Fire has transformative effects on soil biological, chemical, and physical properties in terrestrial ecosystems around the world. While methods for estimating fire characteristics and associated effects aboveground have progressed in recent decades, there remain major challenges in characterizing soil heating and associated effects belowground. Overcoming these challenges is crucial for understanding how fire influences soil carbon storage, biogeochemical cycling, and ecosystem recovery. In this paper, we present a novel framework for characterizing belowground heating and effects. The framework includes (1) an open‐source model to estimate fire‐driven soil heating, cooling, and the biotic effects of heating across depths and over time (Soil Heating in Fire model; SheFire) and (2) a simple field method for recording soil temperatures at multiple depths using self‐contained temperature sensor and data loggers (i.e., iButtons), installed along a wooden stake inserted into the soil (i.e., an iStake). The iStake overcomes many logistical challenges associated with obtaining temperature profiles using thermocouples. Heating measurements provide inputs to the SheFire model, and modeled soil heating can then be used to derive ecosystem response functions, such as heating effects on microorganisms and tissues. To validate SheFire estimates, we conducted a burn table experiment using iStakes to record temperatures that were in turn used to fit the SheFire model. We then compared SheFire predicted temperatures against measured temperatures at other soil depths. To benchmark iStake measurements against those recorded by thermocouples, we co‐located both types of sensors in the burn table experiment. We found that SheFire demonstrated skill in interpolating and extrapolating soil temperatures, with the largest errors occurring at the shallowest depths. We also found that iButton sensors are comparable to thermocouples for recording soil temperatures during fires. Finally, we present a case study using iStakes and SheFire to estimate in situ soil heating during a prescribed fire and demonstrate how observed heating regimes would influence seed and tree root vascular cambium survival at different soil depths. This measurement‐modeling framework provides a cutting‐edge approach for describing soil temperature regimes (i.e., soil heating) through a soil profile and predicting biological responses.
Bio-loggers are widely used for studying the movement and behavior of animals. However, some sensors provide more data than is practical to store given experiment or bio-logger design constraints. One approach for overcoming this limitation is to utilize data collection strategies, such as non-continuous recording or data summarization that may record data more efficiently, but need to be validated for correctness. In this paper we address two fundamental questions—how can researchers determine suitable parameters and behaviors for bio-logger sensors, and how do they validate their choices? We present a methodology that uses software-based simulation of bio-loggers to validate various data collection strategies using recorded data and synchronized, annotated video. The use of simulation allows for fast and repeatable tests, which facilitates the validation of data collection methods as well as the configuration of bio-loggers in preparation for experiments. We demonstrate this methodology using accelerometer loggers for recording the activity of the small songbird
- Award ID(s):
- 1856423
- NSF-PAR ID:
- 10308181
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Animal Biotelemetry
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2050-3385
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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