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Forest Ecology and Management 359 (2016) 309320

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Forest Ecology and Management

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Demographic response of a neotropical migrant songbird to forestmanagement and climate change scenarios

http://dx.doi.org/10.1016/j.foreco.2015.10.0020378-1127/ 2015 Elsevier B.V. All rights reserved.

Corresponding author at: Environment Canada, Government of Canada,Yellowknife, Northwest Territories X1A 2P7, Canada.

E-mail address: [email protected] (S. Hach).

Samuel Hach a,, Ryan Cameron b, Marc-Andr Villard a,c, Erin M. Bayne a, David A. MacLean baDepartment of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canadab Faculty of Forestry and Environmental Management, University of New Brunswick, Fredericton, New Brunswick E3B 5A3, CanadacDpartement de biologie, Universit de Moncton, Moncton, Nouveau-Brunswick E1A 3E9, Canada

a r t i c l e i n f o

Article history:Received 23 July 2015Received in revised form 30 September2015Accepted 1 October 2015

Keywords:Climate changeForest managementHabitat degradationPopulation dynamicsSeiurus aurocapillaAvian demography

a b s t r a c t

Demographic models for species sensitive to human activities that are still relatively common are ofparticular interest to compare the relative influence of human land use and climate on population trends.Yet, data limitations often restrict our ability to interpret the numerical response of species to habitatalteration and climatic change adds to this challenge. In this study, we used habitat-specific demographicinformation from an individually-marked population of Ovenbird (Seiurus aurocapilla) and a forest timbersupply model to project population trends over an 80-year horizon. We modelled changes in Ovenbirdabundance, productivity, and population growth rate as a function of harvesting scenarios (no harvest,forestry-as-usual, and increased [10% or 20%] harvesting intensity) and projected impacts of climatechange (0%, 10%, and 50% reductions in population size over the 80-year period), as well as contrastingassumptions about population dynamics (i.e. open vs. closed population). Among the many effects ofclimate change, it has been hypothesized that reductions in annual snow cover will occur, causing deeperand more frequent frost penetration into the soil and, in turn, a reduction in invertebrate (food)abundance during the following breeding season. Our models suggest that the study area currently is ademographic sink (k = 0.920) for Ovenbirds, although some habitat types still act as demographic sources.Over the first 7 years, a large decline in abundance of territorial males (25%) is projected, unless popu-lation levels are maintained through immigration. Interestingly, when we allowed for immigration fromoutside the study area, population growth rate remained

310 S. Hach et al. / Forest Ecology and Management 359 (2016) 309320

mechanisms underlying population declines, which may differ (e.g.Allee effect; Stephens et al., 1999) from those acting on populationdynamics when a species is not yet at risk (Beissinger andWestphal, 1998; Reed et al., 2002; Gilroy et al., 2012). Thus, it isimportant to also model the demographic response of speciessensitive to human land use, yet still relatively common, i.e. focalspecies (Lambeck, 1997; e.g. Lindenmayer et al., 2000; Wintleet al., 2005). This proactive approach allows the developmentof adaptive management frameworks (e.g. Dzus et al., 2009)aiming to prevent sensitive species from becoming at risk(Abbitt et al., 2000).

In North America, many forestry companies have implementedsustainable forest management plans in an attempt to conservebiodiversity. For example, the extent and configuration ofcutblocks and mixed-species plantations are increasingly focusedon emulating natural disturbances (Crow and Perera, 2004; Long,2009; Kuuluvainen and Grenfell, 2012). However, important issueshave been raised (e.g. Klenk et al., 2008), including the fact thatharvesting tends to differ from natural disturbances in its occur-rence, extent, severity, and synchronicity across the landscape(Bergeron et al., 2002; Angers et al., 2005). Forestry activities tendto benefit species associated with early-seral forest and many ofthem are threatened in regions without active logging (Askins,2001; Schlossberg et al., 2010; Sheehan et al., 2014). However,management of even-aged stands through clearcutting and planta-tion silviculture reduces the area of suitable habitat for speciesassociated with late-seral stages (Barrientos, 2010; MacKay et al.,2014), whereas partial harvest systems in deciduous stands maydecrease habitat quality for some taxa (Edman et al., 2008;Vanderwel et al., 2009; Work et al., 2010) owing to a gradual lossof old forest characteristics and simplification of vertical structure(Angers et al., 2005).

In addition to forest harvesting, there is growing concern aboutthe effects of climate change on wildlife populations (Burrowset al., 2011; Davey et al. 2012; Reichert et al., 2012). In the north-ern hardwood forest of North America, complex interactionsamong abiotic factors are anticipated to alter the structure ofspecies assemblages (Rodenhouse et al., 2008, 2009; Groffmanet al., 2012). For example, long-term monitoring at Hubbard BrookExperimental Forest in north-central New Hampshire and recentclimatic models suggest that snow cover events (i.e. number oftimes that the snowpack forms and dissipates during the year) willincrease substantially (1440%) by 2100, with a 2079 daydecrease in the number of snow-covered days owing to warmertemperatures (Campbell et al., 2010). These projections, along withthe negative effects of experimental reduction in snow cover onabundance and richness of litter arthropods the following spring(Templer et al., 2012), suggest a mechanism by which ground-foraging birds feeding on invertebrates such as the Ovenbird maybe affected by climate change (Groffman et al., 2012).

The Ovenbird (Seiurus aurocapilla) is considered to be one ofthe vertebrate species most sensitive to habitat alteration in thenorthern hardwood forest (Vanderwel et al., 2007, 2009). Declinesin density or even local extinctions have been documentedollowing intensive partial harvest treatments such as shelterwoodharvesting (5070% of tree removal; Vanderwel et al., 2009). Whenharvesting is less intensive (e.g. 3040% tree removal throughselection harvesting), reductions in Ovenbird density and produc-tivity per unit area tend to be proportional to the wood volumeremoved (Prot and Villard, 2009; Hach et al., 2013a; but seeMorris et al., 2013). Nonetheless, this ground-foraging songbirdremains regionally common (Porneluzi et al., 2011), making iteasier to develop demographic models and project future trendsunder alternative forest management scenarios (e.g. Larson et al.,2004). Depending on greenhouse gas emission scenarios, thebioclimatic models of Rodenhouse et al. (2008) projected that

Ovenbird incidence in the Breeding Bird Survey (i.e. proportion ofyears per decade with species presence along a BBS route [Saueret al., 2001], averaged for 1233 routes) would be 7.245.6% lowerby the end of the century. Yet, very small differences in occurrencewere projected (0% to 1.5%), suggesting that by the end of thecentury, the species would occupy the same area, but at lowerdensities. Similar patterns are projected for other ground-foraging species and neotropical migrants (Rodenhouse et al.,2008). Understanding how different land use and climatic scenar-ios will influence focal populations in intensively managed forestlandscapes is critical to determine the relative importance ofalternative threats and adjust conservation/management plansaccordingly (e.g. Harris et al., 2014; Virkkala et al., 2014).

The objective of this study was to evaluate the effects of differ-ent forest management scenarios and climate change projectionson a breeding population of Ovenbirds in northwestern NewBrunswick, Canada. We combined empirical data on thedemographic response of this species to habitat alteration (Hachand Villard, 2010; Hach et al., 2013a; Hach et al., 2014a;Vernouillet et al., 2014), projected timber yields from a foresttimber supply model developed by J.D. Irving, Limited (Black BrookDistrict), and anticipated impacts of climate change on our focalspecies to model the number of territorial males and youngproduced, as well as population growth rate (k) over an 80-yearperiod (20122091). We compared the status of a regionalOvenbird population over the projected period according to thecurrent forest timber supply model (forestry-as-usual, hereafterFAU), reductions (10% and 20%) in the ratio of selection harvestingto shelterwood (i.e. larger areas managed through shelterwood),and a no-harvest scenario. These projections were combined withthree scenarios of climatic change on breeding habitat quality:(1) no effect; (2) 10% reduction; and (3) 50% reduction in habitatquality by 2091 (after Rodenhouse et al., 2008). We consideredchanges in the density of breeding males and number of youngproduced to be proportionate to changes in habitat quality associ-ated with climate change. This assumption was based on thedocumented response of Ovenbirds to the alteration of theirhabitat through selection harvesting (Hach et al., 2013a).

Source-sink dynamics, where demographic sources (k > 1)maintain populations in demographic sinks (k < 1), have beenreported or at least suspected in many bird species (Pulliam,1996; Rodenhouse et al., 1997; Murphy, 2001; Tittler et al.,2006). However, the spatial scale at which such populationdynamics take place remains largely unknown (reviewed byHach et al., 2014b). We considered two scenarios with respectto population dynamics. Specifically, we modelled Ovenbirdpopulation size: (1) irrespective of habitat-specific populationgrowth rate, assuming that territory vacancies would be filled bybirds from demographic sources outside the study area (i.e. openbreeding population); and (2) considering intrinsic change inpopulation size as a function of population growth rate in theabsence of emigration or immigration (i.e. closed breedingpopulation). Support for a closed population comes from stableisotope analyses indicating that most individuals recruited inindividually-marked subpopulations in the study area had proba-bly fledged locally (i.e. within the Black Brook District; Hachet al., 2014b).

2. Methods

2.1. Study area

The study was conducted in the Black Brook District, northwest-ern New Brunswick, Canada (47230N, 67400W). The land basecovers 2000 km2 and is privately owned by J.D. Irving, Limited.

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Black Brook is one of the most intensively-managed forests in east-ern North America (Montigny and MacLean, 2005). It is composedof deciduous stands (25% of total area; sugar maple [Acer saccha-rum], yellow birch [Betula alleghaniensis], and American beech[Fagus grandifolia]), coniferous stands (20%; black spruce [Piceamariana], white spruce [Picea glauca], and balsam fir [Abiesbalsamea]), mixedwood stands (18%), and conifer plantations(37%; see Etheridge et al., 2005 for details).

For 30 years, J.D. Irving, Limited has managed deciduous standsand deciduous-dominated mixedwood stands using selectionharvest treatments, single-tree selection harvesting being the mostwidely used. This treatment typically removes 3040% of the basalarea (cross-sectional area at breast height [1.35 m] of all stemswith a diameter P10 cm) every 2025 years. The creation of skidtrails (5 m wide) accounts for ca. 20% of the basal area removedand the extra 1020% is harvested from the residual forest betweenskid trails. Other treatments of similar intensity resulting indifferent configurations of residual trees such as strip and patchcuts (i.e. group selection) and pre-commercial thinning are appliedsporadically. Alternatively, shelterwood harvesting removes5070% of the basal area and is applied to improve growing stockof deciduous and deciduous-dominated mixedwood stands andreduce the prevalence of American beech which is severelyaffected by beech bark disease. A second entry to remove theremaining commercial trees occurs when the deciduous regenera-tion is well established (ca. 25 years). Approximately 15 years afterthe second entry, improved stands are thereafter managed througha selection harvesting regime or another shelterwood treatmentcan be applied earlier if further improvement is required.

Since 1957, the company has focused largely on regeneratingspruce species because they are less affected by eastern sprucebudworm (Choristoneura fumiferana) than balsam fir, which other-wise would have predominated. The species most often plantedwere white and black spruce and, more recently, red and Norwayspruce (Picea rubens; Picea abies) and white pine (Pinus strobus)are also being planted as species mixtures. Conifer plantationsare generally harvested when they reach 4050 years (G. Adams,J.D. Irving, Limited, pers. comm.). Naturally-regenerated coniferforests, dominated by black spruce and balsam fir, represent asmall percentage of the district in long-range planning and areassociated with riparian buffer strips, reserves, and lower produc-tivity sites (G. Adams, J.D. Irving, Limited, pers. comm.).

2.2. Ecology and habitat-specific demography of the Ovenbird

The Ovenbird is a neotropical migratory songbird that reachesits highest density and productivity per unit area in mature decid-uous and deciduous-dominated mixedwood stands with a rela-tively closed canopy and sparse understory (Prot and Villard,2009; Porneluzi et al., 2011). It is a ground-nesting species foragingalmost exclusively on litter invertebrates (Holmes and Robinson,1988) and consuming prey proportional to their availability(Stenger, 1958).

Every year from 2006 to 2011, we monitored the demographicresponse of the Ovenbird to selection harvesting in five pairs of25-ha study plots, including five treated plots and five controls.Specifically, we measured density, productivity per unit area, percapita productivity (Hach et al., 2013a), recruitment (Hach andVillard, 2010), and apparent survival of juveniles (Hach et al.,2014a) and adults (Vernouillet et al., 2014) during the first fiveyears following a first entry selection cut, except juvenile survival(until day 14), which was measured during the fourth and fifthyears post-harvest (Table 1). Reductions in density, productivityper unit area, and food abundance, and an increase in territory sizewere observed following selection harvesting, but these effectswere no longer significant by the fifth year post-harvest (Hach

et al., 2013a). Selection harvesting had no significant effecton apparent adult survival rate (Hach and Villard, 2010;Vernouillet et al., 2014), juvenile survival rate (Hach et al.,2014a), or per capita productivity (Hach et al., 2013a; see alsoLeblanc et al., 2011). Unfortunately, we could not determine theeffects of 2nd or 3rd entry selection cuts as these treatments hadyet to be applied in the study area or elsewhere in the region. In2010, we also measured the density and productivity per unit areaof Ovenbirds in recent (first year post-harvest; n = 3) and oldshelterwood (1620 years post-harvest; n = 3; 25-ha study plots)using the same protocol as Hach et al. (2013a). No individualswere detected during four surveys in recent shelterwood, whiledensity (based on eight spot mapping visits) and productivity perunit area in old shelterwood were respectively 41%, and 66% lowerthan in recent selection cuts (i.e. mean values from 1 to 5 yearspost-harvest). Results from point count and spot mapping datasuggest that Ovenbirds can also defend territories in matureconifer-dominated mixedwood and conifer stands and plantations(Gunette and Villard, 2005; MacKay et al., 2014). However, theabundance of territorial males varies as a function of the numberof years following a clearcut. Thus, we reported density estimatesfor conifer stands in three categories (610, 1125, and >25 yearsince harvesting; see Appendix A for details).

2.3. Modelling approach

2.3.1. Step 1. Demographic modelWe used the demographic information provided by the studies

listed above to generate habitat-specific estimates of density,number of young produced, and population growth rate(k; Table 1). Habitat-specific k was calculated as:

k /A w /F /A 1

where /A is the apparent survival rate of adults, w is the per capitaproductivity, and /F represents postfledging survival rate at day 14.We made the following assumptions: (1) survival rate of juvenileswas the same as that of adults after day 14 (little mortality has beenreported between day 14 and independence; Streby and Andersen,2012, 2013; but see Dybala et al., 2013); (2) apparent survival ofadults defending a territory in plantations and shelterwoodwas equal to that observed in recent selection cuts, until post-treatment density and productivity per unit area reached those ofuntreated deciduous stands; then, apparent adult survival wasassumed to be the same as in untreated deciduous stands; and (3)individuals defending territories in conifer stands and spruceplantations do not produce young (see also Porneluzi et al., 2011).

The sex ratio in adult songbirds is generally male-biased(e.g. 1.14:0.86, Donald, 2007; see also Amrhein et al., 2012). Highpairing success has been reported in untreated deciduous standsand recent selection cuts (Bourque and Villard, 2001; Hachet al., 2013a). However, a male-biased sex ratio is expected inrecent shelterwood and conifer stands owing to low habitat qual-ity. This would lower the breeding success of males occupyingthese stands, or reduce it to zero (Table 1).

In post-harvest years for which we did not have empirical data,density and productivity per unit area in deciduous stands wereextrapolated assuming a linear increase with the number of yearspost-harvest, while per capita productivity was assumed to remainconstant (e.g. Hach et al., 2013a). Density and productivity perunit area in these stands were assumed to remain constant oncethey had reached the same values as in untreated stands (Table 1).Values were averaged over 5-year periods to coincide with thetemporal resolution provided by the timber supply model usedby the forestry company (see Step 2).

Table 1Mean values (SE) used to generate abundance, number of young produced, and population growth rate in Ovenbirds breeding in the Black Brook District, New Brunswick.Empirical data used to generate estimates for other habitat types are shown in bold. Select. harv. = Selection harvesting, Shelt. harv = Sheltherwood harvesting, and k = populationgrowth rate.

Year Density Productivity Per capita Survival k

(/25 ha) (/25 ha) Productivity Adult Juvenilea

Untreated deciduous 12.0 (0.6) 21.5 (1.7) 0.86 (0.05) 0.73 (0.02) 0.33 1.01Select. harv. 15 8.8 (0.4) 15.2 (1.5) 0.81 (0.06) 0.67 (0.03) 0.30 0.92

>5 12.0 21.5 0.86 0.73 0.33 1.01

Shelt. harv. 15b 0.7 0.6 0.46 0.67 0.30 0.81610 2.4 2.1 0.46 0.67 0.30 0.811115 4.2 3.6 0.46 0.67 0.30 0.811620b 5.9 5.1 0.46 0.67 0.30 0.812125 7.6 6.6 0.46 0.67 0.30 0.81>25 9.4 16.2 0.81 0.67 0.30 0.92

Conifers 010 0 0 0 0 0 01125 0.7 (0.3) 0 0 0.67 n/a 0.67>25c 6.0 0 0 0.67 n/a 0.67

a We estimated juvenile survival by multiplying postfledging survival (0.46; see Hach et al., 2014a for details) by adult survival.b We only had empirical data from the first and 16th years post-harvest. Values shown represent predicted means for the 5-year periods.c Density estimates from point count data were calibrated (see Appendix A) and we present mean predicted values from two datasets (Gunette and Villard, 2005; Mackay

et al., 2014).

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2.3.2. Step 2. Forest timber supply modelJ.D. Irving, Limited generated its timber supply model for the

Black Brook District using Woodstock, which is a linearprogramming optimization software that determines the optimumtreatment schedule to maximize a value across a range ofmanagement constraints (Remsoft Inc., 1996). The simulation isbased on an area file which is an aspatial representation of thestudy landbase that has been subdivided into landscape themesrelative to management objectives. For example, attributes suchas stand type, operability constraints, and ecoregion have beenintegrated. Individual stands were aggregated into strata basedon similar age and stand characteristics. Management interven-tions included were selection harvest, shelterwood harvest, patchharvest, final harvest/tree planting, and precommercial and com-mercial thinning. Operability limits for these actions were basedon J.D. Irving, Limited operation standards, along with thepredicted stand response (i.e. which stand type, class, age, andgrowth projection [yield curve] treated areas will regenerate inpost-harvest years). Stand growth patterns were simulated usingprojections from the STAMAN stand growth model (VanguardForest Management Services Ltd., 1993) using the New Brunswickpermanent sample plot network to calibrate growth projections.The baseline management strategy was set to maximize spruce,fir, pine, and deciduous hardwood harvest, while ensuring that aspecified amount of shelterwood and selection harvest providesthe deciduous harvest volume. Other management constraintswere in place to ensure that non-declining harvest levels, non-declining operable growing stock levels, maintaining protectedareas for biodiversity, non-declining forest cover types, and desiredsilviculture targets are met. The forest timber supply model used inthis study generated projections of the land base every 5 years overan 80-year period (20122091).

Conifer stands (hereafter conifers), i.e. conifer and conifer-dominated mixedwood stands and plantations, were consideredto have the same habitat quality for Ovenbirds. Similarly, decidu-ous and deciduous-dominated mixedwood stands (hereafterdeciduous) were considered equivalent for Ovenbirds. Patch cuts,strip cuts, and pre-commercial thinning were considered to have asimilar effect on Ovenbirds as selection harvesting (Prot andVillard, 2009) and these treatments were pooled and are hereafterreferred to as selection harvesting. For each 5 year period(16 periods; 20142089), the area managed through selectionharvesting was divided into two post-harvest categories (15 and

>5 years post-harvest), whereas the shelterwood area was dividedinto six periods (15, 610, 1115, 1620, 2125, >25 yearspost-harvest). The difference in the number of post-harvest yearsmonitored for each treatment reflects the time required beforereaching values equal to untreated stands or for shelterwoodstands to enter a selection harvesting regime. The forest timbersupply model allowed for some deciduous-dominated mixedwoodstands in yearx to shift to conifer-dominated mixedwood stands insubsequent years and vice versa (after Etheridge et al., 2005 andAmos-Binks et al., 2010). This resulted in temporal variation inthe area covered by conifers and deciduous stands. The timbersupply model did not maintain the same exact area to be managedthroughout the simulation period owing to changes in roadnetwork, infrastructures, and land use.

2.3.3. Step 3. Forest management scenariosFirst, we used the J.D. Irving, Limited forest timber supply

model for the Black Brook district (i.e. forestry-as-usual; FAU) tomodel the Ovenbird population (abundance of territorial males,number of young produced, and population growth rate) over an80-year period (20122091). We explored three additionalmanagement scenarios: (1) no harvesting (i.e. assuming the entirearea is comprised of mature stands); (2) 10%; and (3) 20% decreasein the selection to shelterwood harvesting ratio relative to the FAUscenario (i.e. converting 10% and 20% of the area managed throughselection harvesting into shelterwood throughout the 80-year per-iod). The no harvesting model was meant to provide ecologicalbenchmark values, whereas the two other scenarios quantifiedthe effects of more intensive harvesting on the Ovenbird popula-tion. The no-harvest scenario may appear simplistic because itdoes not account for the effects of insect outbreaks or dieback oneven-aged conifer stands. Such disturbances would create mosaicsof stands of different age across the study area. Yet, this scenario isrealistic for uneven-aged deciduous stands which are the mostimportant for breeding Ovenbirds. Hence, we felt that predictionsderived from this ecological benchmark would be useful to com-pare to those from the different harvesting and climate scenarios.

Because it does not account for natural disturbances, the timbersupply model might underestimate the area harvested throughsalvage logging (see Meehl and Tebaldi, 2004 for anticipatedincrease in drought events). Salvage logging and stands with hightree mortality that cannot be salvaged are both expected to havesimilar effects as shelterwood harvesting on Ovenbird populations.

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Hence, to some extent, the two more intensive harvesting scenar-ios can be used to mimic potential responses of forestry operationsand, ultimately, Ovenbird populations, to natural disturbances. Themain natural disturbances occurring in the study area are insectoutbreaks and fires, but they are highly controlled and rarelyinfluence the dynamics of deciduous stands (G. Adams, J.D. Irving,Limited, pers. comm.). Stand-replacing windthrow events tend tooccur every 1000 years in forests of the Northeast (Seymouret al., 2002) and the analysis of an old growth forest landscape(i.e. mosaic of deciduous, mixedwood, and coniferous stands) ofnorthern Maine indicated a canopy disturbance rate of 9.6% perdecade (Fraver et al., 2009). However, disturbance agents such asdrought and pathogens can interact with abiotic and biotic factorsand the resulting dieback can create spatial heterogeneity andinfluence species composition (Hughes, 1960; Amos-Binks et al.,2010). Some mixedwood stands might also represent a naturaltransition following such natural disturbances (Amos-Binks et al.,2010). In the timber supply model, natural disturbances are notprojected, except for natural senescence beyond a specific standage. However, to some extent, harvest treatments are allocatedto mimic natural disturbances in terms of area and volumeharvested (Etheridge et al., 2006). Hence, landscape stochasticity(e.g. Wintle et al., 2005; Chisholm and Wintle, 2007) was notintegrated into our models.

2.3.4. Step 4. Climate scenariosThe four forest management scenarios above assume no effect

of climate change on our focal species. This is a realistic assump-tion as litter invertebrates might adapt, or the invertebrate com-munity might change in response to climate change, maintainingsimilar overall abundance and biomass. Changes in prey commu-nity composition might have limited consequences on generalistinsectivores such as the Ovenbird (Stenger, 1958). Alternatively,potential negative effects might be compensated by a longer grow-ing season providing opportunities for additional breedingattempts or even double brooding, which has been documentedfor this species at lower latitudes (Podolsky et al., 2007; see alsoTownsend et al., 2013).

In our study area, mean annual temperature was 4.5 C 1.2(SD) between 2009 and 2011 (Environment Canada, 2013).Climatic projections using the Delta method (Ramirez-Villegasand Jarvis, 2010) and the SRES A2 (Special Report on EmissionsScenarios; Nakicenovic et al., 2000) emission scenario from fourclimatic models (ukmo hadgem1: Martin et al., 2006; mpi echm5:Roeckner et al., 2003, 2004; gfdl-cm2.1: Delworth et al., 2006; andcccma_cgcm3_1_t47: Canadian Centre for Climate Modelling andAnalysis, 2013) suggest that mean annual temperature willincrease by 3.4 C (0.8) on average between the 20202029 and20802089 periods (ca. 86.3% increase; Ramirez and Jarvis, 2008).

In New Hampshire, the Hubbard Brook Experimental Forestexperiences a mean annual temperature (20092011; 5.4 C 0.8;Campbell and Bailey, 2013) that is slightly higher than in our studyarea. However, the projected increase in temperature by 2089whenusing the same emission scenarios and climatic models is expectedto be similar to our study area (3.4 C 0.8; see Hayhoe et al., 2007for mean values from a broader range of emission scenarios andmodels). Hence, the anticipated negative effects of climate changeon Ovenbirds and other ground-nesting songbirds in the HubbardBrook Experiment Forest and northeastern United States(Rodenhouse et al., 2008; Groffman et al., 2012; Templer et al.,2012) are likely to apply to our study area given their similar treespecies composition.

We considered two additional scenarios to account for potentialeffects of low (10%) and high (50%) reductions of litter inverte-brates projected as a result of climate change (i.e. lower habitatquality; Groffman et al., 2012; Templer et al., 2012). Ovenbird

territory size, density, and productivity per unit area are positivelycorrelated with the abundance of litter invertebrates (Hach et al.,2013a). To model effects of lower food abundance on Ovenbirds,we decreased habitat-specific density and productivity per unitarea by 0.7% (low) and 3.3% (high) every 5 years for the durationof the simulation period to obtain 10% and 50% reductions, respec-tively, by 2091. In these models, we assumed no effect of reducedfood abundance on per capita productivity (as per Hach et al.,2013a; but see Seagle and Sturtevant, 2005). These two scenariosare consistent with projected declines in Ovenbird incidence innortheastern United States according to different emission scenar-ios and climatic models (Rodenhouse et al., 2008).

2.3.5. Step 5. Source-sink dynamicsAdult male Ovenbirds show high site fidelity (Hach and Villard,

2010), as do adult songbirds in general (Greenwood and Harvey,1982). Hence, the spatial scale at which source-sink dynamics takeplace should be commensurate with the extent of natal dispersalmovements (Tittler et al., 2006), i.e. the movements of juvenilesfrom their natal site to their first breeding site. By combining stableisotope analyses and bivariate assignment tests, we showed thatmost first-year breeding males (94%) probably hatched within ourstudy area (minimum dispersal distance; Hach et al., 2014b).However, the potential area of origin of most individuals extendedup to 200 km (maximum dispersal distance) beyond the limits ofthe Black Brook District. Given this uncertainty in the extent ofnatal dispersal movements, we modelled Ovenbird abundance(territorial males) and number of young produced as a function oftwo population dynamics scenarios. Projections were first gener-ated irrespective of population growth rate (Open), assuming thatsurpluses or deficits of territorial males were compensated throughimmigration and emigration (i.e. large-scale source-sink dynamics;Tittler et al., 2006, 2009). The second scenario assumed that source-sink dynamics occurred over a spatial scale corresponding to thesize of the study area and that population dynamics were onlyinfluenced by local population growth rate (Closed).

For the Open population scenario, density of territorial malesand young produced per unit area (productivity) for each standtype and number of years post-harvest (Table 1) were multipliedby the area of each stand type. This was conducted for each yearof the simulation period (using 5-year averages). Hence, theOvenbird population was only influenced by variation in localhabitat quality in this scenario. For the Closed population scenario,abundance of territorial males and the number of young producedin yearx were adjusted according to the population growth rateestimated in yearx1. We assumed that deciduous and deciduous-dominated mixedwood stands were saturated with Ovenbirdswhen they reached habitat-specific density estimates reported inTable 1. However, conifer stands were allowed to support higherdensities to mimic crowding effects following years where k > 1and instances where population size in yearx would support higherdensities than at the beginning of the simulation. If individualswere added to the population in yearx, i.e. k > 1 in yearx1, newindividuals were assigned to the lowest quality habitat wheremales would be defending a territory (e.g. Shelterwood harvesting1115). In this example, new individuals were added to this standtype until the abundance (and corresponding number of youngproduced) reached the maximum value for this stand type (i.e.maximum abundance = 4.2 males areax; Table 1). The remainingindividuals would then be added to the next more suitable habitatthat would not be supporting territorial males in yearx1 (e.g.Shelterwood harvesting 610). Alternatively, if individuals had tobe removed from the population in yearx, i.e. k < 1 in yearx1, thosedefending a territory in the lowest quality habitat were removed.Using the same example as above, if Shelterwood harvesting610 was the lowest quality habitat supporting territorial males

Fig. 1. Area for each stand category used to model the future status of Ovenbird inBlack Brook from 2012 to 2089. Predictions are from the J.D. Irving, Limited foresttimber supply model.

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in yearx, individuals were first removed there and if more individ-uals had to be removed they would be selected among those in thesecond lowest quality habitat (Shelterwood harvesting 1115).This process reflects the site-dependent regulation of populationproposed by Rodenhouse et al. (1997). Algorithms were built tofollow an automated process using Microsoft Excel 2010.

A total of 9 scenarios (i.e. 4 forest management outcomes, 3 cli-mate change-related habitat alteration levels, and 2 populationdynamics) were combined in 15, 15, and 5 models estimatingabundance, number of young produced, and population growthrate, respectively, to determine the relative importance of differentharvesting, climatic, and population dynamic scenarios on the sta-tus of the Ovenbird in Black Brook (see Table 2 for the scenarioconsidered for each model). For population growth rate, we areonly presenting results from the no climate models because thebest information currently available suggests that the effects of a10% or 50% reduction in habitat quality owing to climate changeon population dynamics (e.g. per capita productivity and survival)would not influence population growth rate (Hach et al., 2013a),but would decrease the carrying capacity of the study area. Resultsare presented for the first year of the study (2012) and as meanannual values per 5-year period thereafter (20122016 = 2014,20172021 = 2019, etc.).

3. Results

From 2012 to 2089, the projected area of deciduous forestremained relatively constant, at 3846% of the total forested area(64,33085,360 ha; Fig. 1). The area of untreated deciduous forestwas projected to decline by 14,000 ha by 2024, but it followed asimilar pattern in subsequent years. By the 10th year, the areamanaged through selection harvesting was projected to increaseby ca. 8000 ha and remain relatively constant thereafter, whileshelterwood harvesting remained at low levels throughout theprojected period (04.8% of the forest land base, respectively).Lastly, the area covered by conifer stands was projected to varybetween 56% and 62% of the total area. Areas for each treatmentas a function of the number of years post-harvest under theforestry-as-usual (FAU) scenario are reported in Appendix B.

According to the FAU scenario without the effects of climatechange, 46,070 territorial males would be present each year duringthe 20122016 period and values were projected to remain rela-tively constant throughout the projected period (47,000 470males; mean SE). Male abundance was projected to be 38,840

Table 2The 15 models used to predict abundance (territorial males) and the number of young fledwere used to estimate population growth rate (k). Open refers to scenarios assuming that pas-usual.

Harvesting Climate Population dynamic

FAU No climate Open10% climate Open50% climate OpenNo climate Closed10% climate Closed50% climate Closed

No harvest No climate Open10% climate Open50% climate Open

10% shelterwood No climate Open10% climate Open50% climate Open

20% shelterwood No climate Open10% climate Open50% climate Open

and 21,580, respectively, by 2089, under scenarios of low (10%)and high (50%) effects of climate change (i.e. lower habitatquality), respectively (Fig. 2). Under the FAU scenario without theeffects of climate change, male abundance in 2012 was 25% lowerthan projected from the no harvest scenario without effects ofclimate change (61,870 males; Fig. 2A). By 2089, male abundancewas higher under the FAU scenario without effects of climatechange (43,160 males) and with a 10% reduction in habitat quality(38,840 males) than under the no harvest scenario with a 50%reduction in habitat quality (30,940 males).

Higher harvesting intensity (i.e. reducing the selection: shelter-wood ratio by 10 and 20%) had less of an effect on the abundance ofterritorial males than the reduction in habitat quality caused byclimate change. Indeed, compared to the FAU scenario, 1092(22) fewer males on average per period (2.0% to 2.9%) werepredicted if there was a 10% increase in harvesting intensity, whilethis difference was 2190 (43) males for a 20% increase in harvest-ing intensity (Fig. 2B).

According to the FAU scenario without effects of climatechange, the number of young produced also remained relatively

ged (Productivity) in Ovenbirds breeding in Black Brook, New Brunswick. Five modelsopulation size are maintained (Open) or not (Closed) by immigration. FAU = forestry-

s Abundance Productivity k

Fig. 2. Number of males projected to defend a territory in the study area over the20122089 period under the forestry-as-usual (FAU) scenario, two potential effectsof habitat degradation owing to climate change (10% and 50% decrease in habitatquality), and immigration (Open population). Values were compared to the noharvest scenario (A), 10% and 20% increases in harvesting intensity (B), andassuming that population size is not maintained by immigration (Closed; C).

Fig. 3. Predicted number of young produced in the study area over the 20122089period under the forestry-as-usual (FAU) scenario, two potential effects of habitatdegradation owing to climate change (10% and 50% decrease in habitat quality), andimmigration (Open population). Values were compared to the no harvest scenario(A) and to 10% and 20% increases in harvesting intensity (B).

Fig. 4. Predicted population growth rate (k) in Ovenbirds breeding in the study areafrom 2012 to 2089 under five harvesting scenarios: (1) forestry-as-usual (FAU); (2)no, (3) moderate, or (4) high harvest levels, assuming immigration from outside thestudy area (Open), and (5) under FAU but assuming no immigration from outsidethe study area (Closed).

S. Hach et al. / Forest Ecology and Management 359 (2016) 309320 315

constant throughout the projected period, at 59,900 (920), onaverage, per period (Fig. 3). Interestingly, based on this scenario,productivity would currently (20122016) be only 6% lower thanvalues projected from the no harvest scenario without effects ofclimate change (Fig. 3A). By 2089, the difference between the num-ber of young produced under the FAU with a 10% reduction in habi-tat quality (climate change) and a 20% increase in harvestingintensity was only 102 young (Fig. 3B). Differences between thenumber of young produced under the FAU scenario and a 10%increase in harvesting intensity was on average 2520 (176),

whereas this difference was, on average, 5040 (352) young perperiod based on a 20% increase in harvesting intensity.

316 S. Hach et al. / Forest Ecology and Management 359 (2016) 309320

Based on the FAU harvesting scenario without effects of climatechange, the study area acted as a demographic sink throughout theprojected period (0.906 0.009; Fig. 4). Mean population growthrate throughout the projected period was only slightly lower for10% and 20% increases in harvesting intensity, with k = 0.901( 0.002) and 0.896 (0.003), respectively. The lowest k (0.869)was under the no harvest scenario (Appendix C). So far, thenumbers of territorial males and young produced were estimatedirrespective of population growth rate and assuming thatpopulation size was maintained by immigration and emigration.If population size was not maintained by immigration, a declinein abundance was projected to occur between 2012 and 2019(25%) and it would stay relatively constant thereafter(mean = 34,000 560; Fig. 2C). This projected change in abundancewould coincide with an increase in population growth rate by0.071 during this period and have a mean value of 0.999 (0.001)in subsequent periods (Fig. 4). Under a scenario assuming noimmigration and a 50% reduction in habitat quality resulting fromclimate change, 14,750 males are projected to defend territories inthe study area by the 2089 period, which is 32% less than thepredicted value under the same conditions, but assuming thatpopulation size is maintained through immigration (i.e. withoutconsidering population growth rate; Fig. 2C). Interestingly, underthe FAU scenario, the predicted number of young produced wasidentical whether population size was maintained by immigrationor not.

4. Discussion

Our simulations reveal two important findings: (1) the pro-jected effects of climate change on population size and productiv-ity are expected to be greater, over the long term, than those ofharvesting, but (2) model projections are very sensitive to popula-tion dynamics. When assuming that populations from outside thestudy area did not supply recruits (FAU scenario and no effect ofclimate change), the study area initially acted as a demographicsink (k = 0.920), population size decreased by 25% by the end ofthe decade (2019) and it remained relatively stable thereafter.The study area currently supports ca. 25% fewer male Ovenbirdsthan it would if the entire study area was comprised of matureunharvested stands. However, the current landscape produces onlyca. 6% fewer young.

Rodenhouse et al. (2008) pointed out the important uncertaintythat surrounds species response to climate change (see also Kujalaet al., 2013). Future studies investigating the effects of varyingweather conditions on the biomass and species composition oflitter invertebrates would be needed to better predict the causalrelationships between climate change and the status of ground-foraging species like the Ovenbird (e.g. White, 2008; Boggs andInouye, 2012). The potential effects of regional differences in theamount of precipitation and elevation, and how they may influencesnow cover and, in turn, litter invertebrates should be further eval-uated. It is also exceedingly difficult to predict interactions amongnatural disturbances, human land use, invasive species, pathogens,or insect outbreaks and climate change. Thus, changes in standcomposition and growth rate are difficult to anticipate (reviewedby Groffman et al., 2012; Selwood et al., 2015; see also Jarzynaet al., 2015). Although we do not know what tree species will dom-inate deciduous stands in Black Brook by 2089, the timber supplymodel was built to maintain a similar proportion of conifer anddeciduous stands throughout the simulation period. The Ovenbirdbreeds in a broad range of deciduous and mixedwood stand types(Porneluzi et al., 2011), suggesting that it is tolerant to tree speciescomposition. The effects of climate change are therefore morelikely to be associated with habitat degradation than with habitatloss due to shifts in stand composition in our study area (see also

Rodenhouse et al., 2008). Even under a low greenhouse gas emis-sion scenario (10% reduction in habitat quality), climate changewas projected to have more important effects on the number ofmale Ovenbirds in Black Brook than the high-intensity harvestingscenario (Fig. 2b). However, we cannot rule out the possibility thatour scenarios without climate change effects are realistic given theuncertainty about species responses to climate change.

Although the Ovenbird population of the study area as a wholeis likely acting as a demographic sink, our simulations suggest thatsource-sink dynamics are taking place within the study area.Untreated deciduous stands and selection cuts >5 years post-harvest are projected to act as demographic sources, whereas allother stand types would act as demographic sinks (Table 1). Thelow population growth rate estimated for our study area is mostlyattributable to the large proportion of conifer stands (up to 60%).This proportion is projected to remain stable throughout the mod-elled period (5762%). Although Ovenbirds are absent or present atlow density in conifer stands, they would still host ca. 24% of ter-ritorial males (2432% over the projected period), assuming a con-stant immigration rate. Under the no harvest scenario, where thestudy area is considered to be comprised only of mature stands,an increasing proportion of individuals were projected to defendterritories in conifer stands (40%). This result reflects the fact thatmature conifer stands support higher densities of Ovenbirds, inspite of their low population growth rate, than the younger, man-aged conifer stands that would be present in all other scenarios.Hence, conifer stands have a greater impact on the overall popula-tion growth rate in this scenario because they support more indi-viduals. This also explains the lower population growth ratepredicted under this scenario even though deciduous stands areexpected to be more productive for Ovenbirds than in any otherscenario (Fig. 4; Appendix C). However, in the absence of immigra-tion, the percentage of breeding Ovenbirds in coniferous stands isprojected to be

S. Hach et al. / Forest Ecology and Management 359 (2016) 309320 317

through the creation of early-seral habitat (Schlossberg et al.,2010; Hach et al., 2013b). Some mature forest specialists havelower abundances in early post-harvest years, but we are unawareof severe declines or local extinctions following such treatments indeciduous stands of North America (e.g. Vanderwel et al., 2009;Poulin et al., 2010; Hach et al., 2013b; Morris et al., 2013).However, the demographic response of mature forest birds topartial harvesting remains largely unknown (Hobson et al., 2013)and data currently available show contrasting responses amongand within species (reviewed by Richmond et al., 2012). Forexample, although the Ovenbird is considered to be one of themost sensitive bird species to partial harvesting (Vanderwelet al., 2007, 2009), numerous lines of evidence from this and otherstudies (see 2.2. and Leblanc et al., 2011; but see Morris et al. 2013)suggest that it may be more tolerant to moderate alteration of itshabitat than previously reported. The demographic response ofthe Ovenbird, combined with the creation of more suitable habitatfor early-seral species, would be consistent with the intermediatedisturbance hypothesis, which predicts a peak in species richnessat intermediate levels of disturbance (Grime, 1973; Connell,1978). Nonetheless, it would be unwise to assume that all matureforest songbirds are as tolerant to habitat alteration. For example,species such as the Brown Creeper (Certhia americana) andOlive-sided Flycatcher (Contopus cooperi) have a lower reproduc-tive success in recent selection cuts or thinned plots (Robertsonand Hutto, 2007; Poulin et al., 2010). Populations of these andecologically-similar species should be closely monitored as forestmanagement intensity increases.

The trend analyses reported in this study were based on theassumption that we could model population dynamics with someprecision. Studies have provided contrasting estimates of k forOvenbird populations. For example, in northern Wisconsin,Flaspohler et al. (2001) reported values of 1.11 and 1.18 for edgeand interior habitats, respectively, whereas Leblanc et al. (2011)estimated k between 0.837 and 0.858 among four harvesttreatments in deciduous stands from central Ontario (see alsoPodolsky et al., 2007). Many studies have reported that adult andjuvenile survival were the most sensitive parameters used to esti-mate population growth rate (e.g. Schmutz et al., 1997; Flaspohleret al., 2001). Yet, to our knowledge, this is the first study modellingpopulation dynamics of Ovenbirds based on apparent adult sur-vival estimates specific to a study area. Owing to low return ratesof birds banded as nestlings or juveniles (Greenwood and Harvey,1982), survival during the first year (a.k.a. juvenile survival)remains largely unknown (Sillett and Holmes, 2002; Dybalaet al., 2013). However, the combination of data on postfledgingand adult survival rates provides the most realistic estimates ofjuvenile survival currently available for migratory bird specieswith large breeding ranges (Dybala et al., 2013; McKim-Louderet al., 2013). That being said, we recognize the uncertainty inherentto our modelling approach. For example, female-specific survivalrates (e.g. Podolsky et al., 2007) and a better understanding ofpopulation dynamics in conifer stands and shelterwoods mightyield slightly different population growth rates. In this study, wealso assumed that the effects of selection harvesting on Ovenbirdpopulations in subsequent entries would be similar to thosereported following the first entry. Yet, more homogeneous standstructure and composition as well as a reduction in the densityof large live trees (>39.1 cm) are expected after multiple entries(Angers et al., 2005) and the implications of such changes onbreeding birds are unknown (e.g. Morris et al., 2013).

Ideally, population dynamics should be modelled throughout aspecies life cycle (Sillett and Holmes, 2002; Faaborg et al., 2013).We recognize that habitat loss/alteration and climate change alsoinfluence Ovenbirds on the wintering grounds and duringmigration. Conditions experienced by individuals during the

nonbreeding season likely influence population dynamics on thebreeding grounds over a spatial scale extending well beyond ourstudy area, irrespective of breeding habitat quality. Hence, althoughwe elected to focus on factors operating during the breeding season,nonbreeding habitat loss/alteration will have an additive effect.

Individual-based, spatially-explicit models would allow explor-ing effects of habitat loss vs. fragmentation on the breedinggrounds (Wintle et al., 2005; Chisholm and Wintle, 2007). TheOvenbird has been shown to respond to landscape structure(Betts et al., 2006, 2007; Wallendorf et al., 2007; Villard andHach, 2012) and, by the 15th year, the mean patch size of decid-uous forest in Black Brook is projected to decrease by ca. 50%(Etheridge et al., 2006). Hence, landscape history (sensu Schrottet al., 2005) should be integrated in future models to betteraccount for the complexity of forestry effects on our focal popula-tion. Nonetheless, to our knowledge, we used the most detailedhabitat-specific demographic information available for a songbirdbreeding in an intensively managed forest of North America (seealso Morris et al., 2013). Our simulations suggest that climatechange will have more important effects on songbird populationsbreeding in the northern hardwood forest than forestry operationsunder the current forest management plan or more intensivescenarios. Although these findings should be interpreted withcaution, they provide insight into future trends in bird populationsand the opportunity to develop proactive conservation plans.

Acknowledgements

We thank J.-F. Poulin, A. Prot, S. Thriault, E. DAstous, andA. Vernouillet for their help with fieldwork planning and datacollection, while M.-C. Blair, P. Bertrand, G. DAnjou, I. Devost,V. Drolet, J. Frenette, S. Frigon, P. Goulet, H. Laforge, A. MacKay,J.-A. Otis, E. Ouellette, T. Ptry, and M. Ricard provided valuablehelp with data collection. This study was supported by grants fromthe Natural Sciences and Engineering Research Council of Canada(NSERC) to M.-A. Villard and E.M. Bayne, by a grant from theNew Brunswick Wildlife Trust Fund to M.-A. Villard, and by aNSERC-J.D. Irving, Industrial Postgraduate Scholarship, NSERC Post-graduate Scholarship, Queen Elizabeth II Graduate Scholarship(University of Alberta), and Dissertation Fellowship (University ofAlberta) to S. Hach. We also thank G. Adams and G. Pelletier fromJ.D. Irving, Limited for comments on earlier versions of the manu-script and logistical support. Lastly, we thank two anonymousreviewers for constructive comments on a previous version of themanuscript.

Appendices AC. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.foreco.2015.10.002.

References

Abbitt, R.J.F., Scott, J.M., Wilcove, D.S., 2000. The geography of vulnerability:incorporating species geography and human development patterns intoconservation planning. Biol. Conserv. 96, 169175. http://dx.doi.org/10.1016/S0006-3207(00)00064-1.

Amos-Binks, L.J., MacLean, D.A., Wilson, J.S., Wagner, R.G., 2010. Temporal changesin species composition of mixedwood stands in northwest New Brunswick:19462008. Can. J. For. Res. 40, 112. http://dx.doi.org/10.1139/X09-162.

Amrhein, V., Scaar, B., Baumann, M., Minry, N., Binnert, J.-P., Korner-Nievergelt, F.,2012. Estimating adult sex ratios from bird mist netting data. Meth. Ecol. Evol.3, 713720. http://dx.doi.org/10.1111/j.2041-210X.2012.00207.x.

Angers, V.A., Messier, C., Beaudet, M., Leduc, A., 2005. Comparing composition andstructure in old-growth and harvested (selection and diameter-limit cuts)northern hardwood stands in Quebec. For. Ecol. Manage. 217, 275293. http://dx.doi.org/10.1016/j.foreco.2005.06.008.

318 S. Hach et al. / Forest Ecology and Management 359 (2016) 309320

Askins, R.A., 2001. Sustaining biological diversity in early successionalcommunities: the challenge of managing unpopular habitats. Wild. Soc. Bull.29, 407412.

Ball, S.J., Lindenmayer, D.B., Possingham, H.P., 2003. The predictive accuracy ofpopulation viability analysis: a test using data from two small mammal speciesin a fragmented landscape. Biodiv. Conserv. 12, 23932413. http://dx.doi.org/10.1023/A:1025821506931.

Barrientos, R., 2010. Retention of native vegetation within the plantation matriximproves its conservation value for a generalist woodpecker. For. Ecol. Manage.260, 595602. http://dx.doi.org/10.1016/j.foreco.2010.05.015.

Beissinger, S.R., Westphal, M.I., 1998. On the use of demographic models ofpopulation viability in endangered species management. J. Wildl. Manage. 62,821841. http://dx.doi.org/10.2307/3802534.

Bergeron, Y., Leduc, A., Harvey, B.D., Gauthier, S., 2002. Natural fire regime: a guide forsustainable management of the Canadian boreal forest. Silva Fenn. 36, 8195.

Betts, M.G., Forbes, G.J., Diamond, A.W., 2007. Thresholds in songbird occurrence inrelation to landscape structure. Conserv. Biol. 21, 10461058. http://dx.doi.org/10.1111/j.1523-1739.2007.00723.x.

Betts, M.G., Forbes, G.J., Diamond, A.W., Taylor, P.D., 2006. Independent effects offragmentation on forest songbirds: an organism-based approach. Ecol. Appl. 16,10761089. http://dx.doi.org/10.1890/1051-0761(2006) 016[1076:IEOFOF]2.0.CO;2.

Blancher, P.J., 2003. Importance of Canadas Boreal Forest to Landbirds. CanadianBoreal Initiative and Boreal Songbird Initiative, Ottawa.

Boggs, C.L., Inouye, D.W., 2012. A single climate driver has direct and indirect effectson insect population dynamics. Ecol. Lett. 15, 502508. http://dx.doi.org/10.1111/j.1461-0248.2012.01766.x.

Bonnot, T.W., Thompson III, F.R., Millspaugh, J.J., 2011. Extension of landscape-based population viability models to ecoregional scales for conservationplanning. Biol. Conserv. 144, 20412053. http://dx.doi.org/10.1016/j.biocon.2011.04.026.

Bourque, J., Villard, M.-A., 2001. Effects of selection cutting and landscape-scaleharvesting on the reproductive success of two neotropical migrant bird species.Conserv. Biol. 15, 184195. http://dx.doi.org/10.1111/j.1523-1739.2001.99436.x.

Burrows, M.T., Schoeman, D.S., Buckley, L.B., Moore, P., Poloczanska, E.S., Brander, K.M., Brown, C., Bruno, J.F., Duarte, C.M., Halpern, B.S., Holding, J., Kappel, C.V.,Kiessling, W., OConnor, M.I., Pandolfi, J.M., Parmesan, C., Schwing, F.B.,Sydeman, W.J., Richardson, A.J., 2011. The pace of shifting climate in marineand terrestrial ecosystems. Science 334, 652655. http://dx.doi.org/10.1126/science.1210288.

Campbell, J., Bailey, A., 2013. Daily Mean Temperature Data. Hubbard Brook DataArchive [Database]. Available from (accessed July 2013).

Campbell, J.L., Ollinger, S.V., Flerchinger, G.N., Wicklein, H., Hayhoe, K., Bailey, A.S.,2010. Past and projected future changes in snowpack and soil frost at theHubbard Brook Experimental Forest, New Hampshire, USA. Hydrol. Process. 24,24652480. http://dx.doi.org/10.1002/hyp.7666.

Canadian Centre for Climate Modelling and Analysis. 2013. Climate Modelling andAnalysis. Environment Canada. Available from (accessed July 2013).

Chisholm, R.A., Wintle, B.A., 2007. Incorporating landscape stochasticity intopopulation viability analysis. Ecol. Appl. 17, 317322. http://dx.doi.org/10.1890/05-1580.

Connell, J.H., 1978. Diversity in tropical rain forest and coral reefs. Science 199,13021310. http://dx.doi.org/10.1126/science.199.4335.1302.

Crow, T.R., Perera, A.H., 2004. Emulating natural landscape disturbance in forestmanagement an introduction. Landsc. Ecol. 19, 231233. http://dx.doi.org/10.1023/B:LAND.0000030762.86156.5d.

Davey, C.M., Chamberlain, D.E., Newson, S.E., Noble, D.G., Johnston, A., 2012. Rise ofthe generalists: evidence for climate driven homogenization in aviancommunities. Glob. Ecol. Biogeogr. 21, 568578. http://dx.doi.org/10.1111/j.1466-8238.2011.00693.x.

Delworth, T.L., Broccoli, A.J., Rosati, A., Stouffer, R.J., Balaji, V., Beesley, J.A., Cooke, W.F., Dixon, K.W., Dunne, J., Dunne, K.A., Durachta, J.W., Findell, K.L., Ginoux, P.,Gnanadesikan, A., Gordon, C.T., Griffies, S.M., Gudgel, R., Harrison, M.J., Held, I.M., Hemler, R.S., 2006. GFDLs CM2 global coupled climate models. Part I:Formulation and simulation characteristics. J. Clim. 19, 643674. http://dx.doi.org/10.1175/JCLI3629.1.

Donald, P.F., 2007. Adult sex ratios in wild bird populations. Ibis 149, 671692.http://dx.doi.org/10.1111/j.1474-919X.2007.00724.x.

Dybala, K.E., Gardali, T., Eadie, J.M., 2013. Dependent vs. independent juvenilesurvival: contrasting drivers of variation and the buffering effect of parentalcare. Ecology 94, 15841593. http://dx.doi.org/10.1890/12-1443.1.

Dzus, E., Grover, B., Dyer, S., Cheyne, D., Pope, D., Schieck, J., 2009. Setting,implementing, and monitoring targets as a basis for adaptive management: aCanadian forestry case study. In: Villard, M.-A., Jonsson, B.G. (Eds.), SettingConservation Targets for Managed Forest Landscapes. Cambridge UniversityPress, New York, pp. 352392.

Edman, M., Eriksson, A.-M., Villard, M.-A., 2008. Effects of selection cutting on theabundance and fertility of indicator lichens Lobaria pulmonaria and Lobariaquercizans. J. Appl. Ecol. 45, 2633. http://dx.doi.org/10.1111/j.1365-2664.2007.01354.x.

Environment Canada, 2013. National Climate Data and Information Archive.Government of Canada. Available from (accessed October 2013).

Etheridge, D.A., MacLean, D.A., Wagner, R.G., Wilson, J.S., 2005. Changes inlandscape composition and stand structure from 19452002 on an industrialforest in New Brunswick, Canada. Can. J. For. Res. 35, 19651977. http://dx.doi.org/10.1139/x05-110.

Etheridge, D.A., MacLean, D.A., Wagner, R.G., Wilson, J.S., 2006. Effects of intensiveforest management on stand and landscape characteristics in northern NewBrunswick, Canada (19452027). Landsc. Ecol. 21, 509524. http://dx.doi.org/10.1007/s10980-005-2378-9.

Faaborg, J., Arendt, W.J., Toms, J.D., Dugger, K.M., Cox, W.A., Mora, M.C., 2013. Long-term decline of a winter-resident bird community in Puerto Rico. Biodiv.Conserv. 22, 6375. http://dx.doi.org/10.1007/s10531-012-0399-7.

Flaspohler, D.J., Temple, S.A., Rosenfield, R.N., 2001. Effects of forest edges onovenbird demography in a managed forest landscape. Conserv. Biol. 15, 173183. http://dx.doi.org/10.1111/j.1523-1739.2001.99397.x.

Fraver, S., White, A.S., Seymour, R.S., 2009. Natural disturbance in an old-growthlandscape of northern Maine, USA. J. Ecol. 97, 289298. http://dx.doi.org/10.1111/j.1365-2745.2008.01474.x.

Fuller, A.K., Harrison, D.J., 2005. Influence of partial timber harvesting on Americanmartens in north-central Maine. J. Wildl. Manage. 69, 710722. http://dx.doi.org/10.2193/0022-541X(2005) 069[0710:IOPTHO]2.0.CO;2.

Gibson, L., Lee, T.M., Koh, L.P., Brook, B.W., Gardner, T.A., Barlow, J., Peres, C.A.,Bradshaw, C.J.A., Laurance, W.F., Lovejoy, T.E., Sodhi, N.S., 2011. Primary forestsare irreplaceable for sustaining tropical biodiversity. Nature 478, 378381.http://dx.doi.org/10.1038/nature10425.

Gilroy, J.J., Virzi, T., Boulton, R.L., Lockwood, J.L., 2012. Too few data and not enoughtime: approaches to detecting Allee effects in threatened species. Conserv. Lett.5, 313322. http://dx.doi.org/10.1111/j.1755-263X.2012.00245.x.

Greenwood, P.J., Harvey, P.H., 1982. The natal and breeding dispersal of birds. Annu.Rev. Ecol. Syst. 13, 121. http://dx.doi.org/10.1146/annurev.es.13.110182.000245.

Grim, J.P., 1973. Competitive exclusion in herbaceous vegetation. Nature 242, 344347. http://dx.doi.org/10.1038/242344a0.

Groffman, P.M., Rustad, L.E., Templer, P.H., Campbell, J.L., Christenson, L.M., Lany, N.K., Socci, A.M., Vadeboncoeur, M.A., Schaberg, P.G., Wilson, G.F., Driscoll, C.T.,Fahey, T.J., Fisk, M.C., Goodale, C.L., Green, M.B., Hamburg, S.P., Johnson, C.E.,Mitchell, M.J., Morse, J.L., Pardo, L.H., Rodenhouse, N.L., 2012. Long-termintegrated studies show complex and surprising effects of climate change inthe northern hardwood forest. BioScience 62, 10561066. http://dx.doi.org/10.1525/bio.2012.62.12.7.

Gunette, J.-S., Villard, M.-A., 2005. Thresholds in forest bird response to habitatalteration as quantitative targets for conservation. Conserv. Biol. 19, 11681180. http://dx.doi.org/10.1111/j.1523-1739.2005.00085.x.

Hach, S., Bayne, E.M., Villard, M.-A., 2014a. Postharvest regeneration, sciuridabundance, and postfledging survival and movements in an Ovenbirdpopulation. Condor 116, 102112. http://dx.doi.org/10.1650/CONDOR-13-002-R2.1.

Hach, S., Hobson, K.A., Bayne, E.M., Van Wilgenburg, S.L., Villard, M.-A., 2014b.Tracking natal dispersal in a coastal population of a migratory songbird usingfeather stable isotope (d2H, d34S) tracers. PLoS One 9, e94437. http://dx.doi.org/10.1371/journal.pone.0094437.

Hach, S., Ptry, T., Villard, M.-A., 2013b. Numerical response of breeding birdsfollowing experimental selection harvesting in northern hardwood forests.Avian Conserv. Ecol. 8, 4. http://dx.doi.org/10.5751/ACE-00584-080104.

Hach, S., Villard, M.-A., 2010. Age-specific response of a migratory bird to anexperimental alteration of its habitat. J. Anim. Ecol. 79, 897905. http://dx.doi.org/10.1111/j.1365-2656.2010.01694.x.

Hach, S., Villard, M.-A., Bayne, E.M., 2013a. Experimental evidence for an ideal freedistribution in a breeding population of a territorial songbird. Ecology 94, 861869. http://dx.doi.org/10.1890/12-1025.1.

Harris, J.B.C., Putra, D.D., Gregory, S.D., Brook, B.W., Prawiradilaga, D.M., Sodhi, N.S.,Wei, D., Fordham, D.A., 2014. Rapid deforestation threatens mid-elevationalendemic birds but climate change is most important at higher elevation. Divers.Distrib. 20, 773785. http://dx.doi.org/10.1111/ddi.12180.

Hayhoe, K., Wake, C.P., Huntington, T.G., Luo, L., Schwartz, M.D., Sheffield, J., Wood,E., Anderson, B., Bradbury, J., DeGaetano, A., Troy, T.J., Wolfe, D., 2007. Past andfuture changes in climate and hydrological indicators in the US Northeast. Clim.Dyn. 28, 381407. http://dx.doi.org/10.1007/s00382-006-0187-8.

Hobson, K.A., Wilson, A.G., Van Wilgenburg, S.L., Bayne, E.M., 2013. An estimate ofnest loss in Canada due to industrial forestry operations. Avian Conserv. Ecol. 8,5. http://dx.doi.org/10.5751/ACE-00583-080205.

Holmes, R.T., Robinson, S.K., 1988. Spatial patterns, foraging tactics, and diets ofground-foraging birds in a northern hardwoods forest. Wilson Bull. 100, 377394.

Hughes, E.L., 1960. Nine years of developments in a mature mixedwood stand,Green River, New Brunswick. For. Chron. 36, 69. http://dx.doi.org/10.5558/tfc36006-1.

Jarzyna, M.A., Porter, W.F., Maurer, B.A., Zuckerberg, B., Finley, A.O., 2015. Landscapefragmentation affects responses of avian communities to climate change. Glob.Change Biol. 21, 29422953. http://dx.doi.org/10.1111/gcb.12885.

Klenk, N., Bull, G., Cohen, D., 2008. What is the END (emulation of naturaldisturbance) in forest ecosystem management? An open question. Can. J. For.Res. 38, 21592168. http://dx.doi.org/10.1139/X08-054.

Kujala, H., Burgman, M.A., Moilanen, A., 2013. Treatment of uncertainty inconservation under climate change. Conserv. Lett. 6, 7385. http://dx.doi.org/10.1111/j.1755-263X.2012.00299.x.

S. Hach et al. / Forest Ecology and Management 359 (2016) 309320 319

Kuuluvainen, T., Grenfell, R., 2012. Natural disturbance emulation in boreal forestecosystem management theories, strategies, and a comparison withconventional even-aged management. Can. J. For. Res. 42, 11851203. http://dx.doi.org/10.1139/x2012-064.

Lambeck, R.J., 1997. Focal species: a multi-species umbrella for nature conservation.Conserv. Biol. 11, 849856. http://dx.doi.org/10.1046/j.1523-1739.1997.96319.x.

Larson, M.A., Thompson, F.R., Millspaugh, J.J., Dijak, W.D., Shifley, S.R., 2004. Linkingpopulation viability, habitat suitability, and landscape simulation models forconservation planning. Ecol. Modell. 180, 103118. http://dx.doi.org/10.1016/j.ecolmodel.2003.12.054.

Leblanc, J.P., Burke, D.M., Nol, E., 2011. Ovenbird (Seiurus aurocapilla) demographyand nest-site selection in response to single-tree selection silviculture in anorthern hardwood managed forest landscape. Ecoscience 18, 2636. http://dx.doi.org/10.2980/18-1-3381.

Lindenmayer, D.B., Franklin, J.F., Lhmus, A., Baker, S.C., Bauhus, J., Beese, W., Brodie,A., Kiehl, B., Kouki, J., Pastur, G.M., Messier, C., Neyland, M., Palik, B., Sverdrup-Thygeson, A., Volney, J., Wayne, A., Gustafsson, L., 2012. A major shift to theretention approach for forestry can help resolve some global forestsustainability issues. Conserv. Lett. 5, 421431. http://dx.doi.org/10.1111/j.1755-263X.2012.00257.x.

Lindenmayer, D.B., Margules, C.R., Botkin, D.B., 2000. Indicators of biodiversity forecologically sustainable forest management. Conserv. Biol. 14, 941950. http://dx.doi.org/10.1046/j.1523-1739.2000.98533.x.

Lloyd, P., Martin, T.E., Redmond, R.L., Langner, U., Hart, M.M., 2005. Linkingdemographic effects of habitat fragmentation across landscapes to continentalsource-sink dynamics. Ecol. Appl. 15, 15041514. http://dx.doi.org/10.1890/04-1243.

Long, J.N., 2009. Emulating natural disturbance regimes as a basis for forestmanagement: a North American view. For. Ecol. Manage. 257, 18681873.http://dx.doi.org/10.1016/j.foreco.2008.12.019.

MacKay, A., Allard, M., Villard, M.-A., 2014. Capacity of older plantations to host birdassemblages of naturally-regenerated conifer forests: a test at stand andlandscape levels. Biol. Conserv. 170, 110119. http://dx.doi.org/10.1016/j.biocon.2013.12.023.

MacKenzie, D.I., Nichols, J.D., Hines, J.E., Knutson, M.G., Franklin, A.B., 2003.Estimating site occupancy, colonization, and local extinction when a speciesis detected imperfectly. Ecology 84, 22002207. http://dx.doi.org/10.1890/02-3090.

Martin, G.M., Ringer, M.A., Pope, V.D., Jones, A., Dearden, C., Hinton, T.J., 2006. Thephysical properties of the atmosphere in the new Hadley Centre GlobalEnvironmental Model (HadGEM1). Part I: model description and globalclimatology. J. Clim. 19, 12741301. http://dx.doi.org/10.1175/JCLI3636.1.

McKim-Louder, M.I., Hoover, J.P., Benson, T.J., Schelsky, W.M., 2013. Juvenilesurvival in a neotropical migratory songbird is lower than expected. PLoS One 8,e56059. http://dx.doi.org/10.1371/journal.pone.0056059.

Meehl, G.A., Tebaldi, C., 2004. More intense, more frequent, and longer lasting heatwaves in the 21st Century. Science 305, 994997. http://dx.doi.org/10.1126/science.1098704.

Montigny, M.K., MacLean, D.A., 2005. Using heterogeneity and representation ofecosite criteria to select forest reserves in an intensively managed industrialforest. Biol. Conserv. 125, 237248. http://dx.doi.org/10.1016/j.biocon.2005.03.028.

Morris, D.L., Porneluzi, P.A., Haslerig, J., Clawson, R.L., Faaborg, J., 2013. Results of 20years of experimental forest management on breeding birds in Ozark forests ofMissouri, USA. For. Ecol. Manage. 310, 747760. http://dx.doi.org/10.1016/j.foreco.2013.09.020.

Morris, W.F., Doak, D.F., 2002. Quantitative Conservation Biology: The Theory andPractice of Population Viability Analysis. Sinauer, Sunderland.

Murphy, M.T., 2001. Source-sink dynamics of a declining Eastern Kingbirdpopulation and the value of sink habitats. Conserv. Biol. 15, 737748. http://dx.doi.org/10.1046/j.1523-1739.2001.015003737.x.

Nakicenovic, N., Alcamo, J., Davis, G., de Vries, B., Fenhann, J., Gaffin, S., Gregory, K.,Grbler, A., Jung, T.Y., Kram, T., La Rovere, E.L., Michaelis, L., Mori, S., Morita, T.,Pepper, W., Pitcher, H., Price, L., Riahi, K., Roehrl, A., Rogner, H.H., Sankovski, A.,Schlesinger, M., Shukla, P., Smith, S., Swart, R., van Rooijen, S., Victor, N., Dadi, Z.,2000. IPCC Special Report on Emissions Scenarios. Cambridge University Press,Cambridge, United Kingdom.

Prot, A., Villard, M.-A., 2009. Putting density back into the habitat-qualityequation: case study of an open-nesting forest bird. Conserv. Biol. 23, 15501557. http://dx.doi.org/10.1111/j.1523-1739.2009.01272.x.

Podolsky, A.L., Simons, T.R., Collazo, J.A., Lank, D.B., 2007. Modeling populationgrowth of the Ovenbird (Seiurus aurocapilla) in the southern appalachians. Auk124, 13591372. http://dx.doi.org/10.1642/0004-8038(2007) 124[1359:MPGOTO]2.0.CO;2.

Porneluzi, P., Van Horn, M.A., Donovan, T.M., 2011. Ovenbird (Seiurus aurocapilla).In: Poole, A. (Ed.), The Birds of North America Online. Cornell Lab of Ornithology.http://dx.doi.org/10.2173/bna.88.

Poulin, J.-F., Villard, M.-A., Hach, S., 2010. Short-term demographic response of anold forest specialist to experimental selection harvesting. Ecoscience 17, 2027.http://dx.doi.org/10.2980/17-1-3297.

Pulliam, H.R., 1996. Sources and sinks: empirical evidence and populationconsequences. In: Rhodes, O.E., Jr., Chesser, R.K., Smith, M.H. (Eds.),Population Dynamics in Ecological Space and Time. University of ChicagoPress, Chicago, pp. 4569.

Ralls, K., Beissinger, S.R., Cochrane, J.F., 2002. Guidelines for using populationviability analysis in endangered species management. In: Beissinger, S.R.,

McCullough, D.R. (Eds.), Population Viability Analysis. University of ChicagoPress, Chicago, pp. 425441.

Ramirez, J., Jarvis, A., 2008. High resolution statistically downscaled future climatesurfaces. Center for Tropical Agriculture (CIAT); CGIAR Research Program onClimate Change, Agriculture and Food Security (CCAFS), Cali.

Ramirez-Villegas, J., Jarvis, A., 2010. Downscaling global circulation model outputs:the Delta method. Decision and Policy Analysis Working Paper No 1: CIAT-CGIAR.

Reed, J.M., Mills, L.S., Dunning Jr., J.B., Menges, E.S., McKelvey, K.S., Frye, R.,Beissinger, S.R., Anstett, M.-C., Miller, P., 2002. Emerging issues in populationviability analysis. Conserv. Biol. 16, 719. http://dx.doi.org/10.1046/j.1523-1739.2002.99419.x.

Reichert, B.E., Cattau, C.E., Fletcher, R.J., Kendall, W.L., Kitchens, W.M., 2012.Extreme weather and experience influence reproduction in an endangered bird.Ecology 93, 25802589. http://dx.doi.org/10.1890/12-0233.1.

Remsoft, Inc., 1996. Woodstock forest modeling system version 1.1 users guide.Remsoft Inc., Fredericton, NB.

Richmond, S., Nol, E., Burke, D., Malcolm, J.R., 2012. Effects of single-tree selectionharvesting on Rose-breasted Grosbeak (Pheucticus leudovicianus) demographyin a northern hardwood forest. For. Ecol. Manage. 276, 2432. http://dx.doi.org/10.1016/j.foreco.2012.03.015.

Robertson, B.A., Hutto, R.L., 2007. Is selectively harvested forest an ecological trapfor Olive-Sided Flycatchers? Condor 109, 109121. http://dx.doi.org/10.1650/0010-5422(2007) 109[109:ISHFAE]2.0.CO;2.

Rodenhouse, N.L., Christenson, L.M., Parry, D., Green, L.E., 2009. Climate changeeffects on native fauna of northeastern forests. Can. J. For. Res. 39, 249263.http://dx.doi.org/10.1139/X08-160.

Rodenhouse, N.L., Matthews, S.N., McFarland, K.P., Lambert, J.D., Iverson, L.R.,Prasad, A., Sillett, T.S., Holmes, R.T., 2008. Potential effects of climate change onbirds of the Northeast. Mitigation Adapt. Strateg. Glob. Chang. 13, 517540.http://dx.doi.org/10.1007/s11027-007-9126-1.

Rodenhouse, N.L., Sherry, T.W., Holmes, R.T., 1997. Site-dependent regulation ofpopulation size: a new synthesis. Ecology 78, 20252042. http://dx.doi.org/10.1890/0012-9658(1997) 078[2025:SDROPS]2.0.CO;2.

Roeckner, E., Buml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M.,Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U.,Schulzweida, U., Tompkins, A., 2003. The atmospheric general circulation modelECHAM5: Part 1. Max Planck Institute for Meteorology; Report No. 349,Hamburg.

Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kornblueh, L.,Manzini, E., Schlese, U., Schulzweida, U., 2004. The atmospheric generalcirculation model ECHAM5: Part II. Max Planck Institute for Meteorology;Report No. 354, Hamburg.

Sauer, J.R., Hines, J.E., Fallon, J., 2001. The North American breeding bird survey,results and analysis 19662000. Available from (accessed July 2013).

Schlossberg, S., King, D.I., Chandler, R.B., Mazzei, B.A., 2010. Regional synthesis ofhabitat relationships in shrubland birds. J. Wildl. Manage. 74, 15131522.http://dx.doi.org/10.1111/j.1937-2817.2010.tb01279.x.

Schmutz, J.A., Rockwell, R.F., Petersen, M.R., 1997. Relative effects of survival andreproduction on the population dynamics of Emperor Geese. J. Wildl. Manage.61, 191201. http://dx.doi.org/10.2307/3802428.

Schrott, G.R., With, K.A., King, A.W., 2005. On the importance of landscape historyfor assessing extinction risk. Ecol. Appl. 15, 493506. http://dx.doi.org/10.1890/04-0416.

Seagle, S.W., Sturtevant, B.R., 2005. Forest productivity predicts invertebratebiomass and ovenbird (Seiurus aurocapillus) reproduction in Appalachianlandscapes. Ecology 86, 15311539. http://dx.doi.org/10.1890/03-0770.

Selwood, K.E., McGeoch, M.A., Nally, R.M., 2015. The effects of climate change andland-use change on demographic rates and population viability. Biol. Rev. 86,837853. http://dx.doi.org/10.1111/brv.12136.

Seymour, R.S., White, A.S., deMaynadier, P.G., 2002. Natural disturbance regimes innortheastern North Americaevaluating silvicultural systems using naturalscales and frequencies. For. Ecol. Manage. 155, 357367. http://dx.doi.org/10.1016/S0378-1127(01)00572-2.

Sheehan, J., Wood, P.B., Buehler, D.A., Keyser, P.D., Larkin, J.L., Rodewald, A.D.,Wigley, T.B., Boves, T.J., George, G.A., Bakermans, M.H., Beauchy, T.A., Evans, A.,McDermott, M.E., Newell, F.L., Perkins, K.A., White, M., 2014. Avian response totimber harvesting applied experimentally to manage Cerulean Warblerbreeding populations. For. Ecol. Manage. 321, 518. http://dx.doi.org/10.1016/j.foreco.2013.07.037.

Sillett, T.S., Holmes, R.T., 2002. Variation in survivorship of a migratory songbirdthroughout its annual cycle. J. Anim. Ecol. 71, 296308. http://dx.doi.org/10.1046/j.1365-2656.2002.00599.x.

Stenger, J., 1958. Food habits and available food of Ovenbirds in relation to territorysize. Auk 58, 335346.

Stephens, P.A., Sutherland, W.J., Freckleton, R.P., 1999. What is the Allee effect?Oikos 87, 185190.

Streby, H.M., Andersen, D.E., 2012. Movement and cover-type selection by fledglingOvenbirds (Seiurus aurocapilla) after independence from adult care. Wilson J.Ornithol. 124, 620625.

Streby, H.M., Andersen, D.E., 2013. Survival of fledgling Ovenbirds: influences ofhabitat characteristics at multiple spatial scales. Condor 115, 403410. http://dx.doi.org/10.1525/cond.2013.110178.

Templer, P.H., Schiller, A.F., Fuller, N.W., Socci, A.M., Campbell, J.L., Drake, J.E., Kunz,T.H., 2012. Impact of a reduced winter snowpack on litter arthropod abundance

320 S. Hach et al. / Forest Ecology and Management 359 (2016) 309320

and diversity in a northern hardwood forest ecosystem. Biol. Fertil. Soils 48,413424. http://dx.doi.org/10.1007/s00374-011-0636-3.

Tittler, R., Fahrig, L., Villard, M.-A., 2006. Evidence of large-scale source-sinkdynamics and long-distance dispersal among Wood Thrush populations.Ecology 87, 30293036. http://dx.doi.org/10.1890/0012-9658(2006) 87[3029:EOLSDA]2.0.CO;2.

Tittler, R., Villard, M.-A., Fahrig, L., 2009. How far do songbirds disperse? Ecography32, 10511061. http://dx.doi.org/10.1111/j.1600-0587.2009.05680.x.

Townsend, A.K., Sillett, T.S., Lany, N.K., Kaiser, S.A., Rodenhouse, N.L., Webster, M.S.,Holmes, R.T., 2013. Warm springs, early lay dates, and double brooding in aNorth American migratory songbird, the black-throated blue warbler. PLoS One8, e123456. http://dx.doi.org/10.1371/journal.pone.0059467.

Vanderwel, M.C., Malcolm, J.R., Mills, S.C., 2007. A meta-analysis of bird responsesto uniform partial harvesting across North America. Conserv. Biol. 21, 12301240. http://dx.doi.org/10.1111/j.1523-1739.2007.00756.x.

Vanderwel, M.C., Mills, S.C., Malcolm, J.R., 2009. Effects of partial harvesting onvertebrate species associated with late-successional forests in Ontarios borealregion. For. Chron. 85, 92104. http://dx.doi.org/10.5558/tfc85091-1.

Vanguard Forest Management Services Ltd., 1993. STAMAN stand growth modeland Calibration of STAMAN model for defoliation impacts. Contract Report toCanadian Forest Service Maritimes Region, Fredericton.

Vernouillet, A., Villard, M.-A., Hach, S., 2014. ENSO, nest predation risk, foodabundance, and male status fail to explain annual variation in the apparentsurvival rate of a migratory songbird. PLoS One 9, e113844. http://dx.doi.org/10.1371/journal.pone.0113844.

Villard, M.-A., Hach, S., 2012. Conifer plantations consistently act as barriers tomovement in a deciduous forest songbird: a translocation experiment. Biol.Conserv. 155, 3337. http://dx.doi.org/10.1016/j.biocon.2012.06.007.

Virkkala, R., Poyry, J., Heikkinen, R.K., Lehikoinen, A., Valkama, J., 2014. Protectedareas alleviate climate change effects on northern bird species of conservationconcern. Ecol. Evol. 4, 29913003. http://dx.doi.org/10.1002/ece3.1162.

Wallendorf, M.J., Porneluzi, P.A., Gram, W.K., Clawson, R.L., Faaborg, J., 2007. Birdresponse to clear cutting in Missouri Ozark forests. J. Wildl. Manage. 71, 18991905. http://dx.doi.org/10.2193/2006-386.

White, T.C.R., 2008. The role of food, weather and climate in limiting the abundance ofanimals. Biol. Rev. 83, 227248. http://dx.doi.org/10.1111/j.1469-185X.2008.00041.x.

Wintle, B.A., Bekessy, S.A., Venier, L.A., Pearce, J.L., Chisholm, R.A., 2005. Utilityof dynamic-landscape metapopulation models for sustainable forest management.Conserv. Biol. 19, 19301943. http://dx.doi.org/10.1111/j.1523-1739.2005.00276.x.

Work, T.T., Jacobs, J.M., Spence, J.R., Volney, W.J., 2010. High levels of green-treeretention are required to preserve ground beetle biodiversity in borealmixedwood forests. Ecol. Appl. 20, 741751. http://dx.doi.org/10.1890/08-1463.1.