Abstract

Soil temperatures play an important role in determining the distribution and function of organisms. However, soil temperature is decoupled from air temperature and varies widely in space. Characterizing and predicting soil temperature requires large and expensive networks of data loggers. We developed an open-source soil temperature data logger and created online resources to ensure our design was accessible. We tested data loggers constructed by students, with little prior electronics experience, in the lab, and in the field in Alaska. The do-it-yourself (DIY) data logger was comparably accurate to a commercial system with a mean absolute error of 2% from −20–0 °C and 1% from 0–20 °C. They captured accurate soil temperature data and performed reliably in the field with less than 10% failing in the first year of deployment. The DIY loggers were ~1.7–7 times less expensive than commercial systems. This work has the potential to increase the spatial resolution of soil temperature monitoring and serve as a powerful educational tool. The DIY soil temperature data logger will reduce data collection costs and improve our understanding of species distributions and ecological processes. It also provides an educational resource to enhance STEM, accessibility, inclusivity, and engagement.

Highlights

  • Temperature plays an important role in the physiology, activity, and distribution of organisms across the globe [1–8]

  • The three data logger systems largely differed in their battery life and data storage capacity

  • We developed an inexpensive DIY soil temperature data logger and educational materials to close “skill gaps” that could prevent others from constructing the device

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Summary

Introduction

Temperature plays an important role in the physiology, activity, and distribution of organisms across the globe [1–8]. Temperatures vary across time and space and can substantially differ between the air, water, and soils. Air temperatures have been extensively measured using global networks or satellites, there has been less attention towards soil and water temperatures [3,6,9,10]. This is unfortunate because many biological and biogeochemical processes rely on proximate temperatures in soil and water that can differ widely from those in the air [10–15]. Temperatures can be difficult to predict from those in the air because of their dependence on radiation load, surface energy budget partitioning, soil depth, and soil thermal properties that vary with soil texture and moisture content [12–14,16–18]. Adequately characterizing the three-dimensional variability in soil temperatures across a site often requires a large number of sensors that can be costly to purchase and deploy

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