Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.</p

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem\u27s carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Termite sensitivity to temperature affects global wood decay rates.

Deadwood is a large global carbon store with its store size partially determined by biotic decay. Microbial wood decay rates are known to respond to changing temperature and precipitation. Termites are also important decomposers in the tropics but are less well studied. An understanding of their climate sensitivities is needed to estimate climate change effects on wood carbon pools. Using data from 133 sites spanning six continents, we found that termite wood discovery and consumption were highly sensitive to temperature (with decay increasing >6.8 times per 10°C increase in temperature)-even more so than microbes. Termite decay effects were greatest in tropical seasonal forests, tropical savannas, and subtropical deserts. With tropicalization (i.e., warming shifts to tropical climates), termite wood decay will likely increase as termites access more of Earth's surface

Lipid Mixtures Containing a Very High Proportion of Saturated Fatty Acids Only Modestly Impair Insulin Signaling in Cultured Muscle Cells

<div><p><i>In vitro</i> examinations of the effect of saturated fatty acids on skeletal muscle insulin action often use only one or two different fatty acid species, which does not resemble the human plasma fatty acid profile. We compared graded concentrations (0.1-0.8mM) of 3 different lipid mixtures: 1) a physiologic fatty acid mixture (NORM; 40% saturated fatty acids), 2) a physiologic mixture high in saturated fatty acids (HSFA; 60% saturated fatty acids), and 3) 100% palmitate (PALM) on insulin signaling and fatty acid partitioning into triacylglycerol (TAG) and diacylglycerol (DAG) in cultured muscle cells. As expected, PALM readily impaired insulin-stimulated pAkt^Thr308/Akt and markedly increased intracellular DAG content. In contrast, the fatty acid mixtures only modestly impaired insulin-stimulated pAkt^Thr308M/Akt, and we found no differences between NORM and HSFA. Importantly, NORM and HSFA did not increase DAG content, but instead dose-dependently increased TAG accumulation. Therefore, the robust impairment in insulin signaling found with palmitate exposure was attenuated with physiologic mixtures of fatty acids, even with a very high proportion of saturated fatty acids. This may be explained in part by selective partitioning of fatty acids into neutral lipid (i.e., TAG) when muscle cells were exposed to physiologic lipid mixtures.</p></div

Responses during the oral glucose tolerance (OGTT) before at after the 2 week high saturated fat diet intervention.

<p>A. Plasma insulin concentration, B. Plasma glucose concentration, and C. “Insulin sensitivity index” (Matsuda Composite Index) calculated from plasma insulin and glucose concentrations during the OGTT.</p

Plasma cholesterol concentrations before the dietary intervention and again after 1 week and 2 weeks of the high saturated fat diet intervention.

<p>Values are means±SE. * Significant difference from BEFORE, P<0.05. Total cholesterol (Total-C), high density lipoprotein colesterol (HDL-C), and low density lipoprotein cholesterol (LDL-C).</p

Fasting plasma substrate and hormone concentrations and other clinical measures before and after the high saturated fat diet intervention.

<p>Fasting plasma substrate and hormone concentrations and other clinical measures before and after the high saturated fat diet intervention.</p