Developing a vocabulary and ontology for modeling insect natural history data: example data, use cases, and competency questions

Insects are possibly the most taxonomically and ecologically diverse class of multicellular organisms on Earth. Consequently, they provide nearly unlimited opportunities to develop and test ecological and evolutionary hypotheses. Currently, however, large-scale studies of insect ecology, behavior, and trait evolution are impeded by the difficulty in obtaining and analyzing data derived from natural history observations of insects. These data are typically highly heterogeneous and widely scattered among many sources, which makes developing robust information systems to aggregate and disseminate them a significant challenge. As a step towards this goal, we report initial results of a new effort to develop a standardized vocabulary and ontology for insect natural history data. In particular, we describe a new database of representative insect natural history data derived from multiple sources (but focused on data from specimens in biological collections), an analysis of the abstract conceptual areas required for a comprehensive ontology of insect natural history data, and a database of use cases and competency questions to guide the development of data systems for insect natural history data. We also discuss data modeling and technology-related challenges that must be overcome to implement robust integration of insect natural history data

Extreme events drive rapid and dynamic range fluctuations

Climate change is altering species’ distributions globally. Increasing frequency of extreme weather and climate events (EWCEs) is one of the hallmarks of climate change. Despite species redistribution being widely studied in response to long-term climatic trends, the contribution of EWCEs to range shifts is not well understood. We outline how EWCEs can trigger rapid and unexpected range boundary fluctuations by impacting dispersal, establishment, and survival. Whether these mechanisms cause temporary or persistent range shifts depends on the spatiotemporal context and exposure to EWCEs. Using the increasing availability of data and statistical tools to examine EWCE impacts at fine spatiotemporal resolutions on species redistribution will be critical for informing conservation management of ecologically, economically, and culturally important species

Monitoring biodiversity change through effective global coordination

The ability to monitor changes in biodiversity, and their societal impact, is critical to conserving species and managing ecosystems. While emerging technologies increase the breadth and reach of data acquisition, monitoring efforts are still spatially and temporally fragmented, and taxonomically biased. Appropriate long-term information remains therefore limited. The Group on Earth Observations Biodiversity Observation Network (GEO BON) aims to provide a general framework for biodiversity monitoring to support decision makers. Here, we discuss the coordinated observing system adopted by GEO BON, and review challenges and advances in its implementation, focusing on two interconnected core components — the Essential Biodiversity Variables as a standard framework for biodiversity monitoring, and the Biodiversity Observation Networks that support harmonized observation systems — while highlighting their societal relevance

Montane mollusk and crustacean survey of western Colorado: 2003 annual report: a report to the Colorado Division of Wildlife

Includes bibliographical references

The “Minimum Information about an ENvironmental Sequence” (MIENS) specification

We present the Genomic Standards Consortium’s (GSC) “Minimum Information about an ENvironmental Sequence” (MIENS) standard for describing marker genes. Adoption of MIENS will enhance our ability to analyze natural genetic diversity across the Tree of Life as it is currently being documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biospher

Tracking trends in monarch abundances over the 20^thcentury is currently impossible using museum records: a response to Boyle et al. (2019)

AbstractThe onslaught of opportunistic data offers new opportunities to examine biodiversity patterns at large scales. However, the techniques for tracking abundance trends with such data are new and require careful consideration to ensure that variations in sampling effort do not lead to biased estimates. The analysis by Boyle et al. (2019) showing a mid-century increase in monarch abundance followed by a decrease starting in the 1960s used an inappropriate correction with respect to three dimensions of sampling effort: taxonomy, place, and time. When the data presentenced by Boyle et al. (2019) are corrected to account for biases in the collection process, the results of their analyses do not hold. The paucity of data that remain after accounting for spatial and temporal biases suggests that analyses of monarch trends back to the beginning of the 20thare currently not possible. Continued digitization of museum records is needed to provide a firm data basis to estimate population trends.</jats:p

Predicting Phenological Anomaly: a Case Study of Yucca in the Southwestern United States

Abstract Yucca in the American desert Southwest typically flowers in early spring, but a well-documented anomalous bloom event occurred during an unusually cold and wet late fall and early winter 2018–2019. We used citizen science photographs as a means to generate flowering presence and absence data. We fit phenoclimatic models to determine which climate variables are explanatory for normal flowering, and then we tested if the same conditions that drive normal blooming also drove the anomalous blooming event. Flowering for Y. brevifolia and Y. schidigera is driven by complex, nonlinear interactions between daylength, temperature, and precipitation. To our surprise, early-season flowering odds are highest in colder and drier conditions, especially for Joshua trees, but increase with precipitation late-season. However, the models used to fit normal blooming overpredicted the number of anomalous blooms compared to what was actually observed. Thus, predicting anomalous flowering events remains a challenge for quantitative phenological models. Because our model overpredicted the number of anomalous blooms, there are likely other factors, such as biotic interactions or other seasonal factors, which may be especially important in controlling what is presumed to be rare, out-of-season flowering in desert-adapted Yucca.</jats:p

Analyzing a phenological anomaly in Yucca of the southwestern United States

Yucca in the American desert Southwest typically flowers in early spring, but a well-documented anomalous bloom event occurred during an unusually cold and wet late fall and early winter 2018-2019. We used community science photographs to generate flowering presence and absence data. We fit phenoclimatic models to determine which climate variables are explanatory for normal flowering, and then we tested if the same conditions that drive normal blooming also drove the anomalous blooming event. Flowering for Yucca brevifolia (Joshua tree) and Yucca schidigera (Mojave yucca) is driven by complex, nonlinear interactions between daylength, temperature, and precipitation. To our surprise, early-season flowering odds are highest in colder and drier conditions, especially for Joshua trees, but increase with precipitation late-season. However, the models used to fit normal blooming overpredicted the number of anomalous blooms compared to what was actually observed. Thus, predicting anomalous flowering events remains a challenge for quantitative phenological models. Because our model overpredicted the number of anomalous blooms, there are likely other factors, such as biotic interactions or other seasonal factors, which may be especially important in controlling what is presumed to be rare, out-of-season flowering in desert-adapted Yucca