantage of stressed out forest ecosystems.

5. Conduct a study on FLD and FFD of spring ephemerals (similar to Heberling et al., 2019)

to determine whether similar trends that have been found in Connecticut can be

observed in the Watershed.

6. Develop public education campaigns- to engage the general public on how climate

change is anticipated to affect natural heritage in the watershed. For example, a

campaign to explain how climate change is affecting populations of spring ephemeral

flowers would trigger an emotional response in people that could be leveraged to

increase advocacy for improved planning for climate change in natural areas.

Conclusion Upon completing this vulnerability assessment, several conclusions were drawn from

the process of using the CCVI and the species results. Most species in this assessment were

ranked as being vulnerable to climate change and the factors that contributed most to that

vulnerability were the hydrological niche, and past changes in precipitation, the presence of

pathogens or pests, dispersal and movement capabilities of seeds, any history of genetic

29

bottlenecks and low genetic variation, phenology, anthropogenic barriers, and thermal niche.

None of the species in this assessment are provincially or regionally rare, which highlights the

need to continue to view species through a lens that is unique to climate change. Traditional

conservation status rankings are not sufficient at identifying the threat of climate change to

natural heritage. The results from this study align with those found in similar assessments,

although different spatial scales likely contribute to differing vulnerability rankings, caused by

less severe exposure scores. Results can be applied spatially by imposing species vulnerabilities

onto ELC mapping communities dominated by species with varying degrees of vulnerability.

This may be useful as a coarse-scale filter to prioritize restoration, assisted migration, and

monitoring activities in the future.

The CCVI has its benefits in that it is generally easy-to-use, accessible, and does not

require much technical expertise beyond basic GIS skills to calculate exposure scores. Since this

has already been completed for CVC, future assessments using this tool will not need to go

through this step. Moving forward, a more concerted effort must be made to develop datasets

for multiple climate change scenarios, tailored to use with the CCVI so that assessors can better

incorporate the uncertainty of climate change into their work. The CCVI is a useful tool to

develop a basic understanding of how climate change may impact species in the future, and to

identify key areas to focus further research and work. In the coming years, I expect more

people will begin using this tool and it will be important to move ahead with clear goals for

managing natural areas for climate change resilience.

30

References

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Appendix A: Figures

Figure 1 Climate data used to calculate species' exposure to climate change in the Climate Change Vulnerability Index (CCVI) A) Projected future drying (Hamon AET:PET) by 2050 in the study area (RCP 4.5) B) Projected future temperature change (C) by 2050 (RCP 4.5) C) Historic mean annual precipitation (mm) for the baseline period (1961-1990) D) Historic mean seasonal temperature for the baseline period (1961-1990)

37

Figure 2 communities mapped based on the ecological land classification system (ELC) in the Credit River watershed, characterized by either Paper birch (HV), Red oak (MV), Sugar maple (MV), or Balsam fir (EV)- dominant. Climate Change Vulnerability Index.

38

Appendix B: Tables

Table 1 modified from Lankford et al. (2014) shows the comparison of the major input requirements for the NatureServe Climate ChangeVulnerability Index-Canadian release v3.0 (NSCCVI), U.S. Forest Service System for Assessing the Vulnerability of Species (SAVS), the Climate Change Sensitivity Database (CCSD), and The Environmental Protection Agency Framework for Categorizing the Relative Vulnerability of Threatened and Endangered Species to Climate Change

Assessment title

Major inputs

Type of tool

Uncertainty

score

Types of species

Geographic

areas covered

Author

SAVS Habitat

Physiology

Phenology

Biotic interactions

Online

questionnaire

yes Terrestrial

vertebrates

Canada and the U.S. US forest

service (Bagne

et al. 2011)

NSCCVI- Canada

v3.0

Downscaled change in

temperature

(Climate Wizard 2050s) and the

Moisture availability

(Hamon AET:PET,

Climate Wizard 2050s)

Current species distribution

Physiological, phenological

species traits

Knowledge of natural and

anthropogenic barriers

Documented adaptation

responses

MS Excel

spreadsheet

yes Terrestrial and

aquatic, all

taxonomic groups

Canada and the U.S. NatureServe

(Young et al.

2015)

CCSD Generalist versus specialist

Physiology

Life history traits

Habitat sensitivities

Dispersal ability

Disturbance regime

Ecological interactions

Database yes Terrestrial and

aquatic, all

taxonomic groups

Pacific

Northwest Canada and U.S.

University of

Washington/

Nature

Conservancy

(2012)

A Framework for

Categorizing the

Relative

Vulnerability of

Threatened and

Endangered Species

to Climate Change

Current population size

Population trend in the last 50

years

Current population trend

Range trend in the last 50 years

Current range trend

Current non-climatic stressors

Likely current stressor future

trends

Individual replacement time

Future vulnerability to

stochastic events

Future vulnerability to policy/

management changes

Future vulnerability to natural

stressors

Physiological traits

Framework yes Terrestrial and

aquatic, all

taxonomic groups

US

Environmental

Protection

Agency (EPA,

2009)

39

Table 2 Future climate conditions for each species, within the Credit River Watershed. Numbers represent the percent of pixels within the species range that fall into each category for change in temperature (C) and moisture (Hamon AET:PET)

Temperature Scope Climate Moisture Deficit Scope

Species English Name >3.8C 3.49-3.8C

3.17-3.48C

2.85-3.16C

2.53-2.84C <2.53C >56.68

38.87-56.68

21.05-38.86

3.23-21.04

-14.59-3.22 <-14.59

Abies balsamea Balsam Fir 0 0 0.32 99.68 0 0 0.1 99.9 0 0 0 0

Acer rubrum Red Maple 0 0 0.32 99.68 0 0 0.11 99.89 0 0 0 0

Acer saccharum Sugar Maple 0 0 0.37 99.63 0 0 0.1 99.9 0 0 0 0

Allaria petiolata Garlic Mustard 0 0 0.32 99.68 0 0 0.1 99.9 0 0 0 0

Arisaema triphyllum Jack-in-the-Pulpit 0 0 0.3 99.7 0 0 0.1 99.9 0 0 0 0

Betula alleghaniensis Yellow Birch 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Betula papyrifera Paper Birch 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Celtis occidentalis Common Hackberry 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Circaea canadensis Broad-Leaf Enchanter's Nightshade 0 0 0.32 99.68 0 0 0.1 99.9 0 0 0 0

Cornus alternifolia Alternate-Leaf Dogwood 0 0 0.32 99.68 0 0 0.1 99.9 0 0 0 0

Cornus sericea Red-Osier Dogwood 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Fagus grandifolia American Beech 0 0 0.32 99.68 0 0 0.1 99.9 0 0 0 0

Fraxinus americana White Ash 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Fraxinus nigra Black Ash 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Fraxinus pennsylvanica Green Ash 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Glyceria Striata Fowl mannagrass 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Impatiens capensis Spotted jewelweed 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Juglans nigra Black Walnut 0 0 0.23 99.77 0 0 0.12 99.88 0 0 0 0

Onoclea sensibilis Sensitive Fern 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Ostrya virginiana Ironwood 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Prunus serotina Black Cherry 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Prunus virginiana Chokecherry 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

40

Quercus rubra Northern Red Oak 0 0 0.32 99.68 0 0 0.1 99.9 0 0 0 0

Rhamnus cathartica Common Buckthorn 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Rubus pubescens Dewberry 0 0 0.33 99.67 0 0 0.1 99.9 0 0 0 0

Sassafras albidum Sassafras 0 0 0 100 0 0 0 100 0 0 0 0

Tilia americana American Basswood 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Tsuga canadensis Eastern Hemlock 0 0 0.33 99.67 0 0 0.1 99.9 0 0 0 0

Tuja occidentalis Eastern White Cedar 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Ulmus americana American Elm 0 0 0.31 99.69 0 0 0.1 99.9 0 0 0 0

Table 3 Scores for each factor of the Climate Change Vulnerability Index (CCVI) by species, in aplphabetical order by Latin name (N= “neutral”, U= “unknown”, SI= “somewhat increase”, Inc= “increase”, GI= “greatly increase”)

Sp

ecie

s

Sea l

evel

Natl

ba

rrie

rs

An

th b

arr

iers

La

nd

Use C

ha

ng

e

Dis

pe

rsal/M

ovem

en

t

His

t. t

he

rmal n

ich

e

Ph

ysio

l. t

he

rmal n

ich

e

His

t. h

yd

rol. n

ich

e

Ph

ysio

l. h

yd

rol. n

ich

e

Dis

turb

an

ce

Ice/s

no

w

Un

co

mm

on

Geo

Fe

atu

res

Oth

er

sp

p f

or

hab

Die

t

Po

llin

ato

rs

Oth

er

sp

p d

isp

Path

og

en

s/e

ne

mie

s

Co

mp

eti

tio

n

Oth

er

inte

rsp

ecif

ic

inte

racti

on

Gen

eti

c v

ar

Gen

bo

ttle

ne

ck

Rep

rod

uc

tive s

yste

m

Ph

en

ol

resp

on

se

Abies balsamea N N N U Inc SI Inc Inc Inc SI-N N N N N/A N N Inc U N SI N/A N/A N

Acer rubrum N N SI-N U SI SI N Inc SI N N U N N/A N N SI N U N N/A N/A SI-N

Acer saccharum N N N U SI SI N Inc SI-N SI-N N N N N/A N N U N U N N/A N/A SI-N

Allaria petiolata N N N U SI-N SI N Inc N N N N N N/A N N N U N N N/A N/A N

Arisaema triphyllum N N SI-N U SI-N SI SI Inc SI SI N N N N/A SI N U N U U U N Inc-SI

Betula alleghaniensis N N N U SI SI SI Inc Inc N N U N N/A N N Inc U N U N N/A U

Betula papyrifera N N SI U Inc SI N Inc N N N U N N/A N N Inc SI-N N N N/A N/A N

Celtis occidentalis N N SI U SI-N SI N SI N U N N N N/A N N N N N SI-N N/A N/A N

Circaea canadensis N N N U SI SI U Inc N N N N N N/A N N N U N N N/A N/A U

Cornus alternifolia N N N U N SI N Inc N U N N N N/A N N U SI-N N U N N/A Inc

41

Cornus sericea N N SI-N U SI-N SI U Inc SI N N N N N/A N N N N N N N/A N/A SI-N

Fagus grandifolia N N N U SI SI N Inc SI N N N N N/A N Inc-SI Inc N N N N/A N/A U

Fraxinus americana N N SI-N U SI SI N Inc SI U N N N N/A N N Inc N U U Inc N/A U

Fraxinus nigra N N SI-N U SI SI N Inc Inc N N U N N/A N N Inc SI N U Inc N/A U

Fraxinus pennsylvanica N N SI U SI SI N Inc N U N N N N/A N N SI N U U SI N/A U

Glyceria Striata N N SI-N U SI SI SI Inc Inc N N U N N/A N N U SI N U N N/A U

Impatiens capensis N N SI-N U GI-Inc SI SI-N Inc Inc U N N N N/A N N N N N Inc-SI N/A N/A U

Juglans nigra N N SI U SI-N SI U Inc SI-N N N U N N/A N Inc-SI SI U N N N/A N/A U

Onoclea sensibilis N N SI U N SI Inc-SI Inc Inc U N N N N/A N N N N N SI-N N/A N/A U

Ostrya virginiana N N N U Inc-SI SI N Inc SI-N N N N N N/A N N N N N U N N/A U

Prunus serotina N N SI U SI-N SI SI-N Inc N SI-N N N N N/A N N U SI-N N N N/A N/A U

Prunus virginiana N N SI U N SI N Inc N N N N N N/A N N SI N U U N N/A U

Quercus rubra N N SI U SI-N SI N Inc N N N N N N/A N N Inc-SI N N N N/A N/A U

Rhamnus cathartica N N N U N SI N Inc N N N N N N/A N N N N N SI-N N/A N/A U

Rubus pubescens N N N U Inc-SI SI U Inc Inc SI N N N N/A N N U N N U U SI-N U

Sassafras albidum N N Inc U SI SI N GI N N N N N N/A N N SI N U U U U U

Tilia americana N N N U SI SI U Inc SI SI N N N N/A N N U N N N N/A N/A N

Tsuga canadensis N N SI U Inc SI U Inc Inc N N N N N/A N N Inc N N SI N/A N/A U

Tuja occidentalis N N SI U Inc SI Inc-SI Inc Inc SI N N N N/A N N N N N SI N/A N/A U

Ulmus americana N N SI U SI SI U Inc Inc SI N N N N/A N N Inc N N U SI-N N/A N

42

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