Streamlining geospatial data processing for isotopic landscape modeling

Abstract

Stable isotopic landscape modeling has become a promising approach for answering research questions in multiple disciplines. However, its application has been hindered by the difficulty for individual researchers to collect, compile, and integrate environmental and isotopic data over large spatial and temporal scales and to develop and interpret geostatistical models. To address these challenges, we developed IsoMAP (http://isomap.org), a science gateway that enables researchers to access and integrate a number of disparate and diverse datasets, develop isoscape models over selected spatiotemporal domains using geostatistical algorithms, predict maps for the stable isotopic ratios, and associate a sample's isotope value with its most likely geographic origin. One main challenge in developing IsoMAP is to efficiently integrate large heterogeneous datasets into the modeling workflow to ensure real-time query response and timely data update. In this paper, we described how the geospatial data processing workflow was implemented in the initial version of gateway and how it has been improved by leveraging the built-in vector and raster data processing capabilities and the materialized view object of the PostgreSQL/PostGIS database. Our experience and lessons learned will be applicable to the development of other geospatial data workflows, a common task in the cyberinfrastructure of many science disciplines.

The validation case on invasive crustaceans of the LifeWatch ERIC Internal Joint Initiative: State of the art and next steps forward

“…It follows that this precious body of information deserves to be properly standardized, managed and disseminated, and made available in the long-term in a stable, reliable, and organized repository. Scientists have long acknowledged the need to build centralized databases for stable isotope data obtained from ecological studies in order to facilitate the integration and re-usability of such data across multiple scientific disciplines (Pauli et al, 2017;Eftimov et al, 2019;Woo et al, 2021). Such a centralized repository of stable isotope data would prevent the time-consuming efforts of data collection from different sources.…”

Leaf water δ18O, δ2H and d‐excess isoscapes for Australia using region‐specific plant parameters and non‐equilibrium vapour

“…The isoscapes developed here, like the global leaf water isoscapes (West et al, 2008), use process-based models to predict isotope ratios. This is in contrast to geostatistical approaches to predict values and/or interpolate between observations (Bowen, 2010a(Bowen, , 2010bWoo et al, 2021). This mechanistic approach is critical for leaf water prediction because leaf water isotope ratios are highly variable spatially and temporally.…”

“…These predictive isoscapes enable examination of isotopic patterns without requiring large reference collections from remote regions, which can be difficult and expensive to generate. Global isoscapes of leaf water have demonstrated the potential of mechanistic models for predicting variations in leaf water oxygen and hydrogen isotope ratios at large spatial scales (West et al, 2008; Woo et al, 2021), but required simplifications that can introduce uncertainties at finer geographic scales. To apply isotope tracers to ecohydrological and forensic questions at more local scales requires high‐resolution, regionally calibrated isoscapes.…”