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• 11. [Article] Evaluation of Juvenile Salmonid Outmigration and Survival in the Lower Umatilla River Basin; Annual Report 2017

  Abstract -- This report summarizes Umatilla River steelhead monitoring and Three Mile Falls Dam (TMFD) PIT tag detection system operations for calendar year 2017. This report also includes updates to long-term ...

  Citation × Citation Citation Abstract Copy Title: Evaluation of Juvenile Salmonid Outmigration and Survival in the Lower Umatilla River Basin; Annual Report 2017 Abstract -- This report summarizes Umatilla River steelhead monitoring and Three Mile Falls Dam (TMFD) PIT tag detection system operations for calendar year 2017. This report also includes updates to long-term status and trend data for the ESA-listed Umatilla steelhead population, which is a large population within the Umatilla/Walla Walla Major Population Group. The project used two fixed site traps, PIT tags, and mark-recapture to assess the status and trend of juvenile abundance and productivity, estimate survival rates, and monitor life history characteristics. Spatial distribution and density of summer steelhead redds were determined using a spatially balanced random sample (Generalized Random Tessellation Stratified) within a temporally based panel design. Redd distribution data was collected from 25–35 individual sites. Title: Evaluation of Juvenile Salmonid Outmigration and Survival in the Lower Umatilla River Basin; Annual Report 2017 Abstract -- This report summarizes Umatilla River steelhead monitoring and Three Mile Falls Dam (TMFD) PIT tag detection system operations for calendar year 2017. This report also includes updates to long-term status and trend data for the ESA-listed Umatilla steelhead population, which is a large population within the Umatilla/Walla Walla Major Population Group. The project used two fixed site traps, PIT tags, and mark-recapture to assess the status and trend of juvenile abundance and productivity, estimate survival rates, and monitor life history characteristics. Spatial distribution and density of summer steelhead redds were determined using a spatially balanced random sample (Generalized Random Tessellation Stratified) within a temporally based panel design. Redd distribution data was collected from 25–35 individual sites. Close

• 12. [Article] Enhanced Computer Graphics for Decision Makers

  Words need a context to be understood. Visual patterns also need a context to convey their meaning. When patterns represent quantities in business graphics, decision makers (DMs) depend on contrasting ...

  Citation × Citation Citation Abstract Copy Title: Enhanced Computer Graphics for Decision Makers Author: Brock, Floyd James, Jr. Year: 1986 Words need a context to be understood. Visual patterns also need a context to convey their meaning. When patterns represent quantities in business graphics, decision makers (DMs) depend on contrasting visual contexts to discern patterns and discover relationships. Depending on the context in which DMs see trends, differences between two trends may point to a problem, to continuity, or to an opportunity. Can enhancing the context in computer graphics help DMs visualize problems? To answer this research question, three experiments were done in the field on computer graphics. One hundred five DMs tried 17 different contexts for time-series trends displayed on a microcomputer monitor. The research objective was to find out whether changing the context in graphics affected the decision efficiency (accuracy/response time) of DMs in determining relationships among trends. Essential for measuring the effect were interactive computer programs that displayed random trends in graphics of differing contexts, collected the DMs' answers to questions about the trends, and graded 1133 graphics based on the answers, response times, and trend data. The experimental results supported the hypothesis that computers can enhance the visual context surrounding time-series trends so that DMs can better visualize problems. Results were based on comparisons of DMs' decision efficiencies between trial graphics with differing contextual enhancements and based on answers to questions about the trial graphics. The results were tested with nonparametric statistics at the 0.05 significance level. Specific findings were: (1) Computer-supplied forecasts, as an enhancement, significantly helped DMs discover differences among trends. (2) Although not statistically significant, stratified presentation of trends and fading chartjunk tended to increase DMs' efficiencies. (3) Adding two colors, as an enhancement, made no difference in efficiency over black and white. (4) Paired trends in windows did not affect efficiency significantly. (5) Sequentially traced trends and composites of enhancements did not affect efficiency significantly. (6) DMs preferred stratified trends most and had the most confidence in graphics with fading context. They least liked and had the least confidence in black-and-white graphics. Title: Enhanced Computer Graphics for Decision Makers Author: Brock, Floyd James, Jr. Year: 1986 Words need a context to be understood. Visual patterns also need a context to convey their meaning. When patterns represent quantities in business graphics, decision makers (DMs) depend on contrasting visual contexts to discern patterns and discover relationships. Depending on the context in which DMs see trends, differences between two trends may point to a problem, to continuity, or to an opportunity. Can enhancing the context in computer graphics help DMs visualize problems? To answer this research question, three experiments were done in the field on computer graphics. One hundred five DMs tried 17 different contexts for time-series trends displayed on a microcomputer monitor. The research objective was to find out whether changing the context in graphics affected the decision efficiency (accuracy/response time) of DMs in determining relationships among trends. Essential for measuring the effect were interactive computer programs that displayed random trends in graphics of differing contexts, collected the DMs' answers to questions about the trends, and graded 1133 graphics based on the answers, response times, and trend data. The experimental results supported the hypothesis that computers can enhance the visual context surrounding time-series trends so that DMs can better visualize problems. Results were based on comparisons of DMs' decision efficiencies between trial graphics with differing contextual enhancements and based on answers to questions about the trial graphics. The results were tested with nonparametric statistics at the 0.05 significance level. Specific findings were: (1) Computer-supplied forecasts, as an enhancement, significantly helped DMs discover differences among trends. (2) Although not statistically significant, stratified presentation of trends and fading chartjunk tended to increase DMs' efficiencies. (3) Adding two colors, as an enhancement, made no difference in efficiency over black and white. (4) Paired trends in windows did not affect efficiency significantly. (5) Sequentially traced trends and composites of enhancements did not affect efficiency significantly. (6) DMs preferred stratified trends most and had the most confidence in graphics with fading context. They least liked and had the least confidence in black-and-white graphics. Close

• 13. [Article] Strategic Planning Development Team Meeting Notes 5/14/2015

  Each member of the group receives a copy of Chronicle of Higher Education’s Trends Report for 2015. Using this document, the SPDT develop main trends that impact PSU. Some of these trends include focusing ...

  Citation × Citation Citation Abstract Copy Title: Strategic Planning Development Team Meeting Notes 5/14/2015 Author: Strategic Planning Development Team Year: 2015 Each member of the group receives a copy of Chronicle of Higher Education’s Trends Report for 2015. Using this document, the SPDT develop main trends that impact PSU. Some of these trends include focusing on employability and alignment of academics with career prep, and student indebtedness. The committee continues their dialogue from previous meetings talking about national trends in college, from the previous meeting. Title: Strategic Planning Development Team Meeting Notes 5/14/2015 Author: Strategic Planning Development Team Year: 2015 Each member of the group receives a copy of Chronicle of Higher Education’s Trends Report for 2015. Using this document, the SPDT develop main trends that impact PSU. Some of these trends include focusing on employability and alignment of academics with career prep, and student indebtedness. The committee continues their dialogue from previous meetings talking about national trends in college, from the previous meeting. Close

• 14. [Article] Open Innovation Trend in Semiconductor Industry - A Foundry's Perspective

  Open Innovation is the new paradigm that most of the industries are incorporating in order to enhance mutual firm-customer value. Companies are bringing customers, suppliers, and partners under the common ...

  Citation × Citation Citation Abstract Copy Title: Open Innovation Trend in Semiconductor Industry - A Foundry's Perspective Author: Murthy, Mamatha, Lin, Chihsun, Honnappa, Lokesh, Xu, Yuan Year: 2011 Open Innovation is the new paradigm that most of the industries are incorporating in order to enhance mutual firm-customer value. Companies are bringing customers, suppliers, and partners under the common goal of shortening design time, minimizing time-to-volume and speeding time-to-market and ultimately time-to-money. This paper analyzes the trend of open innovation in top pure-play foundries through literature research. Case study company, TSMC, is evaluated against a set of criteria that were derived out of the general trend in top foundries such as Chartered Semiconductor, UMC, Global Foundries and SMIC. The results show an increasing trend in the adoption of a collaborative style of open innovation in these companies. Title: Open Innovation Trend in Semiconductor Industry - A Foundry's Perspective Author: Murthy, Mamatha, Lin, Chihsun, Honnappa, Lokesh, Xu, Yuan Year: 2011 Open Innovation is the new paradigm that most of the industries are incorporating in order to enhance mutual firm-customer value. Companies are bringing customers, suppliers, and partners under the common goal of shortening design time, minimizing time-to-volume and speeding time-to-market and ultimately time-to-money. This paper analyzes the trend of open innovation in top pure-play foundries through literature research. Case study company, TSMC, is evaluated against a set of criteria that were derived out of the general trend in top foundries such as Chartered Semiconductor, UMC, Global Foundries and SMIC. The results show an increasing trend in the adoption of a collaborative style of open innovation in these companies. Close

• 15. [Article] Not That Kind of Publisher: How NovelRank and BookScan Can Benefit Small Publishers' Marketing and Promotions

  How can NovelRank be used for more than simply tracking the ranking of a given title in the Amazon ecosystem, but rather identifying sales trends across a group of titles? For a group of titles of your ...

  Citation × Citation Citation Abstract Copy Title: Not That Kind of Publisher: How NovelRank and BookScan Can Benefit Small Publishers' Marketing and Promotions Author: Wallace, Geoff Year: 2015 How can NovelRank be used for more than simply tracking the ranking of a given title in the Amazon ecosystem, but rather identifying sales trends across a group of titles? For a group of titles of your choosing, what kinds of sales trends can be identified using this method? How do the trends identified using NovelRank for this group of titles compare to the trends that can be identified using Nielsen BookScan? Title: Not That Kind of Publisher: How NovelRank and BookScan Can Benefit Small Publishers' Marketing and Promotions Author: Wallace, Geoff Year: 2015 How can NovelRank be used for more than simply tracking the ranking of a given title in the Amazon ecosystem, but rather identifying sales trends across a group of titles? For a group of titles of your choosing, what kinds of sales trends can be identified using this method? How do the trends identified using NovelRank for this group of titles compare to the trends that can be identified using Nielsen BookScan? Close

• 16. [Article] Climate-Driven Variability and Trends in Mountain Snowpack in Western North America

  Records of 1 April snow water equivalent (SWE) are examined here using multiple linear regression against reference time series of temperature and precipitation. This method permits 1) an examination of ...

  Citation × Citation Citation Abstract Copy Title: Climate-Driven Variability and Trends in Mountain Snowpack in Western North America Author: Mote, Philip W. Records of 1 April snow water equivalent (SWE) are examined here using multiple linear regression against reference time series of temperature and precipitation. This method permits 1) an examination of the separate roles of temperature and precipitation in determining the trends in SWE; 2) an estimation of the sensitivity of SWE to warming trends, and its distribution across western North America and as a function of elevation; and 3) inferences about responses of SWE to future warming. These results emphasize the sensitivity to warming of the mountains of northern California and the Cascades of Oregon and Washington. In addition, the contribution of modes of Pacific climate variability is examined and found to be responsible for about 10%–60% of the trends in SWE, depending on the period of record and climate index. Title: Climate-Driven Variability and Trends in Mountain Snowpack in Western North America Author: Mote, Philip W. Records of 1 April snow water equivalent (SWE) are examined here using multiple linear regression against reference time series of temperature and precipitation. This method permits 1) an examination of the separate roles of temperature and precipitation in determining the trends in SWE; 2) an estimation of the sensitivity of SWE to warming trends, and its distribution across western North America and as a function of elevation; and 3) inferences about responses of SWE to future warming. These results emphasize the sensitivity to warming of the mountains of northern California and the Cascades of Oregon and Washington. In addition, the contribution of modes of Pacific climate variability is examined and found to be responsible for about 10%–60% of the trends in SWE, depending on the period of record and climate index. Close

• 17. [Article] Retail Seafood: A New Paradigm

  The presenter discusses supply trends, consumer trends, retail trends and new product opportunities.

  Citation × Citation Citation Abstract Copy Title: Retail Seafood: A New Paradigm Author: Johnson, Howard M. Year: 2001 The presenter discusses supply trends, consumer trends, retail trends and new product opportunities. Title: Retail Seafood: A New Paradigm Author: Johnson, Howard M. Year: 2001 The presenter discusses supply trends, consumer trends, retail trends and new product opportunities. Close

• 18. [Article] Long-Term Sea Surface Temperature Variability along the U.S. East Coast

  Sea surface temperature variations along the entire U.S. East Coast from 1875 to 2007 are characterized using a collection of historical observations from lighthouses and lightships combined with recent ...

  Citation × Citation Citation Abstract Copy Title: Long-Term Sea Surface Temperature Variability along the U.S. East Coast Author: Shearman, R. Kipp, Lentz, Steven J. Sea surface temperature variations along the entire U.S. East Coast from 1875 to 2007 are characterized using a collection of historical observations from lighthouses and lightships combined with recent buoy and shore-based measurements. Long-term coastal temperature trends are warming in the Gulf of Maine [1.0° ± 0.3°C (100 yr)⁻¹] and Middle Atlantic Bight [0.7° ± 0.3°C (100 yr)⁻¹], whereas trends are weakly cooling or not significant in the South Atlantic Bight [−0.1° ± 0.3°C (100 yr)⁻¹] and off Florida [−0.3° ± 0.2°C (100 yr)⁻¹]. Over the last century, temperatures along the northeastern U.S. coast have warmed at a rate 1.8–2.5 times the regional atmospheric temperature trend but are comparable to warming rates for the Arctic and Labrador, the source of coastal ocean waters north of Cape Hatteras (36°N). South of Cape Hatteras, coastal ocean temperature trends match the regional atmospheric temperature trend. The observations and a simple model show that along-shelf transport, associated with the mean coastal current system running from Labrador to Cape Hatteras, is the mechanism controlling long-term temperature changes for this region and not the local air–sea exchange of heat. Title: Long-Term Sea Surface Temperature Variability along the U.S. East Coast Author: Shearman, R. Kipp, Lentz, Steven J. Sea surface temperature variations along the entire U.S. East Coast from 1875 to 2007 are characterized using a collection of historical observations from lighthouses and lightships combined with recent buoy and shore-based measurements. Long-term coastal temperature trends are warming in the Gulf of Maine [1.0° ± 0.3°C (100 yr)⁻¹] and Middle Atlantic Bight [0.7° ± 0.3°C (100 yr)⁻¹], whereas trends are weakly cooling or not significant in the South Atlantic Bight [−0.1° ± 0.3°C (100 yr)⁻¹] and off Florida [−0.3° ± 0.2°C (100 yr)⁻¹]. Over the last century, temperatures along the northeastern U.S. coast have warmed at a rate 1.8–2.5 times the regional atmospheric temperature trend but are comparable to warming rates for the Arctic and Labrador, the source of coastal ocean waters north of Cape Hatteras (36°N). South of Cape Hatteras, coastal ocean temperature trends match the regional atmospheric temperature trend. The observations and a simple model show that along-shelf transport, associated with the mean coastal current system running from Labrador to Cape Hatteras, is the mechanism controlling long-term temperature changes for this region and not the local air–sea exchange of heat. Close

• 19. [Article] Declining Attendance Trends in Collegiate and Professional Sports

  83 pages. A thesis presented to the Lundquist College of Business and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree of Bachelor of Science, ...

  Citation × Citation Citation Abstract Copy Title: Declining Attendance Trends in Collegiate and Professional Sports Author: Grenier-Hemphill, Ronnie Year: 2015 83 pages. A thesis presented to the Lundquist College of Business and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree of Bachelor of Science, Spring 2015. Title: Declining Attendance Trends in Collegiate and Professional Sports Author: Grenier-Hemphill, Ronnie Year: 2015 83 pages. A thesis presented to the Lundquist College of Business and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree of Bachelor of Science, Spring 2015. Close

• 20. [Article] Effects of spatial scale and heterogeneity on avian occupancy dynamics and population trends in forested mountain landscapes

  Population trends and patterns in species distributions are the major currencies used to examine responses by biodiversity to changing environments. Effective conservation recommendations require that ...

  Citation × Citation Citation Abstract Copy Title: Effects of spatial scale and heterogeneity on avian occupancy dynamics and population trends in forested mountain landscapes Author: Frey, Sarah Jean Kiuama Population trends and patterns in species distributions are the major currencies used to examine responses by biodiversity to changing environments. Effective conservation recommendations require that models of both distribution dynamics and population trends accurately reflect reality. However, identification of the appropriate temporal and spatial scales of animal response, and then obtaining data at these scales present two major challenges to developing predictive models. In heterogeneous forested mountain landscapes I examined: A) the relative drivers of climatic variability at fine spatial scales under the forest canopy ('microclimate'), B) the influence of microclimate on local-scale occupancy dynamics of bird communities, and C) the effects of spatial scale and imperfect bird detection on long-term avian population trends. Climate change has been predicted to cause widespread biodiversity declines. However, the capacity of climate envelope models for predicting the future of biodiversity has been questioned due to the mismatch between the scale of available data (i.e., global climate models) and the scales at which organisms experience their environment. Local-scale variation in microclimate is hypothesized to provide potential ‘microrefugia’ for biodiversity, but the relative role of elevation, microtopography, and vegetation structure in driving microclimate is not well known. If the microrefugia hypothesis is true, I expected to see areas on the landscape that remained relatively cooler (i.e., buffered sites). To test this, I collected temperature data at 183 sites across elevation and forest structure gradients in complex terrain of the H. J. Andrews Experimental Forest in the Cascade Mountains of Oregon, USA (Chapter 2). I used boosted regression trees, a novel machine learning approach, to determine the relative influence of vegetation structure, microtopography, and elevation as drivers of microclimate and mapped fine-scale distributions of temperature across the landscape. Models performed extremely well on independent data - cross-validation correlations between testing and training data were 0.69 - 0.98 for ten selected climate variables. Elevation was the dominant driver in fine-scale microclimate patterns, although vegetation and microtopography also showed substantial relative influences. For instance, during the spring-summer transition, maximum monthly temperatures observed in old-growth sites were 2.6°C (95% CI: 1.8 - 3.3°C) cooler than plantation sites and minimum temperatures during winter months were 0.6°C (95% CI: 0.4 - 0.8°C) warmer. This suggests that older forest stands mediate changes in temperature by buffering against warming during summer months and moderating cold temperatures during the winter. Climate is generally considered most influential on species distributions at large spatial scales; however much microclimate variability exists within regional patterns. I tested whether this high degree of microclimate variability has relevance for predicting species distributions and occupancy dynamics of the Andrews Forest bird community. I collected bird occurrence data in 2012 and 2013 at all 183 sites with fine-scale temperature measurements. I used dynamic occupancy models to test the effects of temperature on occupancy and apparent within-season bird movement while statistically accounting for vegetation effects and imperfect bird detection (Chapter 3). Most species (87%) exhibited within-season shifts in response to local-scale temperature metrics. Effects of temperature on within-season occupancy dynamics were as large or larger (1 to 1.7 times) than vegetation. However, individual species were almost as likely to shift toward warmer sites as toward cooler sites, suggesting that microclimate preferences are species-specific. My results emphasize that high-resolution temperature data provide valuable insight into avian distribution dynamics in montane forest environments and that microclimate is an important variable in breeding season habitat selection by forest birds. I hypothesize that microclimate-associated distribution shifts may reflect species' potential for behavioral buffering from climate change in complex terrain. Factors influencing population trends often differ depending on the spatial scale under consideration. Further, accurate estimation of trends requires accounting for biases caused by imperfect detection. To test the degree to which population trends are consistent across scales, I estimated landscape-scale bird population trends from 1999-2012 for 38 species at the Hubbard Brook Experimental Forest (HBEF) in the White Mountains of New Hampshire, USA and compared them to regional and local trends (Chapter 4). I used a new method - open-population binomial mixture models - to test the hypothesis that imperfect detection in bird sampling has the potential to bias trend estimates. I also tested for generalities in species responses by predicting population trends as a function of life history and ecological traits. Landscape-scale trends were correlated with regional and local trends, but generally these correlations were weak (r = 0.12 - 0.4). Further, more species were declining at the regional scale compared to within the relatively undisturbed HBEF. Life history and ecological traits did not explain any of the variability in the HBEF trends. However, at the regional scale, species that occurred at higher elevations were more likely to be declining and species associated with older forests have increased. I hypothesize that these differences could be attributed to both elevated rates of land-use change in the broader region and the fact that the structure of regional data did not permit modeling of imperfect detection. Indeed, accounting for imperfect detection resulted in more accurate population trend estimates at the landscape scale; without accounting for detection we would have both missed trends and falsely identified trends where none existed. These results highlight two important cautions for trend analysis: 1) population trends estimated at fine spatial scales may not be extrapolated to broader scales and 2) accurate trends require accounting for imperfect detection. Title: Effects of spatial scale and heterogeneity on avian occupancy dynamics and population trends in forested mountain landscapes Author: Frey, Sarah Jean Kiuama Population trends and patterns in species distributions are the major currencies used to examine responses by biodiversity to changing environments. Effective conservation recommendations require that models of both distribution dynamics and population trends accurately reflect reality. However, identification of the appropriate temporal and spatial scales of animal response, and then obtaining data at these scales present two major challenges to developing predictive models. In heterogeneous forested mountain landscapes I examined: A) the relative drivers of climatic variability at fine spatial scales under the forest canopy ('microclimate'), B) the influence of microclimate on local-scale occupancy dynamics of bird communities, and C) the effects of spatial scale and imperfect bird detection on long-term avian population trends. Climate change has been predicted to cause widespread biodiversity declines. However, the capacity of climate envelope models for predicting the future of biodiversity has been questioned due to the mismatch between the scale of available data (i.e., global climate models) and the scales at which organisms experience their environment. Local-scale variation in microclimate is hypothesized to provide potential ‘microrefugia’ for biodiversity, but the relative role of elevation, microtopography, and vegetation structure in driving microclimate is not well known. If the microrefugia hypothesis is true, I expected to see areas on the landscape that remained relatively cooler (i.e., buffered sites). To test this, I collected temperature data at 183 sites across elevation and forest structure gradients in complex terrain of the H. J. Andrews Experimental Forest in the Cascade Mountains of Oregon, USA (Chapter 2). I used boosted regression trees, a novel machine learning approach, to determine the relative influence of vegetation structure, microtopography, and elevation as drivers of microclimate and mapped fine-scale distributions of temperature across the landscape. Models performed extremely well on independent data - cross-validation correlations between testing and training data were 0.69 - 0.98 for ten selected climate variables. Elevation was the dominant driver in fine-scale microclimate patterns, although vegetation and microtopography also showed substantial relative influences. For instance, during the spring-summer transition, maximum monthly temperatures observed in old-growth sites were 2.6°C (95% CI: 1.8 - 3.3°C) cooler than plantation sites and minimum temperatures during winter months were 0.6°C (95% CI: 0.4 - 0.8°C) warmer. This suggests that older forest stands mediate changes in temperature by buffering against warming during summer months and moderating cold temperatures during the winter. Climate is generally considered most influential on species distributions at large spatial scales; however much microclimate variability exists within regional patterns. I tested whether this high degree of microclimate variability has relevance for predicting species distributions and occupancy dynamics of the Andrews Forest bird community. I collected bird occurrence data in 2012 and 2013 at all 183 sites with fine-scale temperature measurements. I used dynamic occupancy models to test the effects of temperature on occupancy and apparent within-season bird movement while statistically accounting for vegetation effects and imperfect bird detection (Chapter 3). Most species (87%) exhibited within-season shifts in response to local-scale temperature metrics. Effects of temperature on within-season occupancy dynamics were as large or larger (1 to 1.7 times) than vegetation. However, individual species were almost as likely to shift toward warmer sites as toward cooler sites, suggesting that microclimate preferences are species-specific. My results emphasize that high-resolution temperature data provide valuable insight into avian distribution dynamics in montane forest environments and that microclimate is an important variable in breeding season habitat selection by forest birds. I hypothesize that microclimate-associated distribution shifts may reflect species' potential for behavioral buffering from climate change in complex terrain. Factors influencing population trends often differ depending on the spatial scale under consideration. Further, accurate estimation of trends requires accounting for biases caused by imperfect detection. To test the degree to which population trends are consistent across scales, I estimated landscape-scale bird population trends from 1999-2012 for 38 species at the Hubbard Brook Experimental Forest (HBEF) in the White Mountains of New Hampshire, USA and compared them to regional and local trends (Chapter 4). I used a new method - open-population binomial mixture models - to test the hypothesis that imperfect detection in bird sampling has the potential to bias trend estimates. I also tested for generalities in species responses by predicting population trends as a function of life history and ecological traits. Landscape-scale trends were correlated with regional and local trends, but generally these correlations were weak (r = 0.12 - 0.4). Further, more species were declining at the regional scale compared to within the relatively undisturbed HBEF. Life history and ecological traits did not explain any of the variability in the HBEF trends. However, at the regional scale, species that occurred at higher elevations were more likely to be declining and species associated with older forests have increased. I hypothesize that these differences could be attributed to both elevated rates of land-use change in the broader region and the fact that the structure of regional data did not permit modeling of imperfect detection. Indeed, accounting for imperfect detection resulted in more accurate population trend estimates at the landscape scale; without accounting for detection we would have both missed trends and falsely identified trends where none existed. These results highlight two important cautions for trend analysis: 1) population trends estimated at fine spatial scales may not be extrapolated to broader scales and 2) accurate trends require accounting for imperfect detection. Close