Biology subjects

Sanderman, J.

Publications and source records attributed to Sanderman, J..

3 recordsLinked to original sources

bioRxiv2025

Low quality evidence dominates discussion of carbon benefits of alternative grazing strategies

There is enormous interest in utilizing alternative grazing strategies to improve rangeland condition, increase profitability and decrease the carbon footprint of livestock production via soil organic carbon (SOC) sequestration. Here we present a systematic review and meta-analysis of the literature on alternative grazing strategies and their impact on SOC. Most studies (47 out of 70) failed multiple quality criteria. The 10 studies with 27 observations that met all inclusion criteria showed no change in SOC. Further dividing these observations by study design (controlled small-plot experiment versus observational paired site study) or grazing management style (adaptive or prescribed) or by aridity class or by grassland type failed to reveal any trends. Gains in SOC were only found for a secondary group of 13 studies with 25 observations, primarily composed of paired comparisons where there were unresolved questions about the quality of the site pairings for supporting causal inference. This divergence in results between primary and secondary studies highlights that low-quality evidence dominates the discussion around the climate benefits of alterative grazing strategies, underscoring a critical need for stronger evidence before asserting climate change mitigation benefits from alternative grazing practices. For submission toCommunications Earth & Environment

ecology↗

bioRxiv2023

Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement

Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference datasets for training machine learning (ML) models, which are called soil spectral libraries (SSLs). Similarly, the prediction capacity of new samples is also subject to the number and diversity of soil types and conditions represented in the SSLs. To help bridge this gap and enable hundreds of stakeholders to collect more affordable soil data by leveraging a centralized open resource, the Soil Spectroscopy for Global Good has created the Open Soil Spectral Library (OSSL). In this paper, we describe the procedures for collecting and harmonizing several SSLs that are incorporated into the OSSL, followed by exploratory analysis and predictive modeling. The results of 10-fold cross-validation with refitting show that, in general, mid-infrared (MIR)-based models are significantly more accurate than visible and near-infrared (VisNIR) or near-infrared (NIR) models. From independent model evaluation, we found that Cubist comes out as the best-performing ML algorithm for the calibration and delivery of reliable outputs (prediction uncertainty and representation flag). Although many soil properties are well predicted, total sulfur, extractable sodium, and electrical conductivity performed poorly in all spectral regions, with some other extractable nutrients and physical soil properties also performing poorly in one or two spectral regions (VisNIR or Neospectra NIR). Hence, the use of predictive models based solely on spectral variations has limitations. This study also presents and discusses several other open resources that were developed from the OSSL, aspects of opening data, current limitations, and future development. With this genuinely open science project, we hope that OSSL becomes the driver of the soil spectroscopy community to accelerate the pace of scientific discovery and innovation.

bioinformatics↗

bioRxiv2020

Future carbon emissions from global mangrove forest loss

Mangroves have among the highest carbon densities of any tropical forest. These "blue carbon" ecosystems can store large amounts of carbon for long periods, and their protection reduces greenhouse gas emissions and supports climate change mitigation. The incorporation of mangroves into Nationally Determined Contributions to the Paris Agreement and their valuation on carbon markets requires predicting how the management of different land-uses can prevent future greenhouse gas emissions and increase CO2 sequestration. Management actions can reduce CO2 emissions and enhance sequestration, but should be guided by predictions of future emissions, not just carbon storage. We project emissions and forgone soil carbon sequestration potential caused by mangrove loss with comprehensive global datasets for carbon stocks, mangrove distribution, deforestation rates, and drivers of land-use change. Emissions from mangrove loss could reach 2,397 Tg CO2eq by the end of the century, or 3,401 Tg CO2eq when considering forgone carbon sequestration. The highest emissions were predicted in southeast and south Asia (West Coral Triangle, Sunda Shelf, and the Bay of Bengal) due to conversion to aquaculture or agriculture, followed by the Caribbean (Tropical Northwest Atlantic) due to clearing and erosion, and the Andaman coast (West Myanmar) and north Brazil due to erosion. Together, these six regions accounted for 90% of the total potential CO2eq future emissions. We highlight hotspots for future emissions and the land-use specfic management actions that could avoid them with appropriate policies and regulation.

biochemistry↗