Long-term monitoring and research projects are essential to understand ecological change and the effectiveness of management activities. An inherent characteristic of long-term projects is the need for consistent data collection over time, requiring rigorous attention to data management and quality assurance. Recent papers have provided broad recommendations for data management; however, practitioners need more detailed guidance and examples. We present general yet detailed guidance for the development of comprehensive, concise, and effective data management for monitoring projects. The guidance is presented as a graded approach, matching the scale of data management to the needs of the organization and the complexity of the project. We address the following topics: roles and responsibilities; consistent and precise data collection; calibration of field crews and instrumentation; management of tabular, photographic, video, and sound data; data completeness and quality; development of metadata; archiving data; and evaluation of existing data from other sources. This guidance will help practitioners execute effective data management, thereby, improving the quality and usability of data for meeting project objectives as well as broader meta-analysis and macrosystem ecology research.

We examined spatial relations of arrested stomatal initials and their differentiated state on leaves of the monocotyledon Tradescantia. The placement and proximity of stomata and arrested stomatal initials to the five nearest stomata were studied to test the hypothesis that if developing stomatal initials occur too close to one another, initials will arrest. The results showed that arrested stomatal initials were not randomly placed, but were closely associated with another stoma, most often in an adjacent cell file. The distance to their nearest stomatal neighbors was less than the equivalent distance between stomata that mature. After stomatal initials form, their position within or across cell files was not adjusted by cell division or expansion. Synergistic effects from several neighboring stomata could not be linked to stomatal arrest; rather, arrest was associated only with the nearest stomatal neighbor. Since the arrest of stomatal initials was distance dependent, a failure intrinsic to the arrested initials is not solely responsible for halting stomatal development. These data show that an inhibitory mechanism adjusts stomatal development to influence the final distribution of Tradescantia stomata. The pigmentation and expansion characteristics of arrested stomatal initials were like those of epidermal cells, indicating that the initials did not remain halted at a specific point in their development. The capacity of arrested initials to differentiate in the epidermal cell pathway indicates that they remain pluripotent after their initial specification and that the opportunity for patterning is long enough to permit their entry into the epidermal cell pathway.

Abstract. Monitoring species in National Parks facilitates inference regarding effects of climate change on population dynamics because parks are relatively unaffected by other forms of anthropogenic disturbance. Even at early points in a monitoring program, identifying climate covariates of population density can suggest vulnerabilities to future change. Monitoring landbird populations in parks during the breeding season brings the added benefit of allowing a comparative approach to inference across a large suite of species with diverse requirements. For example, comparing resident and migratory species that vary in exposure to non-park habitats can reveal the relative importance of park effects, such as those related to local climate. We monitored landbirds using breeding-season point-count data collected during 2005-2014 in three wilderness areas of the Pacific Northwest (Mount Rainier, North Cascades, and Olympic National Parks). For 39 species, we estimated recent trends in population density while accounting for individual detection probability using Bayesian hierarchical N-mixture models. Our analyses integrated several recent developments in N-mixture modeling, incorporating interval and distance sampling to estimate distinct components of detection probability while also accommodating count intervals of varying duration, annual variation in the length and number of point-count transects, spatial autocorrelation, random effects, and covariates of detection and density. As covariates of density, we considered metrics of precipitation and temperature hypothesized to affect breeding success. We also considered effects of park and elevational stratum on trend. Regardless of model structure, we estimated stable or increasing densities during 2005-2014 for most populations. Mean trends across species were positive for migrants in every park and for residents in one park. A recent snowfall deficit in this region might have contributed to the positive trend, because population density varied inversely with precipitation-as-snow for both migrants and residents. Densities varied directly but much more weakly with mean spring temperature. Our approach exemplifies an analytical framework for estimating trends from point-count data, and for assessing the role of climatic and other spatiotemporal variables in driving those trends. Understanding population trends and the factors that drive them is critical for adaptive management and resource stewardship in the context of climate change.

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