Soil Carbon Stocks Are Stable under New Zealand Hill Country Pastures with Contrasting Phosphorus and Sheep Stocking Regimes

A temporal and spatial assessment is required to quantify the effects of nutrient inputs and varying grazing management regimes on soil organic carbon (SOC) stocks under grazed pastures in complex landscapes. We examined SOC stocks under permanent pastures in three farmlets under a range of different annual phosphorus (P) fertiliser and associated sheep stocking regimes. The farmlets examined had either no annual P applied (NF), 125 kg single superphosphate (SSP) ha-1 (LF), or 375 kg SSP ha-1 (HF) on an annual basis since 1980. Soils were sampled to three depths (0-75, 75-150, 150-300 mm) in 2003 and 2020, and to the two upper depths in 2014. Each farmlet included three slope classes [low slope (LS), medium slope (MS), high slope (HS)], on three different aspect locations [east (E), southwest (SW), northwest (NW)]. Although a trend (P = 0.07) was observed for greater SOC stocks in the upper depth of the HF farmlet (34.0 Mg C ha-1) compared with the other two farmlets (31.6 Mg C ha-1), this trend was discontinued in deeper layers. Accumulated SOC stocks (0-300 mm) were 111.1 (NF), 109.8 (LF) and 111.5 (HF) Mg C ha-1. Soil samples collected on HS resulted in higher soil bulk densities (BD) and carbon-to-nitrogen (C:N) ratios, and lower C concentration and SOC stocks, compared with samples collected on the other two slope classes. Soil samples collected on the NW-facing slopes resulted in higher BD, and lower C concentration and SOC stocks, compared with samples collected on the other two aspect locations. Under the current conditions, contrasting P fertiliser and sheep stocking regimes had minimal effects on SOC stocks. In contrast, topographic features had major effects on SOC stocks, and need to be considered in soil sampling protocols that monitor soil organic carbon stocks over space and time

Biochar increases soil enzyme activities in two contrasting pastoral soils under different grazing management

Context: Soil enzyme activities are key regulators of carbon and nutrient cycling in grazed pastures. Aims: We investigated the effect of biochar addition on the activity of seven enzymes involved in the carbon, nitrogen and phosphorus cycles in a Sil-Andic Andosol and a Dystric Cambisol under permanent pastures. Methods: The study consisted of a one-year field-based mesocosm experiment involving four pastures under different nutrient and livestock practices: with and without effluent under dairy cow grazing on the Andosol, and with either nil or high phosphorus fertiliser input under sheep grazing on the Cambisol. Soil treatments were: (1) willow biochar added at 1% w/w; (2) lime added at the liming equivalence of biochar (positive control); (3) no amendments (negative control). Key results: Compared with the Cambisol, the Andosol had higher dehydrogenase, urease, alkaline and acid phosphatase and, especially, nitrate-reductase activities, aligning with its higher pH and fertility. In both soils, biochar addition increased the activity of all enzymes, except for acid phosphatase and peroxidase; lime addition increased peroxidase and nitrate-reductase activity. Conclusions: The increased enzyme activity was strongly positively correlated with soil biological activity following biochar addition. Biochar caused a 40-45% increase in cellulase activity, attributed to increased root biomass following biochar addition. The response in acid and alkaline phosphatase activity can be attributed to the impact of biochar and lime addition on soil pH. Implications: The results provide more insights in realising the potential benefits of biochar to the provision of ecosystem services for grazed pastures.fals

Effects of spatial data resolution on the modelling and mapping of soil organic carbon content in hill country grassland landscapes

Limited use has been made of spatially explicit modelling of soil organic carbon (SOC) in highly complex farmed landscapes to advance current mapping efforts. This study aimed to address this gap in knowledge by evaluating the spatial prediction of SOC content in the 0–75 mm soil depth in hill country landscapes in New Zealand (NZ) using point-based training data, along with topographic covariates and Sentinel 2 spectral band ratios using an automated set of machine learning (AutoML) tools in ArcGIS. Subsequently, it also focused on quantifying the effects of spatial data resolution (i.e., 1, 8, 15, and 25 m) in terms of predicted map accuracy. Farmlets with contrasting phosphorus fertilizer and sheep grazing histories located at the Ballantrae Hill Country Research Station, NZ were selected to conduct the research. Six candidate algorithms incorporated in the AutoML tools (i.e., XGBoost, LightGBM, linear regression, decision trees, extra trees, random forest) and ensemble model were utilized to model the spatial pattern of SOC content. The results show that the ensemble model that combine predictions of various algorithms applied for 1 m data resolution enables the highest performance and accuracy (i.e., R2 =.76, RMSE = 0.66%). Among the predictive variables used in the model, slope, wetness, and topographic position indices were found to be the most important topographical features that explain SOC patterns in the study area. Inclusion of spectral indices derived from remote sensing, including surface soil moisture and clay minerals ratio, made further improvement to the SOC content prediction. The study reveals that a decrease in the resolution of the geospatial data does not substantively affect the mean SOC content estimation of a farm-scale modelling. However, using coarser resolution data reduces the ability of the model to predict changes in the spatial pattern of SOC content across a hill country grassland landscape.fals

Identifying the World's Most Climate Change Vulnerable Species: A Systematic Trait-Based Assessment of all Birds, Amphibians and Corals

Climate change will have far-reaching impacts on biodiversity, including increasing extinction rates. Current approaches to quantifying such impacts focus on measuring exposure to climatic change and largely ignore the biological differences between species that may significantly increase or reduce their vulnerability. To address this, we present a framework for assessing three dimensions of climate change vulnerability, namely sensitivity, exposure and adaptive capacity; this draws on species’ biological traits and their modeled exposure to projected climatic changes. In the largest such assessment to date, we applied this approach to each of the world’s birds, amphibians and corals (16,857 species). The resulting assessments identify the species with greatest relative vulnerability to climate change and the geographic areas in which they are concentrated, including the Amazon basin for amphibians and birds, and the central Indo-west Pacific (Coral Triangle) for corals. We found that high concentration areas for species with traits conferring highest sensitivity and lowest adaptive capacity differ from those of highly exposed species, and we identify areas where exposure-based assessments alone may over or under-estimate climate change impacts. We found that 608–851 bird (6–9%), 670–933 amphibian (11–15%), and 47–73 coral species (6–9%) are both highly climate change vulnerable and already threatened with extinction on the IUCN Red List. The remaining highly climate change vulnerable species represent new priorities for conservation. Fewer species are highly climate change vulnerable under lower IPCC SRES emissions scenarios, indicating that reducing greenhouse emissions will reduce climate change driven extinctions. Our study answers the growing call for a more biologically and ecologically inclusive approach to assessing climate change vulnerability. By facilitating independent assessment of the three dimensions of climate change vulnerability, our approach can be used to devise species and area-specific conservation interventions and indices. The priorities we identify will strengthen global strategies to mitigate climate change impacts

Disturbance and the Dynamics of Coral Cover on the Great Barrier Reef (1995–2009)

Coral reef ecosystems worldwide are under pressure from chronic and acute stressors that threaten their continued existence. Most obvious among changes to reefs is loss of hard coral cover, but a precise multi-scale estimate of coral cover dynamics for the Great Barrier Reef (GBR) is currently lacking. Monitoring data collected annually from fixed sites at 47 reefs across 1300 km of the GBR indicate that overall regional coral cover was stable (averaging 29% and ranging from 23% to 33% cover across years) with no net decline between 1995 and 2009. Subregional trends (10–100 km) in hard coral were diverse with some being very dynamic and others changing little. Coral cover increased in six subregions and decreased in seven subregions. Persistent decline of corals occurred in one subregion for hard coral and Acroporidae and in four subregions in non-Acroporidae families. Change in Acroporidae accounted for 68% of change in hard coral. Crown-of-thorns starfish (Acanthaster planci) outbreaks and storm damage were responsible for more coral loss during this period than either bleaching or disease despite two mass bleaching events and an increase in the incidence of coral disease. While the limited data for the GBR prior to the 1980's suggests that coral cover was higher than in our survey, we found no evidence of consistent, system-wide decline in coral cover since 1995. Instead, fluctuations in coral cover at subregional scales (10–100 km), driven mostly by changes in fast-growing Acroporidae, occurred as a result of localized disturbance events and subsequent recovery

Extraction of pure components from overlapped signals in gas chromatography-mass spectrometry (GC-MS)

Gas chromatography-mass spectrometry (GC-MS) is a widely used analytical technique for the identification and quantification of trace chemicals in complex mixtures. When complex samples are analyzed by GC-MS it is common to observe co-elution of two or more components, resulting in an overlap of signal peaks observed in the total ion chromatogram. In such situations manual signal analysis is often the most reliable means for the extraction of pure component signals; however, a systematic manual analysis over a number of samples is both tedious and prone to error. In the past 30 years a number of computational approaches were proposed to assist in the process of the extraction of pure signals from co-eluting GC-MS components. This includes empirical methods, comparison with library spectra, eigenvalue analysis, regression and others. However, to date no approach has been recognized as best, nor accepted as standard. This situation hampers general GC-MS capabilities, and in particular has implications for the development of robust, high-throughput GC-MS analytical protocols required in metabolic profiling and biomarker discovery. Here we first discuss the nature of GC-MS data, and then review some of the approaches proposed for the extraction of pure signals from co-eluting components. We summarize and classify different approaches to this problem, and examine why so many approaches proposed in the past have failed to live up to their full promise. Finally, we give some thoughts on the future developments in this field, and suggest that the progress in general computing capabilities attained in the past two decades has opened new horizons for tackling this important problem

Impacts of Sediments on Coral Energetics: Partitioning the Effects of Turbidity and Settling Particles

Sediment loads have long been known to be deleterious to corals, but the effects of turbidity and settling particles have not previously been partitioned. This study provides a novel approach using inert silicon carbide powder to partition and quantify the mechanical effects of sediment settling versus reduced light under a chronically high sedimentary regime on two turbid water corals commonly found in Singapore (Galaxea fascicularis and Goniopora somaliensis). Coral fragmentswere evenly distributed among three treatments: an open control (30% ambient PAR), a shaded control (15% ambient PAR) and sediment treatment (15% ambient PAR; 26.4 mg cm22 day21). The rate of photosynthesis and respiration, and the dark-adapted quantum yield were measured once a week for four weeks. By week four, the photosynthesis to respiration ratio (P/R ratio) and the photosynthetic yield (Fv/Fm) had fallen by 14% and 3–17% respectively in the shaded control,contrasting with corals exposed to sediments whose P/R ratio and yield had declined by 21% and 18–34% respectively. The differences in rates between the shaded control and the sediment treatment were attributed to the mechanical effects of sediment deposition. The physiological response to sediment stress differed between species with G. fascicularis experiencing a greater decline in the net photosynthetic yield (13%) than G. somaliensis (9.5%), but a smaller increase in the respiration rates (G. fascicularis = 9.9%, G. somaliensis = 14.2%). These different physiological responses were attributed, in part, to coral morphology and highlighted key physiological processes that drive species distribution along high to low turbidity and depositional gradients

Implementation and evaluation of a multi-level mental health promotion intervention for the workplace (MENTUPP): study protocol for a cluster randomised controlled trial

Background Well-organised and managed workplaces can be a source of wellbeing. The construction, healthcare and information and communication technology sectors are characterised by work-related stressors (e.g. high workloads, tight deadlines) which are associated with poorer mental health and wellbeing. The MENTUPP intervention is a flexibly delivered, multi-level approach to supporting small- and medium-sized enterprises (SMEs) in creating mentally healthy workplaces. The online intervention is tailored to each sector and designed to support employees and leaders dealing with mental health difficulties (e.g. stress), clinical level anxiety and depression, and combatting mental health-related stigma. This paper presents the protocol for the cluster randomised controlled trial (cRCT) of the MENTUPP intervention in eight European countries and Australia. Methods Each intervention country will aim to recruit at least two SMEs in each of the three sectors. The design of the cRCT is based on the experiences of a pilot study and guided by a Theory of Change process that describes how the intervention is assumed to work. SMEs will be randomly assigned to the intervention or control conditions. The aim of the cRCT is to assess whether the MENTUPP intervention is effective in improving mental health and wellbeing (primary outcome) and reducing stigma, depression and suicidal behaviour (secondary outcome) in employees. The study will also involve a process and economic evaluation. Conclusions At present, there is no known multi-level, tailored, flexible and accessible workplace-based intervention for the prevention of non-clinical and clinical symptoms of depression, anxiety and burnout, and the promotion of mental wellbeing. The results of this study will provide a comprehensive overview of the implementation and effectiveness of such an intervention in a variety of contexts, languages and cultures leading to the overall goal of delivering an evidence-based intervention for mental health in the workplace