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Katherine D. Jones

Publications and source records attributed to Katherine D. Jones.

3 recordsLinked to original sources

PS3: The Pheno-Synthesis software suite for integration and analysis of multi-scale, multi-platform phenological data

Phenology is the study of recurring plant and animal life-cycle stages which can be observed across spatial and temporal scales that span orders of magnitude (e.g., organisms to landscapes). The variety of scales at which phenological processes operate is reflected in the range of methods for collecting phenologically relevant data, and the programs focused on these collections. Consideration of the scale at which phenological observations are made, and the platform used for observation, is critical for the interpretation of phenological data and the application of these data to both research questions and land management objectives. However, there is currently little capacity to facilitate access, integration and analysis of cross-scale, multi-platform phenological data. This paper reports on a new suite of software and analysis tools – the “Pheno-Synthesis Software Suite,” or PS3 – to facilitate integration and analysis of phenological and ancillary data, enabling investigation and interpretation of phenological processes at scales ranging from organisms to landscapes and from days to decades. We use PS3 to investigate phenological processes in a semi-aride, mixed shrub-grass ecosystem, and find that the apparent importance of seasonal precipitation to vegetation activity (i.e., “greenness”) is affected by the scale and platform of observation. We end by describing potential applications of PS3 to phenological modeling and forecasting, understanding patterns and drivers of phenological activity in real-world ecosystems, and supporting agricultural and natural resource management and decision-making.

Ecological Informatics

Landslides triggered by the 14 November 2016 Mw 7.8 Kaikōura Earthquake, New Zealand

The 14 November 2016 M w "> M w Mw 7.8 Kaikōura earthquake generated more than 10,000 landslides over a total area of about 10 , 000    km 2 "> 10 , 000 km 2 10,000 km2 , with the majority concentrated in a smaller area of about 3600    km 2 "> 3600 km 2 3600 km2 . The largest landslide triggered by the earthquake had an approximate volume of 20 ( ± 2 )    M   m 3 "> 20 ( ± 2 ) M m 3 20(±2) M m3 , with a runout distance of about 2.7 km, forming a dam on the Hapuku River. In this article, we present version 1.0 of the landslide inventory we have created for this event. We use the inventory presented in this article to identify and discuss some of the controls on the spatial distribution of landslides triggered by the Kaikōura earthquake. Our main findings are (1) the number of medium to large landslides (source area ≥ 10 , 000    m 2 "> ≥ 10 , 000 m 2 ≥10,000 m2 ) triggered by the Kaikōura earthquake is smaller than for similar‐sized landslides triggered by similar magnitude earthquakes in New Zealand; (2) seven of the largest eight landslides (from 5 to 20    M   m 3 "> 20 M m 3 20 M m3 ) occurred on faults that ruptured to the surface during the earthquake; (3) the average landslide density within 200 m of a mapped surface fault rupture is three times that at a distance of 2500 m or more from a mapped surface fault rupture; (4) the “distance to fault” predictor variable, when used as a proxy for ground‐motion intensity, and when combined with slope angle, geology, and elevation variables, has more power in predicting landslide probability than the modeled peak ground acceleration or peak ground velocity; and (5) for the same slope angles, the coastal slopes have landslide point densities that are an order of magnitude greater than those in similar materials on the inland slopes, but their source areas are significantly smaller.

Bulletin of the Seismological Society of America

The plant phenology monitoring design for the National Ecological Observatory Network

Phenology is an integrative science that comprises the study of recurring biological activities or events. In an era of rapidly changing climate, the relationship between the timing of those events and environmental cues such as temperature, snowmelt, water availability or day length are of particular interest. This article provides an overview of the plant phenology sampling which will be conducted by the U.S. National Ecological Observatory Network NEON, the resulting data, and the rationale behind the design. Trained technicians will conduct regular in situ observations of plant phenology at all terrestrial NEON sites for the 30-year life of the observatory. Standardized and coordinated data across the network of sites can be used to quantify the direction and magnitude of the relationships between phenology and environmental forcings, as well as the degree to which these relationships vary among sites, among species, among phenophases, and through time. Vegetation at NEON sites will also be monitored with tower-based cameras, satellite remote sensing and annual high-resolution airborne remote sensing. Ground-based measurements can be used to calibrate and improve satellite-derived phenometrics. NEON’s phenology monitoring design is complementary to existing phenology research efforts and citizen science initiatives throughout the world and will produce interoperable data. By collocating plant phenology observations with a suite of additional meteorological, biophysical and ecological measurements (e.g., climate, carbon flux, plant productivity, population dynamics of consumers) at 47 terrestrial sites, the NEON design will enable continentalscale inference about the status, trends, causes and ecological consequences of phenological change.

Ecosphere