scholarly journals Amplifying Signals and avoiding surprises: Potential synergies between ICOS and eLTER at the Water-Climate-Greenhouse Gas nexus

2021 ◽  
Author(s):  
Martyn Futter ◽  
Syed Ashraful Alam ◽  
Roland Baatz ◽  
Jaana Bäck ◽  
Eugenio Diaz-Pines ◽  
...  
Keyword(s):  
Environmental Change ◽  
Greenhouse Gas ◽  
Water Cycle ◽  
Regime Shifts ◽  
Probability Of Detection ◽  
Ecosystem Dynamics ◽  
Carbon Accounting ◽  
Environmental Drivers ◽  
National Academy Of Sciences

<p>Environmental thresholds. tipping points and subsequent regime shifts associated with the water/climate/greenhouse gas nexus pose a genuine threat to sustainability. Both the ongoing forest dieback in Central Europe caused by the extreme droughts of the last years and the effect of global warming on ecosystem functioning have the potential to cause ecological surprise (<em>sensu</em> Lindenmayer et al. 2010) where ecosystems are pushed into new, unexpected and usually undesirable states.</p><p>Formulating appropriate scientific and societal responses to such regime shifts requires breadth, depth, intensity and duration of environmental, ecological and socio-ecological monitoring. Broad geographic coverage to encompass relevant biophysical and societal gradients, consideration of all appropriate parameters, adequate measurement frequency and long-term, standardized observations are all needed to provide reliable early warnings of severe environmental change, test ecosystem models, avoid double counting in carbon accounting and to reduce the likelihood of undesirable ecological outcomes. This is especially true of events driven by simultaneous changes in climate, the water cycle and human activities.</p><p>Well-supported, site-based research infrastructures (RIs; e.g., eLTER and ICOS) are essential tools with the necessary breadth, depth, intensity and duration for early detection and attribution of environmental change. Individually, the eLTER and ICOS RIs generate a wealth of data supporting the ecosystem and carbon research communities. Achieving synergies between the two RIs can add value to both communities and potentially offer meaningful insight into the European water-climate-greenhouse gas nexus.</p><p>The unique insights into processes and mechanisms of ecosystem dynamics and functioning obtained from high intensity monitoring conducted by the ICOS RI greatly increase the likelihood of detecting signals of environmental change. These signals must be placed into the context of their long-term trajectory and potential societal and environmental drivers. The spatially extensive, long-term, multi-disciplinary monitoring conducted at LTER sites and LTSER platforms under the umbrella of the eLTER programme can provide this context.</p><p>Here, we outline one potential roadmap for achieving synergies between the ICOS and eLTER RIs focussing on the value of co-location for improved understanding of the water/climate/greenhouse gas nexus. Based on data and experiences from intensively studied research sites, we highlight some of the possibilities for reducing the likelihood of ecological surprise that could result from such synergies.</p><p>Lindenmayer, D.B., Likens, G.E., Krebs, C.J. and Hobbs, R.J., 2010. Improved probability of detection of ecological “surprises”. Proceedings of the National Academy of Sciences, 107(51), pp.21957-21962.</p>

scholarly journals Impacts of Fire on Forest Biomass Dynamics at the Southern Amazon Edge

2019 ◽  
Vol 46 (4) ◽  
pp. 285-292 ◽  
Author(s):  
Denis S Nogueira ◽  
Beatriz S Marimon ◽  
Ben Hur Marimon-Junior ◽  
Edmar A Oliveira ◽  
Paulo Morandi ◽  
...  
Keyword(s):  
Environmental Change ◽  
Forest Type ◽  
Forest Biomass ◽  
Riparian Forests ◽  
Environmental Drivers ◽  
Biomass Carbon ◽  
Forest Types ◽  
Change Rate ◽  
Biomass Dynamics

SummaryOver recent decades, biomass gains in remaining old-growth Amazonia forests have declined due to environmental change. Amazonia’s huge size and complexity makes understanding these changes, drivers, and consequences very challenging. Here, using a network of permanent monitoring plots at the Amazon–Cerrado transition, we quantify recent biomass carbon changes and explore their environmental drivers. Our study area covers 30 plots of upland and riparian forests sampled at least twice between 1996 and 2016 and subject to various levels of fire and drought. Using these plots, we aimed to: (1) estimate the long-term biomass change rate; (2) determine the extent to which forest changes are influenced by forest type; and (3) assess the threat to forests from ongoing environmental change. Overall, there was no net change in biomass, but there was clear variation among different forest types. Burning occurred at least once in 8 of the 12 riparian forests, while only 1 of the 18 upland forests burned, resulting in losses of carbon in burned riparian forests. Net biomass gains prevailed among other riparian and upland forests throughout Amazonia. Our results reveal an unanticipated vulnerability of riparian forests to fire, likely aggravated by drought, and threatening ecosystem conservation at the Amazon southern margins.

scholarly journals State tagging for improved earth and environmental data quality assurance

2020 ◽  
Author(s):  
Michael Tso ◽  
Peter Henrys ◽  
Susannah Rennie ◽  
John Watkins
Keyword(s):  
Quality Assurance ◽  
Environmental Change ◽  
Data Science ◽  
Contextual Information ◽  
Environmental Data ◽  
Prediction Intervals ◽  
Environmental Drivers ◽  
System State ◽  
System States

<p>Long-term monitoring data that considers a wide array of environmental variables provides key insights to environmental change because responses of ecosystem functions and services to environmental drivers are inherently long-term and strongly interlinked. To ensure that the data are reliable for analysis and interpretation, they must undergo quality assurance procedures. However, the expected or acceptable range of data values vary greatly as the state of the ecosystem changes. Current quality assurance procedures for environmental data take no consideration of the system state at which each measurement is made, and provide the user with little contextual information on the probable cause for a measurement to be flagged out of range. We propose the use of data science techniques to tag each measurement with an identified system state. The term “state” here is defined loosely and they are identified using k-means clustering, an unsupervised machine learning method. The meaning of the states is open to specialist interpretation. Once the states are identified, state-dependent prediction intervals can be calculated for each observational variable. This approach provides the user with more contextual information to resolve out-of-range flags and derive prediction intervals for observational variables that considers the changes in system states. Our highly flexible and efficient approach is applicable to any point data time series in earth and environmental sciences, regardless of their sub-discipline. Such advantage is particularly relevant when conducting simultaneous analysis of multiple processes and feedbacks, where a wide variety of data is used.</p><p>We illustrate our approach using the moth and butterfly data from the UK Environmental Change Network (ECN), where meteorological variables are used to define system states. A web application is publicly available to allow users to explore the method on various ECN site, while a generic is also available for users to upload their own data files. Our work contributes to the ongoing development of a better data science framework that allows researchers and other stakeholders to find and use the data they need more readily and reliably.</p><p> </p>

Low-Carbon Russia: Prospects after the Crisis

2009 ◽  
pp. 107-120 ◽  
Author(s):  
I. Bashmakov
Keyword(s):  
Economic Growth ◽  
Potential Energy ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Low Carbon ◽  
Modeling Tools ◽  
Gas Emissions ◽  
Scenario Approach

On the eve of the worldwide negotiations of a new climate agreement in December 2009 in Copenhagen it is important to clearly understand what Russia can do to mitigate energy-related greenhouse gas emissions in the medium (until 2020) and in the long term (until 2050). The paper investigates this issue using modeling tools and scenario approach. It concludes that transition to the "Low-Carbon Russia" scenarios must be accomplished in 2020—2030 or sooner, not only to mitigate emissions, but to block potential energy shortages and its costliness which can hinder economic growth.

scholarly journals Seasonal biological carryover dominates northern vegetation growth

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Xu Lian ◽  
Shilong Piao ◽  
Anping Chen ◽  
Kai Wang ◽  
Xiangyi Li ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Growing Season ◽  
Ecosystem Dynamics ◽  
Environmental Drivers ◽  
Subsequent Growth ◽  
Ecosystem Models ◽  
Carryover Effect ◽  
Vegetation Growth ◽  
Sequestration Potential ◽  
Future Warming

AbstractThe state of ecosystems is influenced strongly by their past, and describing this carryover effect is important to accurately forecast their future behaviors. However, the strength and persistence of this carryover effect on ecosystem dynamics in comparison to that of simultaneous environmental drivers are still poorly understood. Here, we show that vegetation growth carryover (VGC), defined as the effect of present states of vegetation on subsequent growth, exerts strong positive impacts on seasonal vegetation growth over the Northern Hemisphere. In particular, this VGC of early growing-season vegetation growth is even stronger than past and co-occurring climate on determining peak-to-late season vegetation growth, and is the primary contributor to the recently observed annual greening trend. The effect of seasonal VGC persists into the subsequent year but not further. Current process-based ecosystem models greatly underestimate the VGC effect, and may therefore underestimate the CO2 sequestration potential of northern vegetation under future warming.

scholarly journals Long-term greenhouse gas emissions from hydroelectric reservoirs in tropical forest regions

1999 ◽  
Vol 13 (2) ◽  
pp. 503-517 ◽  
Author(s):  
Corinne Galy-Lacaux ◽  
Robert Delmas ◽  
Georges Kouadio ◽  
Sandrine Richard ◽  
Philippe Gosse
Keyword(s):  
Tropical Forest ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Gas Emissions ◽  
Hydroelectric Reservoirs ◽  
Forest Regions

scholarly journals Verification of greenhouse gas emission reductions: the prospect of atmospheric monitoring in polluted areas

2011 ◽  
Vol 369 (1943) ◽  
pp. 1906-1924 ◽  
Author(s):  
Ingeborg Levin ◽  
Samuel Hammer ◽  
Elke Eichelmann ◽  
Felix R. Vogel
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Catchment Area ◽  
Greenhouse Gas Emission ◽  
Atmospheric Transport ◽  
Atmospheric Measurements ◽  
Transport Modelling ◽  
Gas Emissions ◽  
Atmospheric Transport Modelling

Independent verification of greenhouse gas emissions reporting is a legal requirement of the Kyoto Protocol, which has not yet been fully accomplished. Here, we show that dedicated long-term atmospheric measurements of greenhouse gases, such as carbon dioxide (CO 2 ) and methane (CH 4 ), continuously conducted at polluted sites can provide the necessary tool for this undertaking. From our measurements at the semi-polluted Heidelberg site in the upper Rhine Valley, we find that in the catchment area CH 4 emissions decreased on average by 32±6% from the second half of the 1990s until the first half of the 2000s, but the observed long-term trend of emissions is considerably smaller than that previously reported for southwest Germany. In contrast, regional fossil fuel CO 2 levels, estimated from high-precision 14 CO 2 observations, do not show any significant decreasing trend since 1986, in agreement with the reported emissions for this region. In order to provide accurate verification, these regional measurements would best be accompanied by adequate atmospheric transport modelling as required to precisely determine the relevant catchment area of the measurements. Furthermore, reliable reconciliation of reported emissions will only be possible if these are known at high spatial resolution in the catchment area of the observations. This information should principally be available in all countries that regularly report their greenhouse gas emissions to the United Nations Framework Convention on Climate Change.

A Review of Crack Detection In-Line Inspection Case Studies

2010 ◽  
Author(s):  
Neil Bates ◽  
David Lee ◽  
Clifford Maier
Keyword(s):  
Crack Growth ◽  
Case Studies ◽  
Crack Detection ◽  
Growth Parameters ◽  
Probability Distributions ◽  
Low Frequency ◽  
Probability Of Failure ◽  
Probability Of Detection ◽  
Inspection Data

This paper describes case studies involving crack detection in-line inspections and fitness for service assessments that were performed based on the inspection data. The assessments were used to evaluate the immediate integrity of the pipeline based on the reported features and the long-term integrity of the pipeline based on excavation data and probabilistic SCC and fatigue crack growth simulations. Two different case studies are analyzed, which illustrate how the data from an ultrasonic crack tool inspection was used to assess threats such as low frequency electrical resistance weld seam defects and stress corrosion cracking. Specific issues, such as probability of detection/identification and the length/depth accuracy of the tool, were evaluated to determine the suitability of the tool to accurately classify and size different types of defects. The long term assessment is based on the Monte Carlo method [1], where the material properties, pipeline details, crack growth parameters, and feature dimensions are randomly selected from certain specified probability distributions to determine the probability of failure versus time for the pipeline segment. The distributions of unreported crack-related features from the excavation program are used to distribute unreported features along the pipeline. Simulated crack growth by fatigue, SCC, or a combination of the two is performed until failure by either leak or rupture is predicted. The probability of failure calculation is performed through a number of crack growth simulations for each of the reported and unreported features and tallying their respective remaining lives. The results of the probabilistic analysis were used to determine the most effective and economical means of remediation by identifying areas or crack mechanisms that contribute most to the probability of failure.

The Southern Ocean benthic fauna and climate change: a historical perspective

1992 ◽  
Vol 338 (1285) ◽  
pp. 299-309 ◽  
Keyword(s):  
Global Warming ◽  
Southern Ocean ◽  
Environmental Change ◽  
Benthic Communities ◽  
Benthic Fauna ◽  
Marine Fauna ◽  
Short Term Change ◽  
Term Change ◽  
Continental Ice Sheets

Environmental change is the norm and it is likely that, particularly on the geological timescale, the temperature regime experienced by marine organisms has never been stable. These temperature changes vary in timescale from daily, through seasonal variations, to long-term environmental change over tens of millions of years. Whereas physiological work can give information on how individual organisms may react phenotypically to short-term change, the way benthic communities react to long-term change can only be studied from the fossil record. The present benthic marine fauna of the Southern Ocean is rich and diverse, consisting of a mixture of taxa with differing evolutionary histories and biogeographical affinities, suggesting that at no time in the Cenozoic did continental ice sheets extend sufficiently to eradicate all shallow-water faunas around Antarctica at the same time. Nevertheless, certain features do suggest the operation of vicariant processes, and climatic cycles affecting distributional ranges and ice-sheet extension may both have enhanced speciation processes. The overall cooling of southern high-latitude seas since the mid-Eocene has been neither smooth nor steady. Intermittent periods of global warming and the influence of Milankovitch cyclicity is likely to have led to regular pulses of migration in and out of Antarctica. The resultant diversity pump may explain in part the high species richness of some marine taxa in the Southern Ocean. It is difficult to suggest how the existing fauna will react to present global warming. Although it is certain the fauna will change, as all faunas have done throughout evolutionary time, we cannot predict with confidence how it will do so.

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