https://cpw.cvlcollections.org/files/original/8c39df70bf91be29988e53a8be40b38b.pdf 176aafd892cf59948699467b1a5b29e6 PDF Text Text The research in this publication was partially or fully funded by Colorado Parks and Wildlife. Dan Prenzlow, Director, Colorado Parks and Wildlife • Parks and Wildlife Commission: Marvin McDaniel, Chair • Carrie Besnette Hauser, Vice-Chair Marie Haskett, Secretary • Taishya Adams • Betsy Blecha • Charles Garcia • Dallas May • Duke Phillips, IV • Luke B. Schafer • James Jay Tutchton • Eden Vardy �Biological Conservation 200 (2016) 51–59 Contents lists available at ScienceDirect Biological Conservation journal homepage: www.elsevier.com/locate/bioc The diet of black bears tracks the human footprint across a rapidly developing landscape Rebecca Kirby a,⁎, Mathew W. Alldredge b, Jonathan N. Pauli a a b Department of Forest and Wildlife Ecology, University of Wisconsin – Madison, Madison, WI 53706, USA Colorado Parks and Wildlife, Fort Collins, CO 80526, USA a r t i c l e i n f o Article history: Received 12 December 2015 Received in revised form 13 May 2016 Accepted 20 May 2016 Available online 9 June 2016 Keywords: Foraging Human-wildlife conﬂict Resource subsidies Stable isotopes Ursus americanus a b s t r a c t Food subsidies have become a widely available and predictable resource in human-modiﬁed landscapes for many vertebrate species. Such resources can alter individual foraging behavior of animals, and induce population-wide changes. Yet, little consensus exists about the relative inﬂuence of the availabilities of native and human food subsidies to wildlife foraging throughout altered landscapes. We explored this unresolved question by analyzing the effects of landscape factors on American black bear (Ursus americanus) diet across the state of Colorado, USA. We estimated assimilated diet using stable isotope analysis of harvested black bear tissues to determine the contribution of human-derived foods to bear diets throughout Colorado, as well as how increasing reliance on human-derived food subsidies increases the risk of conﬂict. We found that bears (n = 296) showed strong regional diet variability, but substantial use of human-derived food subsidies in eastern Colorado (N30% assimilated diet). The age-sex class of the bear and housing density of its harvest location were the most inﬂuential predictors of 13C enrichment (a tracer of human food subsidies). Furthermore, foraging on subsidies increased risk of conﬂict; the odds of being a nuisance bear increased by 60% for each ~1‰ increase in δ13C. Our study conﬁrms the efﬁcacy of δ13C as a proxy for human activity, and indicates that while demographic differences play a clear role in the foraging ecology of bears, availability of subsidies coincident with varying levels of human activity appears to be a major driver in predicting black bear diet throughout the western United States. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction Human-modiﬁed landscapes now prevail globally (Ellis et al., 2010), and urban landscapes show particularly extreme changes in productivity and resource availability (Shochat et al., 2006). Human-derived foods, especially in the form of food waste (Parﬁtt et al., 2010) or agricultural crops (Oro et al., 2013), are often widely available (Fedriani et al., 2001; Newsome et al., 2014a) and are a temporally and spatially predictable supplemental resource for many species of wildlife (Oro et al., 2013; Yirga et al., 2012). While supplemental food can enhance individual nutritional status and reproduction (Marzluff and Neatherlin, 2006), it also can have substantial ecological costs (Parker and Nilon, 2008). For example, it can shift phenological timing (Beckmann and Berger, 2003a; Robb et al., 2008) or modify prey use (Newsome et al., 2014a), altering well-established interspeciﬁc interactions (Rodewald et al., 2011) and potentially restructuring trophic cascades (Newsome et al., 2014b). Across mammalian species, increasing reliance on food subsidies can increase population sizes and decrease home ranges and activity levels (Newsome et al., 2014b; Parker and Nilon, 2012). Furthermore, wildlife habituation to supplemental food can have societal costs ⁎ Corresponding author. E-mail address: rebeccakirby@wisc.edu (R. Kirby). http://dx.doi.org/10.1016/j.biocon.2016.05.012 0006-3207/© 2016 Elsevier Ltd. All rights reserved. through increased conﬂict with humans (Beckmann and Lackey, 2008). Understanding then, how anthropogenic inputs to the environment are utilized has important ecological and conservation implications. As opportunistic omnivores, American black bears (Ursus americanus) exhibit highly plastic foraging strategies and are increasingly found in modiﬁed landscapes (Beckmann and Berger, 2003a). Diet preferences and food intake vary by sex, reproductive status, and season (Jacoby et al., 1999; Robbins et al., 2004). In the spring, bears consume primarily herbaceous plants and graminoids (Raine and Kansas, 1990), incorporating a wide variety of soft and hard mast during summer and fall as they enter hyperphagia (Hellgren et al., 2005; Ryan et al., 2007). Ungulates, small mammals, and insects, especially ants, can also be signiﬁcant in the diet of some populations (Noyce et al., 1997; Zager and Beecham, 2006), as well as human-derived foods (Breck et al., 2009; Hopkins et al., 2014; Merkle et al., 2013). Despite high variability among populations, food availability is generally the primary predictor for habitat use, reproduction, denning chronology, and population density (Baldwin and Bender, 2010; Costello et al., 2003; Hilderbrand et al., 1999; Noyce and Garshelis, 1994; Rogers, 1987). Further, foraging preferences may vary by age-sex class to avoid risky competition or take advantage of differing prey availabilities (Ben-David et al., 2004; Edwards et al., 2011). Regardless of food availability in a particular year, adult survival in most black bear populations tends to be high �52 R. Kirby et al. / Biological Conservation 200 (2016) 51–59 (Noyce and Garshelis, 1994), but cub production declines in years with limited food availability (Bridges et al., 2011; Elowe and Dodge, 1989). Urbanized areas can supplement diets during these food-limited years, stabilizing cub production, though in some cases also increasing adult mortality due to lethal conﬂict with humans (Baruch-Mordo et al., 2014; Beckmann and Lackey, 2008). Increasing bear-human conﬂicts have been attributed to a combination of growing bear populations (Garshelis and Hristienko, 2006; Spencer et al., 2007), natural food failures (Hristienko and McDonald, 2007), and the availability of and attraction to human-derived foods (Beckmann et al., 2008; Can et al., 2014; Greenleaf et al., 2009; Hopkins et al., 2014). The western U.S., in particular, is experiencing both increasing urbanization, and the expansion of anthropogenic impacts into exurban and rural areas through infrastructure such as roads and power lines (Hansen et al., 2005; Leu et al., 2008). The Colorado Front Range is one of the largest wildland-urban interfaces (Radeloff et al., 2005), exposing black bears to variable levels of human activity and habitat quality, and increasing bear-human conﬂicts (Baruch-Mordo et al., 2008). These conﬂicts appear to be highly variable across space and time, and among age-sex class (Baruch-Mordo et al., 2008, 2014; Beston, 2011), generating uncertainty about accurately predicting which bears might become problematic. Further, the relative inﬂuence of native and human-derived foods on such conﬂicts remains in question. Some studies suggest that habituated bears will return to previously encountered food subsidies (Beckmann et al., 2004; Hopkins and Kalinowski, 2013; McCarthy and Seavoy, 1994; Merkle et al., 2013), while others indicate that use of urban environments is more ﬂexible (Johnson et al., 2015), and increases primarily in poor food years (Baruch-Mordo et al., 2014; Kavčič et al., 2015). Due to high local variation in diet, few generalizations about bears across regions exist (Bojarska and Selva, 2012). Traditional methods for diet reconstruction (e.g., scat, stomach content analyses) tend to underestimate highly digestible resources, including human-derived foods (e.g. Newsome et al., 2010). However, isotopic analysis examines assimilated diet, avoiding this bias, and has been successfully used to detect human-derived food consumption in omnivorous mammals including foxes (Lavin et al., 2003; Newsome et al., 2010), coyotes (Garwood et al., 2015; Newsome et al., 2015), and bears (Hobson et al., 2000; Hopkins et al., 2012, 2014; Mizukami et al., 2005). For example, Hopkins et al. (2014) demonstrated that consumption of human-derived foods by black bears in Yosemite National Park varied temporally with management policies of trash. Additionally, in British Columbia (Hobson et al., 2000) and central Japan (Mizukami et al., 2005) bears identiﬁed as nuisances or caught near human development were enriched in 13C relative to their conspeciﬁcs. Because cornand cane sugar-dominated human foods and their derivatives are enriched in 13C relative to a C3 native plant base (Jahren et al., 2006; Jahren and Kraft, 2008; Chesson et al., 2008), such bears could be consuming either human food waste, agricultural crops, or even livestock that are enriched in 13C due to their feed (Jahren and Kraft, 2008). Most recently, black bears residing in an agricultural landscape in Minnesota were found to regularly consume corn crops, based on GPS movements and 13C enrichment (Ditmer et al., 2015b). Further, Hopkins et al. (2012) and Mizukami et al. (2005) found management bears also were enriched in 15N, suggesting foraging at a higher trophic position, which they could obtain from consuming either natural or human foods that were rich in animal matter (meat, insects). Although there have been a number of site-speciﬁc studies, there have been few landscape-level studies on wildlife diet (e.g. Mowat and Heard, 2006) because diet reconstruction with stable isotopes depends on adequately characterizing the prey base. Herein, we used stable isotopes to examine black bear diets across the state of Colorado. We analyzed individual bear hair and blood samples, and potential prey across the state, to determine the extent to which bears relied on human-derived food subsidies, and considered how landscape factors representing human activity and primary productivity related to diet. We anticipated that bears in poorer quality habitat and exposed to more human subsidies would consume a greater proportion of anthropogenic foods, which would vary as a function of age and sex class (Johnson et al., 2015). We further compared nuisance bears (lethal removal) to the hunter-harvested population to determine if eating anthropogenic foods increased the risk of being a conﬂict bear, as has been shown in other populations (Hopkins et al., 2014). Our ﬁndings provide insight to bear foraging at the landscape-level, and how food subsidies associated with the expanding human footprint inﬂuence black bear foraging ecology and management. 2. Materials and methods 2.1. Study area We examined black bear diet throughout their range in Colorado, USA. Black bears occupy the western two-thirds of the state, in the Southern Rocky Mountains, which is a complex patchwork of land use types consisting of forests, agricultural lands, and urban developments. Black bears are hunted throughout their range from September–January, with the majority of harvest in September and October. Colorado does not allow baiting, and manages the bear population at the level of Game Management Unit (GMU), which are on average ~ 1900 km2. Housing density within GMUs ranges from 0.04 to 121 housing units/ km2, and tends to be denser in eastern Colorado (t = 5.98, P b 0.001) along the Front Range, a rapidly expanding wildland-urban interface. The vegetation community varies widely throughout the state, transitioning from ponderosa pine and piñon-juniper (Pinus edulis/ Juniperus spp.) woodlands at lower elevations into lodgepole pine (Pinus contorta), aspen (Populus tremuloides), Douglas-ﬁr (Pseudotsuga menziesii), and spruce (Picea spp.)-subapline ﬁr (Abies lasiocarpa) forests at higher elevations. Areas of Gambel oak (Quercus gambelli), considered especially high-quality bear habitat, are distributed throughout the Southern Rockies (Beck, 1991). 2.2. Sample collection and preparation We sampled hair and blood from hunter-harvested black bears across Colorado during the fall hunting season in 2011 (n = 296 hair; n = 113 blood). Because we opportunistically sampled bear carcasses during registration with hunters' permission, sample locations are not evenly distributed, and not all carcasses contained sufﬁcient blood for sampling. For each harvested bear, GPS locations (or minimally the management unit) are provided by the hunter (Fig. 1). Our samples represent ~27% of Colorado bear harvest in 2011. Hair growth in black bears typically occurs late spring into the fall, and its isotopic signature is representative of assimilated diet throughout its growth (Hilderbrand et al., 1996, Jacoby et al., 1999). Whole blood represents more recent diet than hair, approximately the last month or two in bears (Hilderbrand et al., 1996). We examined seasonal changes in diet within individuals by analyzing hair and blood isotopic signatures, comparing spring-summer diet (hair) to late summer-fall diet (blood). Though we recognize the uncertainty in the exact time period each tissue represents, as well as some temporal overlap, we hereafter refer to “spring-summer” or “late summer-fall” for simplicity. Due to the wide geographic spread of bear samples, we aimed to ﬁrst characterize the isotopic signatures of the native forage base in ﬁve general regions: Northeastern Front Range, Southeastern Front Range, Southwestern San Juan Mountains, Uncompaghre Plateau, and Northwestern Colorado. We collected known bear foods that grouped broadly into native vegetation (n = 288) (acorns, berries, and herbaceous plants) or animal matter (n = 116) (mule deer, rabbit, ants and other insects) (see Appendix A, Table A1). We rinsed hair samples three times with 2:1 chloroform:methanol solution to remove surface oils, homogenized them with surgical scissors, and dried samples for 72 h at 56 °C (Pauli et al., 2009). Whole blood samples were dried for 72 h at 60 °C, and homogenized with a �R. Kirby et al. / Biological Conservation 200 (2016) 51–59 Fig. 1. Sample locations of hunter-harvested bears (n = 273) in 2011, shown with Colorado black bear range (as estimated by Colorado Parks and Wildlife) and management regions. spatula. Vegetation samples were dried at 56 °C for a minimum of 72 h and homogenized in a ball mill (Mixer Mill MM200, Restch Inc. Newton, PA, USA). We weighed samples (N 50% in duplicate) into tin capsules for δ13C and δ15N analysis at the University of Wyoming's Stable Isotope Facility using a Costech 4010 and Carlo Erba 1110 Elemental Analyzer (Costech, Valencia, CA) attached to a Thermo Finnigan Delta Plus XP Continuous Flow Isotope Ratio Mass Spectrometer (Thermo Fisher Scientiﬁc Inc., Waltham, MA). We provide results as per mil (‰) ratios relative to the international standards of Vienna Peedee Belemnite for C and atmospheric N2 for N, with calibrated internal laboratory standards. 53 has been applied in previous work on omnivorous carnivores (Hopkins et al., 2012; Newsome et al., 2010). We make the assumption then that black bears would discriminate an all human foods diet similarly to humans, and thus apply no trophic correction for hair samples (Hopkins and Ferguson, 2012) (Fig. 2). For blood sample analysis, it was necessary to correct the human hair samples to blood samples, so we applied a trophic correction to the human-derived foods diet group by calculating the difference between discrimination factors developed for red blood cells and those developed for hair in an omnivore consuming a mixed diet (Δ13C: −1.7 ± 0.1 and Δ15N: −0.7 ± 0.2; Kurle et al., 2014). We estimated proportional importance of each forage group to regional bear populations with Bayesian-based mixing models in the package Stable Isotope Analysis in R (SIAR; Parnell et al., 2010). Models were parameterized with uniform priors, allowing the data to drive the model, as well as trophic discrimination and concentration dependence (mean digestible elemental concentrations for each diet group; Hopkins and Ferguson, 2012). Data are expressed as medians of the probability density functions with 95% credible intervals, which represent each diet group's likely level of contribution to bear diet (Parnell et al., 2010). We also estimated dietary proportions by age-sex class. To ensure that minor differences in the isotopic signatures of regional diet sources (i.e., regional mixing spaces) did not bias results, we also re-ran models parameterized with mean statewide diet sources, and found no signiﬁcant differences in group estimates. Therefore, we were conﬁdent in using raw isotopic values as proxies for diet throughout the state, with increased enrichment in 13C as indicative of increased anthropogenic food consumption and increased enrichment in 15N as indicative of either increased anthropogenic food or animal matter consumption (i.e. trophic position). 2.4. Variable predictors of diet and model selection We examined how potential variables, speciﬁcally demographic class, habitat productivity, and human activity, were correlated with isotopic signature, and therefore diet. For these analyses we limited our dataset to bear samples with GPS harvest locations (hair n = 273; blood n = 104). Although black bears can vary widely in their home range size, collared bears in two Colorado studies generally ranged up to 50 km2 (Baldwin, 2008; Baruch-Mordo et al., 2014). Thus, we buffered each bear harvest location by a radius of 4 km (~50 km2) to analyze variables representing both habitat productivity and human activity. To 2.3. Stable isotope analyses Choice of discrimination factors can strongly inﬂuence mixing models, and be particularly challenging in omnivores where sources can differ greatly in isotopic signature (Caut et al., 2009). We applied tissue-speciﬁc mean discrimination factors recently developed for omnivorous mammals to each sampled bear food group for hair and blood samples separately (hair: animal matter, Δ13C: 2.1 ± 0.1 and Δ15N: 3.9 ± 0.3, native vegetation, Δ13C: 3.4 ± 0.2 and Δ15N: 2.4 ± 0.2; blood: animal matter, Δ13C: 0.6 ± 0.1 and Δ15N: 3.0 ± 0.3, native vegetation, Δ13C: 1.3 ± 0.2 and Δ15N: 1.9 ± 0.2; Kurle et al., 2014). Though we analyzed whole blood, we assumed the appropriate discrimination factors would be most similar to those of red blood cells (e.g. Caut et al., 2009). To deﬁne isotopically distinct diet groups, we used a K nearestneighbor randomization test (KNN; Rosing et al., 1998), comparing forage items ﬁrst within each region, and subsequently across regions. Uncompaghre Plateau samples were indistinguishable from Southwestern Colorado, so we combined these areas, and proceeded with 4 geographical regions of Colorado. To deﬁne a human-derived foods signature, we used human hair samples from across the U.S. (δ13C = − 16.9 ± 0.8; δ15N = 8.8 ± 0.5; Bowen et al., 2009), which Fig. 2. Isotopic signatures of potential diet items and black bear hair samples, 2011. Generalized diet groups for Colorado shown with means and standard deviations, corrected for trophic discrimination: native vegetation, animal matter, human-derived foods. Geographic origin of hunter-harvested bear samples indicated by symbols: eastern CO (dark gray circles), western CO (light gray circles). �54 R. Kirby et al. / Biological Conservation 200 (2016) 51–59 examine whether our analysis was sensitive to scale, we also considered initially buffers of 10, 250, and 1000 km2. As we found the same patterns regardless of scale, we present results from 50 km2 as the most representative of a black bear home range. To estimate habitat productivity in 2011, we examined the Normalized Difference Vegetation Index (NDVI) (Wiegand et al., 2008), with higher NDVI values representing greater primary productivity. We took global monthly composites (0.1 degrees) for 2011 collected by Terra/MODIS (NASA Earth Observations) and averaged them across the growing season (April – October) in ArcGIS (ESRI, v.10). Mean growing season NDVI of each buffered bear location was extracted using Geospatial Modelling Environment (GME, v. 0.7.2.1), and then used in subsequent comparisons. We considered three possible measures of human activity that could be related to bear diet: road density from TIGER 2013 primary and secondary Colorado road layer (US Census Bureau), housing density from 2010 Block Level Housing Density (Radeloff et al., 2010) and percent crop cover from National Landcover Database (NLCD, 2011). Because road density and housing density were highly correlated (r = 0.60, t = 11.86, P b 0.001), likely capturing similar measures of human development, we selected housing density to represent human development and crop cover for agricultural development. Bears were not harvested in areas of high crop cover – 87% of their locations contained no croplands. We accordingly categorized bear location for presence or absence of any amount of croplands. As Colorado bear habitat can vary with elevation (e.g., high elevations have greater precipitation and colder temperatures), we also calculated average elevation of each location from National Elevation Dataset (USGS, 2009). We ﬁrst examined variables individually with Pearson's correlations or ANOVAs. We then compared linear models using δ13C and δ15N as response variables, and used Akaike's Information Criterion to select the best models to predict δ13C and δ15N separately. Covariates examined include age-sex class (adult female, adult male, subadult female, subadult male), elevation, housing density, crop cover, and growing season NDVI. Housing density was log transformed to meet assumptions of normality. We also initially considered environmental covariates including precipitation, snow, and temperature, but these were highly correlated with elevation and growing season NDVI, therefore we did not include them in the models. We conducted these analyses for both hair and blood samples. We tested for spatial autocorrelation in the model residuals by running a spline correlogram with 1000 permutations (Bjørnstad and Falck, 2001), and found no signiﬁcant autocorrelation that would warrant additional spatial analyses (Appendix A, Fig. A1). Because hunter-harvested bears are more likely to be killed along transportation corridors, our samples of hunter-harvested bears may underrepresent remote wildland bears that have little access to human-derived food subsidies. However, as hunting is not permitted within urban areas, we are likely also missing bears that have the greatest access to subsidies. Regardless, analyses up to this point did not include known roadkill or nuisance bears. We considered conﬂict bear diet independently by analyzing samples from bears killed by vehicle collision (n = 14) and lethal nuisance removal by CPW (n = 14), representing ~16% and 11% of each mortality type in 2011, respectively, and were killed during the same time period as the hunted bears and in similar locations. Nuisance bears may have been lethally removed due to conﬂicts around housing developments (e.g. property damage) or agricultural operations (e.g. crop depredation). Roadkill bears are also classiﬁed broadly as conﬂict bears by Colorado Parks and Wildlife due to injury and damage to humans and property (e.g. Baruch-Mordo et al., 2008). To determine whether isotopic signature is predictive of being a conﬂict bear, we compared nuisance bears and roadkill bears to a subset of harvested bears (n = 62) from within the same areas (GMUs) as the conﬂict bears, thus removing potential geographical bias. We compared dietary estimates among bears grouped by mortality type, and used logistic regression to estimate the odds ratios for mortality types based on isotopic signature. 3. Results 3.1. Regional bear diet Comparisons between spring-summer and late summer-fall diet yielded similar patterns of forage within regions. Bear hair isotopic values exhibited large variation between individuals in both δ13C (x = − 21.78; range: − 24.23 to − 17.15), and δ15N (x = 5.17; range: 2.12 to 10.19). Because we found signiﬁcant, albeit slight, isotopic differences by region – vegetation in southwest Colorado was enriched relative to the northeast (KNN, P = 0.01) and animal matter in the southeast was enriched relative to the northeast (KNN, P b 0.001) – we estimated proportional diet contributions separately for each region. As expected, native vegetation made up the primary spring-summer diet group for Colorado bears in all regions, ranging from a low of 66% in the northeast to a high of 80% in the southwest (Table 1). However, there were strong longitudinal differences in estimates of human food contributions, with eastern bears consuming N30% human-derived foods, while western bears consumed ≤ 21%. Because we used region-speciﬁc diet samples to parameterize the model, these differences are not based on an isotopic difference in prey base. Bear blood samples were less enriched in 13C than hair samples, but slightly enriched in 15N, showing a tissue-speciﬁc (i.e., season-speciﬁc) effect (RM-MANOVA, Pillai's trace, F2,111 = 0.80, P b 0.001), suggesting that any seasonal change in diet was consistent across individuals. Blood samples indicated similar consumption of food subsidies during the fall compared to the summer, with a low of 22% in the west and a high of 36% in the northeast (Table 1). The 95% credible intervals for diet estimates from blood samples overlap with estimates derived from hair samples, but were larger, likely due to smaller sample sizes with greater variation. Regardless of minor differences in model estimates, both seasons show a consistent longitudinal pattern, with higher human-derived food consumption in the eastern region. Table 1 Assimilated dietary estimates from Bayesian mixing models (SIAR) for hunter-harvested black bears in the spring-summer and late summer-fall seasons in 2011, obtained from the isotopic signatures of hair and blood, respectively. Estimates provided by region of Colorado. Diet groups Median proportion (95% credible intervals) NE CO SE CO NW CO SW CO Hair (n) Native vegetation Animal matter Human-derived foods 29 0.66 (0.58–0.72) 0.01 (0.00–0.05) 0.33 (0.26–0.40) 71 0.67 (0.63–0.72) 0.00 (0.00–0.02) 0.32 (0.28–0.37) 104 0.78 (0.76–0.80) 0.01 (0.00–0.03) 0.21 (0.18–0.23) 92 0.80 (0.78–0.83) 0.01 (0.00–0.03) 0.19 (0.16–0.21) Blood (n) Native vegetation Animal matter Human-derived foods 9 0.45 (0.20–0.63) 0.19 (0.00–0.49) 0.36 (0.17–0.52) 29 0.61 (0.54–0.69) 0.02 (0.00–0.07) 0.36 (0.28–0.45) 37 0.68 (0.60–0.73) 0.10 (0.00–0.22) 0.22 (0.14–0.29) 38 0.73 (0.69–0.77) 0.04 (0.00–0.10) 0.22 (0.17–0.28) �R. Kirby et al. / Biological Conservation 200 (2016) 51–59 55 Table 2 Assimilated dietary estimates from Bayesian mixing models (SIAR) for age-sex class of black bears in the spring-summer and late summer-fall seasons in 2011, obtained from the isotopic signatures of hair and blood, respectively. Median proportion (95% credible intervals) Adult male Adult female Subadult male Subadult female Hair (n) Native vegetation Animal matter Human-derived foods 93 0.68 (0.66–0.71) 0.01 (0.00–0.02) 0.31 (0.28–0.33) 71 0.75 (0.72–0.78) 0.01 (0.00–0.02) 0.24 (0.21–0.27) 93 0.75 (0.73–0.78) 0.01 (0.00–0.02) 0.24 (0.21–0.26) 39 0.77 (0.73–0.81) 0.02 (0.00–0.06) 0.21 (0.16–0.25) Blood (n) Native vegetation Animal matter Human-derived foods 38 0.63 (0.58–0.68) 0.06 (0.00–0.14) 0.31 (0.22–0.39) 30 0.65 (0.60–0.69) 0.02 (0.00–0.08) 0.32 (0.27–0.37) 35 0.66 (0.60–0.72) 0.04 (0.00–0.14) 0.29 (0.21–0.36) 10 0.64 (0.43–0.77) 0.10 (0.00–0.39) 0.25 (0.07–0.39) 3.2. Covariates inﬂuencing bear diet For spring-summer diet, we found that presence of crop cover was unrelated to 13C enrichment (t = −1.53, P = 0.13); however, it was related to housing density as bear locations with some crop cover tended to have greater housing densities than locations without any crop cover (t = − 2.66, P = 0.01). Because of the very limited crop cover in our study area, we could not adequately tease it apart from the broader measure of human activity at this scale. Thus, we did not include crop cover in regression analyses. Age-sex class was an inﬂuential predictor of the hair isotopic signature of bears, with all four age-sex groups exhibiting signiﬁcant differences. Adults were enriched in both 13C and 15N over subadults, though adult females were the most enriched in 13C, while adult males were the most enriched in 15N (MANOVA, Wilk's λ = 0.84, P b 0.001). Stable isotope mixing model estimates suggest that adults consumed more human-derived foods than subadults (Table 2). The top linear model for hair δ13C also included age-sex class, NDVI, and housing density (Table 3). NDVI tended to have a slight negative relationship with δ13C (β = −0.001, P = 0.01), suggesting that bears in areas of higher productivity consumed more native vegetation. Housing density was positively related to 13C enrichment (β = 0.650, P b 0.001), and thus, to bear reliance on human-derived foods, regardless of agesex class (Fig. 3). The top model for hair δ15N included NDVI as an important covariate (β = −0.001, P = 0.005) (Table 3). For late summer-fall diet, age-sex class was not signiﬁcantly related to blood δ13C and δ15N (MANOVA, Wilk's λ = 0.97, P = 0.74) suggesting diet later in the season was less variable across age-sex classes than earlier (Table 2). Similar to hair samples, however, housing density and NDVI were inﬂuential covariates for blood δ13C and δ15N (Table 3), though the relationships were not as strong as with hair samples. Housing density was positively related to δ13C (β = 0.622, P = 0.090) and NDVI was negatively related to both δ13C (β = − 0.003, P = 0.002) and δ15N (β = − 0.001 P = 0.068). Though there are clearly some seasonal differences, hair and blood samples corroborate the relationships of housing density and NDVI with bear diet. 3.3. Conﬂict bears Conﬂict bears and the subset of hunter-harvested bear samples were similarly distributed among ages (t = −1.48, P = 0.15), and split evenly between males and females. Hair samples from either type of conﬂict bears (nuisance removals or vehicle collisions) were typically enriched in isotopic signature compared to hunter-harvested bears (MANOVA, Wilk's λ = 0.93, P = 0.04), with nuisance bears being the most enriched (Fig. 4A). Enrichment in 13C is related to an increased probability of being a nuisance bear, as opposed to a hunter-harvested bear. Because δ13C and δ15N are correlated in this system (r = 0.44, t = 4.63, P b 0.001), we report only δ13C, as it is a tracer of human foods. The odds of being a nuisance bear increased by 60% for each ~1‰ increase in δ13C (odds-ratio: 1.6, 95% CI: 1.1–2.51, P = 0.02). This pattern is also still signiﬁcant for the more general conﬂict bear, which includes vehicle collisions in addition to nuisance removals (δ13C odds-ratio: 1.4, 95% CI: 1.03–2.0, P = 0.04). This corresponds to an increased estimated dietary contribution from human-derived foods - nuisance Table 3 Top linear models to predict δ13C and δ15N signatures in hair and blood, representing spring-summer diet and late summer-fall diet, respectively. Covariates tested were age-sex class, mean housing density (log transformed), growing season productivity (NDVI), and mean elevation (all calculated within a 50 km2 buffer of harvest location). Models were ranked using AIC (only b2 ΔAIC are shown). ΔAIC Weight Adjusted R2 25.56 26.64 0.00 1.08 0.59 0.34 0.16 0.16 109.39 110.69 110.97 0.00 1.31 1.59 0.42 0.22 0.19 0.10 0.10 0.10 59.41 60.42 60.92 0.00 1.01 1.51 0.44 0.27 0.21 0.19 0.17 0.17 40.74 41.50 42.16 42.41 42.49 0.00 0.76 1.42 1.67 1.76 0.24 0.16 0.12 0.10 0.10 0.02 0.02 0.02 0.02 0.02 AIC Hair δ13C Age-sex class + housing density + NDVI Age-sex class + housing density + NDVI + elevation δ15N Age-sex class + NDVI Age-sex class + NDVI + elevation Age-sex class + NDVI + housing density Blood δ13C Housing density + NDVI + elevation NDVI + elevation Housing density + NDVI δ15N NDVI NDVI + elevation Intercept NDVI + elevation + housing density NDVI + housing density �56 R. Kirby et al. / Biological Conservation 200 (2016) 51–59 Fig. 3. Linear regression of δ13C on housing density within 50 km2 of bear harvest location (log transformed), showing a positive relationship between increased housing density and 13C enrichment of hunter-harvested bear hair. Though age-sex class was also a signiﬁcant predictor variable, slopes were similar across classes, so only a single regression is shown, with points representing age-sex classes: adult male (ﬁlled black circles), adult female (ﬁlled gray circles), subadult male (open black circles), subadult female (open gray circles). bears consumed on average 12% more human-derived foods than hunter-harvested bears (Fig. 4B). 4. Discussion We found that black bears across Colorado exhibited regional variability in diet. As has been demonstrated in previous populations (e.g. Hellgren et al., 2005), vegetation is the most important dietary group regardless of location. However, bears in the eastern regions along the Front Range consumed a high amount of human-derived foods (over 30% of assimilated diet), while in western Colorado, bears relied more on native vegetation. Native animal matter contributed little to total bear diet. At the landscape scale, human density and activity (as indexed by housing density) appeared to be the strongest predictor of human-derived food consumption (Table 3, Fig. 3). This relationship held regardless of age-sex class, tissue type, or native vegetative productivity. Further, use of food subsidies was predictive of conﬂict, conﬁrming that lethally removed nuisance bears consumed more human-derived foods than hunter-harvested bears (Fig. 4B). Whether bears turn to food subsidies only in food-limited years (Baruch-Mordo et al., 2014) or utilize subsidies regardless of natural food availability (Beckmann et al., 2008) has been studied with conﬂicting results. Most recently, an analysis of bears in three systems in the western U.S. indicated that individual bear use of development was a dynamic interaction between their physiological state and environmental conditions – bears tended to use developed areas more during poor food years, later in the season, and as they aged, with males using development more overall (Johnson et al., 2015). Our study scale allowed for examination of broad dietary patterns across a range of variable black bear habitat. Though these bears were only sampled in a single year, Colorado Parks and Wildlife estimated 2011 as an average year for bear fall forage (Apker, unpublished data), suggesting that in a mast failure year, human-derived food consumption could be even higher. Previous work has found black bears consuming crops, livestock, trash, and other human-derived foods can lead to conﬂict in Colorado (Baruch-Mordo et al., 2008). Our results indicate that crop cover is not substantial in areas of bear harvests. Crop cover is also unrelated to 13 C enrichment, suggesting, at the landscape scale, human-derived food consumption is not being strongly driven by agricultural crops. Rather, we suggest that subsidies associated with human development and habitation are primarily driving bear diet. Such subsidies may include trash, planted fruit trees, and bird feeders (e.g. Baruch-Mordo et al., 2008; Beckmann and Berger, 2003a; Merkle et al., 2013). Our study is further conﬁrmation that managing human behavior to reduce availability of subsidies is paramount to reducing bear reliance on human-derived foods. Future work examining different types of human development at a ﬁner scale (e.g. housing developments as opposed to campgrounds) could also be valuable to ascertain differences in subsidy availability. It is worth noting that although our study area had little crop cover, the few areas with non-negligible crop cover also possessed high housing densities. So, while crops are not an important factor driving bear food subsidy use throughout the Colorado landscape, they may still contribute to 13C enrichment, at least in some locations. B 9 12 Animal matter Human-derived food Native vegetation Nuisance removal 6 A 0 3 8 0.0 0.2 0.4 0.6 0.8 1.0 Density 10 6 Vehicle collisions 5 15 N 15 7 0.0 0.2 0.4 0.6 0.8 1.0 30 0 5 Hunter-harvested 22 21 20 19 18 20 4 0 C 10 13 0.0 0.2 0.4 0.6 0.8 Proportion 1.0 Fig. 4. (A) Isotopic signatures of bears separated by mortality type: hunter-harvested (light gray), roadkill (medium gray), and nuisance bears (black); and (B) Assimilated dietary estimates shown as proportional density distributions for each group of bears. �R. Kirby et al. / Biological Conservation 200 (2016) 51–59 We also found a slight negative relationship between NDVI, as a measure of vegetative productivity, and 13C enrichment. This suggests that the quality of the available habitat could play a role in food subsidy use that we have not adequately captured with NDVI, which may be limited when averaged over a period of months. It is possible that we have underestimated natural forage availability as NDVI can miss some important bear foods, such as berries or insects (Wiegand et al., 2008), or over-represent conifers, which offer little forage for Colorado bears. We further found adults were more likely to be consuming food subsidies than subadults (Table 2). Males, however, were enriched in nitrogen-15, indicating higher trophic level foraging (and theoretically better forage), while females were more enriched in carbon-13. As adult male bears typically access the best food resources, our study suggests that human-derived foods may be exhibited large variation between individuals in both considered a preferred resource, which could increase the potential for conﬂicts. Complicating this situation, female consumption of high caloric food subsidies can enhance reproduction and overall increase population size (Beckmann and Lackey, 2008). Further, females that forage with their cubs in developed areas are more likely to rear cubs that prefer developed areas as adults (Mazur and Seher, 2008), creating a population that is ever more reliant on food subsidies. The large amount of anthropogenic foods consumed by eastern Colorado bears is comparable to that estimated for bears inhabiting Yosemite National Park during years of poor trash management (Hopkins et al., 2014) and when food subsidies were abundant. Human-derived food subsidies are likely abundant throughout eastern Colorado, which features more human development compared to western Colorado. Whether individuals are ﬂexible in their use of subsidies between years or become habituated to them remains in question. Previous behavioral studies on black bears in Nevada found that dependency on food subsidies was irreversible (Beckmann and Berger, 2003a), but another study in northern Colorado showed interannual ﬂexibility in subsidy use (Baruch-Mordo et al., 2014). Locations featuring more human development may constrain dietary options for bears, leading to a greater reliance on human foods. As urbanization is predicted to continue to increase throughout bear range (Bierwagen et al., 2010), the increasing dependence on food subsidies seems likely, and research such as this into patterns of consumption will be critical to mitigating human-bear conﬂicts. Bears most frequently involved in conﬂicts throughout their range tend to be subadults, particularly males (Hristienko and McDonald, 2007), or females with cubs (Rode et al., 2006). Though we found adult males in the hunter-harvested Colorado population consumed the greatest amount of food subsidies, females with cubs were likely underrepresented in our sample, as hunters are prohibited from harvesting them. Thus, we may be underestimating the amount of human foods consumed by adult females, in general. On the other hand, we also recognize that our sample of hunter-harvested bears are a subset of the population that could potentially miss the most wildland bears with less access to subsidies. We did, however, ﬁnd that even within our sample pool, δ13C in Colorado bear hair is predictive of risk of conﬂict regardless of age-sex class. As we considered only bears in GMUs that had both non-conﬂict and conﬂict mortalities, simply residing in an area of high human density did not necessarily lead to conﬂict, but increased foraging on food subsidies did. Some GMUs with high human development also feature high quality habitat for bears. Thus, regardless of whether bears were selecting for or against this habitat as measured at the GMU level (e.g. due to intraspeciﬁc competition; Elfström et al., 2014), some bears may have still avoided human-derived foods and, thus, decreased their risk. Feeding trials suggest that bears may have innate food preferences and sex-speciﬁc differences in use of novel foods, with males more likely to try unfamiliar diet items (e.g. crops), compared to females. However, after exposure to novel foods, females will eventually preferentially seek out those food sources (Ditmer et al., 2015a). Our results also suggest that such individual 57 differences in foraging preferences could predict the likelihood of conﬂict. Regardless, roadkills were enriched over hunter-harvested bears, and nuisance bears were even enriched over roadkills (Fig. 4A), indicating δ13C could be indicative of conﬂict type. This corroborates previous work indicating that nuisance bears tend to be enriched in 13C (Hobson et al., 2000; Mizukami et al., 2005). Our results suggest some individuals are certainly consuming more human-derived foods than others. Because some bears reside in developed habitats and avoid use of subsidies, a general strategy of lethal removals of urban bears (Hopkins et al., 2014; Lewis et al., 2014) may not be sustainable longterm as they will likely be replaced with other individuals. More generally, our ﬁndings corroborate the utility of δ13C as a tracer of human-derived food in temperate North American systems (Hopkins et al., 2014; Lavin et al., 2003; Newsome et al., 2010, 2015). Carbon-13 enrichment is primarily attributed to high use of corn in human foods (Jahren et al., 2006; Jahren and Kraft, 2008); the similar enrichment of 15 N in human hair is likely due to high meat consumption in North America (Schoeller et al., 1986). Traditional diet studies tend to underestimate highly digestible food such as human-derived food, and few studies have reconstructed diet using stable isotopes on such a large regional scale, because changes in forage base will affect mixing model estimates (e.g. Phillips et al., 2005). We are conﬁdent in our characterization of the potential forage mixing space, however, because surveying native plants and animals throughout the regions did not yield important regional differences (Appendix A, Table A1). In particular, vegetation in eastern Colorado was not enriched in 13C, conﬁrming that enrichment found in those bears was not inﬂated due to a difference in carbon-13 signature of vegetation. Native animals, however, were slightly enriched in 13C in southeastern Colorado, signifying a general increased use of food subsidies throughout the area. Regardless of slight isotopic differences in forage base, δ13C appears to track human food consumption well in animals throughout this altered landscape. Because of its relationship to human foods, we have primarily restricted our discussion to δ13C; however, δ15N is correlated with δ13C in this system and we found it to be similarly predictive of conﬂict bears as well as human-derived food consumption, as has been shown in other bear populations (Hopkins et al., 2012; Mizukami et al., 2005). The primary landscape variable associated with nitrogen-15 enrichment was a negative relationship with NDVI, suggesting that bears forage at a slightly lower trophic level in areas of higher productivity. Whether this relationship is driven by the correlation between δ15N and δ13C and their incorporation into tissues (Hobson et al., 2000) or by true differences in foraging is unknown. Future research could beneﬁt from combining individual level landscape selection with isotopic diet analysis to disentangle some of these remaining questions. Synanthropic species tend to show pronounced plasticity in their diet as part of their association with anthropogenic features (Luniak, 2004), but whether individuals overlap in their resource use or some specialize on human-derived foods remains unknown. We found less variability within individuals than between tissue types, suggesting that some specialize more on food subsidies. We also found similar levels of consumption throughout summer and fall, which is in contrast to increased bear use of development during the fall found by Johnson et al. (2015). This discrepancy may be due to differences in the study scales, as well as the overlap in foraging periods represented by hair and blood samples. Though we used tissue-speciﬁc discrimination factors, segmenting hair samples in future work could provide a ﬁner timescale of diet changes to compare with seasonal foraging movements. Clearly, black bears can use human food subsidies extensively, and such bears tend to have higher reproduction, shorter activity and denning, and larger body sizes (Beckmann and Berger, 2003b; Graber, 1982), which are all indicative of better forage availability. While there may be some individual specialization occurring, those consuming the most human-derived foods could be marginalized to such habitat (Elfström et al., 2014) or driven by physiological necessity (Johnson et �58 R. Kirby et al. / Biological Conservation 200 (2016) 51–59 al., 2015). Those consuming more human-derived foods within such altered habitats though are further at an increased risk of conﬂict. Though high-caloric food subsidies may enhance reproduction, the costs due to conﬂict mortality (Beckmann and Lackey, 2008), increased stress (Malcolm et al., 2014; Rode et al., 2006), and unknown effects of human “junk food” (Heiss et al., 2009), suggest that urban areas may in effect be an ecological trap, and use of food subsidies in particular may not be an adaptive strategy. As urbanization and human activity expands, this is further evidence that proper trash management to minimize human food subsidies will be essential in mitigating conﬂict. Evaluating the underlying causes of and degree to which such species as black bears are exploiting human food subsidies is a crucial component when considering human impacts on ecosystems. Acknowledgements Funding was provided by Colorado Parks and Wildlife (IGA-17562012), and an American Society of Mammalogists Grant-in-Aid. 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The role of American black bears and brown bears as predators on ungulates in North America. Ursus 17, 95–108. � https://cpw.cvlcollections.org/files/original/074a07ff49e0baf9d72b8e1f9364f8be.pdf 91f4a4b36fd44818dd51f0ccf369018a PDF Text Text SUPPORTING INFORMATION The diet of black bears tracks the human footprint across a rapidly developing landscape Rebecca Kirby*, Mathew W. Alldredge, Jonathan N. Pauli *Corresponding author. Tel: +1 (608) 215 2203; fax: +1 (608) 262 9922. Email address: rebeccakirby@wisc.edu. Table A1. Stable isotope signatures of potential diet sources collected throughout Colorado in 2012, grouped by region and broad diet category. Different superscripts denote significance of K nearest-neighbor randomization at P < 0.05. δ13C (‰) Diet Groups n Northeast δ15N (‰) Mean SD Mean SD 139 Berries 40 -27.60 1.63 0.64 2.48 Herbaceous 36 -28.84 1.18 -0.08 2.96 Insects 13 -23.32 0.94 3.46 2.69 Ungulates 39 -24.10 0.68 4.35 1.45 Rabbits 11 -25.26 1.30 2.15 2.57 Berries 28 -27.18 1.40 2.12 1.98 Hard Mast 1 -26.70 Herbaceous 37 -27.46 1.33 0.91 2.54 Insects 7 -23.27 0.60 4.35 1.89 Ungulates 2 -24.66 1.36 4.13 0.01 Berries 11 -26.37 0.86 2.29 2.54 Herbaceous 38 -27.82 1.58 1.61 1.92 Insects 9 -22.56 1.43 5.37 1.36 Rabbits 2 -23.02 0.82 6.42 1.45 Berries 27 -26.45 1.34 1.98 2.05 Hard Mast 12 -26.83 1.35 2.75 2.87 Northwest 75 Southeast 3.95 60 Southwest 129 �Herbaceous 57 -26.93 1.43 0.29 1.49 Insects 14 -22.95 1.48 5.54 1.38 Ungulates 15 -24.03 0.50 5.01 1.13 Rabbits 4 -24.40 0.96 3.18 1.53 δ13C (‰) δ15N(‰) Diet Groups Region Mean SD Mean SD Animal matter NEa -24.17 1.03 3.71 2.05 (insects, ungulates, NWab -23.58 0.94 4.30 1.64 rabbits) SEb -22.64 1.32 5.56 1.37 SWab -23.62 1.20 5.01 1.45 Native vegetation NEa -28.19 1.56 0.30 2.72 (berries, hard mast, NWab -27.33 1.35 1.47 2.38 herbaceous plants) SEab -27.49 1.57 1.76 2.07 SWb -26.78 1.40 1.07 2.09 �Figure A1. Spline correlogram run with 1,000 permutations on δ13C global model residuals, testing for spatial autocorrelation (bear harvest locations), shown with 95% confidence intervals. Though some correlation was detected at the smaller distances, it was not sufficient to warrant additional analyses (Bjørnstad and Falck, 2001). � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal Articles Description An account of the resource CPW peer-reviewed journal publications Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The diet of black bears tracks the human footprint across a rapidly developing landscape Description An account of the resource Food subsidies have become a widely available and predictable resource in human-modified landscapes for many <a href="https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/vertebrates" title="Learn more about Vertebrates from ScienceDirect's AI-generated Topic Pages" class="topic-link">vertebrate</a> species. Such resources can alter individual <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/foraging-behavior" title="Learn more about Foraging Behavior from ScienceDirect's AI-generated Topic Pages" class="topic-link">foraging behavior</a> of animals, and induce population-wide changes. Yet, little consensus exists about the relative influence of the availabilities of native and human food subsidies to wildlife foraging throughout altered landscapes. We explored this unresolved question by analyzing the effects of landscape factors on <a href="https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/american-black-bear" title="Learn more about American Black Bear from ScienceDirect's AI-generated Topic Pages" class="topic-link">American black bear</a> (Ursus americanus) diet across the state of Colorado, USA. We estimated assimilated diet using <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/stable-isotope" title="Learn more about Stable Isotope from ScienceDirect's AI-generated Topic Pages" class="topic-link">stable isotope</a> analysis of harvested black bear tissues to determine the contribution of human-derived foods to bear diets throughout Colorado, as well as how increasing reliance on human-derived food subsidies increases the risk of conflict. We found that bears (n = 296) showed strong regional diet variability, but substantial use of human-derived food subsidies in eastern Colorado (> 30% assimilated diet). The age-sex class of the bear and housing density of its harvest location were the most influential predictors of 13C enrichment (a tracer of human food subsidies). Furthermore, foraging on subsidies increased risk of conflict; the odds of being a nuisance bear increased by 60% for each ~ 1‰ increase in δ13C. Our study confirms the efficacy of δ13C as a proxy for human activity, and indicates that while demographic differences play a clear role in the foraging ecology of bears, availability of subsidies coincident with varying levels of human activity appears to be a major driver in predicting black bear diet throughout the western United States. Bibliographic Citation A bibliographic reference for the resource. Recommended practice is to include sufficient bibliographic detail to identify the resource as unambiguously as possible. Kirby, R., M. W. Alldredge, and J. N. Pauli. 2016. The diet of black bears tracks the human footprint across a rapidly developing landscape. Biological Conservation 200:51–59. <a href="https://doi.org/10.1016/j.biocon.2016.05.012" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.biocon.2016.05.012</a> Creator An entity primarily responsible for making the resource Kirby, Rebecca Alldredge, Mathew W. Pauli, Jonathan N. Subject The topic of the resource Foraging Human-wildlife conflict Resource subsidies Stable isotopes Ursus americanus Extent The size or duration of the resource. 9 pages Date Created Date of creation of the resource. 2016-08 Rights Information about rights held in and over the resource <a href="http://rightsstatements.org/vocab/InC-NC/1.0/" target="_blank" rel="noreferrer noopener">In Copyright - Non-Commercial Use Permitted</a> Format The file format, physical medium, or dimensions of the resource application/pdf Language A language of the resource English Is Part Of A related resource in which the described resource is physically or logically included. Biological Conservation Type The nature or genre of the resource Article