Summary of Breeding Bird Trends in the Chippewa and Superior National Forests of Minnesota

Transcription

1 Summary of Breeding Bird Trends in the Chippewa and Superior National Forests of Minnesota Report to Chippewa National Forest and Superior National Forest, October 2012 Gerald J. Niemi, Alexis Grinde, Josh Bednar, Edmund Zlonis Natural Resources Research Institute University of Minnesota Duluth 5013 Miller Trunk Highway Duluth, MN This is NRRI technical report: NRRI/TR-2012/39 Suggested citation: Niemi, G.J., A. Grinde, J. Bednar, E. Zlonis Summary of breeding bird trends in the Chippewa and Superior national forests of Minnesota NRRI technical report NRRI/TR-2012/39, University of Minnesota Duluth.

2 SUMMARY A total of 314 existing forest stands were surveyed for breeding birds including 124 and 190 stands (936 survey points) in the Chippewa, and Superior National Forests (NFs), respectively in Trends in relative abundance were calculated for a total 73 bird species, including 64 species in the Chippewa NF and 63 in the Superior NF for 18 years from 1995 to All trends are reported as significant when P < The Chippewa NF had 19 species that increased, five species that significantly decreased, and 41 species that were relatively stable from 1995 to Hence, approximately 92 % of the species (59/64 species) with adequate trend information are estimated to be stable or increasing over the past 18 years in the Chippewa NF. The Superior NF had 20 species that increased, eight that decreased, and 35 species that were relatively stable from 1995 to Hence, approximately 87 % of the species (55/63 species) with adequate trend information are estimated to be stable or increasing over the past 18 years in the Superior NF. Nine species increased in both the Chippewa and Superior NFs, including Black-and-White Warbler, Black-capped Chickadee, Black-throated Green Warbler, Blue Jay, Nashville Warbler, Pileated Woodpecker, Pine Warbler, Red-breasted Nuthatch, and White-throated Sparrow. The Connecticut Warbler was the only species with a declining trend in both the Chippewa and Superior NFs. All of the guild analyses showed signficant increases during the period except for nonsignificant trends for bird species associated with early-successional forests in the Chippewa NF. The guild trends are primarily influenced by the large number of species that have positive trends relative to the number of negative trends. The overall trend information indicates that most breeding bird species within these NFs that we are capable of monitoring and detecting trends are either increasing or stable in populations, while a few species such as the Connecticut Warbler continue to have trends that remain a concern. This is the first year that we have presented results without the Chequamegon NF included in the trend calculations. The last time the Chequamegon NF was montored was in 2010 and several species that we identified as in population decline, such as the Scarlet Tanager, no longer show a signficant decline. This is partly a reflection of the sample size necessary to detect a significant trend for species. For instance almost half the observations of Scarlet Tanager in trend calculations from came from stands within the Chequamegon NF. Hence, the power to detect trends and identify potential reasons for declines over longer time period will subsequently be reduced. INTRODUCTION The breeding bird communities of the western Great Lakes region have among the richest diversity of breeding bird species in North America (Green 1995, Howe et al. 1997, Rich et al. 2004). The importance of this diversity and past concerns with potential declines of some species has led to a strong interest in monitoring forest bird populations in the region. The relatively heavily forested landscapes of northern Minnesota and Wisconsin are considered to be population 'sources' for many forest bird species and may be supplementing population 'sinks' in the agricultural landscapes of the lower Midwest (Robinson et al. 1995, Temple and Flaspohler 1998). Analysis of population trends is used as an 'early-warning system' of potential problems in a species population and serves as a measure of the ecological condition of the environment (Niemi and McDonald 2004a).

3 Recently, a draft of a general technical report on a summary of the twenty-plus year data that have been gathered in the Chequamegon, Chippewa, Nicolet, and Superior NFs from the late 1980s through 2011 has been completed (Niemi et al. 2013). This report is due for publication during the spring of It summarizes a substantial amount of information that has been gathered on population trends, habitat relationships, bird community assemblages, factors potentially affecting population trends, management recommendations for bird species of concern, and a brief review of potential invasive species affecting bird species. Large-scale population monitoring programs such as the U.S. Geological Survey s Breeding Bird Survey (BBS) provide important information on trends at a continental scale. However, limited coverage in some areas can make it difficult to use BBS data to characterize population trends at smaller geographic scales (Peterjohn et al. 1995). Continental trends also have the potential to mask regional population trends (Holmes and Sherry 1988), thus there is a need for regional monitoring programs that can provide more localized information (Howe et al. 1997). In response to the need for regional population data, a long-term forest breeding bird monitoring program was established in 1991 in the Chippewa and Superior NFs. The Forest Service is mandated to monitor certain management indicator species (Manley et al. 1993), and our monitoring program expands beyond indicator species to include all forest songbird species that we can adequately sample. Currently, approximately 314 stands (942 points) within the two NFs are surveyed during the breeding season (June 1 to July 10). The primary objective of this report is to update U.S. Forest Service personnel on results of the forest bird monitoring program. Here we focus on relative abundance trends of individual species during the period from (18 years) and summarize the most important recent results. DESIGN AND METHODS Sample Design Originally, the monitoring program was designed to provide an accurate estimate of population change for forest bird species on three national forests in northern Minnesota and Wisconsin: Chequamegon NF (WI), Chippewa NF (MN), and Superior NF (MN). After the 2010 field season, the Chequamegon NF was unable to continue to fund the program. In contrast, the Nicolet NF has continued to be implemented and results from both the Chequamegon through 2010 and the Nicolet NF through 2011 were included in the general technical report (Niemi et al. 2013). The spatial extent of the Chippewa and Superior NFs is large, on the order of hundreds of thousands of hectares, and each area includes a mosaic of forest stand types. We distributed sampling locations across the forest mosaic in a stratified random manner. A list of forest stands was created for each study area, and stands with the same stand type according to dominant tree species and stocking density were grouped into strata. Stands were 16 ha (40 acres) and were identified from the individual national forest inventories. For each national forest, a number of stands were selected from each stratum so that the final proportion of stands of each stand type was equal to the proportion of forested land area of each stand type (Hanowski and Niemi 1995). Our sample of stands is therefore representative of the forest cover in each NF. Figure 1. General locations of forest breeding bird point counts in northern Minnesota and Wisconsin Annual Report Forest Bird Monitoring 2

4 A total of 124 and 190 stands were established in the Chippewa and Superior National Forests, respectively (Figure 1). Stands were large enough to accommodate three sampling points a minimum of 220 meters apart. Changes to forest cover through natural and anthropogenic disturbance have occurred on sampling locations since the beginning of the study and may have caused concomitant changes in bird populations. Because sampling locations are permanently marked, we are able to incorporate such changes into our descriptions of bird population patterns through time. Sampling Point count sampling used in our program follow national and regional standards (Ralph et al. 1993, 1995, Howe et al. 1997). Ten-minute point counts were conducted at each point between June and early July (Reynolds et al. 1980, Hanowski et al. 2005, Etterson et al. 2009). Point counts are appropriate for determining the relative abundance of most singing passerine species, but are likely inadequate for waterfowl, grouse, woodpeckers, and most raptors. However, because these data are collected off-road and within specific habitat types, they are useful for habitat and landscape analyses associated with forest management. Point counts were conducted by trained observers from approximately 0.5 hour before to 4 hours after sunrise on days with little wind (< 15 km/hr) and little or no precipitation. All birds heard or seen from the point were recorded with estimates of their distance from that point. From , we included all birds heard or seen from the point regardless of distance so that our results could be compared with other monitoring programs in this region (Howe et al. 1997). The number of individuals observed for each species can be summed for 3, 5, and 10-minute periods so regional comparisons are possible with data gathered using 3 or 5-minute point counts. However, in 2010 we began to gather data at one-minute intervals, after the first two minutes of sampling, in an attempt to gain a better understanding of bird detectability (Etterson et al. 2009). We attempted to have each observer sample a similar number of stands of each forest cover type. This was done to minimize bias due to observer differences in sampling different forest cover types. Weather data (cloud cover, temperature, and wind speed) and time of day were recorded before each count. Observer Training Prior to the field season, tapes of 120+ bird songs were provided as a learning tool, and all observers were required to pass an identification test of at least 75 bird songs. A standard for number of correct responses was established by giving the test to observers who were trained in identifying birds by sound, and who had four to five years of field experience. This was done to identify songs on the tape that were not good representations of songs heard in northern Minnesota and Wisconsin. Based on results of trained observers, the standard for passing was set at 85% correct responses. Songs on the tape were grouped by habitat (e.g. upland deciduous, lowland coniferous) to simulate field cues that would aid in song identification. Observer field training was conducted during the last week of May in the Superior National Forest. Observers conducted simultaneous practice counts at several points used in the monitoring program. Data were compiled for each observer, and species lists and number of individuals recorded on the count by each observer were compared with experienced observers. Deviations from the average or species missed were noted on the field sheets and returned. In addition to field training and testing, all observers were required to have a hearing test to ensure that their hearing was within normal ranges, as established by audiologists, for all frequencies (125 to 8000 hertz) Annual Report Forest Bird Monitoring 3

5 Analysis The pattern of population change through time can be viewed in two distinct ways: 1) as a population trajectory, the path of a population through time, including its ups and downs, and 2) as population trend, the overall pattern of increase or decrease over the course of the study, presented as a positive or negative number. We built statistical models of species relative abundance as a function of time to describe these features of bird populations. Relative abundance For each species, yearly relative abundance was calculated using all individuals of a species detected from a point. Relative abundance for species from the three national forests was calculated by summing the number of individuals of each species across two points per stand. To avoid double-counting of individuals, data from the two farthest separated points within a stand were summed and analyzed. We used a set of criteria to ensure that our analyses provided reliable population information. Stands were included in the analysis only if they had been sampled in at least six years. Data were included for a species if it was observed on a minimum of five stands and for at least three years in a stand.. Population trajectory Population trajectory can be thought of simply as the size of a population across time. Because we do not record every individual bird present in our study areas, we cannot know true population size. Instead, we must rely on our sample design to give an index of population size in each year. Central to our analytical process is how we scaled up bird abundance recorded at the stand level to an annual index of population size for the study areas. We used a non-parametric route regression procedure similar to that described by James et al. (1996), in which observed abundances on each stand are smoothed and then combined to give a region-wide index of population size. We used locally-weighted (LOESS) regression to smooth the time series of species relative abundance for each stand. In LOESS-regression, fitted values (points along the curve) for years are calculated by giving a small amount of weight to neighboring years, for example, a year with high raw abundance for a species would tend to bring up the fitted values for the year before and the year after. We then computed the arithmetic mean and 95% confidence intervals using the fitted values from the within-stand regressions for each species in each year. The mean fitted value represents the annual index of population size. By plotting the mean fitted values and confidence intervals in a time series, we get a graphic depiction of the population trajectory (Appendix A). With every year of sampling, we can expect the modeled abundance of a species in a given year to vary slightly from previous years results, due to the way fitted abundance values are calculated in the LOESS-regression. Population trend Population trend can be thought of as a statement of the direction and magnitude of population change over a given time period (Link and Sauer 1997). Because a significant trend implies a unidirectional change, linear methods can be used to detect trend without asserting that the population trajectory is linear (Urquhart and Kincaid 1999). To assess trend, we modeled the relationship between the annual index of population size for a study area (described in Population Trajectory above) and time using simple linear regression. We used the slope coefficient to characterize direction and magnitude of the trend. To facilitate comparison, slopes were converted to units of percent annual change by dividing annual population indexes by the predicted value of the index at the midpoint of the survey period prior to regressing the index against time (Bart et al. 2003). We assessed the significance of the regressions using a bootstrap procedure (Manly 1991) in which trends were computed for 500 bootstrap resamples of the stands used to calculate the annual population index. For each bootstrap resample, trend was calculated using the same steps as for the original trend. For each original trend, an exact p-value was calculated as the percentile at which zero occurred in the distribution of 500 bootstrapped slopes. For example, p = 0.01 would be equivalent to 99% of 2012 Annual Report Forest Bird Monitoring 4

6 bootstrapped slopes being greater than zero, which would give us a high degree of confidence that the true population slope was different from zero. Guild analyses We report the results for all of the guilds (e.g., migratory, nesting, and habitat types). Guild categories were taken from Ehrlich et al. (1988) and Freemark and Collins (1992), with modifications based on personal experience and data from the region. Note that some species use different migration strategies, nesting substrates, and vegetation types in different portions of their geographic range. Guild analyses also can be complicated by a lack of agreement on how to categorize guilds, and there will always be species that use multiple guilds. Species guilds are not mutually exclusive and the species pool in a migration guild, for example, can be very similar to the species pool in a nesting guild (Sauer et al. 1996). Directional trends in abundant species can strongly affect all the guilds that those species are categorized in. Given these limitations, we still feel it is important to look for underlying similarities among groups of increasing and decreasing species, but these results must be interpreted with caution. RESULTS AND DISCUSSION Over the course of 18 field seasons we have detected over 300,000 individual birds of 175 species on approximately 17,000 ten-minute point counts (over 2,800 hours of sampling) in the Chippewa and Superior NFs. In 2012, we sampled 124 stands in the Chippewa NF and 190 in the Superior NF. Seventythree species were tested for trends in at least one national forest, including 64 in the Chippewa NF and 63 in the Superior NF (Table 1). As monitoring has proceeded through the years, new species have met our criteria for inclusion in trend analyses on each national forest. The number of tested species has increased steadily from 36 in 2000, when the criteria were first applied, to 73 in Overview of Population Trends Twenty-nine species (39%) increased in at least one national forest and 12 (16%) species decreased in at least one national forest (Table 1). Therefore, 34 species (45%) had stable or non-significant population trends among those in which we could detect a trend. Only one species had conflicting trends, the Myrtle Warbler significantly decreased in the Chippewa NF, but increased in the Superior NF. Nineteen species increased in the Chippewa NF and 20 species increased in the Superior NF. Of these, nine species increased in both NFs. These included the Pileated Woodpecker, Blue Jay, Black-capped Chickadee, Red-breasted Nuthatch, Black-and-White Warbler, Nashville Warbler, Black-throated Green Warbler, Pine Warbler, and White-throated Sparrow (Tables 2 and 3). In contrast, five species decreased in the Chippewa NF and eight species decreased in the Superior NF (Table 4). One species, the Connecticut Warbler, decreased in both NFs. Appendix A includes trend graphs of individual species trajectories within the Chippewa and Superior NFs. Appendix B is a complete statistical summary of the trend analysis including species, its four alphabet code, its trend within each NF, the significance of the trend, the explained variation of the trend, and the number of stands in which the species was detected sufficiently to include in the trend calculation. The combination of the p-value and the explained variation indicate the strength of the trend for each species within each NF. Appendix C describes the common name, scientific name, four-letter code used in field identification, and a summary of the three major guilds included here: migration strategy, nest site, and vegetation type primarily used by the species. Appendices D and E identify the number individuals observed for species not included in the trend calculations for each NF from 1995 to 2012, respectively. Chippewa National Forest Of the 64 species tested in the Chippewa NF, 19 species (30 %) increased significantly (Table 2) and five (8%) declined (Table 4). Compared with trends from when six species had significantly declined; the Scarlet Tanager no longer had a significant declining trend (p=0.16, Appendix A). The other 2012 Annual Report Forest Bird Monitoring 5

7 five species were consistent with trends through 2011 and included the Connecticut Warbler, Goldenwinged Warbler, Myrtle Warbler, Song Sparrow, and Yellow-throated Vireo. Both the Connecticut Warbler and Golden-winged Warbler are species of concern in Minnesota and, therefore, the trends for these species are of concern. Each of these species is discussed in some detail in Niemi et al. (2013). The Yellow-throated Vireo is a relatively uncommon species in the Chippewa NF; however, 33 forest stands were included in the analysis of its trend (Appendix A). Its decline has been steady from 2001 to This declining pattern within the Chippewa NF since 2001 is also true for the Golden-winged Warbler and Song Sparrow. Superior National Forest Of the 63 species tested in the Superior NF, 20 species (32%) were increasing (Table 2) and eight (13%) were decreasing (Table 4). Compared with the results through 2011, the Broad-winged Hawk, Connecticut Warbler, Evening Grosbeak, Magnolia Warbler, Ruffed Grouse, Swainson s Thrush, and Yellow-bellied Flycatcher continued to show declining trends through The Common Loon was the only new species that showed a significant decline, while the Great Crested Flycatcher and Wilson Snipe no longer had significant declining trends; though the Great Crested Flycatcher is nearly significant (p = 0.06). The declining trends in the Connecticut Warbler was previously noted above, while the Yellow-bellied Flycatcher and Swainson s Thrush are also of concern and discussed in some detail in Niemi et al. (2013). Primary habitat for all of these three species includes lowland coniferous forest. The Evening Grosbeak has been declining over a large area of the northern U.S. and Canada. Potential reasons include disease transmitted at bird feeders, reduced food supplies due to logging of hardwood forests in Canada (is primary breeding area), and changes in its breeding and wintering distribution due to shifting climatic conditions (Niemi 2012).The decline in the Common Loon was detected primarily because of the use of unlimited distance point counts. The point count methodology is not the best technique for monitoring Common Loons and, therefore, the decline in observations of this species should be viewed with caution unless substantiated with other data. Management Activities on Study Areas Of the survey sites in the three national forests, approximately 16% have been at least partially harvested since the beginning of monitoring, which continues to be about 1% a year. A small number of our monitoring points have also had prescribed burns since the start of monitoring, but this is usually done after harvest. This harvest rate is comparable to the 4.8% change from mature forest to early-successional types on federally managed forest lands in northeastern Minnesota between 1990 and 1995 (i.e. ~1% annual change; Wolter and White 2002). Thus, it appears that management activities on our sample sites have continued to be representative of these two national forests. Guild Analyses The analysis of migratory, nesting, and habitat association guilds almost all showed significant increases from (Table 5). The only exception was species associated with early-successional forests in the Chippewa NF which was non-significant. This is interesting because it parallels the reduction in logging that has occurred in these two NFs over the past 10 years as documented in Niemi et al. (2013). Among the guilds included in the analysis, one would expect that breeding bird species associated with earlysuccessional forests would be those most affected by a reduction in logging activity. There were no guilds that significantly decreased. A continued noteworthy pattern; however, are the trends among the migratory guilds. Permanent residents continue to show the greatest overall percentage increase over the past 18 years with an increase of 3.1% per year within both the Chippewa and Superior NFs (Table 5). Both short-distance migrants and long-distance migrants have also had increasing trends but not as high as the permanent residents (Table 5). Note that a 3.1% per year increase over an 18-year period represents an approximate 56% increase in the number of permanent resident individuals within these two NFs in 2012 compared with Annual Report Forest Bird Monitoring 6

8 The possible hypotheses why permanent residents may be increasing at a greater rate than the short and long distance migrants include the following. (1) Over-winter survival has increased for permanent residents because the climate is warming and winters are less severe in terms of temperature. (2) Winter feeding of birds has been increasing over the past 18 years and supplemental food aids in over-winter survival. (3) Climatic warming results in earlier emergence of food (insects, berries, buds, etc.) and, hence, the earlier nesting species such as permanent residents would gain the greatest benefit from this shift in phenology. These hypotheses are not mutually exclusive, but some of the data presented in the recent general technical report on climate patterns over the past 18 years suggests some support for hypotheses 1 and 3 (Niemi et al. 2013). CONCLUSIONS There are several possible hypotheses on why so many species seem to be stable or increasing in relative abundance over the past 18 years. First, logging activity has steadily decreased in both the Chippewa and Superior NFs over the past ten years; primarily due to the economic downturn of the recent recession and other factors that have contributed to reduced demand for lumber, paper, and other forest products. Because the majority of breeding bird species in these forests is found in mid-to-late successional forests, it is logical that most of these species would also be stable or increasing. The exceptions among the species that are decreasing include the Broad-winged Hawk, Connecticut Warbler, Evening Grosbeak, Magnolia Warbler, Myrtle Warbler, Swainson s Thrush, and Yellow-bellied Flycatcher; all of which are found in mid-to-late successional forests. For each, there are potential reasons for their exceptions. Connecticut Warbler, Myrtle Warbler, Swainson s Thrush, and Yellow-bellied Flycatcher are all highly associated with lowland coniferous forests. There is some evidence that drought conditions and lower food supplies over the past ten years may have affected reproduction for these species that rely on an insectivorous diet to feed their young (Niemi et al. 2013). Declining populations of the Broad-winged Hawk (5 stands the minimum for inclusion) is based on relatively sparse data and the Ruffed Grouse (23 stands) may be better monitored earlier in the year with spring drumming counts. The population decline in the Magnolia Warbler is enigmatic and potential management recommendations were reviewed in Niemi et al. (2013). Changes in understory conifer cover within aspen-birch-spruce mixed forests would likely have a negative effect on this species, but competitive interactions with other Setophaga warblers such as the Cape May Warbler may also be possibilities. Among the major conclusions of the 20-year summary of the national forest bird monitoring program (Niemi et al. 2013) is our inability to definitively pinpoint specific causes for increases or decreases of specific species. Because these species range over relatively wide areas these populations are subject to many potential factors that can affect their population. These factors include climate, weather, landscape and habitat change due to both natural and anthropogenic disturbances (e.g., forest fire, logging, wind, exurban development and insect defoliation), and invasive species on their breeding ground. Hazards of migration and over-wintering conditions can also influence population levels. Yet, given the number of species that we are able to monitor, if there is an influence of a large-scale forest management activity, then it is likely that such a signal would be detected by these data. In fact, the clearest signal we may have is reflected in the large number of species that are increasing or are stable; largely due to the reduction in logging activity in these forests as well as the annual changes in ambient weather conditions (e.g., drought and mild winters). This perspective is also supported by the lack of a significant increase for bird species within the early-successional forest bird guild in the Chippewa NF. This is the one guild that would reflect reductions in early-successional forests due to a reduction in logging activity. The overall message in this report is positive regarding breeding forest birds in the Chippewa and Superior NF. Yet, from a historical perspective over the past 200 years, most of these forest-associated breeding species likely have much lower populations today than in the past because of the reductions in forest habitat. For example, Minnesota has lost almost half of its forest area from 31 million acres in the mid Annual Report Forest Bird Monitoring 7

9 1800 s to less than 17 million acres today. These rates of forest loss are even conservative relative to other U.S. states and in over-wintering habitats of Mexico and in Central and South America. Maintaining adequate forest area will be a challenge for many generations to come. LITERATURE CITED Bart, J., B. Collins, and R. I. G. Morrison Estimating population trends with a linear model. Condor 105: Etterson, M. A., G. J. Niemi, and D. P. Danz Estimating the effects of detection heterogeneity and overdispersion on trends estimated from avian point counts. Ecological Applications 19: Ehrlich, P. R., D. S. Dobkin, and D. Wheye The Birder's Handbook: A Field Guide to the Natural History of North American Birds. Simon and Schuster, New York. Freemark, K., and B. Collins Landscape ecology of birds breeding in temperate forest fragments. Pages in Ecology and conservation of Neotropical migrant landbirds (J.M. Hagan and D.W. Johnston, eds). Smithsonian Institution Press, Washington, D.C. Green, J. C Birds and forests: A management and conservation guide. Minnesota Department of Natural Resources. St. Paul, MN. 182 pp. Hanowski, J. M., and G. J. Niemi Experimental design considerations for establishing an off-road, habitat specific bird monitoring program using point counts. Pages in Monitoring bird populations by point counts. General Technical Report PSW-GTR-149. Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture, Albany, CA. Hanowski, J., J. Lind, N. Danz, G. Niemi, T. Jones Regional breeding bird monitoring in western Great Lakes national forests. Pages in C.J. Ralph and T.D. Rich (eds). Bird conservation implementation and integration in the Americas: proceedings of the Third International Partners in Flight Conference March 20-24; Asilomar, California; Volume 2. Gen. Tech. Rep. PSW-GTR Albany CA: Pacific Southwest Research Station, Forest Service, 643 pp. Holmes, R. T., and T. W. Sherry Assessing population trends of New Hampshire forest birds: Local vs. regional trends. Auk 105: Howe, R. W., G. J. Niemi, G. J. Lewis, and D. A. Welsh A standard method for monitoring songbird populations in the Great Lakes region. Passenger Pigeon 59: James, F. C., C. E. McCulloch, and D. A. Wiedenfeld New approaches to the analysis of population trends in land birds. Ecology 77: Link, W. A., and J. R. Sauer New approaches to the analysis of population trends in land birds: comment. Ecology 78: Manley, P. N., W. M. Block, F. R Thompson, G. S. Butcher, C. Paige, L. H. Suring, D. S. Winn, D. Roth, C. J. Ralph, E. Morris, C. H. Flather, and K. Byford Guidelines for monitoring populations of neotropical migratory birds on National Forest System lands. USDA Forest Service Monitoring Task Group Report, Washington, D.C. Manly, B. F. J Randomization and Monte Carlo methods in biology. Chapman & Hall, London, UK. Niemi, G. J., and M. McDonald Application of ecological indicators. Annual Review of Ecology and Systematics 35: Niemi, G. J Ups and downs of forest birds. Minnesota Conservation Volunteer 75: Niemi, G. J., R. W. Howe, B. R. Sturevant, L. R. Parker, A. R. Grinde, N. P. Danz, M. Nelson, E. J. Zlonis, N. G. Walton, E. E. Geise Twenty years of forest bird monitoring in national forests of the 2012 Annual Report Forest Bird Monitoring 8

10 western Great Lakes region: trends, underlying drivers, and management recommendations. NRRI technical report NRRI/TR-2012/32, University of Minnesota Duluth. Peterjohn, B. G., J. R. Sauer, and C. S. Robbins Population trends from the North American Breeding Bird Survey. Pages 3-39 in Ecology and management of Neotropical migratory birds (T. E. Martin and D. M. Finch, eds.). Oxford University Press, New York. Ralph, C. J., G. R. Geupel, P. Pyle, T. E. Martin, and D. F. DeSante Handbook of field methods for monitoring landbirds. Gen. Tech. Rep. PSW-GTR-144. Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture, Albany, CA. 41 pp. Ralph, C. J., J. R. Sauer, and S. Droege (eds.) Monitoring bird populations by point counts. General Technical Report PSW-GTR-149. Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture, Albany, CA. 181 pp. Reynolds, R. T., J. M. Scott, and R. A. Nussbaum A variable circular-plot method for estimating bird numbers. Condor 82: Rich, T. D., C. J. Beardmore, H. Berlanga, P. J. Blancher, M.S. Bradstreet, G. S. Butcher, D. W. Demarest, E. H. Dunn, W. C. Hunter, E. E. Iñigo-Elias, J. A. Kennedy, A. M. Martell, A. O. Panjabi, D. N. Pashley, K. V. Rosenberg, C. M. Rustay, J. S. Wendt, and T. C. Will Partners in Flight North American Landbird Conservation Plan. Cornell Lab of Ornithology, Ithaca, NY. Robinson, S. K., F. R. Thompson III, T. M. Donovan, D. R. Whitehead, and J. Faaborg Regional forest fragmentation and the nesting success of migratory birds. Science 267: Sauer, J. R., G. W. Pendleton, and B. G. Peterjohn Evaluating causes of population change in North American insectivorous songbirds. Conservation Biology 10: Temple, S. A., and D. J. Flaspohler The edge of the cut: implications for wildlife populations. Journal of Forestry 96: Urquhart, N. S., and T. M. Kincaid Designs for detecting trend from repeated surveys of ecological resources. Journal of Agricultural, Biological, and Environmental Statistics 4: Wolter, P. T., and M. A. White Recent forest cover type transitions and landscape structural changes in northeast Minnesota. Landscape Ecology 17: Annual Report Forest Bird Monitoring 9

11 Table 1. Trends for three individual national forests (NF) and pooled NF's based on linear regression of loess-smoothed annual index of abundance (See Methods) ( ). I= significantly increasing, D= significantly decreasing. *P < 0.05, ** P < See Appendix A for species graphs and Appendix B for test statistics and sample sizes. Chippewa NF Superior NF Alder Flycatcher ns ns American Crow I* ns American Goldfinch I** ns American Redstart ns ns American Robin ns I** Black-and-white Warbler I** I** Blackburnian Warbler ns ns Black-billed Cuckoo - ns Black-capped Chickadee I** I** Black-throated Blue Warbler - ns Black-throated Green Warbler I** I* Blue Jay I** I** Blue-headed Vireo ns ns Broad-winged Hawk - D** Brown Creeper ns ns Brown-headed Cowbird ns - Canada Warbler I* ns Cape May Warbler - I** Cedar Waxwing ns I** Chestnut-sided Warbler ns ns Chipping Sparrow ns ns Common Loon ns D* Common Raven ns ns Common Yellowthroat ns ns Connecticut Warbler D** D** Downy Woodpecker ns ns Eastern Wood-Pewee ns ns Evening Grosbeak - D* Golden-crowned Kinglet ns I** Golden-winged Warbler D** ns Gray Catbird ns - Gray Jay ns I* Great Crested Flycatcher ns - Hairy Woodpecker ns I** Hermit Thrush I** ns Indigo Bunting ns - Least Flycatcher ns ns Magnolia Warbler ns D** Mourning Dove I** - Mourning Warbler ns ns Nashville Warbler I** I** Northern Flicker (Yellow-shafted) ns I** Northern Parula ns I** Northern Waterthrush ns ns Olive-sided Flycatcher ns ns Ovenbird I** ns Palm Warbler (Western) ns - Pileated Woodpecker I** I* Pine Warbler I** I* Purple Finch ns I* Red-breasted Nuthatch I** I** Red-eyed Vireo I** ns

12 Red-winged Blackbird ns ns Rose-breasted Grosbeak ns ns Ruby-crowned Kinglet - I** Ruby-throated Hummingbird ns - Ruffed Grouse - D** Scarlet Tanager ns ns Song Sparrow D** ns Swainson's Thrush - D* Swamp Sparrow ns ns Tennessee Warbler - ns Veery I** ns White-breasted Nuthatch ns - White-throated Sparrow I** I** Wilson's Snipe ns ns Winter Wren ns ns Wood Thrush I* ns Yellow Warbler ns - Yellow-bellied Flycatcher ns D** Yellow-bellied Sapsucker I** ns Yellow-rumped Warbler (Myrtle) D* I* Yellow-throated Vireo D** Annual Report Forest Bird Monitoring 2

13 Table 2. Species with significantly increasing trends (P < 0.05) for three national forests ( ), based on regression of loess-smoothed annual index of abundance. **P < Species graphs can be found in Appendix A. Chippewa NF Superior NF American Crow American Goldfinch** Black-and-white Warbler** Black-capped Chickadee** Black-throated Green Warbler** Blue Jay** Canada Warbler Hermit Thrush** Mourning Dove** Nashville Warbler** Ovenbird** Pileated Woodpecker** Pine Warbler** Red-breasted Nuthatch** Red-eyed Vireo** Veery** White-throated Sparrow** Wood Thrush Yellow-bellied Sapsucker** American Robin** Black-and-white Warbler** Black-capped Chickadee** Black-throated Green Warbler Blue Jay** Cape May Warbler** Cedar Waxwing** Golden-crowned Kinglet** Gray Jay Hairy Woodpecker** Myrtle Warbler Nashville Warbler** Northern Flicker (Yellow-shafted)** Northern Parula** Pileated Woodpecker Pine Warbler Purple Finch Red-breasted Nuthatch** Ruby-crowned Kinglet** White-throated Sparrow**

14 Table 3. Summary of species with increasing trends (P < 0.05) on two national forests ( ). Individual species graphs can be found in Appendix A. Increased in one NF American Crow American Goldfinch American Robin Canada Warbler Cedar Waxwing Cape May Warbler Golden-crowned Kinglet Gray Jay Hairy Woodpecker Hermit Thrush Mourning Dove Myrtle Warbler Northern Flicker (Yellow-shafted) Northern Parula Ovenbird Purple Finch Ruby-crowned Kinglet Red-eyed Vireo Veery Wood Thrush Yellow-bellied Sapsucker Increased in both NFs Black-and-white Warbler Black-capped Chickadee Black-throated Green Warbler Blue Jay Nashville Warbler Pileated Woodpecker Pine Warbler Red-breasted Nuthatch White-throated Sparrow

15 Table 4. Species with significantly decreasing trends (P < 0.05) for two national forests ( ), based on regression of loess-smoothed annual index of abundance. **P < Species graphs can be found in Appendix A. Chippewa NF Superior NF Connecticut Warbler** Broad-winged Hawk** Golden-winged Warbler** Common Loon Myrtle Warbler Connecticut Warbler** Song Sparrow** Yellow-throated Vireo** Evening Grosbeak Magnolia Warbler** Ruffed Grouse** Swainson's Thrush Yellow-bellied Flycatcher**

16 Table 5. Test statistics and sample sizes for guild trend analyses on two national forests ( ). All species combined within each guild category and analyzed as a group, regardless of whether a species meets criteria for individual species analyses. Trend= percent annual change in population trend. N= number of stands analyzed. See appendix A for trend graphs. Chippewa NF Superior NF Guild Category Trend P R 2 N Trend P R 2 N Short distance migrants 0.77 < < Long distance migrants 1.14 < < Permanent residents 3.08 < < Ground nesting 1.37 < < Shrub/Sub-canopy nesting Canopy nesting 1.14 < < Cavity nesting 3.46 < < Coniferous forest 1.94 < < Lowland coniferous < Deciduous forest 1.48 < < Early-succession Mixed forest 2.46 < <

17 APPENDICES 1 Appendix A. Species population trend graphs of mean smoothed count index

18 ALFL APPENDICES 2 Annual Change = -1.38% p=0.43 n = 18 stands Annual Change = 1.26% p=0.56 n = 43 stands

19 AMCR APPENDICES 3 Annual Change = 1.33% p=0.03 n = 104 stands Annual Change = -0.72% p=0.44 n = 64 stands

20 AMGO APPENDICES 4 Annual Change = 7.82% p<0.001 n = 19 stands Annual Change = 4.69% p=0.36 n = 6 stands

21 AMRE APPENDICES 5 Annual Change = 1.38% p=0.15 n = 64 stands Annual Change = 0.74% p=0.36 n = 78 stands

22 AMRO APPENDICES 6 Annual Change = 0.40% p=0.62 n = 99 stands Annual Change = 2.65% p<0.001 n = 145 stands

23 BAWW APPENDICES 7 Annual Change = 5.20% p<0.001 n = 93 stands Annual Change = 3.76% p<0.001 n = 130 stands

24 BBCU APPENDICES 8 Annual Change = 3.66% p=0.34 n = 5 stands

25 BCCH APPENDICES 9 Annual Change = 2.87% p<0.001 n = 98 stands Annual Change = 3.46% p<0.001 n = 121 stands

26 BHCO APPENDICES 10 Annual Change = -1.52% p=0.63 n = 14 stands

27 BHVI APPENDICES 11 Annual Change = -0.20% p=0.87 n = 42 stands Annual Change = 1.51% p=0.40 n = 41 stands

28 BLBW APPENDICES 12 Annual Change = 0.79% p=0.44 n = 70 stands Annual Change = 1.21% p=0.07 n = 128 stands

29 BLJA APPENDICES 13 Annual Change = 1.44% p<0.001 n = 118 stands Annual Change = 2.45% p<0.001 n = 147 stands

30 BRCR APPENDICES 14 Annual Change = -1.16% p=0.26 n = 41 stands Annual Change = -0.71% p=0.61 n = 56 stands

31 BTBW APPENDICES 15 Annual Change = -0.76% p=0.72 n = 12 stands

32 BTNW APPENDICES 16 Annual Change = 4.27% p<0.001 n = 67 stands Annual Change = 1.78% p=0.02 n = 89 stands

33 BWHA APPENDICES 17 Annual Change = % p<0.001 n = 5 stands

34 CAWA APPENDICES 18 Annual Change = 5.47% p=0.04 n = 16 stands Annual Change = 0.55% p=0.37 n = 86 stands

35 CEDW APPENDICES 19 Annual Change = 1.73% p=0.34 n = 30 stands Annual Change = 5.03% p<0.001 n = 39 stands

36 CHSP APPENDICES 20 Annual Change = 0.53% p=0.49 n = 69 stands Annual Change = -0.86% p=0.38 n = 64 stands

37 CMWA APPENDICES 21 Annual Change = 6.13% p<0.001 n = 21 stands

38 COLO APPENDICES 22 Annual Change = -0.16% p=0.85 n = 69 stands Annual Change = -3.04% p=0.03 n = 36 stands

39 CONW APPENDICES 23 Annual Change = -6.64% p<0.001 n = 14 stands Annual Change = -8.45% p<0.001 n = 5 stands

40 CORA APPENDICES 24 Annual Change = 0.85% p=0.54 n = 47 stands Annual Change = 0.33% p=0.76 n = 55 stands

41 COSN APPENDICES 25 Annual Change = 4.99% p=0.27 n = 5 stands Annual Change = -3.60% p=0.09 n = 8 stands

42 COYE APPENDICES 26 Annual Change = -0.12% p=0.92 n = 84 stands Annual Change = 0.79% p=0.53 n = 65 stands

43 CSWA APPENDICES 27 Annual Change = -0.25% p=0.72 n = 105 stands Annual Change = -0.29% p=0.62 n = 133 stands

44 DOWO APPENDICES 28 Annual Change = -0.39% p=0.84 n = 15 stands Annual Change = -7.47% p=0.10 n = 6 stands

45 EAWP APPENDICES 29 Annual Change = -0.38% p=0.52 n = 86 stands Annual Change = -1.20% p=0.62 n = 25 stands

46 EVGR APPENDICES 30 Annual Change = -9.27% p=0.01 n = 10 stands

47 GCFL APPENDICES 31 Annual Change = -2.61% p=0.06 n = 36 stands

48 GCKI APPENDICES 32 Annual Change = 1.53% p=0.24 n = 23 stands Annual Change = 3.32% p<0.001 n = 70 stands

49 GRAJ APPENDICES 33 Annual Change = 2.83% p=0.31 n = 12 stands Annual Change = 3.86% p=0.01 n = 35 stands

50 GRCA APPENDICES 34 Annual Change = -1.01% p=0.82 n = 20 stands

51 GWWA APPENDICES 35 Annual Change = -4.60% p<0.001 n = 24 stands Annual Change = 2.60% p=0.20 n = 11 stands

52 HAWO APPENDICES 36 Annual Change = 2.21% p=0.27 n = 17 stands Annual Change = 5.15% p<0.001 n = 17 stands

53 HETH APPENDICES 37 Annual Change = 1.78% p<0.001 n = 98 stands Annual Change = 0.67% p=0.11 n = 135 stands

54 INBU APPENDICES 38 Annual Change = -3.41% p=0.35 n = 19 stands

55 LEFL APPENDICES 39 Annual Change = -1.04% p=0.13 n = 81 stands Annual Change = 1.78% p=0.19 n = 92 stands

56 MAWA APPENDICES 40 Annual Change = -2.71% p=0.22 n = 13 stands Annual Change = -1.96% p<0.001 n = 111 stands

57 MODO APPENDICES 41 Annual Change = 7.22% p<0.001 n = 7 stands

58 MOWA APPENDICES 42 Annual Change = -0.83% p=0.36 n = 62 stands Annual Change = -0.92% p=0.16 n = 121 stands

59 MYWA APPENDICES 43 Annual Change = -1.84% p=0.02 n = 64 stands Annual Change = 1.47% p=0.05 n = 110 stands

60 NAWA APPENDICES 44 Annual Change = 2.20% p<0.001 n = 106 stands Annual Change = 2.19% p<0.001 n = 147 stands

61 NOPA APPENDICES 45 Annual Change = 2.03% p=0.09 n = 40 stands Annual Change = 3.11% p<0.001 n = 78 stands

62 NOWA APPENDICES 46 Annual Change = 2.26% p=0.43 n = 16 stands Annual Change = 1.84% p=0.34 n = 15 stands

63 OSFL APPENDICES 47 Annual Change = -4.32% p=0.14 n = 11 stands Annual Change = -0.86% p=0.60 n = 5 stands

64 OVEN APPENDICES 48 Annual Change = 2.51% p<0.001 n = 122 stands Annual Change = 0.31% p=0.28 n = 147 stands

65 PIWA APPENDICES 49 Annual Change = 2.36% p<0.001 n = 49 stands Annual Change = 4.87% p=0.02 n = 14 stands

66 PIWO APPENDICES 50 Annual Change = 7.75% p<0.001 n = 18 stands Annual Change = 3.22% p=0.01 n = 52 stands

67 PUFI APPENDICES 51 Annual Change = -1.88% p=0.31 n = 12 stands Annual Change = 4.26% p=0.02 n = 9 stands

68 RBGR APPENDICES 52 Annual Change = 1.02% p=0.21 n = 86 stands Annual Change = -0.05% p=0.98 n = 121 stands

69 RBNU APPENDICES 53 Annual Change = 8.36% p<0.001 n = 80 stands Annual Change = 4.68% p<0.001 n = 122 stands

70 RCKI APPENDICES 54 Annual Change = 9.71% p<0.001 n = 22 stands

71 REVI APPENDICES 55 Annual Change = 1.14% p<0.001 n = 126 stands Annual Change = -0.09% p=0.69 n = 147 stands

72 RTHU APPENDICES 56 Annual Change = -0.40% p=0.93 n = 6 stands

73 RUGR APPENDICES 57 Annual Change = -6.60% p<0.001 n = 23 stands

74 RWBL APPENDICES 58 Annual Change = -0.50% p=0.71 n = 15 stands Annual Change = 3.54% p=0.37 n = 7 stands

75 SCTA APPENDICES 59 Annual Change = -0.84% p=0.16 n = 87 stands Annual Change = -1.86% p=0.32 n = 21 stands

76 SOSP APPENDICES 60 Annual Change = -5.32% p<0.001 n = 46 stands Annual Change = -1.67% p=0.34 n = 38 stands

77 SWSP APPENDICES 61 Annual Change = -0.77% p=0.63 n = 37 stands Annual Change = 0.98% p=0.39 n = 23 stands

78 SWTH APPENDICES 62 Annual Change = -2.36% p=0.02 n = 66 stands

79 TEWA APPENDICES 63 Annual Change = -3.04% p=0.63 n = 5 stands

80 VEER APPENDICES 64 Annual Change = 2.17% p<0.001 n = 100 stands Annual Change = -0.70% p=0.17 n = 129 stands

81 WBNU APPENDICES 65 Annual Change = 1.21% p=0.44 n = 32 stands

82 WIWR APPENDICES 66 Annual Change = -1.17% p=0.06 n = 59 stands Annual Change = 0.86% p=0.06 n = 122 stands

83 WOTH APPENDICES 67 Annual Change = 4.33% p=0.03 n = 14 stands Annual Change = -1.42% p=0.84 n = 5 stands

84 WPWA APPENDICES 68 Annual Change = -1.69% p=0.33 n = 8 stands

85 WTSP APPENDICES 69 Annual Change = 1.58% p<0.001 n = 71 stands Annual Change = 1.88% p<0.001 n = 147 stands

86 YBFL APPENDICES 70 Annual Change = -1.24% p=0.38 n = 27 stands Annual Change = -4.76% p<0.001 n = 76 stands

87 YBSA APPENDICES 71 Annual Change = 3.90% p<0.001 n = 95 stands Annual Change = 0.90% p=0.14 n = 109 stands

88 YSFL APPENDICES 72 Annual Change = 3.30% p=0.07 n = 28 stands Annual Change = 2.92% p<0.001 n = 69 stands

89 YTVI APPENDICES 73 Annual Change = -6.01% p<0.001 n = 33 stands

90 YWAR APPENDICES 74 Annual Change = 1.50% p=0.62 n = 14 stands

91 Coniferous Forest Habitat APPENDICES 75 Annual Change = 1.94% p<0.001 n = 123 stands Annual Change = 1.73% p<0.001 n = 147 stands

92 Deciduous Forest Habitat APPENDICES 76 Annual Change = 1.48% p<0.001 n = 126 stands Annual Change = 0.60% p<0.001 n = 147 stands

93 Early-successional Habitat APPENDICES 77 Annual Change = 0.31% p=0.55 n = 124 stands Annual Change = 0.86% p=0.04 n = 147 stands

94 Lowland Coniferous Habitat APPENDICES 78 Annual Change = 0.77% p=0.02 n = 119 stands Annual Change = 1.22% p<0.001 n = 147 stands

95 Mixed Forest Habitat APPENDICES 79 Annual Change = 2.46% p<0.001 n = 126 stands Annual Change = 1.58% p<0.001 n = 147 stands

96 Long-Distance Migrants APPENDICES 80 Annual Change = 1.14% p<0.001 n = 126 stands Annual Change = 0.51% p<0.001 n = 147 stands

97 Permanent Residents APPENDICES 81 Annual Change = 3.08% p<0.001 n = 126 stands Annual Change = 3.11% p<0.001 n = 147 stands

98 Short Distance Migrants APPENDICES 82 Annual Change = 0.77% p<0.001 n = 126 stands Annual Change = 1.77% p<0.001 n = 147 stands

99 Canopy Nesting APPENDICES 83 Annual Change = 1.14% p<0.001 n = 126 stands Annual Change = 2.08% p<0.001 n = 147 stands

100 Cavity Nesting APPENDICES 84 Annual Change = 3.46% p<0.001 n = 126 stands Annual Change = 3.23% p<0.001 n = 146 stands

101 Ground Nesting APPENDICES 85 Annual Change = 1.37% p<0.001 n = 126 stands Annual Change = 0.79% p<0.001 n = 147 stands

102 Shrub or Sub-canopy Nesting APPENDICES 86 Annual Change = 0.56% p=0.03 n = 126 stands Annual Change = 0.52% p=0.02 n = 147 stands

103 APPENDICES 87 Appendix B. Population trend estimates (% annual change) and associated test statistics Chippewa Superior Species Trend P R 2 N Trend P R 2 N Alder Flycatcher ALFL American Crow AMCR American Goldfinch AMGO American Redstart AMRE American Robin AMRO Black-and-white Warbler BAWW Black-billed Cuckoo BBCU Blackburnian Warbler BLBW Black-capped Chickadee BCCH Black-throated Blue Warbler BTBW Black-throated Green Warbler BTNW Blue Jay BLJA Blue-headed Vireo BHVI Broad-winged Hawk BWHA Brown Creeper BRCR Brown-headed Cowbird BHCO Canada Warbler CAWA Cape May Warbler CMWA Cedar Waxwing CEDW Chestnut-sided Warbler CSWA Chipping Sparrow CHSP Common Loon COLO Common Raven CORA Common Yellowthroat COYE Connecticut Warbler CONW Downy Woodpecker DOWO Eastern Wood-Pewee EAWP Evening Grosbeak EVGR Golden-crowned Kinglet GCKI Golden-winged Warbler GRAJ Gray Catbird GRCA Gray Jay GWWA Great Crested Flycatcher GCFL Hairy Woodpecker HAWO Hermit Thrush HETH Indigo Bunting INBU