INCIDENTAL TAKE and POPULATION DYNAMICS of NESTING BIRDS in a RED PINE (Pinus Resinosa) PLANTATION in SOUTHERN ONTARIO UNDER SINGLE-TREE SELECTION HARVESTING

INCIDENTAL TAKE AND POPULATION DYNAMICS OF NESTING BIRDS IN A RED PINE (Pinus resinosa) PLANTATION IN SOUTHERN ONTARIO UNDER SINGLE-TREE SELECTION HARVESTING

A Thesis Submitted to the Committee on Graduate Studies in Partial Fulfillment of the Requirements for the Degree of Masters of Science in the Faculty of Arts and Science

TRENT UNIVERSITY Peterborough, Ontario, Canada © Copyright by Ian R. Fife 2015 Environmental and Life Sciences Graduate M.Sc. Program May 2015 ii

Abstract

INCIDENTAL TAKE AND POPULATION DYNAMICS OF NESTING BIRDS IN A RED PINE (Pinus resinosa) PLANTATION UNDER SINGLE-TREE SELECTION HARVESTING

Ian R. Fife

I determined the direct influence of single-tree selection harvesting on the daily nest survival rates and nest success of 5 focal bird species within a monotypic red pine (Pinus resinosa) plantation on the western edge of the Oak Ridges Moraine in southern Ontario, Canada. I located and monitored 290 nests during the 2012 and 2013 breeding season. I used the logistic-exposure method to evaluate the daily nest survival rates of American Robin (Turdus migratorius), Eastern Wood-pewee (Contopus virens), Ovenbird (Seiurus aurocapilla), Rose-breasted Grosbeak (Pheucticus ludovicianus), and Red-eyed Vireo (Vireo olivaceus). Only five nests were destroyed as a result of forestry activity over the study period. Neither daily nest survival rates nor nest success of these focal species were substantially affected by single-tree selection harvesting. I also monitored the impact of single-tree selection harvesting on the density and territory size of 4 of 5 focal species. Ovenbird had a significantly smaller territory size but decreased density in the harvested areas. Although not significant, Eastern Wood-pewee and Red-eyed Vireo tended to have higher densities and larger territory sizes in harvested areas, whereas Rose-breasted Grosbeak showed a mixed effect as density was higher while territory size was smaller. Single-tree selection produces minor to moderate disturbance that takes place locally over a short period of time. As a result, nests that are indirectly disturbed by nearby harvesting, felling trees and mechanical operations and are not destroyed remain and adults do not appear to abandon eggs or young from the disturbance. Habitat alteration from harvesting of the general forest structure and especially the forest floor must be minimized in order to conserve forest bird species diversity. Further research examining incidental take using various intensities of single- tree selection harvesting would provide important insight into maintaining avian and forest diversity by means of forest management.

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Keywords: incidental take, forest management, single-tree selection harvesting, nest success, daily nest survival, logistic-exposure, density, territory size, Red Pine, monotypical forest, Northumberland County Forest, American Robin, Eastern Wood- pewee, Ovenbird, Rose-breasted Grosbeak, Red-eyed Vireo. iv

Acknowledgements

First and foremost I would like to thank Dr. Erica Nol for her direction and her support throughout my undergraduate and graduate career and especially during the completion of this thesis. I am grateful for the input from my committee members, Drs. Ken Abraham and Jeff Bowman whom provided very thoughtful and insightful comments towards the completion of this thesis. Your input during meetings and comments on my thesis pushed and challenged me to become a better student, writer and researcher. My gratitude is also highly expressed to Ben Walters for his statistical help and insight into forest management. Also, thanks are given to Dr. Samuel Haché for comments and insight on my thesis regarding landbird ecology and harvesting practices. I am also grateful for the field staff who helped during the 2012 and 2013 field season. Without their assistance I could not have completed this thesis. Thank you to David Geale, Mike Stefanuk, Devin Turner, and Walter Wehtje for every bit of help during my field seasons. A very special thank you to Steven Van Drunen, his expertise in nest searching was inspiring and always motivated me to find more nests. This study also could not be financially possible without the funding from Northumberland County and Trent University. Furthermore, to all the amazing friends I have met along this path; especially K. Chan and A. Marques. You helped me keep my sanity…most of the time. Finally, I would like to thank my family for their encouragement and support that was greatly needed throughout the completion of my thesis. Thank you Mom, Joanne, Michelle and Gary. Last but not least, thank you Jennifer Vincent for continued support throughout my endeavors.

Table of Contents Abstract ...... ii Acknowledgements ...... iii Table of Contents ...... iv List of Figures ...... vi List of Tables ...... viii

Chapter 1: General Introduction: Canadian Policy on Incidental Take of Migratory Birds within the Forestry Industry ...... 1 The Legal Framework for Incidental Take ...... 1 Issues Associated with Applying the MBR to Forestry Operations ...... 3 Canada’s Enforcement of Incidental Take Under the MBCA ...... 6 Present – Future implications of non-compliance with the MBCA ...... 9 Incidental Take and Indirect Measures of Bird Loss Through Single-tree Selection Harvesting ...... 12

Chapter 2: Incidental Take of Birds from Single-tree Selection Harvesting in a Southern Ontario Red Pine (Pinus resinosa) Plantation ...... 15 ABSTRACT ...... 15 INTRODUCTION ...... 16 METHODS ...... 19 Study Area ...... 19 Nest Searching ...... 20 Nest Monitoring ...... 21 Statistical Analysis ...... 21 RESULTS...... 22 DISCUSSION ...... 24

CHAPTER 3: Effects of Single-tree Selection on Density and Territory Size of 4 Bird Species in a Southern Ontario Red Pine (Pinus resinosa) Plantation ...... 41 ABSTRACT ...... 41 INTRODUCTION ...... 42 METHODS ...... 44 Study Site ...... 44 Territory Mapping ...... 46 Density and Territory Size ...... 48 Habitat Measurements ...... 49 RESULTS...... 50 vi

DISCUSSION ...... 54 Eastern Wood-pewee density and territory size ...... 55 Ovenbird density and territory size ...... 56 Rose-breasted Grosbeak density and territory size ...... 58 Red-eyed Vireo density and territory size...... 59 CONCLUSION ...... 61

CHAPTER 4: General Discussion ...... 73

LITERATURE CITED ...... 77

APPENDIX ...... 91

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List of Figures

Figure 2.1. Google Earth satellite image of the NCF. White outline in western portion of the forest indicates the area where the study and harvesting took place...... 28

Figure 2.2. The 27 forest compartments amalgamated into the 17 study sites comprising the study area. B-sites were harvested in winter/summer of 2013, C-sites are Control (unharvested) sites, S-sites are those that were harvested in the summer of 2012, and T-sites are those that were harvested in late winter of 2012. Map was produced using ArcGIS 10.1...... 29

Figure 2.3. The map displays the 28 nesting zones associated with the regional nesting periods within Canada. NCF falls within the C2 nesting zone of Lower Great Lakes/St. Lawrence Plain region. The lower image indicates the nesting calendar for the nesting zone and shows a total of 84 known forest bird species breeding in this region. The white area indicates 0 - <5% of the known breeding birds are nesting during this time period, yellow indicates 11 – 20%, orange – 21 – 40%, red – 41 – 60%, and dark red indicates 61 – 100% of known breeding bird species are nesting during this period (Environment Canada 2014a)...... 30

Figure 2.4. Nest outcomes during single-tree selection harvesting in the NCF over the 2012 and 2013 field season. Incidental Take referred to any disturbance, desertion and/or destruction presumed to be directly caused by forestry activity. Damaged and undamaged nests were empty of eggs or any other content most likely predated or deserted but confirmation of an appropriate outcome could not be determined by the observer ...... 31

Figure 2.5. Nest success of the 5 study species from the 2012 and 2013 field season in the NCF. Error bars indicate 95% confidence intervals...... 32

Figure 2.6. Comparison of daily nest survival rates (DNSR) with standard error bars of the 5 focal species by year and treatment factors in the NCF. Variation in daily nest survival rates was due to individual’s nest exposure and survival period. Only 2012 and Summer 2013 treatments are shown for Ovenbird due to lack of comparison as no nests were found in the Control treatment in 2013 or Winter 2012 treatments in 2012 ...... 33

Figure 2.7. Overall daily nest survival rates of the 5 focal species in 2012 in the 4 treatments. In 2012, Summer 2013 harvest period is treated as a control as the stand had yet to be harvested ...... 34

Figure 2.8. Overall daily nest survival rates of the 5 focal species in 2013 within the 4 treatments ...... 35

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List of Tables

Table 2.1. AIC model selection for daily nest survival rates for American Robin, Eastern Wood- pewee, Ovenbird, Rose-breasted Grosbeak, Red-eyed Vireo in Northumberland County Forest in 2012 ...... 36

Table 2.2. AIC model selection for daily nest survival rates for American Robin, Eastern Wood- pewee, Ovenbird, Rose-breasted Grosbeak, Red-eyed Vireo in Northumberland County Forest in 2013 ...... 36

Table 2.3. Nest success and daily nest survival rates (DNSR) of the 5 focal species during the 2012 and 2013 breeding season in the Northumberland County Forest (NCF) under single-tree selection harvesting ...... 36

Table 2.4. Results of AIC additive time effects model selection for American Robin, Eastern Wood-pewee, Ovenbird, Rose-breasted Grosbeak and Red-eyed Vireo in the Northumberland County Forest from 2012 – 2013. Focal species top-ranked models determined from AIC weight were carried over to the second suite of model selection against year and treatment. The null model was the top-ranked time effects model for Red-eyed Vireo and was not considered for further model selection ...... 37

Table 2.5. Exploratory AIC model selection including year, treatment and the top-ranked time effects suite for American Robin, Eastern Wood-pewee, Ovenbird and Rose-breasted Grosbeak on daily nest survival rates in the Northumberland County Forest in 2012 and 2013. Candidate models were considered if ΔAICc was < 4. Since no single model exhibited an AIC weight > 0.9, model-averaged parameter estimates were considered from the candidate models ...... 39

Table 3.1. Habitat models describing the densities of 4 focal species in the Northumberland County Forest. Eight model variables, with the exception of Rose-breasted Grosbeak which contained 16 model variables were selected based on each species known habitat preferences from the literature. Only the models with cumulative weight (ωi) > 0.9 were retained ...... 63

Table 3.2. Model averaged parameter estimates with associated 95% confidence intervals of the density estimates of 4 focal species from habitat variables in the Northumberland County Forest during the 2012 and 2013 breeding season. Significant parameter estimate habitat coefficients are bolded and italicized ...... 64

Table 3.3. Habitat models describing the territory sizes of 4 focal species in the Northumberland County Forest. Eight model variables, with the exception of Rose-breasted Grosbeak which contained 16 model variables were selected based on each species known habitat preferences from the literature. Only the models with cumulative weight (ωi) > 0.9 were retained ...... 65

Table 3.4. Model averaged parameter estimates with associated 95% confidence intervals of the territory size estimates of 4 focal species from habitat variables in the Northumberland County Forest during the 2012 and 2013 breeding season. Significant parameter estimate habitat coefficients are bolded and italicized ...... 66

Table 3.5. Habitat characteristics in the Northumberland County Forest measured after the 2013 harvest period. Variable means were compared between treatments using one-way ANOVA ...... 67

APPENDIX

Table A. Mean density and territory sizes of the four focal species throughout the Northumberland County Forest in 2012 and 2013 ...... 87

Table B. Mean densities of four focal bird species by harvest treatment in the Northumberland County Forest in the 2012 and 2013 breeding season. Significant changes in species’ territory sizes are bolded and italicized. Significance was set at α = 0.05 ...... 88

Table C. Mean territory size by treatment level of the 4 focal species in the Northumberland County Forest during the 2012 and 2013 breeding season. Significant changes in species’ territory sizes are bolded and italicized. Significance was set at α = 0.05 ...... 89

Chapter 1: General Introduction: Canadian Policy on Incidental Take of Migratory Birds within the Forestry Industry

The Legal Framework for Incidental Take Birds often breed in habitats that are also used by humans for many purposes (e.g., industry, mining, forestry, road building, homes, agriculture). Most migratory birds have legal protection under Canadian federal and/or provincial law. Thus when industrial, economic, or recreational activities negatively affect birds, this is termed “incidental take”. Environment Canada defines “incidental take” as the inadvertent disturbance and/or destruction of a bird’s nest and eggs (Environment Canada 2014a). Historically, the importance of preserving and conserving migratory birds has been recognized since the United States and Great Britain, for Canada, signed an international agreement on December 8, 1916 entitled Migratory Birds Convention (CEC 2006). Under the original document the two governments agreed to “regulate their take” and protect the lands on which migratory birds depend (Holland and Hart, LLC 2010). The Migratory Birds Convention was amended in 1995 and collectively named Canada Treaty (Holland and Hart, LLC 2010). The amendment clearly states under Article II.3 that the taking of nests or eggs of migratory birds is strictly prohibited unless for scientific, educational, propagating or “other specific purposes” that may seem appropriate. Other specific purposes are not clearly defined, but the Treaty’s distinct objective is to preserve migratory bird habitat and the maintenance of sustainable populations (Holland and Hart, LLC 2010). Nationally, incidental take falls under s. 12(h) of the Migratory Birds Convention Act, 1994 (MBCA) and is regulated under s. 6 of the Migratory Birds Regulations (MBR). The MBCA states that the Government of Canada can establish regulation prohibiting the, “…killing, capturing, injuring, taking or disturbing of migratory birds or the damaging, destroying, removing or disturbing of nests”. The MBCA was originally passed in 1917 making it an offence punishable by law to incidentally take any migratory bird species and upon conviction a fine and/or prison sentence would be served (CEC 2006). Disturbances described within s. 12(h) can come in many forms such as mining, agriculture, electrical generation and transmission, fishing, management of

1 infrastructure, urban development, and forestry (Calvert et al. 2013, Environment Canada 2014a). Similar to the amendment made to the Canada Treaty in 1995, s. 12(h) of the MBCA was amended in 1995 under Article V and included the statement that “High Contracting Powers” have the ability to permit “other specific purposes” that are deemed appropriate for the taking of all migratory birds listed under Article I of the MBCA. Also, Article VII allows killing of migratory birds listed under Article I if the birds becomes a serious risk to “agriculture or other interests”. In Ontario, under the Ontario provincial, Fish and Wildlife Convention Act, 1997, incidental take is referred to in s. 7 with minor differences between this Act and the MBCA. Also, the Fish and Wildlife Conservation Act s. 7(4) refers back to the MBCA for migratory bird protection. Since the MBCA is federal legislation and was signed while Canada was governed by the United Kingdom, constitutional stipulations were made when the Treaty was signed to give the federal government sole authority to implement regulations associated with the MBCA (Opalka 2011). However, environmental protection, including the MBCA, is not expressed in the Constitution, therefore provinces have jurisdiction over many environmental issues (Opalka 2011, Becklumb 2013). To enact environmental regulations the federal government must obtain provincial signoff, as the provinces felt it was within their rights to produce their own laws and authority when it came to development, conservation and management of non-renewable resources as well as forestry resources (CEC 2006, Opalka 2011, Natural Resources Canada 2014a). Consequently, Constitutional legislation entitles provincial jurisdiction to rule over federal regulations if the defence claims can be proven in court. However, with regards to the MBCA, federal regulations have been upheld in court. Constitutional legislation further dictates that provinces have the ability to regulate most business and industrial activity on their land under sections 92(5) (management of provincial Crown land) and 92(13) (property and civil rights) (Becklumb 2013). Since most public land in Ontario is owned by the province (s.109 of the Constitution), Crown land can be sold or leased to a third-party and the province has the authority to allow logging on Crown land (CEC 2006).

Issues Associated with Applying the MBR to Forestry Operations There are three primary silviculture methods used in Ontario: shelterwood, single-tree selection cutting and clear-cutting (OMNR 2000, Jobes et al. 2004). Shelterwood involves a series of 2 – 4 harvest cuts retaining significant forest cover or a well-established young forest immediately after the final harvest (OMNR 2001). Each cut is typically done for a specific reason and the second and third cut will depend on good seed years to establish healthy offspring from the residual parent trees (OMNR 2000). Single-tree selection is the least intensive form of silviculture and is intended to mimic natural small scale, gap-phase disturbances such as blowdown and tree senescence and allows for tree regeneration (Jobes et al. 2004, Tozer et al. 2010). Single-tree selection harvesting attempts to obtain a target basal area through partial cutting and always maintains a forest canopy. Typically, selection systems occur 8 – 25 years and are completed by removing 1/3 of the forest canopy during each cut. For management purposes, single-tree selection attempts to increase shade-tolerant trees and maintain uneven-aged forests (OMNR 1998, Jobes et al. 2004). After many harvests, uneven-aged timber management results in the creation of a stand with uneven tree age and size with acceptable regeneration as younger cohorts take the place of the removed canopy trees (Millington et al. 2011). Clear-cutting, by contrast, involves clearing all commercially valuable trees and creates large openings and is intended for the harvest of even-aged forests creating high light levels (Jobes et al. 2004, OMNR 1998). This method of silviculture is the most common practice used in the boreal forest of northern Ontario and is predominantly used for economic reasons. Furthermore, clear-cutting is the most common technique to emulate large natural disturbances such as wind storms, fire, disease and insects that can clear thousands of hectares and is necessary for forest renewal (OMNR 1998, Pitt 2012). The boreal forest consists of even-aged stands, and for this reason, clear-cutting can also provide ecological benefits that mimic natural disturbances (Pitt 2012). Originally, clear-cuts were designed with large geometric shapes but recent practise has moved away from this design to give residual structure of forest stands a more natural

3 outcome by retaining large trees and sustaining and restoring complexity in the forest (Pitt 2012, Montgomery et al. 2013). Residual structure also provides wildlife with more natural habitat to add to biological diversity (Pitt 2012). On a larger scale, unpredictable environmental conditions (i.e., wildfire or disease) could lead to overharvesting and result in additional removal of habitat for birds and other wildlife. The ambiguous wording of certain aspects of the MBCA results in governments that allow the taking of migratory birds (Villard and Nudds 2010). For example, a nest must be recognized as a “known value” (OMNR 2009a). However, as there is uncertainty as to what is considered a “known value” it is not perceived to hold any political or legal guidance according to the Secretariat that provides administrative, technical and operational support to the Council of the Commission for Environmental Cooperation (CEC) of the North American Free Trade Agreement. This term holds very broad implications as there is no definitive explanation as to its specificities and the object given a “known value” can be omitted if there is inadequate information (refer to OMNR 2009b for definition). Another example relates to practise around raptor (Accipitridae spp.) and Great Blue Heron (Ardea herodias) nests during forestry activities, where, once raptors and heron nests are found, the nests are considered an “area of concern”. However, “areas of concern” are provincial policy and not subjected to criminal law. In most provincial forest management plans, once raptor or Great Blue Heron nests are located the area is established as a “known value” and buffers must be placed around these nests. Since Great Blue Herons, Eagles (Haliaeetus leucocephalus) and Ospreys (Pandon haliaetus) will renest in the same location year-after-year, this term can hold throughout the year when environmental assessments are being completed. However, for most forest management plans the terms, “known value” and “area of concern” seem to be irrelevant for any other breeding migratory bird species that renest in different yearly locations unless protected under the Species at Risk Act, 2002 (s. 32). Furthermore, some provincial forest management plans add “value” to only certain bird species (i.e., raptors, heronries and waterfowl (Anatidae spp.) while a project is undergoing environmental assessments (Declaration Order MNR-71 2003).

Despite an increase in sustainable development policies, political will and the funding to enforce policies remains inadequate (McRobert and Ruby 2009). The current direction for Environment Canada is the cooperation between individuals, government and industry to maintain sustainable bird populations by (1) promoting awareness and compliance of the MBCA and its Regulations, (2) developing and communicating strategies for conservation efforts and; (3) following up with actions to investigate and ensure legislation is being properly observed (Environment Canada 2014a). To ensure that these three criteria are met, environmental assessments must be completed throughout the entire stage of development. In northern Ontario, Quebec and British Columbia, where the majority of clear-cut forestry (one of the largest industrial impacts on migratory birds) takes place, the assessment costs of these areas may be too great to mitigate a certain level of incidental take. For example, a 3-year collaborative study on incidental take carried out by Environment Canada and Tembec assessed habitat models for 6 bird species in 1.5 million hectares of a 2.7 million hectare management unit resulting in total project cost of $86,000 (Wells et al. 2009). However, this cost did not include the cost for the third criteria of investigating to ensure forestry operations were adhering to the regulations of the MBR within the study’s management unit. Furthermore, under the Canadian Environmental Assessment Act, 2012 s. 52(4), if the economic benefits outweigh the ecological and assessment costs, the Governor in Council may deem a particular project justified if the project does not have “significant adverse environmental effects”. Under the regulations of the Canadian Environmental Assessment Act, 2012 s. 5(1)(a)(iii) all migratory birds mentioned in the MBCA are considered when an environmental assessment is required. However, habitat and bird surveys are not complete as most of these surveys produce large gaps as a small portion of the entire area is sampled with subsequent analyses using models to extrapolate the likelihood that species can be found within a given area (Barry and Elith 2006, Lele et al. 2012). Furthermore, it would be nearly impossible and impractical to locate all nests of migratory birds, as most are small, hidden away high in the canopy, or closer to the

5 ground and well concealed by vegetation. Despite this drawback, habitat and bird surveys provide the most practical way to acquire the information needed to mitigate incidental take over broad landscapes. In southern Ontario for example, where selection cutting is the most widely used silviculture method, the planner must walk the forest to mark the trees to be harvested. As a result, nests are easier to find and classification and logistical cost for finding nests are greatly reduced before harvesting begins. On the other hand, in northern Ontario where clear-cutting is the main harvesting method, aerial surveys for large raptors and some heron nests are completed but the majority of all bird nests get over-looked or funding is not available because the logistical cost to cover large tracts of land is so great (CEC 2006).

Canada’s Enforcement of Incidental Take Under the MBCA Environment Canada authorities do not regulate incidental take but rather suggest that the company or individual causing the disturbance should practice due diligence with respect to the MBCA and its regulations (Environment Canada 2014a). On indictment for taking migratory birds under the MBCA, a maximum fine of $1,000,000 and up to 3 years in prison can be issued (s. 13(1.1)(a)); a repeated offence can result in a doubling of the original fine (s. 13(2)). Furthermore, if destruction continues on a daily basis, each day is counted as a separate offence just as each destroyed or disturbed nest can be considered as a separate offence (s. 13(3-4)). Other court orders can include one or more of appropriate monetary or environmental actions such as undergoing an environmental audit, carrying out remedial or preventative action to migratory birds, and/or paying an environmental group for management, conservation or protection of migratory birds (s. 16). The CEC drew up an environmental report for the North American Agreement on Environmental Cooperation (NAAEC) regarding forestry practice in Ontario and in order to apply charges in Ontario to a stakeholder for a practice such as forestry, a nest must be identified as such and then mapped according to Ontario’s Forest Management Planning Manual as a “known value” and “area of concern” (OMNR 2009a). The stakeholder must consider avoid felling the tree where the nest was found and a buffer of trees must be left around the nest(s) (OMNR 2000, CEC

2006). If indicted, to avoid conviction under the MBCA the stakeholder in question must provide evidence that, beyond a reasonable doubt, they took the appropriate actions to circumvent the destruction of migratory birds and their nests and eggs (CEC 2006, see also Migratory Birds Convention Act s. 13(17)). Under the Canadian Environmental Assessment Act, 2012, it is the responsibility of the proponent of a project that might lead to incidental take of migratory birds to provide an environmentally sound assessment of the area to be disrupted. To best avoid indictment under the MBCA, Environment Canada suggests Beneficial Management Practice (BMP) for individuals and companies to decrease the risk of interfering with “unregulated” migratory birds and their nests and eggs. However, individuals and companies and stakeholders are therefore subject to voluntary actions when conducting business because Environment Canada cannot authorize the implementation of BMP’s. Environment Canada provides a service to proponents to determine which BMP would provide the most protection for migratory birds. While best business, management and conservation practices should be the priority with respect to the environment and migratory birds, this however provides an opening for violation of the MBCA (Environment Canada 2014a). If BMP’s are recommended over enforcement of regulations of the MBCA then Canada violates the international agreement made with the CEC (Ecojustice Canada 2011). The BMP’s allow industry to build, harvest or mine areas where migratory birds may be nesting with the expectation that industry is providing the best course of action to avoid destroying valuable habitat required for nesting migratory birds (Environment Canada 2014a). Furthermore, Environment Canada does not have authority to recommend which BMP is most effective given a particular industrial circumstance. Instead, Environment Canada provides development recommendations to industry based on timing of bird arrival on the breeding grounds (Environment Canada 2014a). As with most acts, there are complications with ambiguity of interpretation; adding to the difficulty is the federal-provincial disconnect between the MBCA and constitutional law which may favor provincial legislation over federal (Opalka 2011).

Since 1917 only two known cases have gone to court from industry, for either depositing a harmful substance or for the destruction or disturbance of migratory birds or their nests. The first case (R. v. Syncrude Canada Ltd., 2010 ABPC 229) fell under s. 5.1(1) which states a harmful substance, in this case, bitumen in a tailing pond that resulted in the death of a number of birds, cannot be deposited in habitat frequented by migratory birds. The defence claimed De minimis, which suggests the defence believed the death of the birds was trivial and not worthy of the Courts time, however the Court ruled that Syncrude Canada Ltd. did not apply due diligence and should have foreseen the offence to occur and the company was subsequently found guilty of the offence. The only filed court case of incidental take from forestry activity occurred in 2008 (R. v. J.D. Irving Ltd.) when J.D. Irving Ltd., a large Canadian forestry company, damaged or disturbed a colony of eight Great Blue Heron nests in the province of New Brunswick. Under New Brunswick’s Forest Management Plan, Great Blue Heron nests require a buffer zone of 50m during the non-breeding season and ≥ 200m of no-activity zone and a ≥ 400m no-roads zone during the breeding season (Government of New Brunswick 2004). J.D. Irving Ltd. alleged s. 6 of the MBR was directed towards hunting legislation and not towards industrial activity. The defence also claimed the law unconstitutional as the federal legislation imposed upon the provincial jurisdiction over property and civil rights (ECELAW 2014). Additionally, J.D. Irving Ltd. argued s. 7 of the Charter in which terms such as “destroy”, “disturb” and “nest” were vague and overbroad. Despite its argument, the heronry area was identified by J.D. Irving Ltd. during the environmental assessment and in an effort to protect the habitat; the heronry was marked to avoid destruction and/or disturbance. However, while creating a roadway to access a management unit, the trees in which the nests were contained were damaged and/or destroyed. The court dismissed J.D. Irving Ltd.’s assessment of the MBR as hunting legislation. The Court also referred to Canada’s obligation to implement the NAFTA international treaty under NAFTA’s environmental sector, the CEC. With regard to the dispute of vagueness, the Court held the terms are understood by the average citizen

8 and the argument void. The Court also ruled the regulations were not overbroad because the objective that the protection and conservation of migratory bird habitat was perfectly clear and their nests are not to be damaged or destroyed (ECELAW 2014). As a result, J. D. Irving Ltd. was found guilty and penalized $60,000 for the infraction. J. D. Irving Ltd. allocated the $60,000 towards a $10,000 fine and a $50,000 contribution to Bird Studies Canada.

Present – Future implications of non-compliance with the MBCA Before October 2010, Environment Canada had been developing a regulatory initiative that would conserve migratory birds and their nests by creating enforceable conditions that would have penalized logging, mining, pipeline laying, and agriculture practices for any unnecessary destruction of migratory birds (Ecojustice Canada 2011). Villard and Nudds (2010) note that Environment Canada has chosen to work with interested parties to come up with a plan that benefits both the migratory birds and stakeholders. As a result, the original initiative was abandoned largely due to stakeholder input and a change in Environment Canada’s overall priorities (van Havre 2011). Rather, Environment Canada works with stakeholders and provides scientific information on risk factors associated with incidental take. By providing stakeholders with consistent and appropriate information, increasing awareness to migratory bird conservation and protection of migratory birds and their nests and eggs can be improved (van Havre 2011). Environment Canada has recently provided a map on its website (Figure 2.3) delineating Canada into 5 nesting zones and split further into 28 regional nesting periods based on mean annual temperature (Environment Canada 2014a). Environment Canada then provides nesting calendars of these 28 regions which provides peak nesting periods and buffer zones for all species’ nests protected under the MBCA to stakeholders and the general public who can then plan optimal work planning to avoid peak breeding periods (Environment Canada 2014a). An overlooked condition with the structure of this conservation plan occurs during peak migration periods of birds through the flyways of Canada. If a forestry company is to abide by the nesting calendars provided by Environment Canada,

9 harvesting would ideally take place during non-breeding periods. However, under some provincial legislation, conservation efforts cannot excessively reduce the timber supply and in some cases a mandate is in place that limits timber supply to be reduced by no greater than one percent (see Forest Planning and Practices Regulation, B.C. Reg. 14/2004 s.7(1)) (ELC 2010). This leads to greater amounts of harvesting during non- breeding periods and imposing then on peak migratory periods such as fall and spring. Furthermore, regulations such as the B.C. Reg. 14/2004, clearly describe that the policy fails to protect key species habitat resources, habitat connectivity, and population viability (Ministry of Land, Water and Air Protection 2004, ELC 2010). However, if an important stopover site is destroyed before or during migration, the risk of adding stress to an already physiologically demanding event for many species potentially causes greater stress on the individual as well as their ability to produce a successful nest (O’Connor et al. 2014). Therefore, an individual’s or a population’s condition could succumb to potential carryover effects from migration on subsequent breeding success (O’Connor et al. 2014). Furthermore, these regulations are not enforced and it is the responsibility of the forest managers to attain the required permits and adhere to the specified laws and regulations. Incidental take is still quite prominent on the landscape especially in areas that are being developed and, as a result, assessments will always be required to incorporate a formal framework that allows a certain level of incidental take that benefits development while minimizing harm to wildlife species (Runge et al. 2009). However, a lack of formal framework creates issues at a much greater level as each industry produces a separate level of incidental take. In order to reduce the level of take produced by a specific industrial activity, assessments for each activity site would be required to establish bird densities during the different seasons. Furthermore, a particular industry such as forestry has different levels of take depending on the method of silviculture employed. For example, single-tree selection harvesting will have a different level of incidental take compared to clear-cut harvesting. As of yet, little

10 research has been completed on the effects industry causes to nesting migratory birds through incidental take. In an effort to reduce incidental take on forested landscapes, Environment Canada (2014a) suggests that industry consider Beneficial Management Practices (BMP) before harvesting. BMP’s are intended to provide sound conservation strategies based on scientific research on ecological management of migratory birds. In Ontario, the Crown Forest Sustainability Act, 1994 regulates forestry operations to achieve forest sustainability. Additionally, each province has a specific Forest Management Plan (FMP) directed at industry with focus on sustainability and resource management policies, strategies and conservation efforts (OMNR 2009a). When Loehle et al. (2006) simulated Sustainable Forestry Initiative with multiple habitat and economic variables into a forest management strategy, they found that increasing landscape age heterogeneity by leaving small patches of forest maintains avian diversity and provides economic stability by reducing forestry operation costs and should be a consideration to forest managers to provide a more sustainable and biologically diverse forest. Therefore, BMP’s in conjunction with provincial FMP presents industry with an opportunity to lessen the impact placed on migratory birds and their habitat while not suffering economic loss. The most important aspect of a forest contributing to avian diversity and productivity is providing a diverse structure. Over the past 30 years across North America, pressure to create sustainable forest management systems resulted in the forestry industry shifting its efforts towards emulating natural disturbances as a method for conserving biodiversity, as well as economic longevity (Long 2009). In fact, the Crown Forest Sustainability Act (1994) in Ontario mandates the use of natural disturbance emulation for the “long term health and vigor” of provincially owned forests. The practice of mimicking natural disturbances revolves around the premise that wildlife have adapted and evolved around stand and landscape alterations produced by natural processes such as fire, wind throw, etc. (Long 2009, Villard et al. 2012). Thus, sudden anthropogenic changes in habitat conditions that mimic these may potentially benefit species that rely on landscape alterations to complete certain life-history strategies

(Long 2009, Newell and Rodewald 2012). However, the extent of emulating natural disturbances for conservation efforts is limited when taking into account the spatial and temporal factors of natural conditions that can differ greatly among regions (Mori 2011). For example, a literature review conducted by Schieck and Song (2006) found bird diversity differed greatly immediately post-harvest and post-disturbance from that present prior to the disturbance. After 30 years of natural regeneration, similar bird communities were first noticed between the post-disturbance and post-harvest treatments, it was almost 60 years before bird communities between the treatments became similar to pre-harvest and pre-disturbance levels. In Ontario, harvesting and thinning during prime breeding periods (June, July, and August) accounts for only 0.04% of Canada’s harvested forests (Thompson et al. 2009). Therefore, Thompson et al. (2009) suggest that mortality of migratory birds during the breeding season as a result of forest harvesting is relatively low compared to natural disturbances, such as wildfire which can average up to 11 times that area in any given year. Despite this, species richness and density, food availability, predation, male pairing and nest success can all be affected by forestry operations (Burke and Nol 1998, Ellis 2010, Eng et al. 2011, Sheehan et al. 2013).

Incidental Take and Indirect Measures of Bird Loss Through Single-tree Selection Harvesting

The response birds have to single-tree selection forest management can be complex. For example, generalists are typically more resilient while specialists are sensitive to sudden changes (Doyon et al. 2005, Tozer et al. 2010, Boves et al. 2013). Birds nesting at various tree heights or in various substrates (e.g., on the ground, in snags or downed logs) can be differentially sensitive to forest management (Barber et al. 2001, Rodewald and Yahner 2001, Sallabanks and Arnett 2005, Straus et al. 2011, Newell and Rodewald 2012). Maintaining vertical and horizontal heterogeneity of the stand is very important to consider when managing for bird diversity (Millington et al. 2011). Habitat alteration from single-tree selection harvesting during the breeding period may lead to an impact on nest success and also increase incidental take.

Partially harvested forests (e.g., shelterwood and selection) can also create ecological traps. Late successional specialist Cerulean Warblers (Setophaga cerulea) increased in abundance post-harvest and males were in better condition in partially harvested forests than males in unharvested forests (Boves et al. 2013). Abundance however, did not relate well to productivity and nest success, as both these latter measures were lower in the managed forest. Boves et al. (2013) suggest management should be considered at the local and the broader landscape scale to maintain high productivity for this particular species. On a broader scale, Barber et al. (2001) suggested that single-tree selection produced an intermediate number of nesting birds, and hence, provides a more suitable strategy for managing forests for avian biodiversity. Moreover, a literature review by Sallabanks and Arnett (2005) acknowledged an increase in bird populations from single-tree selection harvesting when compared to even-aged forest management. A recent estimate of incidental take by forestry activity in boreal forests of Canada was conservatively calculated to be between 616,000 – 2.09 million potentially damaged nests (Hobson et al. 2013). These authors based the estimate on nesting density from point count data and acknowledge, however, that point count data may not be an accurate method to measure incidental take because the information is not designed to measure avian nest density; and instead, spot mapping would provide a better estimation for nest density. Additionally, monitoring nests of various bird species while harvesting is occurring contributes to a more reliable estimation of whether silviculture practices have an effect on nesting success (Barber et al. 2001), especially in evaluating the impacts of partial harvest methods on birds. At the same time, attempting to locate all bird nests in such an expansive area as the boreal forest presents issues, such as an incomprehensible amount of time and money (CEC 2006, Wells et al. 2009). The goal of establishing threshold ranges is not to determine if alterations to avian habitat from harvesting has an effect on forest birds. Instead the objective should be to locate and identify threshold ranges of harvest so habitat changes do not significantly alter bird populations (Guénette and Villard 2005). Forest managers

13 often make a compromise between silviculture methods that balance economic gross income with providing maintenance of habitat for wildlife and ecosystem function (Becker et al. 2011). Forest managers will continue to depend on scientific information for answers to ecological and management questions such as: what is the minimum amount of altered forest habitats that must be preserved to avoid species loss, what species are more important to conserve (keystone, umbrella species or species-at-risk) and, should threshold targets be placed conservatively to prevent species extinction (Rompré et al. 2010)? Therefore, the need to directly evaluate the level of take from forestry operations should be a priority measure in order to maximize bird productivity while ensuring regulatory enforcement actions are carried out under federal and provincial regulations.

Chapter 2: Incidental Take of Birds from Single-tree Selection Harvesting in a Southern Ontario Red Pine (Pinus resinosa) Plantation

ABSTRACT In 2012 and 2013, I measured the short-term effect of single-tree selection harvesting occurring during the breeding season on adult daily nest survival rates and nesting success of 5 focal breeding bird species in a 244 ha red pine plantation located in southern Ontario. Single-tree selection is a relatively low intensity harvesting treatment intended to remove an average of one-third of the basal area within the stand. I predicted single-tree selection harvesting would not have a serious impact on the daily nest survival rates or the nesting success of the five focal species. I searched for and monitored nests while harvesting was taking place and measured daily nest survival rates and nest success of the focal species using the logistic-exposure method. Daily nest survival rates of the five focal species ranged from 0.883 – 0.976 and nest success of the five focal species ranged from 21.1% - 43.0% over the 2012 and 2013 breeding periods, respectively. There was no significant effect on these rates from single-tree selection harvesting among all treatment levels. These findings suggest that low intensity harvesting from single-tree selection silviculture when compared to non- harvested areas does not significantly affect the daily nest survival rates and nest success of these five focal species. From early May to late June, single-tree selection harvesting took place and resulted in incidental take on the study area with 3% and 1% of nests located prior to harvesting directly destroyed due to forestry activities in 2012 and 2013, respectively. Similar studies should incorporate objectives to quantify incidental take in response to silvicultural practices taking place during the breeding season with different levels of harvesting intensities and forest types to determine a threshold of incidental take that would not negatively affecting migratory birds.

INTRODUCTION Avian “incidental take” refers to the inadvertent disturbance and/or destruction of a bird’s nest and eggs (Environment Canada 2014a). This disturbance can come in the form of mining, agriculture, electrical generation and transmission, fishing, management of infrastructure, urban development, and forestry (Longcore and Smith 2013, Environment Canada 2014a). Incidental take is regulated under the federal Migratory Birds Convention Act, 1994 (MBCA) and the Migratory Birds Regulations. Despite the federal regulations, provinces have jurisdiction over management of most natural resources, including forestry, where extractive activities affect migratory birds and their habitat. Forestry can potentially produce a great risk to migratory bird nests and eggs depending on the time of year harvesting takes place. However, despite the increasing human awareness of the need for avian conservation in forested landscapes, there is still much concern over the impact of incidental take from forestry operations, on the nesting success of certain bird species (Natural Resources Canada 2010). Three silviculture methods are employed in Ontario to emulate natural disturbances. Clear cuts are similar in spatial extent and severity to wildfire, insect outbreaks and disease and are primarily prescribed in even-aged boreal forests of Ontario (OMNR 2000). Selection and shelterwood harvesting mimic windthrow and natural death of single trees and are intended to produce an uneven-aged forest stand usually with an existing established diversity of shade-tolerant hardwood trees such as maple (Acer spp.) and American beech (Fagus grandifolia) (OMNR 2000). These methods are prescribed in southern Ontario where more hardwood forests are located but are also used occasionally in boreal forests where stands of aspen (Populus spp.) are dominant. The potential ecological benefits of single-tree selection systems are the preservation of intact vertical forest structure and heterogeneity, thereby retaining habitat for birds and other wildlife (OMNR 2000; but see Angers et al. 2005). Low intensity harvesting such as single-tree selection cutting has been shown to have a much lower impact on bird nesting success compared to intensive silviculture methods such as

clear-cut harvesting (Smith et al. 2006, Straus et al. 2011, Kendrick et al. 2014). Given that single-tree selection harvesting systems are an economically viable approach that would minimize the impacts of forestry on the ecosystem, it is often the most applied harvesting method across North America (Vanderwel et al. 2007, Falk et al. 2008). Nevertheless, quantifying the direct effects of silviculture methods is becoming a growing concern for birds nesting in Canada (Hobson et al. 2013). Many forests in the mixedwood plains ecozone of southern Ontario have been replanted with red pine (Pinus resinosa). Red pine became the most planted tree species in southern Ontario in the 1920s because it grows well in poor soil and is merchantable (OMNR 2010). It was also planted to restore nutrient depleted land from poor land use practices over the past century (i.e., agriculture). Ultimately, the goal of these plantations is to restore mixedwood forests; however, proper management of red pine plantations by thinning and harvesting mature trees early is required to do so. For example, mature plantations with closed canopies have lower soil temperatures than more open stands which in turn reduce organic matter decomposition rates and increase conifer litter depth and impede healthy forest development (Cavard et al. 2011). At maturity, a monotypic conifer forest will release an abundance of conifer litter resulting in a decrease in soil fertility and acidification (Prescott et al. 2000, Augusto et al. 2002, Cavard et al. 2011). Consequently, improper management of red pine plantations results in die offs from root diseases, poor soil nutrients and insects (OMNR 2010). Thinning between selection rotations complements harvesting by removing immature and/or poor quality trees (i.e., trees 15-20 years old or those with higher susceptibility to disease) to increase average stand diameter and economic value (OMNR 2000). Management of high density mature pine plantations through thinning or harvesting provides the microclimatic conditions (i.e., light and water) where early deciduous succession can be established to produce the structural and functional diversity characteristic of mixedwood forests (Betts et al. 2010, OMNR 2011). Progression towards mixedwood stands that produce early seral deciduous vegetation has been shown to have a positive effect on avian species richness as well as fledgling

survival (Doyon et al. 2005, Betts et al. 2010, Swanson et al. 2011, Streby and Andersen 2013). Studies on Ovenbird (Seiurus aurocapilla) site selection have shown a preference for areas with high invertebrate biomass produced by a deep deciduous leaf litter layer (Burke and Nol 1998; Haché et al. 2013). Forest floors consisting of greater leaf diversity have also been shown to have more high quality detritus required to support high invertebrate biomass and in turn high Ovenbird fledgling success (Seagle and Sturtevant 2005). Thus, as mature pine plantations become ready for harvesting, it is important to monitor the impacts of harvesting on the current bird community and determine the extent to which some species respond negatively to the treatment. No known studies have measured the direct impacts of timber harvesting on birds nest success or nest tree loss while it was taking place. Instead, estimations of the impacts of timber harvesting on productivity have been modeled based on avian point count assessments of abundance (Barber et al. 2001, Toms et al. 2006, Haulton 2008, Villard and Nudds 2010). The objective of my study was to attempt to quantify incidental take by searching and monitoring bird nests during single-tree selection harvesting in a monotypical red pine plantation. Specifically, I wanted to provide an estimate for daily nest survival rates and determine how many nests failed as a result of the silvicultural treatment for 5 focal bird species (American Robin, Turdus migratorius; Eastern Wood-pewee, Contopus virens; Ovenbird, Seiurus aurocapilla; Rose-breasted Grosbeak, Pheucticus ludovicianus; and Red-eyed Vireo, Vireo olivaceus). These focal species were selected based on their abundance and because they occupied a wide range of nesting habitats within the vertical structure of the forest. I located and monitored nests during the breeding season (May – September) of 2012 and 2013 before, during and after the treatment to determine the proportion of nests directly impacted by the treatment. I compared untreated stands to treated stands to determine whether single-tree selection harvesting had an effect on nest success. I expected the proportion of nests that failed (or were destroyed) to match the proportion of basal area removed by the treatment. I estimated daily nest survival rates to quantify the indirect impact of single-tree selection harvesting on the success of nests that were not

directly damaged by the forestry operations. I hypothesized that the direct effects of single-tree selection harvesting on bird habitat (e.g., removal of a tree with an active nest, heavy ground disturbance from machinery) would not be at a level that would prevent successful production of fledglings. Single-tree selection harvesting is intended to be a low intensity method of harvesting with minimal impact to the surrounding environment as well as causing intermittent disturbance to the local environment. I predicted that there would be no effect of single-tree selection harvesting on daily nest survival rates of the 5 focal species.

METHODS Study Area The study was conducted in the Northumberland County Forest (NCF) (44°05’53N 78°06’26W) located in south central Ontario between Rice Lake and Lake Ontario (Figure 2.1). The NCF is a 2,195 ha forest used for a wide range of recreational activities from ATV and snowmobile riding to hiking, horseback riding and hunting. Currently, the mature forest consists mainly of red pine and red maple (Acer rubrum). However, there is an extensive emergent understory dominated by red and sugar maple (A. saccharum) and red and white pine (Pinus strobus). This understory also includes: red and white oak (Quercus rubra and Q. alba), white ash (Fraxinus americana) and black cherry (Prunus serotina). The shrub layer was comprised mainly of poison ivy (Toxicodendrens radicans), red and black raspberry (Rubus idaeus and R. occidentalis) and red-osier dogwood (Cornus sericea). The forest is in the eastern portion of the Oak Ridges Moraine which is an ecologically important geological formation and protected under provincial legislation of the Oak Ridges Moraine Conservation Act of 2001 and is designated as a Natural Core Area of the Oak Ridges Moraine Conservation Plan. The study site was in the western portion of the NCF (Figure 2.1). When the forest was purchased by the provincial government in 1924, it was separated into forest compartments. These compartments were further divided based on numerous considerations including land ownership, rights-of-way, topography, soil type and most

importantly, forest types. The western portion of the NCF is comprised of 27 forest compartments ranging in size from 3 to 24 ha for a total area of 244 ha. The 27 forest compartments were managed through single-tree selection at three different periods: 1) 27 January to 16 March of 2012 (hereafter: Winter 2012); 2) 29 May to 13 July of 2012 (hereafter: Summer 2012); and 3) 28 May to 23 June of 2013 (hereafter: Summer 2013). Additional stands comprised of unharvested mature red pine plantation (approximately 60 years old) were used as controls. Additionally, Summer 2013 was treated as a control treatment in 2012 as the stand had yet to be harvested in 2012. Each treatment was sub-divided into study sites based on their timing of harvest. The sixteen study sites consisted of 2 Winter 2012 sites (T1 and T2, 24.0 ± 0.51 ha), 4 Summer 2012 sites (S1 - S3 and S5, 29.1 ± 6.1 ha), 5 Summer 2013 sites (B1 – B5, 24.8 ± 8.0 ha) and 5 control sites (C1 – C5, 26.2 ± 3.2 ha) (Figure 2.2). The NCF is being managed for timber harvest in 20 year rotations using single- tree selection harvesting and adheres to the Silvicultural Guide to Managing Southern Ontario Forests (2000) provided by the Ministry of Natural Resources and Forestry. Although other silvicultural methods (i.e., shelterwood silviculture) are typically employed in red pine forests, single-tree selection was used in the NCF. For foresters, employing single-tree selection harvesting allows them to mark trees that are most valuable rather than harvesting declining trees, which is normally what occurs from single-tree selection harvesting. For forest managers, the method of employing single- tree selection in red pine forests, especially for timber management in the red pine plantation of the NCF, has the main objective to reduce the red pine overstory and promote mixedwood regeneration for ecological conservation. For both years of this study, the harvest prescription for the NCF is intended to reduce red pine by 30-50% to an overall basal area of 20 – 22 m2/ha. The average age and basal area of the harvested areas prior to the treatment was 70 ± 10 years and 26.2 ± 4.0 m2/ha, respectively. The average basal area harvested was 8.4 m2/ha (range 3.3 – 18.4 m2/ha). The average basal area removed in the study plots was 30.4% (range 12.7 – 70.3%).

Nest Searching Between early May and mid-September 2012 and 2013, I searched for nests of the five focal species with the aid of field assistants. Study sites were monitored every 1 to 10 days (mean 4.5 ± 1.7 days) over the course of the two years. Observers used parental behavioural cues (i.e., adult carrying nest material or food, alarm calls near nest, territorial behavior and adult flying from the interior of a tree) to locate nests. Nest site description and local habitat type were recorded as per the Royal Ontario Museum’s Ontario Nest Records Scheme Coding System. Although nest searching was not exhaustive (i.e., did not find 100% of all focal species nests), the nests found are probably a representative sub-sample of all nests in the forest. For American Robin, Eastern Wood-pewee, I estimate we found 80% - 90% of all nests as these species were abundant and easy to locate. For Red-eyed Vireo and Rose-breasted Grosbeak, I estimate locating about 65% - 75% of all nests, and for Ovenbird, I estimate about 20% - 30% of all nests were found.

Nest Monitoring Nest monitoring consisted of first observing parental behaviour to determine nest activity (i.e., building, incubating or feeding). If active, we determined the content of each nest. A telescopic pole with an attached convex mirror was used to determine the content of nests higher than 2 metres from the ground. To reduce the risk of predation, nests would not be checked or would be revisited later the same day if potential nest predators [e.g., Blue Jay (Cyanocitta cristata)] were seen or heard nearby. Nests were monitored during rotational site visits until they were deemed successful or unsuccessful. A nest was considered successful if any young fledged. An active nest was considered “incidentally taken” if the tree was removed as part of the harvesting prescription or in the part of a tree damaged as part of the treatment.

Statistical Analysis The logistic-exposure method (Shaffer 2004) was used to estimate daily nest survival rates (DNSR) and nest success of the five focal species and to test for species-

specific effects of single-tree selection harvesting and year using a model selection approach and the Akaike’s Information Criterion (AIC). DNSR and nest success estimates were calculated from the intercept parameters of the general linear models, the natural logarithm base and estimated time of fledging for each focal species. DNSR and nest success were reported with 95% confidence intervals. I removed nuisance time variables by selecting top-ranked linear and non-linear Julian date time effects parameters against DNSR for each focal species. Julian nest date parameters were treated as linear, quadratic and cubic (Reidy et al. 2009) to account for non-linear nest survival that can occur during the breeding season (Grant and Shaffer 2012). If the null model was the best-ranked model, no further analysis was required. I included the top weighted time effects candidate model as an additive model that included also year and treatment effects for the model selection process to explain variation in daily nest survival rates of each focal species.

I assessed the models using second order criterion AICc because I used a large number of candidate models against a small number of nest per focal species (small sample size; n/K < 40) (Hurvich and Tsai 1989). I used model-averaged parameter estimates from candidate models with a ΔAICc values < 4 to account for model selection uncertainty. Model-averaged coefficients were reported with 85% confidence intervals due to small sample sizes and to account for model parameters that may support lower AIC values (Burnham and Anderson 2002, Arnold 2010). Cumulative AIC weights for potential candidate models were all over 0.90 with the exception of the Ovenbird (0.68) due to the distribution of a large number of candidate models (> 60) from the global time effects model selection. Odds ratios with 95% confidence intervals were presented to determine the effect size of the variables in the selected models. Odds ratios equal to 1.0 implied daily nest survival rate did not differ from the corresponding candidate model and a confidence interval that includes 1.0 also implies no difference between the DNSR and the corresponding candidate model (Bentzen et al. 2008). Intercepts are generally not

important in odds ratio interpretation and were overlooked for interpretation (Bruin 2006). All statistical analysis was computed using R 2.15.2 (R Development Core Team).

RESULTS During the two years of this study, I located and monitored a total of 290 nests

(n2012 = 150, n2013 = 140) including 98 Eastern Wood-pewee nests (n2012 = 47, n2013 = 51),

86 American Robin nests (n2012 = 39, n2013 = 47), 47 Rose-breasted Grosbeak nests (n2012

= 28, n2013 = 19), 32 Red-eyed Vireo nests (n2012 = 15, n2013 = 17) and 27 Ovenbird nests

(n2012 = 21, n2013 = 6). The active breeding period in the NCF of all focal species was established as the period between the date that the first nest was found (e.g., adult building) and the date that the final young fledged. In 2012, the nesting period was 98 days from 19 May 2012 to 25 August 2012. In 2013, the nesting period was 119 days from 7 May 2013 to 3 September 2013 (Figure 2.3). Overall proportion of successful nests for all focal species was 14% and 18% in 2012 and 2013, respectively (Figure 2.4). Harvesting over both years extended through the early- and mid-portion of the prime nesting period in southern Ontario [13 May (day 134) – 27 July (day 209)] as established by Environment Canada (2014a) (Figure 2.3). Harvesting was first recorded in S2 on 29 May 2012 (day 150) and was recorded as complete in S1 on 21 July 2012 (day 203), for a total of 53 harvesting days during the active breeding period (Figure 2.2). Harvesting in 2013 was first recorded in B1 on 28 May 2013 (day 148) and last recorded in B3 as post-harvest on 23 June 2013 (day 174) for a total of approximately 26 total harvesting days during the active breeding period (Figure 2.2). Single-tree selection harvesting had no direct effect on the daily nest survival rates of the 5 focal species in the Northumberland County Forest during the 2012 and 2013 field seasons (Table 2.1 & 2.2). I found only 3% (n = 4 nests) and 1% (n = 1 nest) of total nests found in 2012 and 2013, respectively, that were damaged directly by forestry activity. These numbers are negligible when comparing nest outcomes with natural

factors such as predation, which accounted for 50% in 2012 and 63% in 2013 (Figure 2.4). Nest success of focal species ranged from 21.1% (Ovenbird in 2012) to 43.0% (Rose-breasted Grosbeak in 2013) in the NCF over the 2012 and 2013 breeding seasons (Figure 2.5). For each species, with the exception of the Red-eyed Vireo, nest success and DNSR was slightly higher in 2013 than in 2012 (Table 2.3). Additionally, Red-eyed Vireo DNSR was lower in the Control treatments in both years suggesting these sites did not provide adequate nesting habitat compared to the other treatments (Figures 2.7 and 2.8). For all species, the time effects models (Figure 2.4) ranked higher than models containing treatments and/or year effects (Table 2.5). Model-averaged parameter estimates for the American Robin, Rose-breasted Grosbeak and Ovenbird, saw DNSR decline as a function of Julian date, while the opposite pattern was observed for the Eastern Wood-pewee (Table 2.6).

DISCUSSION The level of single-tree selection harvesting taking place during the breeding season in the Northumberland County Forest did not have an effect on the daily nest survival rates or nesting success of these 5 focal species. While incidental take did occur from the single-tree selection harvesting, the destruction of nests and eggs was minimal in absolute terms as well as in relation to naturally occurring destruction of bird nests and eggs. The lower incidental take occurring in 2013 was the result of harvesters spending less time in the forest. However, with the haste at which work was completed, the overall habitat structure was altered greatly resulting in the reduction of density and territory sizes of some species (see Chapter 3). Although this study’s primary objective was to measure forest harvest effects on daily nest survival rates on the 5 focal bird species, I did note an increase in predation rates between 2012 and 2013; this result may have been due to other factors such as good versus poor harvesting practices taking place between years. The speed at which harvesting was completed in 2013 created large gaps in the canopy more similar to

those expected from group selection harvesting in some areas of the study site, as well as a fragmented landscape produced by large skidder trails that disturbed the forest floor. Avian and small mammal predators are known to have the largest impact on bird nests as a result of forest edges created by agriculture and forestry (Bayne and Hobson 1997, Schaefer 2004, Ludwig et al. 2012). Therefore, it is important to monitor the harvesting progress through follow-ups on environmental assessments as recommended within provincial FMP guidelines as these guidelines are put in place to uphold natural resource and ecologically sustainable practices. Higher mortality rates are also more likely to occur during or immediately after a human-related disturbance (Longcore and Smith 2013). Vanderwel et al. (2009) reported an increase in forest harvest intensity resulted in unsuitable habitat for approximately 1/4 of late successional species, subsequently resulting in a reduction in species richness and abundance. Further research examining various levels of cutting regimes would provide insight into the threshold at which incidental take may become additive to natural mortality during forestry operations. As a result, future research could establish harvesting thresholds of incidental take and provide considerations to current FMP’s that would maximize economic benefits while maintaining ecological and natural resource sustainability as well as maintaining forest stand structure. The forestry industry in Ontario attempts to emulate natural disturbances in multi-patch stand structure while considering the various life-history necessities of individual avian species, which can prove difficult and produce mixed results such as altering species richness and abundance (Vanderwel et al. 2009, Tozer et al. 2010). The DNSR of American Robin, Rose-breasted Grosbeak and Red-eyed Vireo was not affected by harvest treatments. For American Robin and Rose-breasted Grosbeak, this may be an indication of the ability of these species to quickly adapt and/or not be deterred by human disturbances (Wyatt and Francis 2002, Jobes et al. 2004, Smith et al. 2006, Vanderhoff et al. 2014). Additionally, Rose-breasted Grosbeak pairs were witnessed following behind the harvester gleaning insects from felled and trampled deciduous trees, further indicating their opportunism in finding novel food sources (personal

observation). Similarly, Red-eyed Vireo may not have been deterred by human disturbance due to their broad preference for both mature and sapling deciduous habitat (Pagen et al. 2000, Jobes et al. 2004, Reidy et al. 2014). As deciduous trees were not the focus of harvest, minor disturbance may have resulted in the consistency of Red- eyed Vireo nest success and DNSR for both years especially in harvested treatments. The Control treatment sites were very characteristic of a monotypical red pine plantation with evenly spaced red pine and very little deciduous canopy and sub-canopy layers. On the other hand, the deciduous canopy and sub-canopy layers were more present in the harvested treatments. As a result, Red-eyed Vireo DNSR and nest success in 2012 and 2013 were lower in the Control treatment than harvested treatments. Red-eyed Vireos prefer nesting sites with dense deciduous canopy cover and surrounded by dense vegetation (Cimprich et al. 2000, Siepielski et al. 2001). An example of mixed results from a single species was reported by Boves et al. (2013) who determined that natural disturbance emulation revealed mixed results for demographics and reproduction of Cerulean Warblers (Setaphaga cerulea). Although territory-occupying males increased in density and were in better condition in treatment sites compared to control males, reproduction and nest success was lower in treatment sites. Sensitivity to forestry operations has been well documented for Ovenbird (Burke and Nol 1998, Bayne and Hobson 2001, LeBlanc et al. 2011, Newell and Rodewald 2012, Vitz and Rodewald 2013). However, Ovenbird DNSR and nest success were not compromised as a result of forestry operation in the NCF, although my sample size for nests of this species, especially in 2013, was quite small so the power to detect a difference may not have been there. Despite the disturbance, Ovenbird’s may have remained in harvested areas as a considerable amount of energy and resources are expended to complete the nesting process. Ovenbird territory size and density was significantly reduced as a result of silviculture in the NCF (see Chapter 3), suggesting those individuals remaining in the harvested area may have held optimal foraging and resource opportunities to complete nesting abilities.

Environment Canada has made recommendations for Beneficial Management Practices (BMP) to reduce the incidental take on the landscape using Avoidance Guidelines based on scientific research. For the forestry industry, proper management results in planning and completing harvesting outside of crucial nesting periods as laid out by Environment Canada (2014a). Furthermore, incorporating BMP’s as a conservation strategy along with the demands from the forestry industry also presents complications and overlap in an attempt to lessen or remove incidental take. However, implementing BMP’s by utilizing Avoidance Guidelines within the forestry industry should proceed with caution as there is a lack of knowledge between nest loss from forestry activity and quantifying the level of nest loss at different harvesting intensities. Single-tree selection harvesting is a rare form of harvesting in monotypical red pine forests as generally shelterwood cuts are employed. This method did not significantly affect direct nest loss in the NCF between the two years of study. The minimal impact that occurred from single-tree selection harvesting during the 2012 and 2013 breeding season was much lower than expected. I suggest this may provide an opportunity for the forestry industry to harvest monotypical red pine forests during the breeding season using single-tree selection methods. A large scale assessment of nest loss from harvesting incorporating all bird species and a variety of forests (e.g., mixed- hardwood, boreal, Carolinian) is required before moving forward with this suggestion in other forest types. The intention for single-tree selection harvesting in the NCF was to re-establish a more diverse forest structure by promoting shade tolerant hardwoods. Also, there was a pronounced difference in harvesting styles between the two operators in the 2 years. Examination into forest growth and development between the two styles could illustrate how the forest responds to different harvest operating methods. Finally, the MBCA was put in place to protect migratory birds during life-history stages and Environment Canada outlined Avoidance Guidelines and BMP’s to avoid disturbing or destroying birds and/or their eggs. Thus, if the forestry industry is to apply BMP’s and Avoidance Guidelines to single-tree selection harvesting (or other types of harvesting)

more research is required into nest loss from varying levels of harvest intensities before full confidence can be placed in these guidelines.

Figure 2.1. Google Earth satellite image of the NCF. White outline in western portion of the forest indicates the area where the study and harvesting took place.

Figure 2.2. The 27 forest compartments amalgamated into the 17 study sites comprising the study area. B-sites were harvested in winter/summer of 2013, C-sites are Control (unharvested) sites, S-sites are those that were harvested in the summer of 2012 and T- sites are those that were harvested in late winter of 2012. Map was produced using ArcGIS 10.1.

Figure 2.3. Map displays the 28 nesting zones associated with the regional nesting periods within Canada. NCF falls within the C2 nesting zone of Lower Great Lakes/St. Lawrence Plain region. The lower image indicates the nesting calendar for the nesting zone and shows a total of 84 known forest bird species breeding in this region. The white area indicates 0 - <5% of the known breeding birds are nesting during this time period, yellow indicates 11 – 20%, orange – 21 – 40%, red – 41 – 60%, and dark red indicates 61 – 100% of known breeding bird species are nesting during this period (Environment Canada 2014a).

0.70

0.60

0.50 2012 2013 0.40

PercentofNests 0.30

0.20

0.10

0.00 Successful Predation Incidental Take Abandoned Damaged Nest Undamaged Nest

Nest Outcome

Figure 2.4. Nest outcomes during single-tree selection harvesting in the NCF over the 2012 and 2013 field season. Incidental Take referred to any damage, desertion and/or destruction presumed to be directly caused by forestry activity. Damaged and undamaged nests were empty of eggs or any other content independent of harvesting activity. Damaged and undamaged nests were most likely depredated or abandoned but confirmation of an appropriate outcome could not be determined.

0.8

0.7 2012 2013

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0.5

Nest Success 0.4

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0.2

0.1

0 AMRO EAWP OVEN RBGR REVI Species

Figure 2.5. Nest success calculated from logistic exposure method of the 5 study species from the 2012 and 2013 field season in the NCF. Error bars indicate 95% confidence intervals.

Figure 2.6. Comparison of daily nest survival rates (DNSR) with standard error bars of the 5 focal species by year and treatment factors in the NCF. Variation in daily nest survival rates was due to individual’s nest exposure and survival period. Only Summer 2012 and Summer 2013 treatments are shown for Ovenbird due to lack of comparison as no nests were found in the Control treatment in 2013 or Winter 2012 treatments in 2012.

Figure 2.7. Overall daily nest survival rates of the 5 focal species in 2012 in the 4 treatments. In 2012, Summer 2013 harvest period is treated as a control as the stand had yet to be harvested.

Figure 2.8. Overall daily nest survival rates of the 5 focal species in 2013 within the 4 treatments.

Table 2.1. AIC model selection for daily nest survival rates for American Robin, Eastern Wood-pewee, Ovenbird, Rose-breasted Grosbeak, Red-eyed Vireo in Northumberland County Forest in 2013.

Models K AICc ΔAICc ωi Null Model 1 679.27 0 0.753

Focal Species 5 682.92 3.65 0.122

Harvest Treatment 4 683.12 3.85 0.11

Focal Species + Harvest Treatment 8 687.1 7.83 0.015 Focal Species * Harvest Treatment 19 701.27 22 0

Table 2.2. AIC model selection for daily nest survival rates for American Robin, Eastern Wood-pewee, Ovenbird, Rose-breasted Grosbeak, Red-eyed Vireo in Northumberland County Forest in 2013.

Models K AICc ΔAICc ωi Null Model 1 609.09 0 0.89 Harvest Treatment 4 614.4 5.32 0.06 Focal Species 5 614.93 5.84 0.05 Focal Species + Harvest Treatment 8 620.47 11.38 0 Focal Species*Harvest Treatment 19 633.2 24.12 0

Table 2.3. Nest Success and daily nest survival rates (DNSR) of the 5 focal species during the 2012 and 2013 breeding season in the Northumberland County Forest (NCF) under single-tree selection harvesting.

Species Year Nest Success (%) 95% C.I. DNSR DNSR C.I. AMRO 2012 24.0 13.4 - 36.5 0.947 0.926 - 0.962 2013 28.9 18.4 - 40.2 0.953 0.937 - 0.966

EAWP 2012 26.5 16.4 - 37.8 0.956 0.941 - 0.968 2013 29.4 18.8 - 40.9 0.960 0.945 - 0.970

OVEN 2012 21.1 8.5 - 37.8 0.925 0.884 - 0.953 2013 39.4 12.2 - 66.7 0.955 0.900 - 0.980

RBGR 2012 23.7 11.7 - 38.1 0.938 0.909 - 0.958 2013 43.0 24.3 - 60.6 0.963 0.939 - 0.978

REVI 2012 26.2 9.7 - 46.6 0.950 0.914 - 0.971 2013 20.7 7.5 - 38.7 0.941 0.905 - 0.964

Species Model K logLik AICc ΔAICc ωi AMRO Day 2 -177.400 358.834 0.000 0.220 day2 2 -177.427 358.887 0.054 0.214 day3 2 -177.497 359.027 0.193 0.200 Global 4 -175.900 359.913 1.079 0.128 day + day3 3 -177.389 360.845 2.011 0.080 day + day2 3 -177.398 360.863 2.029 0.080 day2 + day3 3 -177.424 360.916 2.082 0.078 Null 1 -187.094 376.198 17.365 0.000

EAWP day3 2 -216.999 438.023 0.000 0.218 day2 2 -217.029 438.083 0.060 0.211 Day 2 -217.077 438.181 0.157 0.201 Null 1 -218.939 439.886 1.863 0.086 day + day2 3 -216.955 439.962 1.938 0.083 day + day3 3 -216.969 439.990 1.967 0.081 day2 + day3 3 -216.976 440.004 1.981 0.081 Global 4 -216.697 441.479 3.456 0.039

OVEN Global 4 -52.938 114.296 0.000 0.602 day + day2 3 -55.491 117.232 2.936 0.139 day + day3 3 -55.683 117.616 3.320 0.115 day2 + day3 3 -55.881 118.012 3.716 0.094 Null 1 -59.348 120.738 6.441 0.024 Day 2 -59.283 122.691 8.394 0.009 day2 2 -59.320 122.764 8.467 0.009 day3 2 -59.341 122.805 8.509 0.009

RBGR day + day2 3 -103.635 213.389 0.000 0.200 day + day3 3 -103.697 213.513 0.123 0.188 day3 3 -103.769 213.656 0.267 0.175 Global 4 -103.147 214.493 1.104 0.115 Day 2 -105.251 214.562 1.173 0.111 day2 2 -105.442 214.942 1.553 0.092 day3 2 -105.624 215.308 1.919 0.077 Null 1 -107.224 216.467 3.077 0.043

Table 2.4 cont’d

Species Model K LogLik AIC ΔAICc ωi REVI Null 1 -68.599 139.229 0.000 0.208 day2 2 -67.662 139.417 0.188 0.190 Day 2 -67.663 139.418 0.190 0.189 day3 2 -67.664 139.420 0.192 0.189 day + day3 3 -67.662 141.510 2.281 0.067 day + day2 3 -67.662 141.510 2.282 0.067 day2 + day3 3 -67.662 141.511 2.282 0.067 Global 4 -67.619 143.551 4.322 0.024

Species Model K logLik AICc ΔAICc ωi AMRO Day 2 -177.400 358.834 0.000 0.578 Day + year 3 -177.361 360.788 1.955 0.217 Day + treatment 4 -176.845 361.801 2.968 0.131

EAWP day3 2 -216.999 438.023 0.000 0.393 day3 + year 3 -216.636 439.323 1.300 0.205 Null 1 -218.939 439.886 1.863 0.155 day3 + treatment 4 -216.417 440.920 2.897 0.092 Year 2 -218.870 441.765 3.742 0.060

OVEN global date + year 5 -50.628 111.894 0.000 0.417 global date 4 -52.938 114.296 2.402 0.126 global date + year +treatment 7 -50.064 115.346 3.452 0.074 day + day2 + year 4 -53.632 115.684 3.790 0.063

RBGR day + day2 +year 4 -100.592 209.383 0.000 0.230 day + year 3 -101.884 209.887 0.505 0.179 day2 + year 3 -102.152 210.424 1.041 0.137 day + treatment + year 5 -100.570 211.439 2.057 0.082 day + day2 + treatment + year 6 -99.640 211.702 2.319 0.072 day2 + treatment + year 5 -100.861 212.021 2.639 0.062 day + treatment + year + year*treatment 7 -98.770 212.105 2.723 0.059 day2 + treatment + year + year*treatment 7 -98.991 212.547 3.165 0.047 day + day2 + treatment + year + year*treatment 8 -98.220 213.172 3.789 0.035

Table 2.6. Model-averaged parameter estimates with 85% confidence intervals and odds ratios with 95% confidence intervals developed from the second suite of exploratory variables explaining daily nest survival rates of American Robin, Eastern Wood-pewee, Ovenbird and Rose-breasted Grosbeak from single-tree selection harvesting in the Northumberland County Forest in 2012 and 2013. Species Coefficient Estimate Adjusted SE 85% C.I. Odds Ratio 95% C.I. AMRO (Intercept) 7.24 1.03 5.76, 8.72 1392.92 184.66, 10507.28 day -0.02 0.01 -0.03, -0.02 0.98 0.97, 0.99 Year 2013 -0.07 0.24 -0.42, 0.28 0.93 0.58, 1.51 EAWP (Intercept) 3.69 0.45 3.05, 4.33 40.18 16.80, 96.12 day3 0.00 0.00 -0.00, -0.00 1.00 1.00, 1.00 Summer 2013 0.03 0.31 -0.41, 0.47 1.03 0.56, 1.89 Control 0.28 0.27 -0.11, 0.66 1.32 0.78, 2.23 Year 2013 0.20 0.23 -0.14, 0.54 1.22 0.77, 1.93 OVEN (Intercept) 680.80 345.40 185.13, 1176.46 4.61E+295 43.14, Inf day -11.14 5.83 -19.51, -2.76 0.00 0.00, 1.35 day2 0.06 0.03 0.01, 0.11 1.06 1.00, 1.13 day3 0.00 0.00 -0.00, -0.00 1.00 1.00, 1.00 Summer 2013 0.76 0.74 -0.29, 1.82 2.15 0.51, 9.12 Control 0.15 0.53 -0.61, 0.91 1.16 0.41, 3.27 Year 2013 1.07 0.54 0.30, 1.85 2.92 1.01, 8.47 RBGR (Intercept) 15.46 15.42 -6.72, 37.63 5.16E+06 0.00, 6.87e+19 day -0.16 0.18 -0.42, 0.11 0.86 0.60, 1.22 day2 0.00 0.00 0.00, 0.00 1.00 1.00, 1.00 Summer 2013 0.11 0.59 -0.73, 0.96 1.12 0.35, 3.54 Control 0.48 0.50 -0.25, 1.20 1.61 0.60, 4.34 Year 2013 0.88 0.43 0.27, 1.49 2.41 1.05, 5.55 Summer 2013 x Year 2013 0.18 1.31 -1.69, 2.06 1.20 0.09, 15.49 Control x Year 2013 1.39 0.79 0.25, 2.53 4.02 0.85, 18.97 * reference level for categorical variables are Year 2012 and 2012 Harvest

CHAPTER 3: Effects of Single-tree Selection on Density and Territory Size of Four Bird Species in a Southern Ontario Red Pine (Pinus resinosa) Plantation

ABSTRACT Of the different silvicultural methods, single-tree selection offers the least intensive form of forest harvesting. Post-harvest forest stands in single-tree selection systems are intended to mimic uneven aged forests by creating gaps in the canopy that provide early-successional deciduous habitat patches, representative of natural disturbances such as wind throw and tree senescence. However, disturbances to avian habitat such as soil compaction and major alterations to the vertical and horizontal forest structure can occur as a result of harvesting machinery. These disturbances from forestry activity can potentially have either negative and/or positive effects on avian populations. I monitored the impact of single-tree selection harvesting on the population dynamics of four focal species by measuring changes in density and territory size in the Northumberland County Forest, Ontario (NCF). Three focal species: Eastern Wood-pewee, Rose-breasted Grosbeak and Red-eyed Vireo all exhibited slight, but non- significant increases in density as a result of single-tree selection harvesting. However, Ovenbird density and territory size significantly decreased as a result of single-tree selection harvesting. Eastern Wood-pewee and Red-eyed Vireo territory size increased and Rose-breasted Grosbeak territory size declined as a result of single-tree selection harvesting. Single-tree selection harvesting can be an ecologically sustainable practice for forest management if guidelines are followed. Localized harvesting occurs on a short time scale, and can be advantageous for some bird species if landscape disturbance is kept to a minimum.

INTRODUCTION Single-tree-selection harvesting attempts to retain 70% of the forest structure and is the least intensive form of silviculture. It is intended to mimic natural disturbances such as tree senescence and windthrown trees, creating an early successional ecosystem important to many forest bird species (OMNR 2000, Bourque and Villard 2001, OMNR 2009, Swanson et al. 2011). Single-tree selection attempts to increase shade-tolerant trees and develop uneven-aged forests by creating small-scale gaps in the canopy (OMNR 1998, Jobes et al. 2004). Natural disturbances and selection harvested canopy gaps dramatically increase growth rates of the sub-canopy of shade tolerant individuals, due to increased light availability. The greatest increase in tree growth rates occurs over the first few years post-harvest eventually reaching a maximum growth rate between 5 - 15 years post-harvest (Jones et al. 2009). Under single-tree selection harvesting, increases in tree height help to quickly restore the vertical structure of the forest. Harvesting schedules typically occur in 20-year rotations, greatly reducing regeneration time and this method results in establishment of a matrix of early and mature forest vertical structure. Furthermore, tree species diversity is maintained which subsequently provides or retains mixed habitats for forest birds as well as meets the intended goals of forest management in a relatively short period of time. Despite the benefits of single-tree selection for silvicultural objectives, altering forest composition by unintentionally increasing harvest intensity could cause habitat alteration for forest birds and many other wildlife species, potentially causing a reduction in existing populations. While single-tree selection harvesting causes increased growth of the sub-canopy trees, the network of roads and skidder trails used to convey logging equipment can change the understory for early and late-successional species and cause long-term population changes through habitat loss and fragmentation (Barber et al. 2001, Doyon et al. 2005, Natural Resources Canada 2010). During silviculture operations, soil compaction and disturbance from harvesting is the primary negative impact having long-term effects and can greatly reduce tree stocking, growth and productivity as well as delay the natural tree regeneration process occurring post-

harvest (Williamson and Neilson 2000, Rab 2004). Compaction from skid trails can last up to 20 years or more, inhibiting root movement leading to surface run-off and ultimately to soil erosion (Rab 2004, Drever et al. 2006, Ponder, Jr. et al. 2012). Additionally, road networks created by harvesters increase disturbance of the forest floor and open the forest canopy, creating habitat more suitable for weedy and generalist forest taxa as well as invasive species that prefer disturbed areas (Burke et al. 2008). Therefore, assessing bird populations and their habitat as a result of anthropogenic disturbances is important to inform management of ecological sustainability and biodiversity in Canadian forests. Although there are negative changes to forest structure due to harvesting equipment, previous studies have indicated that single-tree selection harvesting can also have positive aspects for avian populations, habitat and species composition. Maintaining residual mature forest habitat while emulating early-successional forest structure can provide suitable habitat for mature and early forest bird species thus maintaining avian biodiversity. However, some juvenile and adult forest bird species have been shown to use early-successional habitat that was produced from single-tree selection harvesting throughout the breeding period (Becker et al. 2011, Vitz and Rodewald 2013). Some species can nest successfully in the presence of habitat disturbance. For example, gap creation from small-scale disturbances in hardwood forests increased forest bird abundance by increasing habitat quality for nest sites and resource availability (Doyon et al. 2005, Jones et al. 2009, Forsman et al. 2010). Maintaining vertical forest structure diversity can also maintain forest bird abundance in a managed landscape (Chandler et al. 2012). I monitored the population dynamics of four bird species during single-tree selection silviculture in a monotypic red pine plantation in southcentral Ontario, Canada, to determine if harvesting had short-term post-harvest impacts on their densities and territory sizes. The focal species included the Eastern Wood-pewee (Contopus virens), Ovenbird (Seiurus aurocapilla), Rose-breasted Grosbeak (Pheucticus ludovicianus) and Red-eyed Vireo (Vireo olivaceus). I hypothesized that while disturbance from harvesting

was capable of altering bird densities and individual territory sizes of the 4 focal species, the responses would be species specific. I predicted: (1) that Eastern Wood-pewee would increase in densities post-harvest and have decreased territory size due to the small gaps that are created in the canopy which are used by this species for nesting and resource acquisition (McCarty 1996); (2) that Ovenbird abundance and territory size would both decrease, as the Ovenbird is a late-successional, ground-nesting species that acquires food resources from the leaf litter on the forest floor. Alteration to preferred habitat may directly remove Ovenbirds thereby reducing density, while fragmentation from skidder trails creates barriers that may act as territory boundaries and restrict Ovenbird movement (Bayne et al. 2005). I also predicted that (3) Rose-breasted Grosbeak density would increase because vertical forest structure is important for Rose- breasted Grosbeaks who prefer to nest in trees and shrubs and use the canopy for feeding and later in the breeding season to increase fledgling success (Moore et al. 2010). Additionally, Rose-breasted Grosbeak have been documented to be resilient in response to anthropogenic disturbances (Smith et al. 2006). Finally, I predicted that (4) Red-eyed Vireo density and territory size would remain consistent between treatment and years. Red-eyed Vireos are a deciduous, generalist forest species and with retention of preferred deciduous habitat, there would be no change to Red-eyed Vireo density or territory size.

METHODS Study Site The Northumberland County Forest (NCF) is a 2,195ha multi-use forest located south of Rice Lake in south-central Ontario. Historically, it was deforested in the late 1800’s and used for agricultural purposes but the region’s sandy soils did not support agricultural practices as nutrients were quickly depleted. Replanting began with red pine (Pinus resinosa) in the early 1900’s which led to the creation of the Reforestation Act of Ontario in 1921. The NCF was initially managed by the province but Northumberland County maintained ownership. In 2000, Northumberland County took over responsibility

of managing the forest from the province. The forest was established in part to support a number of recreational activities, from ATV trails to hiking in the summer and snowmobiling to cross-country skiing during the winter months. The NCF is protected under Ontario’s provincial legislation under the Oak Ridges Moraine Conservation Act (2001). Under the Reforestation Act of 1921, Northumberland and the surrounding counties entered into a mutual agreement to reforest large tracts of degraded land. Over the next 40 years, approximately 60% of the NCF was planted with red pine (Pinus resinosa). Currently, the mature forest consists mainly of red pine and red maple (Acer rubrum); however, there is an extensive emergent understory dominated by red and sugar maple (A. saccharum) and red and white pine (Pinus strobus). This understory also includes red and white oak (Quercus rubra and Q. alba), white ash (Fraxinus americana) and black cherry (Prunus serotina). The shrub layer was comprised mainly of poison ivy (Toxicodendrens radicans), red and black raspberry (Rubus idaeus and R. occidentalis) and red-osier dogwood (Cornus sericea). The western portion of NCF was used as a study area and was subdivided into 4 treatment groups based on: (1) current and past harvesting schedules; (2) forest compartments; and (3) total area of forest compartments. The 4 different treatments consisted of 15 study sites which included: 4 B-sites (B1, B2, B3, B5 area range = 9.3 – 14.0 ha, total area = 45.5 ha) harvested in the summer of 2013 (HS-2013) in the middle of the breeding season beginning on 28 May 2013 and finishing around 23 June 2013, 5 C-sites (C1, C2, C3, C4, C5; area range = 10.1 – 16.3; total area = 64.8 ha) which acted as control sites that were not subject to harvesting during the study period, 4 S-sites (S1, S2, S3, S5; area range = 8.2 – 13.9; total area = 45.8 ha) harvested in the summer of 2012 (HS-2012) beginning 29 May 2012 and ending 13 July 2012 and 2 T-sites (T1 = 10.1 ha, T2 = 13.0 ha) harvested in late winter between 27 January and 16 March of 2012 (HW-2012) well prior to the breeding season of 2012. Site S4 was omitted from the study after the 2012 field season as it was mainly comprised of mature aspen (Populus spp.) and maple (Acer spp.) with very few and small conifers.

Approximately one third of the forest is recommended to be removed under single-tree selection harvest (OMNR 2000). However in some sites, forest managers of the NCF had requested 33 – 50% of the red pine to be harvested (B. Walters, pers. comm). In 2012, HW-2012 and HS-2012 had approximately removed 7.8% of the stands basal area and HS-2013 removed 9.0% of the stands basal area which accounted for an overall basal area removal of 30.4% within the study area. Territory Mapping Territory mapping (hereafter referred to as mapping) was conducted from mid- May to mid-August of 2012 and 2013. Mapping focused on adult males of the four focal species. A minimum of 8 ha and a maximum of 20 ha were established as per Bibby et al. (2000) as a suitable area to cover in the 2 hour time period to adequately map all 4 focal species in all study sites. Study sites were completed in rotation and were revisited a minimum of every 5 days with 2 sites visited daily. Mapping began at local sunrise times (Eastern Standard Time) and individuals in each site would be mapped for a minimum of 2 hours. Each day observers received an orthographic map of the mapping area for reference and used handheld GPS units to annotate species and harvesting observations on a grid map of the area. The field sheet grid was divided into 30m2 areas which allowed for easier notation in the field. Observers listened for songs and calls of males and females of each focal species. Upon visual location, observers identified the general area of the species and a UTM location was taken and noted in the appropriate area on the grid map. Notation followed Bibby et al. (2000) with minor changes. Notation included a 2-letter species code (e.g., OV for Ovenbird) and the last 3 eastings digits and the last 4 northings digits. In some cases, call playback was employed (Bibby et al. 2000) to elicit a response from an individual in order to get a visual location. To avoid creating bias by eliciting a response from an individual from a neighbouring territory, this technique was more often used when the observer was in a known area where an adult male was heard singing but not seen. Additionally, once an individual was located, the observer would

follow the individual, especially if long flights occurred. Known avian and mammalian predators were also mapped. All points from 2012 and 2013 mapping sessions were downloaded into ArcGIS 10.1 (ESRI 2011). Point clusters for each of the 4 focal species were separated into their appropriate year. Minimum Convex Polygons (MCP) were created based on point clusters and field site observations to establish the area of an individual’s territory. Nests found in a point cluster were also assumed to belong to the occupying pair’s territory. Nests were considered as a point when delineating MCPs if pairs of the focal species share parental responsibility during the nesting period. Also, the direction in which an individual flew was used to help delineate territories. If an individual flew >30m but was not followed to record its location with an accurate GPS point, a compass was used to determine the direction and the estimated distance the individual flew. To avoid inflating territory size the distance in the field was estimated conservatively. A minimum of 4 male locations was used to establish an individual’s territory. Territories were delineated using the measure tool in ArcGIS 10.1. If a territory overlapped the border of a study area, only the proportion of the area inside the mapped area was used for density analysis. However for territory size the entire mapped territory measurement was used for analysis.

Habitat Measurements I conducted surveys of post-harvest herbaceous vegetation, forest floor cover and trees (hereafter vegetation and habitat plots) from 3 September 2013 to 16 September 2013 at randomly selected locations (n = 66) throughout the study area using Universal Transverse Mercator (UTM) ranges in a random number generator. Vegetation plots measured the horizontal forest floor structure and habitat plots measured the vertical forest structure. Vegetation and habitat plots were oriented towards the 4 cardinal directions and the area of each plot was 100m2 (10m x 10m). Vegetation plots were established 2m from the centre of the plot in each cardinal direction and a general 1m2 area was used to proportionately describe the forest cover (≤ 0.5m). Forest floor cover was estimated as percent cover to the nearest 5%; however,

in some cases cover would be present in minute amounts and would be estimated at 1%. Measurements included percent cover of: sand, rock, moss, lichen, herbaceous plants, leaf litter cover, shrubs, tree seedlings and coarse woody debris (≥ 5cm). In the habitat plot, I counted and identified the number of live and dead trees of each species, identified the species of shrubs and saplings (height < 3m) and measured the tallest tree in each cardinal direction within 15m of the centre of the habitat plot using a Nikon® Forestry Pro range finder. If more than one tree was similar in height all trees were measured and the tallest tree was recorded. Basal area of the habitat plot was measured using a 2X basal area prism (Cruise Master Prisms, Sublimity, Oregon) from the centre of the plot. The plot centre acts as the vertex for the projected angles between the prism and the laterally displaced tree seen across the prism’s upper edge (Ministry of Forests, Lands and NRO 2014). Trees were either counted “in”, “out” or “borderline” and all tree species counted “in”, and every other “borderline” tree, had the diameter measured at breast height (DBH) (1.2m) using standard 50cm forestry calipers. Canopy cover was estimated using a concave densiometer at a point 10m from the plot centre in each cardinal direction and the average of the 4 measurements was recorded for each plot. I measured the diameter of incidentally cut stumps and shafts of unmarked downed trees and saplings (> 1cm) using standard 50cm forestry calipers. I recorded and identified each tree and estimated the proportion of incidentally cut trees in each stand.

Statistical Analysis Density and Territory Size To analyze density and territory sizes, I combined data within treatments across study sites to increase power. Data from treatments HS-2012 and HW-2012 were also combined because of their relative similarity in harvesting time (late winter versus spring harvest in 2012) and because territories were established while harvesting was taking place. These treatments were then renamed as 2012 Harvest. All focal species densities were calculated as number of individuals per treatment divided by total treatment area. Total treatment area did not change between years. The species means

for each treatment type were calculated and reported as density (number of males/ha ±S.E.). Mean territory sizes for each species and treatment were reported as ha ± S.E. I expected 1) no change in either density or territory size in the control sites between years, 2) no change in density and/or territory size in the sites harvested during the 2013 breeding season (HS-2013) as territories may have been established prior to the scheduled harvest, and 3) a post-harvest change in the density and/or territory size in the sites harvested in 2013 as a response to habitat alteration from single-tree selection harvesting in 2012. I used paired t-tests to determine if single-tree selection harvesting had an effect on density and territory size within the different treatments between years.

Habitat Measurements Initial normality tests determined no habitat variables fit the assumptions of normality, thus they were log transformed and then tested for fit of the assumptions of normality. I used a one-way ANOVA to determine if there were differences in habitat features between treatments. The purpose was not only to see if there were differences between treatment types from single-tree selection harvesting but to establish if habitat alterations within treatments were a result of different harvest operators between the 2012 and 2013 field season. For analysis of each species, I chose particular habitat variables a priori that I assumed would be most important in explaining density or territory for that species based on the literature from a set of 12 habitat measured variables. I included average tree height, basal area and canopy cover for Eastern Wood-pewee (Falconer 2010, Kendrick 2012), average leaf litter, canopy cover and sub-canopy cover for Ovenbird (Burke and Nol 1998, Theriault et al. 2012), percent shrub layer, basal area, canopy cover and sub-canopy cover for Rose-breasted Grosbeak (Smith 2005, Moore et al. 2010, Richmond 2010) and sub-canopy cover, canopy cover and tree height for Red- eyed Vireo (Siepielski 2001, Reidy et al. 2014). The model set including density and territory size for Eastern Wood-pewee, Ovenbird and Red-eyed Vireo each contained 8 a priori models including a null and global model that examined the aforementioned

habitat variables for each species. Rose-breasted Grosbeak contained 16 habitat models to explain density and territory size. Information theoretic approaches with AIC were used to evaluate models of the effect of habitat on density or territory size for each focal species. AICc was used due to small sample sizes (Hurvich and Tsai 1987) and all AICs were carried out with the package MuMIn in R (R version 2.15.2, http://cran.r-project.org). No habitat model had an AIC weight (ωi) > 0.9. Parameter estimates were taken from cumulative AIC weights ≥ 0.9 of the selected models from the initial AIC suite. A top-ranked null model was interpreted to mean that no post-harvest habitat characteristics helped to explain either density or territory size. Parameter estimates with 95% confidence intervals were reported only if a particular habitat variable was in a model above the null. All results were considered significant at P < 0.05.

RESULTS In 2012, I recorded, over 8 visits, 1941 locations of the target species in the 15 study sites between 05:20 hours and 12:45 hours (mean = 2h 16min per visit per site). In 2013, each treatment site was mapped over 9 occasions (n = 1636 location points) between 05:29 hours and 12:40 hours (mean = 2h 25min per visit per site).

Eastern Wood-pewee density and territory I mapped 23 and 33 Eastern Wood-pewee territories in 2012 and 2013, respectively. Although not significant, there was an overall increase in average Eastern Wood-pewee male density in the study area between years (paired t = -1.52, d.f. = 21, P = 0.14) (Table A). When comparing within treatments, the control treatments experienced no significant change in Eastern Wood-pewee density between years (Control2012 = 0.106

±0.038 males/ha, Control2013 = 0.112 ±0.043 males/ha; paired t = -0.68, d.f. = 5, P =

0.50), nor did the 2012 Harvest treatment (2012 Harvest2012 = 0.117 ±0.027 males/ha,

2012 Harvest2013 = 0.196 ±0.057 males/ha; paired t = -1.36, d.f. =4, P = 0.23) (Table B). However, the 2013 Harvest treatment saw a significant increase in Eastern Wood-pewee

density between pre-harvest 2012 and post-harvest 2013 (2013 Harvest2012 = 0.057

±0.020 males/ha, 2013 Harvest2013 = 0.155 ±0.009 males/ha; paired t = -6.89, d.f. = 3, P < 0.01) (Table B). There was no significant change in territory size of Eastern Wood-pewee across all treatments levels. Eastern Wood-pewee territory sizes in the Control treatments were 0.517 ±0.106 ha and 0.463 ±0.087 ha for 2012 and 2013, respectively (paired t = 0.4, d.f. = 15, P=0.70). Territory sizes for Eastern Wood-pewee for the 2012 Harvest sites

(2012 Harvest2012 = 0.568 ±0.071 ha, 2012 Harvest2013= 0.643 ±0.085 ha) and the 2013

Harvest sites (2013 Harvest2012 = 0.333 ±0.111 ha, 2013 Harvest2013 = 0.492 ±0.109 ha) did not differ between years (2012 Harvest: paired t = -0.68, d.f. = 24, P = 0.50; 2013 Harvest: paired t = -1.03, d.f. = 8, P = 0.33) (Table C). Densities and territory sizes for Eastern Wood-pewee changed positively in response to single-tree selection harvest treatment. Canopy cover appeared to be the strongest predictor for explaining variation in Eastern Wood-pewee density (Table 3.1) and the parameter estimates were negative for this variable and did not overlap 0, indicating that as canopy cover declined Eastern Wood-pewee density increased. Canopy cover also accounted for 100% of the relative importance for Eastern Wood-pewee densities (Table 3.2). By contrast, no habitat variables were retained in the model for Eastern Wood-pewee territory size (Table 3.3).

Ovenbird density and territory Ovenbird density in the Control stands was similar in 2012 (0.621 ±0.092 males/ha) compared to 2013 (0.477 ±0.018 males/ha; paired t = 1.66, d.f. = 4, P = 0.17) (Table B). However, Ovenbird density in the 2012 Harvest treatment stands decreased significantly from 2012 (2012 Harvest2012 = 0.505 ±0.054 males/ha) to 2013 (2012

Harvest2013 = 0.344 ±0.040 males/ha; paired t = 3.15, d.f. = 5, P = 0.03). Ovenbird density did not change significantly in the 2013 Harvest treatment stands (2013 Harvest2012 =

0.596 ±0.094 males/ha, 2013 Harvest2013 = 0.432 ±0.072 males /ha) between the pre- harvest (2012) and harvest (2013) years (paired t = 2.42, d.f. = 3, P = 0.09) (Table B).

Ovenbird density tended to be lower in all treatment types in 2013 vs. 2012 which suggests that some unexplained but broad scale environmental effect (e.g., wintering ground effect) may have been responsible. Ovenbirds saw no significant change in territory size in the Control treatments with 0.206 ±0.015 ha in 2012 and 0.194 ±0.021 ha in 2013 (paired t = 0.47, d.f. = 68, P = 0.64) (Table C). Ovenbird territory size responded similarly during both harvest treatments. Territory size decreased significantly between years for both 2012 Harvest

(2012 Harvest2012 = 0.200 ±0.016 ha and 2012 Harvest2013 = 0.117 ±0.146 ha; paired t =

3.83, d.f. = 5, P < 0.001) treatment and 2013 Harvest (2013 Harvest2012 = 0.304 ±0.027 ha and 2013 Harvest2013 = 0.198 ±0.019 ha; paired t = 3.21, d.f. = 3, P < 0.01) treatment (Table C). Of the habitat variables, the null model represented the top-ranked model for both Ovenbird density and territory size (Tables 3.1 and 3.3, respectively). Thus, none of the habitat variables I predicted would explain variation in densities and/or territory sizes entered in the model selection above the null model, although sub-canopy and average leaf litter followed the null model by approximately 1.6 and 1.1 AICc units for density and territory size, respectively (Tables 3.1 and 3.3). However, average leaf litter

(F(2,13) = 1.36, P = 0.29) was not significantly affected from the 2013 harvest treatments despite poor harvesting procedures during the 2013 harvest (Table 3.5).

Rose-breasted Grosbeak density and territory Single-tree selection harvesting had no significant influence on Rose-breasted Grosbeak densities in the NCF. Density for Rose-breasted Grosbeak in the Control treatment between years was 0.201 ±0.045 males/ha and 0.188 ±0.048 males/ha in 2012 and 2013, respectively. Rose-breasted Grosbeak density was higher in the 2012

Harvest 1 year post-harvest, although not significantly (2012 Harvest2012 = 0.121 ±0.028 males/ha and 2012 Harvest2013 = 0.171 ±0.027 males/ha; paired t = -1.16, d.f. = 5, P = 0.26) (Table B). Harvesting occurring in the 2013 season had no effect on Rose-breasted

Grosbeak densities (2013 Harvest2012 = 0.102 ±0.016 males/ha, 2013 Harvest2013 = 0.103 ±0.013 males/ha; paired t = -0.02, d.f. = 3, P = 0.99) (Table B).

There was no difference in Rose-breasted Grosbeak territory size in the Control treatment between 2012 (Control2012 = 0.607 ±0.063 ha) and 2013 (Control2013 = 0.503 ±0.064 ha; paired t = 0.94, d.f. = 30, P = 0.35) (Table C). Territory size for Rose-breasted Grosbeak in the 2012 Harvest treatment was 0.677 ±0.055 ha in 2012, and 0.505 ±0.078 ha in 2013 (paired t = 1.77, d.f. = 27, P = 0.08). However, there was a significant decline in Rose-breasted Grosbeak territory size in stands harvested in 2013 from the territory sizes of 2012 (2013 Harvest2012 = 0.991 ±0.073 ha, 2013 Harvest2013 =0.677 ±0.130 ha; paired t = 3.11, d.f. = 5, P < 0.05) (Table C). Among the candidate habitat models for evaluating the impacts on Rose- breasted Grosbeak densities, the null model had the lowest AICc, followed by a model containing percent cover of the shrub layer with a difference of 1.36 AICc units (Table 3.1). However, the model containing shrub layer had the lowest AICc for the response variable Rose-breasted Grosbeak territory size (Table 3.3). The shrub layer was the most relevant habitat variable and was negatively related to Rose-breasted Grosbeak territory size. Therefore, maintaining the shrub layer during single-tree selection harvesting is important for Rose-breasted Grosbeak as it allows for a decrease in territory use which would increase potential post-harvest Rose-breasted Grosbeak densities.

Red-eyed Vireo density and territory Red-eyed Vireo densities remained relatively stable throughout harvested and control stands with slight, but non-significant increases in all treatments (Table B). Red- eyed Vireo densities in the control (Control2012 = 0.060 ±0.051 males/ha and Control2013 = 0.119 ±0.056 males/ha; paired t = -1.35, d.f. = 4, P = 0.25) were lower than in the other two treatment stands (Table B). Red-eyed Vireo densities in the 2012 Harvest treatment were 0.201 ±0.058 males/ha in 2012 and 0.216 ±0.062 males/ha in 2013 (paired t = - 0.24, d.f. = 5, P = 0.82). In the 2013 Harvest treatment, Red-eyed Vireo density was 0.154 ±0.054 males/ha and 0.168 ±0.54 males/ha in 2012 and 2013, respectively (paired t = -0.26, d.f. = 3, P = 0.81) (Table B). Lower Red-eyed Vireo densities in the Control stands could be attributed to fewer deciduous trees in the red pine control sites than in the harvested sites.

In all treatments territory sizes for Red-eyed Vireo were higher across the two years of study. The Control treatment (paired t = -0.55, d.f. = 12, P > 0.05) was higher in 2012 from 0.141 ±0.031 ha to 0.161 ±0.021 ha in 2013. The 2012 Harvest also saw larger territory sizes between the two years although not significant (2012 Harvest 2012 = 0.131

±0.020 ha and 2012 Harvest 2013 = 0.186 ±0.022 ha; paired t = -1.84, d.f. = 34, P = 0.07). By contrast, the 2013 Harvest treatment saw a significant increase in means (2013

Harvest 2012 = 0.138 ±0.027 ha and 2013 Harvest 2013 = 0.205 ±0.011 ha) between years (paired t = -2.29, d.f. = 16, P = 0.03) (Table C) and may have been a result of the poor harvesting procedures. The null was the top-ranked model of the candidate habitat models for Red-eyed Vireo densities followed by a model containing the sub-canopy with a difference of 0.921 AICc units (Table 3.1). Greater sub-canopy cover appeared to have a positive effect on Red-eyed Vireo densities, although this latter variable was relatively unimportant (Table 3.2). By contrast, the model containing average tree height and sub- canopy was the top-ranked habitat model explaining variation in Red-eyed Vireo territory sizes (Table 3.3). Red-eyed Vireo territory sizes responded negatively to average tree height and positively to the sub-canopy. When the variable tree height was in the model by itself, the parameter estimates approached significance (Table 3.4) and when combined with the sub-canopy cover, these two variables had high importance in explaining variation in the size of Red-eyed Vireo territories (Table 3.3).

DISCUSSION Single-tree selection harvesting had mixed effects on densities and territory sizes of the four focal species in the Northumberland County Forest. The densities of three of the four focal species increased in the post-harvested stands but not in the controls. For Ovenbird, densities decreased significantly in both control and harvested areas in the second year of the study. Territory sizes of each focal species responded similarly to density responses. Thus, if densities decreased, so did territory sizes, again, mostly not significantly as a response to the harvest treatments. The only exception to this pattern

was for the Rose-breasted Grosbeaks where densities and territory sizes were negatively correlated within treatments.

Eastern Wood-pewee density and territory size Mean density of Eastern Wood-pewees in 2012 were slightly lower when compared to densities reported from other studies (0.24 territories/ha, Falconer 2010; range: 0.20 – 0.28 mean/ha, Holmes et al. 2012; 0.19 territories/ha, Newell and Rodewald 2012). However the three-fold increase in Eastern Wood-pewee densities in post-harvest stands in 2013 became more comparable to these studies. This could be attributed to particular harvesting practices employed in 2013 which opened the forest canopy extensively creating more of the available edge habitat preferred by Eastern Wood-pewee (Hespenheide 1971, McDermott et al. 2010). As I did not have any control over the degree to which the foresters removed wood in the experimental treatments, it appears that a cut that removes more of the canopy can enhance Eastern Wood- pewee densities (Table 3.5). Most dramatically was a 150% increase in Eastern Wood- pewee density immediately after the 2013 Harvest when compared to the previous year. Further thinning from single-tree selection may provide Eastern Wood-pewees with more suitable habitat. Post-harvest increases in Eastern Wood-pewee densities have also been noted in a study from Ohio (Newell and Rodewald 2012) and a second study from northern Ontario (Holmes et al. 2012). As a result, creating gaps in the canopy and edge habitat as well as maintaining tree height post-harvest are important aspects to consider when managing for this declining aerial insectivore (McCarty 1996, Environment Canada 2014b). Territory size for Eastern Wood-pewee is not often reported in the literature and no literature appears to be available in explaining territory sizes as a result of forest management. Thus, this study appears to provide the first results of Eastern Wood- pewee territory size within a harvested landscape. Territory sizes of Eastern Wood- pewee in the NCF appeared to be considerably smaller (range = 0.33 – 0.57 ha) than that reported from the limited number of other studies (Falconer 2010 – 1.76 ha, McCarty 1996, range 2.2 – 7.7 ha). Falconer (2010) described that polygynous male Eastern

Wood-pewees hold larger territory sizes than monogamous males in a similar pine plantation habitat to the NCF. Therefore, small territory sizes of Eastern Wood-pewee in the NCF may have been the result of primarily monogamous pairings. In passerine bird species, females are expected to select optimal habitat to fledge young, which may suggest that territories in the NCF are of higher quality than those in other habitats [i.e. intraspecific competition hypothesis for the food value theory (Smith and Shugart 1987)] although this deserves further study. Single-tree harvesting in the NCF may have provided Eastern Wood-pewees with more opportunity for resource acquisition and nest-site selection. The gaps created from single-tree selection harvesting and tree height are important habitat features for this species as Eastern Wood-pewee catches insects on the wing by sallying from a perch as well as preferring nest sites on open lower canopy branches of coniferous and deciduous trees (McCarty 1996, Falconer 2010, Kendrick 2012). Therefore, single-tree harvesting may provide more feeding and nesting opportunities for Eastern Wood- pewee. Additionally, in the Ganaraska Forest, a neighbouring plot of land also on the Oak Ridges Moraine, Falconer (2010) found Eastern Wood-pewees preferred wide- spaced mature pine plantations that have been thinned and also experienced higher reproductive success in those stands. Furthermore, the gaps and edges created by single-tree selection harvesting may increase food resource availability as flying insects can be located at forest edges (McDermott et al. 2010).

Ovenbird density and territory size Densities of Ovenbirds were smaller in the second year of the study in both control and harvested sites. Thus, this suggests that single-tree selection harvesting may not have had an impact on the lower densities. Ovenbirds in harvested areas may have attempted to breed in the year of harvest, despite the disturbance, but then dispersed the following year (in the case of 2012 harvest treatments) due to lack of quality habitat. Switzer (1993) referred to this strategy as the “always stay” strategy where despite an alteration reducing habitat quality during the breeding season, the individual remains to complete the year’s life-

history stage but may disperse to more suitable habitat the following year. Density of Ovenbirds in the control sites could have related to the “win-stay:lose-switch” habitat strategy, in that reproductive success was lower for the controls (refer to Chapter 2 of this study) resulting in fewer individuals returning to the control sites the following year (Switzer 1993). Therefore, site fidelity and low productivity may have been a factor influencing densities of Ovenbirds in the control sites. Ovenbird densities in harvested treatments of a contiguous forest may be due to disturbances to the habitat structure as Ovenbirds are area-sensitive species and fragmentation has been shown to be the cause of male dispersal (Bayne and Hobson 2002, Bernard et al. 2011). Similarly, Ovenbird densities in the harvested areas of the NCF, may have been a result of fragmentation and subsequent male dispersal, whereas unharvested sites may have seen low reproductive success which resulted in male dispersal (Bayne and Hobson 2002, Bernard et al. 2011). Alternatively, densities of Ovenbirds across the NCF may have been due to broad scale impacts either during migration or over the non-breeding season. Examining other sources of data (e.g., BBS) to determine if there were broad scale declines elsewhere over the same time period might help to understand the cause of my results. Ovenbird territory size saw a negative year and treatment effect in all treatment types 1 year post-harvest. Haché et al. (2013) reported Ovenbird territory sizes increased 1 year post-harvest. This may be attributed to the habitat differences of a contiguous mixed hardwood forest compared to the monotypical red pine forest structure in the NCF. While the literature supports smaller Ovenbird territory size as a function of increased prey biomass, this may not be the case in landscapes during harvest (Stenger 1958, Smith and Shugart 1987). Under the assumption that individual Ovenbirds are employing the “always stay” approach, the habitat may have been altered greatly resulting in individuals being constrained to a particular area and territories that were patchily distributed on the landscape. Individuals may have their territory disrupted and remain closer to a core territory area where initial habitat assessments may have more available resources. Territory alteration under direct forestry operations is an area of research for Ovenbirds requiring further investigation.

Rose-breasted Grosbeak density and territory size Despite no significant year effect on Rose-breasted Grosbeak density in harvested treatments, Rose-breasted Grosbeak density tended to be lower 1 year post- harvest in the 2012 harvest sites, but not in the 2013 harvest sites or in the control sites. Rose-breasted Grosbeaks are known for their ability to quickly adapt to anthropogenic disturbances (Thompson 2009, Richmond et al. 2012) and quite easily approach human development for food (e.g., bird feeders) (Collins and Horn 2012). Mean territory sizes declined in the 2013 harvest site and continued to decline from the 2012 harvest treatment which may have been a result of increased density. Furthermore, a negative relationship was observed for Rose-breasted Grosbeaks between density and territory size for all treatment types, a relationship that is much more commonly observed than the positive relationship that I found here for the other focal species. With increased Rose-breasted Grosbeak density in the NCF, the area occupied by Rose-breasted Grosbeak individuals decreased, potentially indicating a very plastic territory as a result of harvest treatment. This could be corroborated by the increased density in the 2012 harvest sites in 2013. The intact tree canopy cover may have resulted in the increased density of Rose- breasted Grosbeak in harvested treatments although analysis revealed none of the predicted habitat variables including basal area, sub-canopy and canopy cover helped to explain variation in density. This lack of any satisfactory habitat variable may be a result of the fact that I only monitored adults. In a study of Rose-breasted Grosbeak in southwestern Ontario, Moore et al. (2010) found higher canopy cover was more important later in the season for fledgling survival and not used greatly by adult Rose- breasted Grosbeak during the nesting period. The decline in territory size was steeper in the 2013 harvest compared to the 2012 harvest. In 2013, Rose-breasted Grosbeak territory size declined only slightly in the 2012 harvest treatment, becoming more similar to the control treatments, suggesting an initial territory size reduction but a quick 1 year post-harvest recovery. Furthermore, Rose-breasted Grosbeak territory size in the NCF post-harvest was found to be

explained by a model that included shrub cover. The shrub layer in the NCF was mainly comprised of red and black raspberry but also red elderberry (Sambucus racemosa), which is a preferred berry for Rose-breasted Grosbeaks (Stutchbury et al. 2005). Additionally, adult Rose-breasted Grosbeaks prefer nesting and foraging in dense shrub cover (Doyon et al. 2005, Moore et al. 2010). Therefore, shrub layer retention from harvested treatments may have resulted in lower territory sizes as density increased among adult Rose-breasted Grosbeaks in both treatment types. Despite the lack of literature explaining Rose-breasted Grosbeak territory sizes, Dunham (1966) noted males may show aggression towards each other early in the breeding period, and will tolerate conspecific non-paired males in their territory later in the breeding period. I observed male Rose-breasted Grosbeaks chasing and fleeing and acting aggressively towards conspecific males in the presence of a female early in the breeding period. Additionally, during the nest building stage, male Rose-breasted Grosbeaks appear to follow females over large distances during nest construction (personal observation). Although nest construction is completed by both adults (Wyatt and Francis 2002, personal observation), in some cases males were not observed carrying nest material while females were building suggesting nest building may be completed independently at certain times. Therefore, males may provide protection against female extra-pair copulations in areas of higher densities during the nest building stage. Although, no literature has explained extra-pair copulation among Rose- breasted Grosbeaks or territorial behaviour attributed to extra-pair copulation, the literature suggests females of the Cardinalidae family engage regularly in extra-pair copulations (Ritchison et al. 1994, Estep et al. 2005). Further research is warranted into understanding the behaviour of this common and charismatic species.

Red-eyed Vireo density and territory size Red-eyed Vireo density in the NCF varied very little between treatments. Given the preference of Red-eyed Vireo for deciduous habitat (Marshall and Cooper 2004), harvesting in a pine plantation does not appear to directly or indirectly affect this species’ density. Similar results examining the impacts of silviculture on bird

communities elsewhere have determined that Red-eyed Vireos show no significant changes in density post-harvest (Rodewald and Yahner 2001, Jobes et al. 2004, Doyon et al. 2005, Thompson et al. 2013). By contrast, territory sizes were significantly (2013 Harvest) or near significantly (2012 Harvest) higher in both harvest treatments. Red-eyed Vireo territory sizes that I have documented are considerably smaller than what has been previously reported in the literature (range = 0.86 – 3.71 ha, Cimprich et al. 2000). The 2013 Harvest treatment saw large fragmentation from overuse of skidder trails, as well as the complete removal of the non-native Scots pine (Pinus sylvestris) resulting in large gaps created in the canopy. As a result, Red-eyed Vireo may have had longer flights to access resources necessary to provision young. However, if only pine trees were taken and deciduous remained in the NCF in both years, territory size should have remained similar between years. Marshall and Cooper (2004) noted a negative relationship between foliage density and territory volume for Red-eyed Vireo which may explain the increase in territory size of Red-eyed Vireo in the pine plantation. Canopy cover from deciduous trees is an important habitat predictor for Red-eyed Vireo nests (Marshall and Cooper 2004). In the NCF the best habitat predictor for increased Red-eyed Vireo territory size appeared to be tree height and to lesser extent sub-canopy abundance. The reason for the importance of tree height to increase territory size may simply be due to lack of deciduous trees in the study areas where individual males hold territories (Williamson 1971). Furthermore, females prefer to nest in the sub-canopy layer of deciduous and mixed deciduous-coniferous forests (Cimprich et al. 2000). The ability of Red-eyed Vireos to remain at the same density while altering territory size suggests Red-eyed Vireos are an adaptable species and capable of altering their habitat as a result of single- tree selection harvesting. This is supported by habitat preferences for a less intact forest with early successional hardwood trees and open conditions reported elsewhere (Rempel 2007, Rempel et al. 2007, Yamasaki et al. 2014).

CONCLUSION While single-tree selection harvesting is initially disruptive, the disruption came at a small price for species in the harvested landscape in this study. Localized disruption of single-tree selection harvesting equipment is short-lived rather than chronic, taking place over a period of a few hours in a single area and as a result in some cases may be advantageous if the opening of the canopy coincides with the habitat preferences of the bird species. The structure of the forest remains intact if proper single-tree harvesting procedures are adhered and helps to maintain avian diversity (Doyon et al. 2005, Rosenvald et al. 2011). Therefore, the upper canopy structure is usually altered positively by creating gaps for species like Eastern Wood-pewee and maintaining canopy cover for species such as the Red-eyed Vireo; both of which use the upper layers for singing, sallying and gleaning. Additionally, retention of deciduous shrub and sub- canopy layers from single-tree selection harvesting can positively influence Red-eyed Vireo and Rose-breasted Grosbeak, as these species utilize these layers for feeding and nesting (Cimprich et al. 2000, Moore et al. 2010). On the other hand, harvesting in 2013 opened the forest canopy extensively and although this appeared to have a positive effect on Eastern Wood-pewees, the overall ecologically sustainable practices as well as forestry guidelines appeared to have been overlooked in 2013 in the NCF. This opinion is justified as the forest manager was required to intervene and briefly stop harvesting during the 2013 harvest period to inform the operators to adhere to guidelines set out in Ontario’s FMP (e.g., avoiding indiscriminate felling and skidding, narrower width of skidder trails). The hastiness at which the harvest occurred in 2013 was the result of poor contractual obligations between the harvest operators and the lumber supply company (Ben Walters, pers. comm.). The shrub and sapling layer of the forest is affected mainly from harvesting disturbance as was seen in the effects of harvesting on the ground nesting and foraging Ovenbird density and especially territory size. When managing forests for specific goals, such as developing an uneven-aged from an even-aged forest, one of the primary causes of reduced tree growth rates caused from logging operations is soil compaction and soil

profile disturbance (Rab 2004). To provide a sustainable forest management system, alterations to forest floor structure should be minimized and is dependent on adhering to the standards and guidelines set by agencies (OMNR 2000). Soil compaction can be minimized in Ontario by harvesting in late winter when snow build-up and a thick frost layer would provide adequate protection from compaction. If harvesting is to take place during the late-spring and summer months, soil compaction can be greatly reduced by minimizing the re-use of the skidder trail. Also, the use of new feller buncher technology such as a walking harvester has the potential to greatly reduce disturbance to the forest’s horizontal structure. Under current harvesting technology such as feller bunchers, tougher enforcement on forestry operations at the site can better maintain ecological sustainability during active harvest.

Table 3.1. Habitat models describing the densities of 4 focal species in the Northumberland County Forest. 8 model variables, with the exception of Rose-breasted Grosbeak which contained 16 model variables were selected based on each species known habitat preferences from the literature. Only the models with cumulative weight (ωi) > 0.9 were retained.

Species Models K logLik AICc ΔAICc ωi

EAWP canopy cover 3 16.792 -25.403 0.000 0.642 tree height 4 17.012 -22.025 3.378 0.119 basal area 4 16.847 -21.695 3.708 0.101 Null 2 13.021 -21.000 4.360 0.073

OVEN Null 2 12.501 -20.001 0.000 0.480 sub-canopy 3 13.279 -18.377 1.624 0.213 average leaf litter 3 12.725 -17.268 2.733 0.122

RBGR null 2 17.315 -29.631 0.000 0.389 shrub layer 3 18.224 -28.267 1.364 0.197 sub-canopy 3 17.453 -26.724 2.907 0.091 basal area 3 17.340 -26.498 3.133 0.081 canopy cover 3 17.319 -26.456 3.175 0.080 canopy cover + shrub layer 4 18.582 -25.200 4.470 0.042

REVI null 2 9.751 -14.502 0.000 0.414 sub-canopy 3 10.882 -13.581 0.921 0.261 tree height 3 10.193 -12.204 2.298 0.131 canopy cover 3 9.783 -11.385 3.117 0.087

Parameter 95% Confidence Adjusted Relative Species Coefficient Estimate Intervals S.E. P Importance

EAWP (Intercept) 3.31 0.92 5.71 1.22 0.01 tree height 0.22 -0.59 1.04 0.42 0.59 0.14

basal area 0.12 -0.73 0.97 0.43 0.79 0.12 canopy cover -1.68 -2.96 -0.39 0.66 0.01 1.00

OVEN (Intercept) 0.57 -0.38 1.52 0.48 0.24 average leaf litter -0.32 -1.41 0.77 0.56 0.57 0.15 sub-canopy 0.20 -0.16 0.56 0.18 0.28 0.26

RBGR (Intercept) 0.10 -0.74 0.93 0.43 0.82 basal area 0.06 -0.58 0.70 0.33 0.85 0.09 canopy cover -0.04 -1.23 1.14 0.61 0.94 0.09 shrub layer -0.13 -0.36 0.09 0.11 0.24 0.27 sub-canopy -0.07 -0.35 0.20 0.14 0.60 0.15

REVI (Intercept) 0.15 -1.32 1.62 0.75 0.84 tree height 0.50 -0.72 1.71 0.81 0.42 0.15 canopy cover 0.21 -1.75 2.18 0.21 0.83 0.10 sub-canopy 0.28 -0.14 0.71 1.32 0.19 0.29

Table 3.3. Habitat models describing the territory sizes of 4 focal species in the Northumberland County Forest. 8 model variables, with the exception of Rose-breasted Grosbeak which contained 16 model variables were selected based on each species known habitat preferences from the literature. Only the models with cumulative weight (ωi) > 0.9 were retained.

Species Models K logLik AIC ΔAIC ω c c i

EAWP null 2 -136.275 277.550 0.000 0.520 basal area 3 -135.739 279.660 2.110 0.181 tree height 3 -136.271 280.723 3.173 0.107

OVEN null 2 -113.642 232.283 0.000 0.377 average leaf litter 3 -112.587 233.356 1.073 0.221 canopy cover 3 -113.167 234.515 2.232 0.124 average leaf litter + canopy cover 4 -111.326 234.651 2.368 0.116

RBGR shrub layer 3 -131.669 271.521 0.000 0.330 null 2 -133.658 272.317 0.796 0.222

canopy cover 3 -133.239 274.659 3.139 0.069

shrub layer + canopy cover 4 -131.400 274.799 3.279 0.064

basal area + shrub layer 4 -131.460 274.919 3.398 0.060

basal area 3 -133.385 274.951 3.430 0.059

canopy cover + shrub layer 4 -131.526 275.052 3.531 0.057

REVI tree height + sub-canopy 4 20.246 -28.491 0.000 0.248

tree height 3 18.331 -28.481 0.010 0.247

null 2 16.633 -28.265 0.226 0.222 canopy cover 3 17.248 -26.315 2.177 0.084 sub-canopy 3 17.008 -25.833 2.658 0.066 tree height + canopy cover 4 18.819 -25.638 2.853 0.060 tree height + canopy cover + sub-canopy 5 21.021 -25.376 3.115 0.052

Parameter 95% Confidence Adjusted Relative Species Coefficient Estimate Interval S.E. P Importance

EAWP (Intercept) 0.20 -2.08 2.48 1.16 0.86 tree height 0.08 -2.03 2.20 1.08 0.94 0.13 basal area 0.78 -0.94 2.51 0.88 0.37 0.22

OVEN (Intercept) 0.12 -1.01 1.25 0.58 0.84 average leaf litter 0.33 -0.14 0.80 0.24 0.17 0.40 canopy cover -0.38 -1.10 0.34 0.37 0.30 0.29

RBGR (Intercept) 1.01 -1.68 3.69 1.37 0.46 basal area 0.42 -1.01 1.85 0.73 0.56 0.14 canopy cover -0.86 -3.57 1.86 1.39 0.54 0.15 shrub layer 0.44 -0.05 0.93 0.25 0.08 0.59 sub-canopy 0.18 -0.41 0.78 0.30 0.55 0.07

REVI (Intercept) 0.85 -0.55 2.26 0.72 0.23 tree height -0.71 -1.45 0.03 0.38 0.06 0.57 canopy cover -0.58 -1.77 0.61 0.61 0.34 0.10 sub-canopy 0.20 -0.08 0.47 0.14 0.16 0.36

Table 3.5. Habitat characteristics in the Northumberland County Forest measured after the 2013 harvest period. Variable means were compared between treatments using one-way ANOVA.

Habitat Variable Treatment Mean ± S.E. F(2,13) P live tree (%) 2012 Harvest 0.055 ± 0.007 2013 Harvest 0.060 ± 0.004 1.493 0.261 Control 0.075 ± 0.011 dead tree (%) 2012 Harvest 0.067 ± 0.011 2013 Harvest 0.065 ± 0.014 0.592 0.568 Control 0.054 ± 0.017 shrub layer (%) 2012 Harvest 0.069 ± 0.009 2013 Harvest 0.076 ± 0.011 3.989 0.0446 Control 0.041 ± 0.008 sub-canopy (%) 2012 Harvest 0.068 ± 0.012 2013 Harvest 0.064 ± 0.007 0.492 0.622 Control 0.054 ± 0.008 canopy cover (% closed) 2012 Harvest 84.89 ± 1.65 2013 Harvest 77.73 ± 0.95 1.755 0.212 Control 84.80 ± 1.36 average tree height (m) 2012 Harvest 15.8 ± 0.6 2013 Harvest 15.2 ± 0.8 0.154 0.859 Control 15.4 ± 1.4 incidental tree removal (%) 2012 Harvest 0.047 ± 0.015 2013 Harvest 0.144 ± 0.02 12.19 0.001 Control* 0.013 basal area (m2/ha) 2012 Harvest 7.76 ± 1.28 2013 Harvest 9.01 ± 2.25 0.233 0.796 Control 7.17 ± 0.65 coarse woody debris (%) 2012 Harvest 15.81 ± 2.67 2013 Harvest 21.29 ± 5.87 2.544 0.117 Control 9.90 ± 2.29

Table 3.5 cont’d

Habitat Variable Treatment Mean +/- S.E. F(2,13) P herbaceous vegetation (%) 2012 Harvest 2.45 ± 0.37 2013 Harvest 2.04 ± 0.38 2.573 0.114 Control 4.05 ± 0.82 average leaf litter (%) 2012 Harvest 82.14 ± 3.43 2013 Harvest 80.41 ± 6.05 1.355 0.292 Control 90.44 ± 2.31 bare ground (%) 2012 Harvest 3.32 ± 1.94 2013 Harvest 3.71 ± 1.83 1.073 0.371 Control 0.39 ± 0.18

* one tree removed by chainsaw during the 2013 field season

CHAPTER 4: General Discussion Enforcement of violators of regulations surrounding incidental take has occurred for industry who have incidentally taken larger birds as per FMP’s (see R. v. Syncrude Canada Ltd., 2010 ABPC 229 and R. v. J.D. Irving Ltd.) but for smaller birds and species- at-risk, regulation of incidental take is non-existent. Recent attempts by Environment Canada to limit incidental take of migratory birds has been done through Avoidance Guidelines, however, directives towards an industrial permit program might provide a more thorough resolution to the issue of incidental take, especially for smaller birds. With relevant scientific data (e.g., direct and indirect nest loss from varying intensities of forestry activity) and required intensive biotic and abiotic assessments of the landscape, forest management proposals could include an evaluation of expected loss of species richness and abundance. The required assessments could provide important information that would allow incorporating a formal framework to permit a certain level of incidental take to benefit natural resource development while attempting to reduce the impact that may incur on wildlife species (Runge et al. 2009). Adaptive management must be included as a policy process to incorporate uncertainty about incidental take of migratory birds (Runge et al. 2009). The United States has already put in place the development of a permit program that would allow some level of take to occur with the intention to provide a universal permit to all industries (Holland and Hart LLC 2010). However, this would require an interdisciplinary approach to migratory bird conservation as well as international agreements congruent to withstanding treaties (Holland and Hart LLC 2010). Whatever the levels of incidental take, both natural resources products and the wildlife occupying the habitat must be sustainable in the face of industrial disturbances. Despite the results of this study showing relatively small impacts of active forestry operations on songbird demography in single tree selection systems, it is still important to consider the biodiversity of the landscape and not to diminish the statutes of provincial and federal policies in Canada such as Ontario’s Fish and Wildlife Conservation Act, 1997 and the Migratory Birds Convention Act, 1994 as well as provincially mandated

FMP guidelines. Incidental take should be more strongly regulated and enforced towards sustainable practices directly affecting bird habitat on a larger scale. Incidental take in southern Ontario will more than likely be prominent on developing landscapes and harvesting schedules that are more demanding on bird habitat than that present in my study. Given this approach, alterations to the provisions of the Migratory Birds Convention Act, 1994 may need to occur to establish a level of incidental take that would be allowable. However, this would require much more extensive research examining the direct effects of all industrial impacts on avian communities before conservation suggestions can be established to make sound proposals towards altering Migratory Birds Convention Act, 1994 provisions and/or its regulations. Chapter 2 of this thesis is the first field examination of a direct effect during single tree selection forest harvesting on nest success of five common songbird species. This thesis identified that there is little direct effect of single-tree selection harvesting on the daily nest survival rates and nest success of five species in the Northumberland County Forest. Depending on a species’ ability to adapt to anthropogenic disturbances, single-tree selection harvesting may produce habitat improvements. However, ground nesting and foraging species may be more sensitive to direct single-tree selection harvesting resulting in a negative impact on density and constraining territory sizes; as a result, reducing productivity if food and habitat resources are not available. In Chapter 2, I determined that single-tree selection harvesting had no effect on the daily nest survival rates and nest success of five focal species. I only chose to evaluate the five focal species. An increase in nest searching effort and field technician experience would be necessary to search for the nests of other species. In future, it might be beneficial to monitor nest success of the Black-capped Chickadee (Poecile atricapillus). This species is a primary cavity-nester that prefers old, dead trees, snags and stumps and is abundant (Lindsay 2011). I would have been interested in determining any changes in chickadee territories, density and success due to direct human disturbance especially given their adaptability to humans (Foote et al. 2010).

In this study I only measured incidental take for one level of single-tree selection harvest intensity (30% removal) and in the specific situation of a monotypic red pine plantation. Vanderwel et al. (2009) show that harvesting intensities ranging from 30% – 75% had negative impacts on vertebrate species abundance, including birds. Therefore, an assessment of a range of single-tree selection intensities would have allowed me to measure potential threshold levels of incidental take. Despite the limitations, this study has important ecological significance because, to the best of my knowledge, it provides the first experimental report quantifying incidental take occurring under a method of silviculture treatment. Further research is needed to examine other silviculture methods and their direct impact on birds. Despite the 2013 Harvest removing more wood through harvest (7.76 m2/ha in 2012 vs. 9.01 m2/ha in 2013) and incidental tree removal (2013 Harvest = 14.4%, 2012 Harvest = 4.7%), there was little difference between all other measured habitat variables of the single-tree selection methods employed during the two harvest occasions. Constraining harvest operators to a consistent procedure under increasing intensities of single-tree selection harvesting could provide an estimate or level of threshold that could be attained before single-tree selection harvesting becomes additive to the natural mortality rate. Chapter 3 described the effects of single-tree selection harvesting on the densities and territory sizes of four focal species within the Northumberland County Forest. I determined that each species has a separate response to single-tree selection harvesting. With the exception of the Ovenbird, density and territory sizes changed in response to the harvest. Generally, if the density increased, so did the territory size. This is interesting because Stenger (1958) had shown that territory sizes decrease in more optimal habitats. However, the understory of the forest from the sub-canopy of the forest to the forest floor were disturbed considerably in both years, but especially in 2013, and would suggest the habitat was either improved by single-tree selection harvesting or the area was not saturated by the four breeding species pre-harvest where a relatively patchy habitat structure resulted.

In conclusion, this thesis provided valuable information on the capacity of five focal bird species to adapt quickly to human disturbance. This study suggests that single- tree selection harvesting in monotypic red pine plantations has only a small effect on the capacity of bird species to complete their nesting duties and in some cases may have a positive impact on bird densities within the Northumberland County Forest. However, caution should be met with respect to area-sensitive mature forest species. Further research is required to examine nest success and population dynamics under single-tree selection harvesting at different intensities of harvesting and in different types of habitat.

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APPENDIX

Table A. Mean density and territory sizes of the four focal species throughout the Northumberland County Forest in 2012 and 2013.

Species Density (# of males/ ha ± S.E.) Territory Size (ha ± S.E.) 2012 2013 2012 2013

EAWP 0.087 ±0.018 0.157 ±0.027 0.509 ±0.054 0.552 ±0.054 OVEN 0.568 ±0.016 0.412 ±0.012 0.227 ±0.011 0.170 ±0.013 RBGR 0.143 ±0.021 0.158 ±0.020 0.699 ±0.043 0.530 ±0.047 REVI 0.142 ±0.034 0.171 ±0.034 0.135 ±0.014 0.183 ±0.012

2012 Density 2013 Density Species Treatment (# of males/ha ± S.E.) (# of males/ha ± S.E.) t (d.f.) P

EAWP 2012 Harvest 0.117 ±0.027 0.196 ±0.057 1.36 (5) 0.23 2013 Harvest 0.057 ±0.020 0.155 ±0.009 6.89 (3) 0.006 Control 0.106 ±0.038 0.112 ±0.043 0.68 (4) 0.53

OVEN 2012 Harvest 0.505 ±0.054 0.344 ±0.040 3.14 0.03 2013 Harvest 0.596 ±0.094 0.432 ±0.072 2.42 0.09 Control 0.621 ±0.092 0.477 ±0.018 1.66 0.17

RBGR 2012 Harvest 0.121 ±0.028 0.171 ±0.027 -1.27 (5) 0.26 2013 Harvest 0.102 ±0.016 0.103 ±0.013 -0.02 (3) 0.99 Control 0.201 ±0.045 0.188 ±0.048 0.44 (4) 0.69

REVI 2012 Harvest 0.201 ±0.058 0.216 ±0.062 -0.24 (5) 0.82 2013 Harvest 0.154 ±0.054 0.168 ±0.054 -0.26 (3) 0.81 Control 0.060 ±0.051 0.119 ±0.056 -1.35 (4) 0.25

2012 Territory Size 2013 Territory Size Species Treatment n (ha ± S.E.) n (ha ± S.E.) t (d.f.) P

EAWP 2012 Harvest 11 0.568 ± 0.071 15 0.643 ±0.085 -0.68 (24) 0.50 2013 Harvest 4 0.333 ± 0.111 8 0.492 ±0.109 -1.03 (8) 0.33 Control 8 0.517 ±0.106 10 0.463 ±0.087 0.4 (15) 0.70

OVEN 2012 Harvest 49 0.200 ±0.016 29 0.117 ±0.146 3.83 (74) <0.001 2013 Harvest 29 0.304 ±0.027 21 0.198 ±0.019 3.21 (46) <0.01

Control 43 0.206 ±0.015 38 0.194 ±0.021 0.47 0.64

RBGR 2012 Harvest 16 0.677 ±0.055 17 0.505 ±0.078 1.80 (27) 0.08

2013 Harvest 6 0.991 ±0.073 6 0.677 ±0.130 3.11 (5) 0.03 Control 13 0.607 ±0.063 17 0.503 ±0.064 0.94 (30) 0.35

REVI 2012 Harvest 19 0.131 ±0.020 18 0.186 ±0.022 -1.84 (34) 0.07 2013 Harvest 13 0.138 ±0.027 9 0.205 ±0.011 -2.29 (16) 0.03 Control 7 0.141 ±0.031 12 0.161 ±0.021 -0.55 (12) 0.59