Woodland caribou scientific review to identify critical habitat: chapter 14

Appendix 6.5

A National Meta-analysis of Boreal Caribou Demography and Range Disturbance

 

Preface

A key step in the critical habitat identifi cation process is determining attributes of a caribou range that support or compromise population persistence (e.g. the ability of the range to support a self-sustaining population). This meta-analysis compiled demographic data from boreal caribou populations across Canada to evaluate the hypothesized relationship between caribou population parameters and levels of anthropogenic and/or natural (fi re) disturbance on caribou ranges. Results from this work provide quantitative guidelines for one of the three assessment criteria (range disturbance) used in the evaluation of local populations for critical habitat identifi cation.

 

Introduction

Woodland caribou (Rangifer tarandus caribou) are designated a species-at-risk nationally, and in most provinces and territories within their range, due to broad-scale range recession and population declines, in large part associated with human settlement and disturbance (Bergerud 1974, Mallory and Hillis 1998, Schaefer 2003, Vors et al. 2007). This species is closely associated with late-successional coniferous forests and peatlands (Rettie and Messier 2000). These forests are a source of lichens, which comprise the bulk of woodland caribou diet – particularly in winter – but lichen availability is generally not considered a limiting factor (Schaefer and Pruitt 1991, Joly et al. 2003, Courtois et al. 2007). More importantly, these forests provide refugia from predators and other ungulates (Bergerud and Elliott 1986). Many woodland caribou populations are in decline, and the proximate cause is thought to be increased predation. Logging and other disturbances that increase the amount of early seral-stage forest promote higher densities of prey species such as moose (Alces alces) and white-tailed deer (Odocoileus virginianus), which support higher predator densities, especially wolves (Canis lupus) (Bergerud and Elliott 1986, Seip 1992, Stuart-Smith et al. 1997, Racey and Armstrong 2000, Wittmer et al. 2005, 2007). In addition, linear disturbances (e.g. roads, seismic lines) that accompany industrial development in the boreal forest facilitate greater predator mobility and hunting effi ciency (James and Stuart-Smith 2000, Dyer et al. 2001, McLoughlin et al. 2003, James et al. 2004). Boreal caribou, an ecotype of woodland caribou, are declining throughout much of their North American range (McLoughlin et al. 2003). Given the increasing levels of industrial development in previously pristine areas, preventing or mitigating further population declines is increasingly the focus of management efforts.

In this study, a simple question is posed: is there a clear relationship between caribou demography and anthropogenic and/or natural (fi re) disturbance levels on caribou ranges across the distribution of boreal caribou in Canada? We expected that adult survival, calf recruitment and overall population growth would be negatively related to changes that create favorable habitat for moose and deer, in keeping with the logic that increased primary prey increases predator density which contributes to caribou population decline. Caribou avoidance of industrial development (Bergerud 1974, Mallory and Hillis 1998, Dyer et al. 2001, Schaefer 2003) and recent burns (Schaefer and Pruitt 1991, Joly et al. 2003, Dunford et al. 2006) have been well documented; thus it is reasonable to postulate that these factors would negatively affect range condition with respect to the ability of an area to support a self-sustaining local population. Wittmer et al. (2007) found that the variation in adult female survival among 10 woodland caribou populations of the arboreal lichen-feeding ecotype was best explained by range condition. Further, in a review of 85 studies that examined impacts of human activity on caribou, Vistnes and Nellemann (2008) concluded that choice of spatial scale for examining impacts strongly influenced conclusions, recommending that accurate assessment required regional-scale studies. Finally, in a recent analysis of 6 boreal caribou populations in Alberta, Sorensen et al. (2008) demonstrated a negative relationship between range condition and population growth rate. Their 2 variable model, which included level of anthropogenic disturbance (%IND) and wildfi re (%FIRE), explained 96% of the variation in caribou population growth rates. Hence, our selection of caribou range as the appropriate unit of analysis is justified.

The Sorensen et al. (2008) regression model represents a significant advance in our understanding of the effects of disturbance on caribou demography at the level of population ranges. However, the study was based on a small sample size and a limited range of values for anthropogenic disturbance (e.g. the minimum level of anthropogenic disturbance was 31.6%). As a result, while the data were suffi cient to demonstrate signifi cance in terms of a relationship between the dependent and independent variables, the model has limited scope for prediction beyond the geographic area and parameter space included in that study, and should be used cautiously within that region when predicting minimum levels at which negative effects on caribou population growth might occur. The objective here was to extend the Sorensen et al. (2008) analysis to populations of boreal caribou across Canada, in order to test whether the relationship documented was robust across a broader spectrum of range conditions, and guide evaluation of the ability of ranges to support self-sustaining populations. Original work on this study was initiated in 2006, as part of an independent effort to address this question. Augmentation and refi nement of this effort was undertaken in conjunction with the Environment Canada scientifi c review of critical habitat for boreal caribou.

 

Methods

Data collection – caribou

Researchers and management agencies were approached to supply demographic information on woodland caribou populations that had been studied for a minimum of two years (the smallest interval included in Sorensen et al. 2008), and for which adult female survival (as determined by radio-telemetry monitoring) and/or calf recruitment (late winter calf/cow population surveys) had been measured. The intent was to assemble data that exhibited a broad range of variation with respect to geography and degree of anthropogenic change to population ranges. A tabular data survey with instructions was circulated to potential contributors. Information on 25 boreal populations from 7 provinces and 1 territory was acquired (Figure 1). There was considerable variability in the intensity and duration of sampling, and availability of ancillary information.

Estimates of population condition

Of the 25 populations included in this study, data for assessing female survival and therefore estimating population growth rates were available for 15 (Table 1). Some populations had only a small number of female caribou collared and concomitant high variability in estimated survival. Therefore, to maximize the number of populations available for analysis, estimates of recruitment rates, which were available for all populations, were used as a surrogate of ‘population condition’. Bergerud and Elliot (1986, 1998) demonstrated that recruitment was directly related to population rate-of-growth in caribou, as well as in other ungulates. Furthermore, recruitment may be a better short-term indicator of population condition in rapidly changing landscapes than either female survival or population growth rate, given that calves are more susceptible to predation than adults, and high adult survival could initially mask the negative effects of landscape change.

To test the relationship between recruitment and population growth, and the appropriateness of using recruitment as the response variable to range condition in the regression analysis, data from the subset of populations for which recruitment and survival were available were used to estimate population rate of change (λ) following Hatter and Bergerud (1991); see also McLoughlin et al. (2003) and Sorensen et al. (2008). However, because averages and not annual data were provided for some local populations, an arithmetic, rather than geometric mean (McLoughlin et al. 2003. Sorensen et al. 2008) was used to estimate average values for each parameter over the years of study included for each population (Table 1). Data for some populations were sub-sampled to be temporally consistent with available data on landscape change; in particular, to avoid inclusion of demographic data that potentially preceded the change. Also, some populations with long-term data exhibited trends suggesting that an average over the entire sampling interval was not representative of the current population condition. Where available, up to 4 years of most recent data, spanning a maximum sampling interval of 5 years, and with greatest temporal correspondence to the landscape change data, were used to estimate demographic parameters for analysis (Table 1). The 6 Alberta populations included in Sorensen et al. (2008) were also included in this study; however, the sampling intervals differed (1993-2001 vs. 2002-2006). Thus, it was possible to also evaluate the relationship between recruitment and population growth for a second subset of temporally non-overlapping data, based on Sorensen et al. (2008).

Delineation of population ranges

Range boundaries were provided by contributors for study populations, obtained from provincial or territorial sources for jurisdictionally-recognized population ranges, or generated from 100% minimum convex polygons (MCPs) of telemetry data provided by contributors. Delineation method is indicated in Table 1 and illustrated in Figure 1. Where a study population corresponded closely to a jurisdictionally recognized range (e.g. ≥90% correspondence), the data were considered representative of the range, and the jurisdictional boundary was used for population delineation and characterization of range condition.

Appendix 6.5 - Figure 1. Location of 25 boreal caribou populations included in this study

Appendix 6.5 - Figure 1. Location of 25 boreal caribou populations included in this study

 

Characterization of range condition and model specifi cation

Following Sorensen et al. (2008), the relationship between recruitment and range condition was evaluated by comparing three candidate models. Model 1 considered the percent of the range area burned within the past 50 years of the most recent recruitment data for each population. Fire data from the Canadian Large Fire Database, augmented by additional coverage for the Northwest Territories, that contained wildfi res >200 ha (NRCan 2008, GNWT 2008) were used. Model 2 considered the percent of the range area affected by anthropogenic disturbance, based on GIS layers obtained from Global Forest Watch Canada (GFWC). GFWC have compiled the only available, nationally-consistent coverage of anthropogenic disturbance across forested regions of Canada. All visible linear and polygonal anthropogenic disturbances were digitized from Landsat images from the period 1985–2003, and combined with additional coverage of roads, reservoirs and mines from databases spanning the period 2002-2006. Linear disturbances included roads, railroads, seismic lines, pipelines, and utility corridors; polygonal features included recently anthropogenically-converted areas such as settlements, populated industrial areas, croplands (both new and abandoned), reservoirs, cutblocks, and mining activity. All features in the database were buffered by 500 m to create a “zone of infl uence”, and merged to create a non-overlapping coverage of all anthropogenic disturbances. Detailed methodology is available from Lee et al. (2006). Sorensen et al. (2008) used a 250-m buffer when quantifying human disturbance. However, we did not have access to the raw data used in the GFWC analysis, so could not select an alternate or varying buffer width. Nevertheless, in a review of reindeer and caribou response to huma n activityfrom regional-scale landscape studies, Vistnes and Nellemann (2008) report reduced use by caribou of areas within 5 km of infrastructure and human activity, thus the 500-m buffer is not unreasonable. Lastly, Model 3 considers the combined effect of fi re and anthropogenic disturbance, herein termed total disturbance.

Characterization of total disturbance and modeling procedure

Sorensen et al. (2008) used a 2 variable model to characterize total disturbance (%FIRE and %IND); however, they found a relatively high correlation between these 2 variables (Pearson correlation of 0.69) which tends to produce least-squares estimates that are exaggerated in absolute value (Montgomery et al. 2001). Multi-colinearity between these 2 variables could also influence parameterization because of the likely non-linear relationship between the proportion of area disturbed and the level of spatial overlap. Specifi cally, at low levels of disturbance the spatial overlap is likely to be low whereas the likelihood of overlap should increase at higher levels of disturbance. Visual inspection of the data revealed such a pattern. Therefore, to describe total disturbance when testing the hypothesis of primary interest (e.g. the combined effects of fire and anthropogenic disturbance), the merged mapped of nonoverlapping disturbances was used to derive a single measure of total disturbance. This method captured the required information from each variable while accounting for the spatial overlap, and increased the power of the test by reducing the number of variables in the model.

Linear regression and related diagnostics were used to test the relationship of recruitment to each measure of range condition specifi ed by the three models. Similarly to Sorensen et al. (2008), herds were considered to be independent and Akaike’s Information Criteria (AIC) with correction for small sample sizes (AICc) was used to test between the three candidate models (Burnham and Anderson 1998).

Appendix 6.5 Table 1. Location, sampling duration, method of range delineation (J= jurisdiction; SA = study area), yearly ratio of calves per 100 cows (R), annual adult female survival (S), and rate of population change () for 25 boreal caribou populations in Canada )

Local Population Prov/Terr Years
Available
Sample # Years Years
Used
Range R S λ
Red Wine NL 1981-1988,
1993-1997,
2001-2003
Y 3 2001-2003 J 45.4 n/a n/a
Mealy Mountain NL

1971,
1974-1975,
1977, 1981,
1985,

1987, 1994,
2002, 2005

Y 2 2002, 2005 J 50.3 89.0 1.19
Lac Joseph NL 2000-2002,
2005, 2007,
2008
Y 4 2000-2002,
2005
J 34.3 n/a n/a
Val-d'Or QC

1987-1988,
1990-1991,
1995-2002,

2004-2005

Y 4 2001-2002,
2004-2005
J 15.3 87.0 0.94
Manicouagan QC 1999-2001 N 3 1999-2001 J 50.5 75.0 1.00
Manouane QC 1999-2001 N 3 1999-2001 J 28.1 86.0 1.00
Pipmuacan QC 1999-2001 N 3 1999-2001 J 40.6 82.0 1.03
Charlevoix QC 2000-2001,
2004-2006
Y 4 2001,
2004-2006
J 35.0 n/a n/a
Jamesie QC 2002-2003 N 2 2002-2003 SA 27.4 n/a n/a
James Bay ON 1998-2000 N 3 1998-2000 SA 21.3 79.0 0.88
Pukaskwa ON 1973-1991,
1997, 1999,
2001
Y 3 1997, 1999,
2001
J 40.3 n/a n/a

Smoothstone-

Wapawekka

SK 1993-1995 N 3 1993-1995 SA 28.0 84.0 0.98
CaribouMountain AB 1995-2007 Y 4 2003-2006 J 17.4 75.0 0.82
ESAR AB 1994-1997,
1999-2007
Y 4 2003-2006 J 13.4 86.6 0.93
Red Earth AB 1995-1997,
1999-2007
Y 4 2003-2006 J 13.6 81.9 0.88
WSAR AB 1994-2007 Y 4 2003-2006 J 20.9 84.2 0.94
Little Smoky AB 2000-2007 Y 4 2003-2006 J 12.3 82.2 0.88
ColdLake AB 1999-2002,
2004-2007
Y 4 2002,
2004-2006
J 12.6 83.8 0.89
Chinchaga AB 2002-2007 Y 4 2003-2006 J 13.9 87.0 0.93
Snake-Sahtaneh BC 2004-2005 N 2 2004-2005 J 7.2 94.0 0.97
CameronHills NWT 2006-2008 N 3 2006-2008 SA 16.4 n/a n/a
Dehcho North NWT 2006-2008 N 3 2006-2008 SA 20.7 n/a n/a
Dehcho South NWT 2006-2008 N 3 2006-2008 SA 32.3 n/a n/a
GSA South NWT 2004-2006 N 3 2004-2006 SA 28.9 n/a n/a
GSA North NWT 2005-2006 N 2 2005-2006 SA 45.4 n/a n/a
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