Soil compaction and water content effects on lodgepole pine seedling growth in British Columbia, SuperSoil Conf.

Abstract Increased mechanization during timber harvesting activities has led to concerns that compaction may negatively affect the long-term productivity of soil. A greenhouse study was carried out to determine the effects of soil compaction under three levels of soil water content. Mineral soil was collected from a landing in central British Columbia, Canada and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) seedlings were grown in pots for 12 weeks. Pots were compacted to densities that corresponded to 67, 72 and 76% of the Proctor maximum bulk density (1798 kg m-3) for the soil. Volumetric water contents of 0.10-0.15, 0.20-0.30 and 0.30-0.35 cm3cm-3 were maintained by weighing the pots, determining the gravimetric water content and adding the required water. Compaction only had an effect on seedling growth at low water content. Diameter growth and total shoot biomass were significantly smaller for 76% compaction compared to 67% compaction. At low water content, 76% and 72% compaction caused decreases in new root biomass and 76% compaction increased shoot macronutrient concentrations. The findings of this study imply that, for the compaction levels observed, water content had a greater impact on seedling growth than compaction

Provincial Government Standards, Criteria, and Indicators for Sustainable Harvest of Forest Biomass in British Columbia: Soil and Biodiversity

Sustainable forest management (SFM) is a cornerstone of forest management, whether the resulting forest products are destined for the manufacturing sector or for the emerging bioenergy feedstock market. In British Columbia, research on the environmental effects of forest management has generated scientific knowledge that has informed two linked areas of government responsibility: 1) a comprehensive set of science-based regulations and policies to ensure soil and water conservation, and 2) a monitoring program to ensure the effectiveness of these regulations and policies. An increasing amount of biomass is being harvested from British Columbia’s forests as a feedstock for bioenergy, and these removals have the potential to incrementally increase machine traffic and organic matter removals from forest sites, compared to harvesting operations focused solely on roundwood for timber or pulp. To the extent that existing standards support SFM, they may be sufficient for ensuring that biomass harvesting is also sustainable. Regardless of the new challenges created by intensive harvesting practices, the principles of soil and biodiversity conservation remain the same. The current framework for BC’s SFM policy is reviewed to examine whether it addresses the major sustainability issues that are likely to arise in the province if intensive biomass harvesting becomes more prevalent. We conclude that intensification of biomass removals will require us to keep focused on stand and landscape sensitivity to coarse woody debris removals and biodiversity requirements, nutrient removals, and cumulative soil disturbance. Keywords: regulations, soil conservation, biodiversity, forest biomass harvesting, mountain pine beetle. Received 30 November 2010, Revised 6 June 2011, Accepted 24 August 2011

A framework for recalibrating pedotransfer functions using nonlinear least squares and estimating uncertainty using quantile regression

Pedotransfer functions (PTFs) have been developed for many regions to estimate values missing from soil profile databases. However, globally there are many areas without existing PTFs, and it is not advisable to use PTFs outside their domain of development due to poor performance. Further, developed PTFs often lack accompanying uncertainty estimations. To address these issues, a framework is proposed where existing equation-based PTFs are recalibrated using a nonlinear least squares (NLS) approach and validated on two regions of Canada; this process is coupled with the use of quantile regression (QR) to generate uncertainty estimates. Many PTFs have been developed to predict soil bulk density, so this variable is used as a case study to evaluate the outcome of recalibration. New coefficients are generated for existing soil bulk density PTFs, and the performance of these PTFs is validated using three case study datasets, one from the Ottawa region of Ontario and two from the province of British Columbia, Canada. The improvement of the performance of the recalibrated PTFs is evaluated using root mean square error (RMSE) and the concordance correlation coefficient (CCC). Uncertainty estimates produced using QR are communicated through the mean prediction interval (MPI) and prediction interval coverage probability (PICP) graphs. This framework produces dataset-specific PTFs with improved accuracy and minimized uncertainty, and the method can be applied to other regional datasets to improve the estimations of existing PTF model forms. The methods are most successful with large datasets and PTFs with fewer variables and minimal transformations; further, PTFs with organic carbon (OC) as one of or the sole input variable resulted in the highest accuracy

Data from: Large, climate-sensitive soil carbon stocks mapped with pedology-informed machine learning in the North Pacific coastal temperate rainforest

Accurate soil organic carbon (SOC) maps are needed to predict the terrestrial SOC feedback to climate change, one of the largest remaining uncertainties in Earth system modeling. Over the last decade, global scale models have produced varied predictions of the size and distribution of SOC stocks, ranging from 1,000 to > 3,000 Pg of C within the top 1 m. Regional assessments may help validate or improve global maps because they can examine landscape controls on SOC stocks and offer a tractable means to retain regionally-specific information, such as soil taxonomy, during database creation and modeling. We compile a new transboundary SOC stock database for coastal watersheds of the North Pacific coastal temperate rainforest, using soil classification data to guide gap-filling and machine learning approaches used to explore spatial controls on SOC and predict regional stocks. Precipitation and topographic attributes controlling soil wetness were found to be the dominant controls of SOC, underscoring the dependence of C accumulation on high soil moisture. The random forest model predicted stocks of 4.5 Pg C (to 1 m) for the study region, 22% of which was stored in organic soil layers. Calculated stocks of 228 ± 111 Mg C ha-1 fell within ranges of several past regional studies and indicate 11-33 Pg C may be stored across temperate rainforest soils globally. Predictions compared very favorably to regionalized estimates from two spatially-explicit global products (Pearson's correlation: ρ = 0.73 vs. 0.34). Notably, SoilGrids250m was an outlier for estimates of total SOC, predicting 4-fold higher stocks (18 Pg C) and indicating bias in this global product for the soils of the temperate rainforest. In sum our study demonstrates that CTR ecosystems represent a moisture-dependent hotspot for SOC storage at mid-latitudes

McNicol-2019-NPCTR-SOC-map

This raster [.tif] is the predicted soil organic carbon for the North Pacific coastal temperate rainforest. Content is displayed in megagrams of carbon per hectare (Mg ha-1) to 1 m in mineral soil, plus overlying organic horizons. Map values are the output of a random forest machine learning algorithm trained on pedon data from within British Columbia and southeast Alaska only, therefore confidence is low for predictions south of the US-Canada border and predictions in that region have not been validated. Lakes, glaciers and ice-fields have also not been masked from the map. More information on the map can be found in the associated manuscript

N Pacific coastal temperate rainforest pedon and soil carbon database

This database compiles pedon data (ca. 1300 soil profile descriptions) from various sources across coastal British Columbia and southeast Alaska. Each profile includes soil class and horizon designations, and some of the data required for soil carbon stock calculations (e.g. bulk density, carbon concentration, horizon depth and coarse fragment content). Missing data which were gap-filled are highlighted and annotated with comments, and were filled according to procedures outlined in the manuscript and supplement. Data formatting across the different sources were harmonized where possible. References, acknowledgements and field descriptors are provided, including comments on calculation steps. More detail is available in the manuscript supplement