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Early-Successional Breeding Bird Communities in Intensively Managed Pine Plantations: Influence of Vegetation Succession but Not Site Preparations
Falyn L. Owens, Philip C Stouffer, Michael J. Chamberlain, and Darren A. Miller

Southeastern Naturalist, Volume 13, Issue 3 (2014): 423–443

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Southeastern Naturalist 423 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 22001144 SOUTHEASTERN NATURALIST 1V3o(3l.) :1432,3 N–4o4. 33 Early-Successional Breeding Bird Communities in Intensively Managed Pine Plantations: Influence of Vegetation Succession but Not Site Preparations Falyn L. Owens1, Philip C Stouffer1,*, Michael J. Chamberlain1, 2, and Darren A. Miller3 Abstract - Birds that require early-successional habitat are declining in North America due to habitat loss. Their increasing reliance on anthropogenic landscapes, such as the extensive Pinus spp. (pine) plantations of the southeastern US, makes it important to assess how management alternatives within these forests influence habitat quality. We examined how 2 site preparation variables, tree row spacing (4.3 m vs. 6.1 m) and arrangement of post-harvest woody debris (piled vs. scattered), influenced species richness, abundance, and breeding activity of disturbance-dependent (early-successional) birds. We studied bird communities and vegetation structure during the first 5 years of growth on replicated plots in 4 intensively managed Pinus taeda (Loblolly Pine ) plantations in Louisiana. We used model selection to determine which site-preparation and vegetation characteristics most influenced avian communities. All measures of bird communities responded positively as vegetation structure and cover increased over time. However, neither row spacing nor debris placement affected vegetation variables important to birds for at least for the first 5 years following stand establishment; bird communities responded to successional changes and variation among plots, but not to site preparation. Land managers seeking to provide early-successional habitat in recently established plantations for disturbance-dependent birds can do so by increasing structural complexity and groundcover through selective herbicide applications, mechanical treatments, or other means. Introduction Birds that live exclusively in early-successional landscapes are among the most threatened avian habitat specialists in North America. Fifty-six percent of grassland species, 39% of shrub-scrub species, and 33% of savannah species have experienced significant declines in the last 45 years (Brawn et al. 2001, North American Bird Conservation Initiative 2009). As of 2011, breeding bird survey data from the US and Canada show declining population trends for 44% of successional or scrub-breeding species, with increases for only 9% of these 160 species (Sauer et al. 2013). Historically, these species preferred habitat conditions perpetuated with regular burning via natural and anthropogenic origins, which prevented encroachment of woody vegetation and maintained habitat structure in a sub-climactic successional state. Today, those habitat types have been drastically reduced by 1School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA, 70803. 2Current address - Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602. 3Southern Timberlands Technology, Weyerhaeuser Company, Columbus, MS, 39704.*Corresponding author - pstouffer@lsu.edu. Manuscript Editor: Paul Leberg Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 424 spread of human-dominated landscapes, fire suppression, and lack of active timber harvest (Beissinger et al. 2000, North American Bird Conservation Initiative 2009, Trani et al. 2001; see Twedt et al. 1999 for a summary of trends in the Mississippi Alluvial Valley). Young, intensively managed Pinus spp. (pine) plantations provide habitat conditions that can support more birds than historically disturbed landscapes (Brawn et al. 2001, DeGraaf 1991, Dickson et al. 1995, Keller et al. 2003, Thompson et al. 1993). Where timber is an important industry, pine plantations can provide a significant amount of disturbed habitat. In the southeastern US, pine plantations account for 20% of forest cover, with Pinus taeda L. (Loblolly Pine) plantations covering 13.4 million ha (Schultz 1997, US Forest Service 2008). The economic value of plantations helps prevent land conversion to more intensive anthropogenic uses, making them important refugia for disturbancedependent birds (Brawn et al. 2001, North American Bird Conservation Initiative 2009). Timber managers’ decisions about how they manage their forests, including row spacing and handling of coarse woody debris (CWD), affect timber production, production costs, and value for wildlife. To understand and improve bird resources in intensively managed timberlands, experimental studies are required to determine influences of different management practices, how they interact to affect birds, and how these patterns change by geographic region (Brawn et al. 2001, Hanberry et al. 2012, Kilgo et al. 2000, Miller et al. 2009). Research has shown that sites where CWD is left after timber harvest support as much as 45% more bird species at 50% higher densities compared to stands where debris is shredded or removed (Horn 2000; Jones et al. 2009a, b; Lohr et al. 2002). If woody debris remains on-site, timber managers have the choice of spreading it between newly planted rows or creating debris piles; this decision may also influence habitat quality for birds. Similarly, row spacing in planted stands may affect habitat quality for birds. Weyerhaeuser Company, one of the largest industrial landowners in the southeastern US, recently switched row spacing from 4.3 m to 6.1 m. In Georgia, Lane et al. (2011) found that wider spacing between rows (6.1 m vs. 3.0 m) improved species richness and abundance, but the study confounded row spacing with debris management; data are limited relative to tree spacing and avian habitat quality. Therefore, we examined how breeding bird communities responded to both row spacing (4.3 m vs. 6.1 m) and woody debris placement (piled vs. scattered) treatments in regenerating Loblolly Pine plantations in Louisiana. Vegetation structure and diversity have been examined on the same plots where we studied birds; neither plant diversity nor species richness was influenced by debris placement or row spacing (Grace et al. 2011). Our specific research objectives were to: (1) evaluate debris placement and rowspacing effects on breeding bird species richness, abundance, and breeding activity during the first 5 years after stand establishment; (2) investigate the influence of changing vegetation composition and structure on breeding bird communities during the 5 years following stand establishment; (3) identify vegetation response to site preparation, which may represent indirect influences of preparation treatments Southeastern Naturalist 425 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 on breeding bird communities; and (4) recommend which combination of row spacing and debris placement provides the most benefit to early-successional breeding bird communities. Methods Site characteristics and experimental design We conducted our study in Louisiana on 4 sites owned and managed by Weyerhaeuser Company (hereafter Weyerhaeuser), the largest industrial landowner in that state. Two sites were in the north-central part of the state, in Winn (site A) and Jackson (site B) parishes, and 2 were in southeastern Louisiana, in Tangipahoa (site C) and Washington (site D) parishes (figure 1 in Owens 2011). Weyerhaeuser managed these sites for production of Loblolly Pine saw-timber. We established our study plots following standard industry practices (D.A. Miller, pers. observ.). Typical silviculture on this area included clearcut harvest at approximately 27–32 years of age, followed by site preparation and planting (~1100 trees/ha), vegetation management, a commercial thinning (target reduction to ~309 trees/ha), pruning, and fertilization. The study plots at each site were established within a single large clearcut, which in turn was embedded within a much larger area of managed Loblolly Pine forest. Small portions of most sites were designated streamside management zones (SMZs), where undisturbed forested vegetation, primarily mature hardwood stands, bordered watercourses. Sites shared similar annual precipitation, temperature, elevation, and soil characteristics; soil drainage ranged from poorly (site C) to well-drained (site D) (Natural Resources Conservation Service 2009, Owens 2011). Following harvest, sites were prepared for planting with a combination of mechanical and chemical treatments tailored to achieve successful regeneration at each site as per Weyerhaeuser standard procedures. After site preparation, trees were planted during winter 2005–2006. To allow us to examine effects of alternative industry choices for row spacing and debris treatments, managers established experimental stands in a randomized block design to compare all combinations of woody debris placement (piled or scattered) and row spacing (4.3 m vs. 6.1 m) in four 10-ha plots at each of the 4 sites (Fig. 1). In piled plots, plantation managers mechanically raked debris into 5 large piles (mean ± SE: 21.7 m ± 11.2 m x 17.2 m ± 5.0 m x 3.6 m ± 0.8 m [Bechard 2008]), which they placed in the center and near the corners of the plots. Scattered sections had woody debris distributed between rows throughout the plot; the rows of trees were elevated onto soil beds to reduce inundation of seedlings and prepare a good planting substrate. To temporarily reduce competing vegetation, all sites received a combination banded application (i.e., herbicide only applied to beds of planted tress) of the herbicides Arsenal® AC (4 oz/ac, BASF Corp. Research Triangle Park, NC) and Oust Extra® (2.5 oz/ac, DuPont™ Crop Protection, Wilmington, DE). Vegetation sampling We collected vegetation data during the peak growing season (mid-July) in 2006, 2007, 2009, and 2010. In each 10-ha plot, we established five 10-m-radius Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 426 circular vegetation plots, equally spaced so that they extended diagonally across the entire length of the 10-ha plot. When necessary, we adjusted plot placement to avoid debris piles. Stem-count data consisted of total live softwood and hardwood stems within the plot, excluding stems shorter than 1 m. We measured percent cover in five 1-m2 subsamples using a Daubenmire frame (Daubenmire 1959), and categorized vegetation as either fern, Ilex vomitoria Aiton (Yaupon), forb, vine, woody, grass, debris, or bare ground. Due to layering of vegetation, total percent cover exceeded 100%. Yaupon received its own category because of its prevalence and uniquely dense structure. We recorded maximum vegetation height (m), average height (m), and vertical obstruction by reading a centrally placed, 1.5-m Robel pole from 10 m away in each cardinal direction (Robel et al. 1970). We obtained 13 different measures of composition and structure on 80 vegetation plots each year. To simplify analyses, we averaged measurements to the vegetation-plot level, yielding 40 observations per individual treatment per year (or 20 observations per treatment combination per year). Avian community sampling We surveyed breeding bird communities for 4 breeding seasons. We initially surveyed the northernmost sites (A and B) during 2006 directly following plantation establishment. We surveyed all sites in 2007, 2009, and 2010. We surveyed plots 5 times each year between late April and early June, during the peak of breeding activity, with gaps of at least 10 days between surveys to increase temporal independence in our data. We did not survey on rainy, windy, or heavily overcast days (following Hamel et al. 1996). Figure 1. Factorial arrangement of row spacing (4.3 m or 6.1 m) and debris placement (scattered or piled) on plots in four Loblolly Pine stands established in 2005 in Louisiana. Circles represent locations of debris piles on piled plots and avian survey-points on all plots. Orientation of plots in relation to one another is not necessarily accurate because plot position was influenced by SMZs and roads. Southeastern Naturalist 427 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 Avian surveys consisted of point counts followed by extended searches. We designated 5 point-count locations per plot, corresponding to the center of the plot and 4 corners (Fig. 1). For piled treatment plots, we shifted survey locations the minimum distance necessary to provide acceptable visibility around debris piles. To increase sample independence and reduce edge effects, we placed survey locations ≥75 m apart and ≥50 m from plot edges. We based survey procedures on Hamel et al. (1996), as adapted by the Lower Mississippi Valley Joint Venture (2004). At each location, during 10-min observation periods, observers noted species, age, sex, distance and direction from sampling points, and any behaviors indicative of breeding, such as males defending territory or birds carrying nesting material. We sampled from 15 min before sunrise until 0900 CDT. We temporally stratified sampling by reversing survey order for each visit. After completing point counts each morning, observers conducted extended searches, revisiting each plot for 1 hour to look for additional evidence of breeding activity. Extended searches typically finished before 1100 CDT. We calculated 3 metrics indicative of habitat quality for breeding birds: species richness, abundance, and breeding activity. We excluded non-breeding winter residents, passage migrants, flyovers, and species with territories larger than a single plot, such as raptors. We also excluded birds primarily residing in SMZs; these species were forest interior and edge specialists that were not present in plots without SMZs. We calculated species richness as number of unique species observed over all point counts and extended searches in a given year for each plot. We accounted for variation in detectability among species by adjusting raw species richness with the program SPECRICH2, which estimates number of species present even if not all are detected, assuming that individual species vary in detectability (Hines 1996, White et al. 1978). For abundance, we determined mean number of individuals per species per survey. We assumed that on some days we did not detect all individuals in a plot and sometimes we detected more individuals than actually used the plots all season (during territory establishment). Therefore, we reported mean abundance to account for this variation. We summed mean abundances over all detected species, yielding total abundance per plot per year. It is important to note that abundance values were valid only relative to each other and should not be used as absolute measures in comparisons outside this study (MacKenzie and Kenda ll 2002). We included a measure of breeding activity in our analyses to address the potential problem of birds using plots without breeding (Brawn et al. 2001, Van Horne 1983). We used an index modified from Vickery et al. (1992) that assigns scores to breeding territories based on strength of evidence that young have successfully fledged from them (Table 1). We gave partial scores to territories with males present for as few as 2 weeks to account for territories that may have been active, but undetected, for a longer period. This method is limited to non-cryptic species whose young are altricial, and whose breeding behaviors are relatively detectable (Rangen et al. 2000, Rivers et al. 2003). For this reason, we excluded Colinus virginianus (L.) (Northern Bobwhite ) and Archilochus colubris (L.) (Ruby-throated Hummingbird) Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 428 from breeding-activity measures. We also excluded the brood parasite Molothrus ater (Boddaert) (Brown-headed Cowbird). The final score for each territory was the greatest evidence from that territory over a season, and the final score for each plot was the sum of territory scores for all species with territories in the plot that year. Statistical analysis We used principal component analysis (PCA) to reduce correlation in the 13 vegetation metrics, employing Cattell’s scree test and the Kaiser-Guttman criterion to identify and retain components that explained the most variance and were most biologically meaningful (PROC FACTOR; Jackson 1993, SAS 2008). We used VARIMAX rotation to increase interpretability of retained components and primarily considered correlations >|0.35| when determining their meaning. Grace et al. (2011) conducted a similar analysis of the vegetation data, but our analysis also included pine stem counts to account for variation in pine seedling survival in the face of insignificant treatment effects of row spacing (Grace et al. 201 1). We used analyses of variance (ANOVA) with repeated measures to test the null hypothesis that avian community metrics, vegetation components, and breeding activity for select species designated by the USFWS (2008) as being of conservation concern (2009 and 2010 only) did not differ among row spacing and debris-distribution treatments. Predictor variables were row spacing, debris placement, and their interaction (fixed), with site as the blocked random effect and year as the repeated measure (PROC MIXED; SAS 2008). We specified autoregressive covariance and the Kenward-Rogers adjustment for degrees of freedom (Kenward and Roger 1997, Kowalchuk et al. 2004). We obtained parameter estimates using maximum likelihood estimation and used Tukey-adjusted P-values. We assessed normality by examining skewness, kurtosis, normal probability plots, and Shapiro- Wilk test results, transforming data when necessary to meet normality assumptions. We also tested response of bird communities and vegetation to year alone, using similar specifications but no repeated measures. To describe patterns in bird-community data, we first examined yearly and overall correlations among the three community metrics. We then used AIC-based model selection for 14 candidate models that included debris-placement treatment, vegetation components, and their interactions in combinations that could be biologically meaningful (Table 2; Burnham and Anderson 2002). We reasoned that Table 1. Breeding-activity ranks, modified from Vickery et al. (1992). Territorial refers to males who sing, monitor a distinct area, or act aggressively toward other males. Score Breeding behavior 0.33 Territorial male present 2 weeks 0.66 Territorial male present 3 weeks 1 Territorial male present 4+ weeks 2 Territorial male and female present 4+ weeks 3 Adults with nesting material, laying or incubating eggs, or diverting attention from nest 4 Adults carrying food or fecal sacs 5 Juveniles present Southeastern Naturalist 429 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 row spacing was represented by proxy in the vegetation data (pine stem counts); this variable was also uninformative in a prior analysis of vegetation diversity on these plots (Grace et al. 2011), so we excluded it from all models. With individual avian community measures specified as response variables, we tested each model as analyses of covariance (ANCOVA) with repeated measures (PROC MIXED; SAS 2008). We evaluated global models using the chi-square goodness-of-fit statistic. Using these ANCOVA models, we considered bird-community responses to debris placement and vegetation components from best-fit models (lowest AICC) and competitive models (ΔAICC < 4) (Burnham and Anderson 2002). Results Vegetation summary We detected 124 separate plant taxa (genera or species) in vegetation sampling plots. Although Loblolly Pine was the only softwood species, sites hosted an array of hardwoods, including natives Liquidambar styraciflua L. (Sweetgum), Sassafras albidum (Nuttall) (Sassafras), Acer rubrum L. (Red Maple), Yaupon, Rhus copallina L. (Winged Sumac), and Quercus spp. (oaks), and the non-natives Ligustrum sinense Lour. (Chinese Privet) and Triadica sebifera (L.) Small (Chinese Tallow). A patchy shrub layer was dominated by Callicarpa americana L. (American Beautyberry), Baccharis halimifolia L. (Eastern Baccharis), and Cyrilla racemiflora L. (Swamp Titi), interwoven with abundant canes of Rubus spp. (blackberries) and some Smilax spp. (greenbriers). Dominant grasses belonged to genera Andropogon and Schizachyrium spp. (bluestem grasses); Solidago spp. (goldenrods), Eupatorium spp. (Joe-pye weeds), Ambrosia spp. (ragweeds), and Aster spp. (asters) were Table 2. Set of candidate models used in AIC-based model selection to determine the response of breeding avian communities to debris placement and vegetation characteristics in four young Loblolly Pine stands in 2006, 2007, 2009, and 2010 in Louisiana. Variables include debris placement and 3 principal components describing vegetation structure (Table 3). Variables Vegetation Evergreen Groundcover Model Debris (D) structure (S) cover (E) (G) Interactions GLOBAL D S E G D*S D*E S*E D S E G D S E D S D*S D S D E D*E D E S E G S*E S E G S E S*E S E S E NULL Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 430 the most common forbs. Differences in soil drainage among sites were reflected in species composition—the wettest site (C) was dominated by lowland hardwood and freshwater marsh species (Nyssa spp. and Saururus cernuus L. [Lizard’s Tail]) and the driest site (D) was characterized by species associated with upland areas (Yaupon and bluestem grasses). Principal component analysis of the 13 vegetation measures (pine and hardwood stem counts, percent groundcover categories, and height measures) yielded 3 composite variables that satisfied retention requirements. We interpreted them as overall vegetation structure, evergreen cover, and groundcover (Table 3). Vegetation structure (Eigenvalue = 4.55) represented a gradient between bare ground and tall, dense vegetation, mostly encompassing the variation in hardwoods. Evergreen cover (Eigenvalue = 1.74) represented a gradient in cover between the 2 evergreen species, Loblolly Pine and Yaupon. Groundcover (Eigenvalue = 1.17) represented a gradient between bare or debris-covered ground and dense grass cover. Although this component accounted for relatively little variance, we retained it for analysis because it was the only metric that notably changed directionality through time, representing the shift from bare ground in 2006 to grassy cover in 2007, and then back to bare ground as woody species shaded out herbaceous growth in the final years of our study (Figs. 2, 3). Overall, year was a significant predictor for vegetation structure (F3, 53 = 12.88, P < 0.001), evergreen cover (F3, 52.5 = 76.04, P < 0.001), and groundcover (F3, 52.7 = 14.01, P < 0.001). When we tested the influence of site preparation on vegetation, we found that none of the vegetation metrics varied with debris placement (F1, 12.3–12.6 < 0.59, P > 0.46), row spacing (F1, 12.3–12.6 < 1.74, P > 0.21), or their interaction (F1, 12.3–12.6 < 0.33, P > 0.58). Avian community response We detected 56 bird species, from which we identified 14 (25%) as disturbance- dependent species based upon their classification as dependent upon Table 3. Correlations between retained principal components and original vegetation measurements. A indicates vegetation characteristics that are highly correlated (P > 0.35) with a component. Vegetation metric PC1-Vegetation structure PC2-Evergreen cover PC3-Groundcover Pine stem count 0.20 0.81A 0.00 Hardwood stem count 0.64A 0.50A -0.50* % cover fern 0.19 -0.10 -0.17 % cover Yaupon 0.30 0.78A -0.20 % cover forb 0.18 0.34 0.24 % cover vine 0.49A 0.32 -0.12 % cover woody 0.76A -0.20 -0.90A % cover grass -0.60A -0.11 0.86A % cover debris -0.60* -0.26 -0.63* % cover bare ground -0.54* 0.18 -0.61* Minimum height 0.74* 0.48* 0.16 Maximum height 0.70* 0.43* 0.33 Average height 0.82* 0.17 0.30 Total variance explained 35.00% 13.40% 9.00% Southeastern Naturalist 431 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 grassland, savanna, shrubland, shrubland, or generalized shrub habitats by Askins (1993) (see Appendix A). The remaining species were habitat generalists, passage migrants, or late-departing winter residents, or primarily occupied SMZs. Of the disturbance-dependent breeders, 71% (n = 10) displayed reproductive activity. We detected 6 species designated as species of conservation concern in the region they were detected (USFWS 2008), including 4 disturbance-dependent species as well as Sitta pusilla Latham (Brown-headed Nuthatch) and Icterus spurius (L.) (Orchard Oriole). The 4 most common species, accounting for 42% of all detections, were disturbance- dependent: Icteria virens (L.) (Yellow-breasted Chat ), Passerina cyanea (L.) (Indigo Bunting), Setophaga discolor (Vieillot) (Prairie Warbler ), and Passerina caerulea (L.) (Blue Grosbeak). In addition to the disturbance-dependent species, we irregularly detected some species associated with more developed forest, such as Poecile carolinensis (Audubon) (Carolina Chickadee), Cyanositta cristata (L.) (Blue Jay), and Baeolophus bicolor (L.) (Tufted Titmouse). As expected, species composition changed as stands matured, with ground-foraging specialists such as Spizella passerina (Bechstein) (Chipping Sparrow) using plots only in the initial 2 years, and shrub-nesting species like Yellow-breasted Chat Figure 2. Changes in vegetation structure through time. Lower and upper box edges represent 25th and 75th percentiles; whiskers represent 10th and 90th percentiles. Lines bisecting boxes represent medians and points signify outliers. Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 432 Figure 3. Changes in evergreen cover and groundcover through time. Lower and upper box edges represent 25th and 75th percentiles; whiskers represent 10th and 90th percentiles. Lines bisecting boxes represent medians and points signify outliers. Southeastern Naturalist 433 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 and Prairie Warbler appearing later (see Appendix A). Often, species that accounted for a large percentage of detections in the first years, such as Carolina Wren and Cardinalis cardinalis (L.) (Northern Cardinal), remained present in comparable numbers, but declined in proportional presence as species richness and overall abundance increased through time. Indigo Bunting was unique in maintaining high relative abundance through all 4 years; it was the most frequently detected species in 2006 and 2007, and second only to Yellow-breasted Chat in 2009 and 2010. For all years and plots combined, the three avian community metrics were strongly correlated (Spearman r2 > 0.41, P < 0.001). For individual years, however, the relationships among the metrics were less clear, with no significant correlations in the first or second years (Spearman r2 < 0.27, P > 0.09). By the third year, breeding score and abundance approached a significant correlation (Spearman r2 = 0.23, P = 0.051). By year four, estimated species richness and abundance, and abundance and breeding score were at least weakly correlated (Spearman r2 = 0.19, P < 0.085). Overall, avian community metrics increased through time, with significant variation among years for estimated species richness (Figs. 4, 5; F3, 53.4 = 10.9, P < 0.001), abundance (F3, 52.3 = 71.6, P < 0.001), and breeding activity (F3, 52.3 = 81.1, P < 0.001). Avian communities did not differ based on debris placement (F1, 15.3–17 < 1.15, P > 0.30), row spacing (F1, 15.3–17 < 0.01, P > 0.93), or their interaction (F1, 15.3–17 < 1.7, P > 0.21). We had enough data (>20 total detections) to individually test two species of conservation concern, neither of which showed a response to these factors: Prairie Warbler (F1, 12 < 0.53, P > 0.48) and Yellowbreasted Chat (F1, 16 < 3.61, P > 0.08). Figure 4. Estimated number of species per plot in young Loblolly Pine plantations in Louisiana. Years represent first (2006), second (2007), fourth (2009), and fifth (2010) breeding seasons (late April–early June) post-planting. Error bars represent standard error. Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 434 Top models for all bird-community metrics included vegetative structure and evergreen cover (Table 4). Upon examination of model estimates, we found that species richness, abundance, and breeding score were positively correlated with these two measures of vegetation (Table 5). As vegetation became taller, denser, Figure 5. Abundance and breeding score per plot in young Loblolly Pine plantations in Louisiana. Years represent first (2006), second (2007), fourth (2009), and fifth (2010) breeding seasons (late April–early June) post-planting. Error bars represent standard error. Southeastern Naturalist 435 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 and more heterogeneous, there was an overall increase in all of our measures of breeding bird use. In addition, groundcover was influential for all community metrics except species richness. Although number of species per plot was not positively correlated with grass cover, more grass cover supported more individuals and more breeding activity, a logical trend because all of the targeted species use herbaceous stems for nest building. Discussion We found no evidence that avian community response varied between 4.3 m and 6.1-m row spacing, or between piled and scattered debris. Likewise, vegetation structure and composition, the primary cues for birds searching for breeding territories, were not influenced by row spacing or debris placement (see also Grace et al. 2011). Although the evergreen structure component was important for birds and included pine stems, which should be reflective of row spacing, there was no relationship between row-spacing treatment and this component (Owens 2011). Stand age was important to birds through its effect on vegetation structure, a pattern consistent with other studies (DeGraaf 1991, Keller et al. 2003, Lane 2010, Lane et al. 2011). Successional change appeared to be particularly important for facilitating breeding because breeding scores, a measure of overall breeding activity on the plots, Table 4. Model-selection results comparing analyses of covariance (ANCOVA), which test response of avian species richness, abundance, and breeding activity to debris placement and 3 vegetation characteristics. L represents likelihood. S, E, and G represent composite variables vegetation structure, evergreen cover, and groundcover, respectively (see Table 3). D refers to debris placement, and * indicates an interaction between two variables. Only competitive (ΔAICC < 4), global, and null models are shown (see Owens [2011] for results of all models). The global model is defined as D S E G D*S D*E S*E. Response variable/model AICC ΔAICC L Weight K -2logL Species richness SE 47.89 0.0 1.000 0.365 3 34.14 SEG 49.07 1.2 0.549 0.200 4 32.69 SES*E 49.35 1.5 0.472 0.172 4 32.97 DSE 50.38 2.5 0.287 0.105 5 33.99 SEG S*E 50.92 3.0 0.223 0.081 5 31.79 DSEG 51.46 3.6 0.165 0.060 6 32.32 GLOBAL 57.15 9.3 0.010 0.004 11 29.01 NULL 67.97 20.1 0.000 0.000 1 59.17 Abundance SEGS*E 147.46 0.0 1.000 0.912 5 128.39 GLOBAL 154.25 6.8 0.033 0.030 11 126.25 NULL 198.60 51.1 0.000 0.000 1 189.82 Breeding score SEG 431.97 0 1.000 0.442 4 415.63 SEGS*E 432.48 0.5 0.779 0.344 5 413.42 D S E G 434.54 2.6 0.273 0.121 6 415.48 GLOBAL 440.47 8.5 0.014 0.006 11 412.47 NULL 506.72 74.8 0.000 0.000 1 500.26 Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 436 steadily increased over the years of the study, ultimately reaching about 15 times the activity in 2010 as in 2006 (Fig. 5). Species richness of potential breeders increased more modestly, approximately doubling in the same interval. Species composition during the first 5 years after stand establishment was characterized more by addition of species than by replacements. This trend has been observed previously in young, regenerating forest stands, where loss of earlysuccessional bird species did not occur until canopy closure, sometime between the 5th and 10th year of growth (Keller et al. 2003, LeGrand et al. 2007). By the end of our study, we saw increased abundance of some closed-canopy forest species, such as Carolina Chickadee and Tufted Titmouse, and a decline in some early-successional species, such as Eastern Bluebird (Sialia sialis [L.])] and Eastern Kingbird (Tyrannus tyrannus [L.]), probably indicating the beginning of a shift toward closed-canopy forest species as canopy and understory developed. By 7–10 years after planting, we would expect stands with narrow row-spacing to support closedcanopy species such as Limnothlypis swainsonii (Audubon) (Swainson’s Warbler; Bassett-Touchell and Stouffer 2006). Our study focused on community-level trends, but it is important to note that the efficacy of grouping entire communities of species, especially when making management recommendations, has its limitations. Individual species belonging to these communities differ in preferred foraging substrate, preferred nesting substrate, and level of specialization—variation that can go undetected when community-level metrics are employed. Land managers require information that enables them to provide habitat conditions for multiple species, but when particular species are of interest, species-level studies help tailor management strategies to their particular habitat needs. Our findings suggest that managing for early-successional species may effectively provide habitat for some species of conservation concern. Table 5. Analysis of covariance results for models that best explain the response of bird community measures to debris placement and vegetation characteristics, as determined via model selection. Tests on species richness and abundance used square root transformed data. Response variable/predictor variable Estimate SE df t P Species richness Intercept 7.56 0.006 3.8 35.71 less than 0.001 Vegetation structure 0.05 0.004 39.7 3.52 0.001 Evergreen cover 0.03 0.003 50.3 3.69 less than 0.001 Abundance Intercept 32.89 0.124 3.9 16.31 less than 0.001 Vegetation structure 0.86 0.018 42.5 6.90 less than 0.001 Evergreen cover 0.48 0.012 47.6 6.25 less than 0.001 Vegetation structure*Evergreen Cover 0.36 0.035 52.0 -3.19 0.002 Groundcover 0.36 0.034 54.0 3.27 0.002 Breeding Score Intercept 29.96 2.008 4.1 14.92 less than 0.001 Vegetation structure 13.01 1.960 47.7 6.64 less than 0.001 Evergreen Cover 16.22 1.563 53.7 10.38 less than 0.001 Groundcover 6.49 2.471 52.8 2.63 0.011 Southeastern Naturalist 437 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 However, this does not necessarily reduce importance of attending to variation on the species or guild level. Because the row spacing and debris treatments we studied did not affect birds, we recommend that managers of intensively managed pine forests in the southeastern US implement the combination of row spacing and debris placement that best meets timber management objectives. However, the wider row spacing examined in this study may be favorable for disturbance-dependent birds in other settings. For example, Lane et al. (2011) found that birds benefited from 6.1-m row spacing (one of the widths in our study) versus 3.0-m rows (a spacing common in industrial plantations, but narrower than those tested in our study) in North Carolina Loblolly Pine plantations, although these results were confounded with CWD management. Additionally, wider rows increase the time until pinecanopy closure occurs, potentially extending the longevity of beneficial habitat conditions for early-successional bird species. Because disturbance-dependent birds responded to general structure, evergreen cover, and groundcover, site preparation and stand establishment methods that positively influence these vegetation characteristics may prove more beneficial to birds than row spacing per se. Timberland managers already work toward maximizing growth of target tree species, concurrently speeding development of structure and cover for birds. Similarly, past research has indicated that increased herbaceous groundcover is often a consequence of vegetation control during stand establishment (e.g., Chamberlain and Miller 2006, Jones et al. 2009a, Miller et al. 2009). Once plantations develop woody structure between planted pine rows, selective herbicides used to control hardwoods (e.g., imazapyr) can extend the window of time that herbaceous vegetation dominates the site (e.g., Welch et al. 2004). We note that this study did not encompass the entire early-successional phase on our experimental plots. As species turnover in the bird community occurs over time and forest specialists begin to replace early-successional species, community responses to row spacing and debris arrangements may appear. For example as mentioned above, wider row spacing may affect timing of canopy closure, extending the early-successional phase of stands. Clearly, there are research needs and opportunities regarding early-successional bird use of intensively managed pine plantations. Acknowledgments Thanks go to M.D. Kaller for providing statistical advice. We acknowledge the work of A.T. Salisbury (LSU) and C. Reynolds (Weyerhaeuser) during preliminary years of the study. We thank J. Nehlig at Lee Memorial Forest, Franklinton, LA, and J. Johnson at Jackson Bienville Wildlife Management Area, Quitman, LA, for offering lodging during data collection. L.M. Palasz, M.E. Brooks, K.S. Mokross, L.L. Powell, C.M. Leumas, E.E. DeLeon, J.D. Wolfe, J.L. Grace, I.T. Knowles, and J.A. Trienekens provided essential help in the field. Paul Leberg and two anonymous reviewers made helpful suggestions that improved the manuscript. Funding was provided by Weyerhaeuser Company. This manuscript was approved for publication by the Director of the Louisiana Agricultural Experimental Station as manuscript number 2014-241-15529. Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 438 Literature Cited Askins, R.A. 1993. Population trends in grassland, shrubland, and forest birds in eastern North America. Current Ornithology 11:1–34. Bassett-Touchell, C.A., and P.C. Stouffer 2006. Habitat selection by Swainson’s Warblers breeding in Loblolly Pine plantations in southeastern Louisiana. Journal of Wildlife Management 70:1013–1019. Bechard, A.M. 2008. Influence of row spacing and debris distribution on vegetation and small mammals in Louisiana pine plantations. M.Sc. Thesis. 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Wildlife Society Bulletin 32:1071–1076. White, G.C., K.P. Burnham, D.L. Otis, and D.R. Anderson. 1978. User’s Manual for Program CAPTURE. Utah State University Press, Logan, UT. Southeastern Naturalist 441 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 Appendix A. Mean abundance of bird species detected in study plots between late-April and mid-July in 2006, 2007, 2009, and 2010. Species are arranged in order of decreasing total detections. * indicates disturbance-dependent species; † signifies species breeding on plots, and ‡ denotes species of conservation concern. Piled and scattered refer to debris, and 4.3 and 6.1 refer to row spacing (m). Conservation score refers to regional combined score for the breeding season (RCS-b), as defined by Pranjabi et al. (2005). Full species names can be found at http://www.birdpop.org/alphacodes.htm. Total = total detected, yrs = years detected. Conservation Mean abundance score for 2006 2007 2009 2010 sites Piled Scattered Piled Scattered Piled Scattered Piled Scattered Species A+B C+D 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % Total Yrs YBCH*† 13 13 1 1 2 4 7 9 12 8 22 29 28 33 16 28 27 24 36 18 261 4 INBU*† 14 11 3 3 4 6 12 10 17 13 14 14 17 26 22 23 12 23 25 18 21 14 245 4 PRAW*†‡ 18 18 0 5 5 6 5 5 18 20 17 19 11 13 12 18 13 9 151 3 BLGR*† 12 12 3 3 6 8 9 9 9 8 9 13 11 10 10 6 8 11 7 8 5 125 4 CARW† 13 13 3 4 4 4 11 7 8 8 10 9 5 8 4 8 4 4 8 6 6 4 97 4 NOCA† 12 10 4 4 5 2 11 8 2 7 7 6 7 6 6 6 4 7 6 8 7 4 92 4 EATO*† 16 10 1 1 2 7 2 3 4 4 8 11 9 10 5 10 6 10 9 6 91 4 COYE*† 13 13 0 3 8 5 5 5 7 8 8 9 5 6 5 6 7 4 77 3 OROR†‡ 16 18 0 3 5 6 1 4 9 7 11 7 5 9 7 5 6 4 76 3 EAKI† 15 13 1 1 3 4 6 7 5 10 4 5 5 3 3 4 1 3 2 56 4 NOMO† 12 10 1 3 3 2 2 3 4 3 5 6 6 4 3 5 4 7 3 3 55 4 CACH 16 16 2 3 5 8 2 2 1 4 4 3 7 2 6 7 3 6 4 54 4 BHCO† 8 11 0 4 1 1 8 3 5 5 3 7 8 4 8 4 53 3 WEVI*† 14 16 1 1 2 1 1 2 2 1 5 2 4 4 2 5 5 9 5 4 47 4 MODO 11 8 1 1 4 1 5 4 3 2 3 3 1 4 1 3 1 3 1 1 1 1 34 4 BGGN† 11 13 1 1 1 1 1 5 4 4 4 2 3 4 2 2 2 31 4 NOBO*† 16 15 0 1 1 1 1 4 5 4 3 2 2 4 2 2 2 29 3 EABL* 11 11 3 1 1 1 5 3 4 1 2 3 2 4 3 2 0 26 3 FISP*† 15 15 0 1 0 2 3 3 1 1 1 2 6 3 2 22 3 BRTH* 15 13 0 1 1 1 1 2 1 1 4 1 1 2 3 3 1 20 3 Southeastern Naturalist F.L. Owens, P.C Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 442 Conservation Mean abundance score for 2006 2007 2009 2010 sites Piles Scattered Piles Scattered Piles Scattered Piles Scattered Species A+B C+D 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % Total Yrs BLJA 14 13 1 2 1 2 5 1 0 3 0 2 1 1 1 14 4 TUTI 13 14 3 2 0 3 1 4 1 1 2 0 14 3 SEWR‡ - - 0 2 2 2 3 2 0 4 1 1 14 2 RHWO*†‡ 15 17 2 1 4 1 1 2 3 2 1 0 14 3 GCFL 12 13 1 1 2 2 1 1 2 1 1 1 1 1 1 0 12 4 RTHU 12 13 1 1 2 1 1 1 1 2 2 1 1 1 1 0 12 4 RBWO 13 12 3 2 1 0 1 4 1 2 0 11 4 PIWA 14 14 2 2 0 2 1 0 4 2 1 11 3 SUTA 16 15 1 1 1 2 1 1 2 2 1 1 1 0 11 4 SWSP - - 0 2 3 2 2 2 0 1 0 10 2 COGR 11 11 0 2 2 3 2 2 0 1 0 10 2 GRCA 11 9 0 1 0 2 2 2 1 1 1 0 9 3 HOWA 14 16 2 2 0 3 1 1 1 1 0 8 3 CGDO*‡ 16 11 0 1 1 1 2 0 2 0 6 3 NOFL 15 14 0 1 0 4 1 1 0 6 2 REVI 11 11 3 1 2 4 0 0 0 6 1 AMCR 11 10 1 1 0 1 1 1 0 0 4 2 BHNU‡ 20 19 2 2 0 1 0 1 0 4 3 CHSP 9 11 1 1 2 2 1 0 0 4 2 HOWR 8 8 0 2 1 1 1 0 0 4 2 RWBL 11 10 0 1 0 1 0 2 0 4 3 DOWO 14 13 0 0 1 0 2 0 3 2 RTHA 9 9 0 2 1 1 0 0 3 1 SOSP 8 - 2 2 1 0 0 0 3 2 YTVI 15 15 1 1 0 1 0 1 0 3 3 WTSP - - 0 1 1 1 0 0 2 1 Southeastern Naturalist 443 F.L. Owens, P.C. Stouffer, M.J. Chamberlain, and D.A. Miller 2014 Vol. 13, No. 3 Conservation Mean abundance score for 2006 2007 2009 2010 sites Piles Scattered Piles Scattered Piles Scattered Piles Scattered Species A+B C+D 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % 4.3 6.1 4.3 6.1 % Total Yrs AMKE 13 13 0 1 0 0 0 1 1 AMRO 6 9 1 1 0 0 0 1 1 BACS*‡ 21 20 0 1 0 0 0 1 1 CWWI 16 16 0 0 1 0 0 1 1 EAWP 14 16 1 1 0 0 0 1 1 MAWR 14 - 0 0 0 1 0 1 1 TUVU 9 10 1 1 0 0 0 1 1 WITU 11 11 0 0 1 0 0 1 1 YBCU† 15 15 0 0 0 1 0 1 1 YRWA - - 0 1 0 0 0 1 1 Total 34 22 39 34 100 83 94 108 106 100 172 190 166 181 100 159 158 143 164 100 1853