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

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

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

The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.U.S. Geological Survey [G16AC00268]; U.S. National Science Foundation (NSF) [NSF-SAVI 1321595]; NSF [DBI-0735191, DBI-1265383]Open access journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Identifiers as Mechanisms for Linking Archaeological Data across Repositories

Zooarchaeological specimens are the remains of animals, including vertebrate and invertebrate taxa, recovered from, or in association with, archaeological contexts of deposition or surrounding landscapes. The physical scope of zooarchaeological specimens is diverse and includes macro- and micro-zooarchaeological specimens composed of archaeologically preserved bone, shell, exoskeletons, teeth, hair or fur, scales, horns or antlers, as well as geochemical (e.g., isotopes) and biochemical (e.g., ancient DNA) signatures derived from faunal remains. Artifacts and objects created from animal remains, such as bone pins, shell beads, preserved animal hides, are also zooarchaeological specimens. Here we present recent work to utilize identifiers for archaeological samples in new data publishing routines, focusing on key challenges. One critical challenge is that archaeological samples are often composited into different units depending on managers of collections and analysts. Thus, in some cases, when migrating datasets for publication, identifiers can refer to different sets of units, even within the same dataset. Another key challenge is assuring that different repositories can share sample identifiers. We show how Open Context, a site-based archaeology-focused repository that also manages objects such as zooarchaeological material, and VertNet, a specimen-oriented biodiversity repository, have collaborated to share sample identifiers. While this illustrates a success story of linking data across repositories, we discuss the complexity of how "occurrence identifiers," but not true sample identifiers, in VertNet are propagated to another system where the identifiers point to a similar record called "Animal Bone" in Open Context

Data_Sheet_1_The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data.pdf

<p>Plant phenology – the timing of plant life-cycle events, such as flowering or leafing out – plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.</p