Maintenance of the health of our oceans is critical for the survival of the oceanic food chain upon which humanity is dependent. Zooplanktonic copepods are among the most numerous multicellular organisms on earth. As the base of the primary consumer food web, they constitute a major biomass in oceans, being an important food source for fish and functioning in the carbon cycle. The potential impact of climate change on copepod populations is an area of intense study. Omics technologies offer the potential to detect early metabolic alterations induced by the stresses of climate change. One such omics approach is lipidomics, which can accurately quantify changes in lipid pools serving structural, signal transduction, and energy roles. We utilized high-resolution mass spectrometry (≤2 ppm mass error) to characterize the lipidome of three different species of copepods in an effort to identify lipid-based biomarkers of copepod health and viability which are more sensitive than observational tools. With the establishment of such a lipid database, we will have an analytical platform useful for prospectively monitoring the lipidome of copepods in a planned long-term five-year ecological study of climate change on this oceanic sentinel species. The copepods examined in this pilot study included a North Atlantic species () and two species from the Gulf of Mexico, one a filter feeder () and one a hunter (). Our findings clearly indicate that the lipidomes of copepod species can vary greatly, supporting the need to obtain a broad snapshot of each unique lipidome in a long-term multigeneration prospective study of climate change. This is critical, since there may well be species-specific responses to the stressors of climate change and co-stressors such as pollution. While lipid nomenclature and biochemistry are extremely complex, it is not essential for all readers interested in climate change to understand all of the various lipid classes presented in this study. The clear message from this research is that we can monitor key copepod lipid families with high accuracy, and therefore potentially monitor lipid families that respond to environmental perturbations evoked by climate change.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10744631PMC
http://dx.doi.org/10.3390/life13122335DOI Listing

Publication Analysis

Top Keywords

climate change
32
lipid-based biomarkers
8
climate
8
change
8
change oceanic
8
oceanic food
8
food chain
8
species copepods
8
study climate
8
lipid families
8

Similar Publications

The carbon footprint associated with cement production, coupled with depletion of natural resources and climate change, underscores the need for sustainable alternatives. This study explores the effect of metakaolin (MK) and nano-silica (NS) on concrete's engineering performance and environmental impact. Initially, compressive, tensile, and flexural strength tests, along with durability assessments like water absorption, sorptivity, rapid chloride permeability, and resistance to acid and sulphate attacks, were conducted.

View Article and Find Full Text PDF

Modelling mixed crop-livestock systems and climate impact assessment in sub-Saharan Africa.

Sci Rep

January 2025

Institute of Crop Science and Resource Conservation, University of Bonn, Katzenburgweg 5, D-53115, Bonn, Germany.

Climate change significantly challenges smallholder mixed crop-livestock (MCL) systems in sub-Saharan Africa (SSA), affecting food and feed production. This study enhances the SIMPLACE modeling framework by incorporating crop-vegetation-livestock models, which contribute to the development of sustainable agricultural practices in response to climate change. Applying such a framework in a domain in West Africa (786,500 km) allowed us to estimate the changes in crop (Maize, Millet, and Sorghum) yield, grass biomass, livestock numbers, and greenhouse gas emission in response to future climate scenarios.

View Article and Find Full Text PDF

As global fertilizer application rates increase, high-quality datasets are paramount for comprehensive analyses to support informed decision-making and policy formulation in crucial areas such as food security or climate change. This study aims to fill existing data gaps by employing two machine learning models, eXtreme Gradient Boosting and HistGradientBoosting algorithms to produce precise country-level predictions of nitrogen (N), phosphorus pentoxide (PO), and potassium oxide (KO) application rates. Subsequently, we created a comprehensive dataset of 5-arcmin resolution maps depicting the application rates of each fertilizer for 13 major crop groups from 1961 to 2019.

View Article and Find Full Text PDF

Due to growing population and technological advances, global electricity consumption is increasing. Although CO emissions are projected to plateau or slightly decrease by 2025 due to the adoption of clean energy sources, they are still not decreasing enough to mitigate climate change. The residential sector makes up 25% of global electricity consumption and has potential to improve efficiency and reduce CO footprint without sacrificing comfort.

View Article and Find Full Text PDF

The quantitative assessment of policies aimed at climate change mitigation requires rigorously identifying abnormal changes in greenhouse gas emissions. We present a new dataset of robust level changes in greenhouse gas emissions that cannot be explained by aggregate socioeconomic fluctuations. Modern methods of structural break identification based on two-way fixed effects models are employed to estimate the size of significant level changes in emissions.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!