Mass balanced trophic models and short-term dynamical simulations for benthic ecological systems of Mejillones and Antofagasta bays (SE Pacific): Comparative network structure and assessment of human impacts

2015 ◽  
Vol 309-310 ◽  
pp. 153-162 ◽  
Author(s):  
Marco Ortiz ◽  
Fernando Berrios ◽  
Leonardo Campos ◽  
Roberto Uribe ◽  
Alejandro Ramirez ◽  
...  
Keyword(s):  
Network Structure ◽  
Human Impacts ◽  
Ecological Systems ◽  
Short Term ◽  
Dynamical Simulations ◽  
Trophic Models

scholarly journals Applying ecological resistance and resilience to dissect bacterial antibiotic responses

2018 ◽  
Vol 4 (12) ◽  
pp. eaau1873 ◽  
Author(s):  
Hannah R. Meredith ◽  
Virgile Andreani ◽  
Helena R. Ma ◽  
Allison J. Lopatkin ◽  
Anna J. Lee ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Antibiotic Treatment ◽  
Bacterial Pathogens ◽  
Ecological Systems ◽  
Essential Property ◽  
Short Term ◽  
Bacterial Response ◽  
Ecological Resistance ◽  
Combination Treatments ◽  
Lactam Antibiotic

An essential property of microbial communities is the ability to survive a disturbance. Survival can be achieved through resistance, the ability to absorb effects of a disturbance without a notable change, or resilience, the ability to recover after being perturbed by a disturbance. These concepts have long been applied to the analysis of ecological systems, although their interpretations are often subject to debate. Here, we show that this framework readily lends itself to the dissection of the bacterial response to antibiotic treatment, where both terms can be unambiguously defined. The ability to tolerate the antibiotic treatment in the short term corresponds to resistance, which primarily depends on traits associated with individual cells. In contrast, the ability to recover after being perturbed by an antibiotic corresponds to resilience, which primarily depends on traits associated with the population. This framework effectively reveals the phenotypic signatures of bacterial pathogens expressing extended-spectrum β-lactamases (ESBLs) when treated by a β-lactam antibiotic. Our analysis has implications for optimizing treatment of these pathogens using a combination of a β-lactam and a β-lactamase (Bla) inhibitor. In particular, our results underscore the need to dynamically optimize combination treatments based on the quantitative features of the bacterial response to the antibiotic or the Bla inhibitor.

A trajectories' guide to the state space - learning missing terms in bifurcating ecological systems

2021 ◽  
Author(s):  
Rahel Vortmeyer-Kley ◽  
Pascal Nieters ◽  
Gordon Pipa
Keyword(s):  
Machine Learning ◽  
Differential Equations ◽  
Algal Blooms ◽  
Ecological Systems ◽  
Short Term ◽  
Specific System ◽  
Worst Case ◽  
System Components ◽  
Full Knowledge

<p>Ecological systems typically can exhibit various states ranging from extinction to coexistence of different species in oscillatory states. The switch from one state to another is called bifurcation. All these behaviours of a specific system are hidden in a set of describing differential equations (DE) depending on different parametrisations. To model such a system as DE requires full knowledge of all possible interactions of the system components. In practise, modellers can end up with terms in the DE that do not fully describe the interactions or in the worst case with missing terms.</p><p>The framework of universal differential equations (UDE) for scientific machine learning (SciML) [1] allows to reconstruct the incomplete or missing term from an idea of the DE and a short term timeseries of the system and make long term predictions of the system’s behaviour. However, the approach in [1] has difficulties to reconstruct the incomplete or missing term in systems with bifurcations. We developed a trajectory-based loss metric for UDE and SciML to tackle the problem and tested it successfully on a system mimicking algal blooms in the ocean.</p><p>[1] Rackauckas, Christopher, et al. "Universal differential equations for scientific machine learning." arXiv preprint arXiv:2001.04385 (2020).</p>

scholarly journals The Influence of the Knowledge-Based Network Structure Hole on Enterprise Innovation Performance: The Threshold Effect of R&D Investment Intensity

2020 ◽  
Vol 12 (15) ◽  
pp. 6155
Author(s):  
Jiajia Hao ◽  
Chunling Li ◽  
Runsen Yuan ◽  
Masood Ahmed ◽  
Muhammad Asif Khan ◽  
...  
Keyword(s):  
Network Structure ◽  
Positive Impact ◽  
Threshold Effect ◽  
Innovation Performance ◽  
Short Term ◽  
The Sustainable Development ◽  
Knowledge Based ◽  
D Investment ◽  
Positive Effect

The purpose of innovation is to consume fewer natural resources in order to create sustainable performance; therefore, innovation can ease the pressure of the ecological load and promote the sustainable development of the economy. Taking the 269 enterprises listed on the main board of the electronic information industry from 2010 to 2019 as samples, using the threshold panel data model, the nonlinear relationship between the knowledge-based network structure hole and the short-term and long-term innovation performance of the enterprises were studied, and the threshold effect of R&D investment intensity was discussed. When the R&D investment intensity is from 1.96% to 15.96%, the knowledge-based network structure hole has a significant positive impact on short-term innovation performance. When the R&D investment intensity is from 5.72% to 10.64%, the knowledge-based network structure hole has a significant positive effect on long-term innovation performance. Lower R&D investment intensity can make the knowledge-based network structure hole promote the increase of short term innovation performance, but to make the knowledge-based network structure hole have a positive impact on long term innovation performance, the R&D investment intensity should be increased by more than 5.72%. When R&D investment intensity is not higher than 15.96%, the knowledge-based network structure hole has a significant positive impact on short term innovation performance, but to make the knowledge-based network structure hole maintain the positive effect on long term innovation performance, R&D investment intensity should not exceed 10.64%. Therefore, enterprises should be guided to optimize the knowledge-based network structure according to the R&D investment intensity in order to improve the short term and long-term innovation performance of an enterprise. These research results can help enterprises to save resources and promote the sustainable development of the economy.

Robustness, institutions, and large-scale change in social-ecological systems: the Hohokam of the Phoenix Basin

2006 ◽  
Vol 2 (2) ◽  
pp. 133-155 ◽  
Author(s):  
JOHN M. ANDERIES
Keyword(s):  
Formal Model ◽  
Irrigation System ◽  
Ecological Systems ◽  
Short Term ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Term Change ◽  
Phoenix Basin ◽  
The Phoenix

Societies frequently generate public infrastructure and institutional arrangements in order to mediate short-term environmental fluctuations. However, the social and ecological consequences of activities dealing with short-term disturbances may increase the vulnerability of the system to infrequent events or to long-term change in patterns of short-term variability. Exploring this possibility requires the study of long-term, transformational change. The archaeological record provides many examples of long-term change, such as the Hohokam who occupied the Phoenix Basin for over a thousand years and developed a complex irrigation society. In the eleventh and fourteenth centuries, the Hohokam society experienced reductions in complexity and scale possibly associated with regional climatic events. We apply a framework designed to explore robustness in coupled social-ecological systems to the Hohokam Cultural Sequence. Based on this analysis, a stylized formal model is developed to explore the possibility that the success of the Hohokam irrigation system and associated social structure may have increased their vulnerability to rare climactic shocks.

scholarly journals Reply to Piperno et al.: It is too soon to argue for localized, short-term human impacts in interfluvial Amazonia

2017 ◽  
Vol 114 (21) ◽  
pp. E4120-E4121 ◽  
Author(s):  
Jennifer Watling ◽  
José Iriarte ◽  
Francis E. Mayle ◽  
Denise Schaan ◽  
Luiz C. R. Pessenda ◽  
...  
Keyword(s):  
Human Impacts ◽  
Short Term

scholarly journals On the temporally flexible structure of plant-pollinator interaction networks

2020 ◽  
Author(s):  
Paul J. CaraDonna ◽  
Nickolas M. Waser
Keyword(s):  
Temporal Variation ◽  
Network Structure ◽  
Species Interactions ◽  
Interspecific Interactions ◽  
Activity Period ◽  
Individual Species ◽  
Ecological Communities ◽  
Short Term ◽  
Temporal Flexibility ◽  
Plant Pollinator

AbstractEcological communities consist of species that are joined in complex networks of interspecific interaction. The interactions that networks depict often form and dissolve rapidly, but this temporal variation is not well integrated into our understanding of the causes and consequences of network structure. If interspecific interactions exhibit temporal flexibility across time periods over which organisms co-occur, then the emergent structure of the corresponding network may also be temporally flexible, something that a temporally-static perspective would miss. Here, we use an empirical system to examine short-term flexibility in network structure (connectance, nestedness, and specialization), and in individual species interactions that contribute to that structure. We investigated weekly plant-pollinator networks in a subalpine ecosystem across three summer growing seasons. To link the interactions of individual species to properties of their networks, we examined weekly temporal variation in species’ contributions to network structure. As a test of the potential robustness of networks to perturbation, we also simulated the random loss of species from weekly networks. We then compared the properties of weekly networks to the properties of cumulative networks that aggregate field observations over each full season. A week-to-week view reveals considerable flexibility in the interactions of individual species and their contributions to network structure. For example, species that would be considered relatively generalized across their entire activity period may be much more specialized at certain times, and at no point as generalized as the cumulative network may suggest. Furthermore, a week-to-week view reveals corresponding temporal flexibility in network structure and potential robustness throughout each summer growing season. We conclude that short-term flexibility in species interactions leads to short-term variation in network properties, and that a season-long, cumulative perspective may miss important aspects of the way in which species interact, with implications for understanding their ecology, evolution, and conservation.

scholarly journals A Novel ICT Framework for Sustainable Development Goals

2019 ◽  
Vol 11 (7) ◽  
pp. 1961 ◽  
Author(s):  
Olivera Kostoska ◽  
Ljupco Kocarev
Keyword(s):  
Sustainable Development ◽  
Sustainable Development Goals ◽  
Integrated Approach ◽  
Ecological Systems ◽  
Short Term ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
The Social ◽  
Development Goals

Sustainable development is critical to ensure the future of humanity. Therefore, the assessment and governance of sustainability becomes a central challenge our society is facing. This paper provides a novel ICT framework for addressing sustainable development goals. It is characterized by both local and global considerations, in the context of economic, ecological, and social aspects of sustainable development. The framework consists of three modules: data module, sustainability module, and governance module. Data module integrates data from several sources, processes data, infers knowledge, and transforms data into understandable information and knowledge. The second module implements SDGs at the level of municipality/city, ensures ranking of locally transformed SDGs to arrange them in line with the values and needs of the local communities, and proposes an integrated approach in modeling the social-ecological systems. By implementing governance theories, the governance module permits an effective citizen engagement in governance of SDGs. The ICT framework addresses short-term and long-term SDGs and allows for the vertical and horizontal linkages among diverse stakeholders, as well as for their contributions to the nested rule structures employed at operational, collective, and constitutional levels. Thus, the framework we provide here ensures a paradigm shift in approaching SDGs for the advancement of our society.

scholarly journals Unveiling dimensions of stability in complex ecological networks

2019 ◽  
Vol 116 (51) ◽  
pp. 25714-25720 ◽  
Author(s):  
Virginia Domínguez-García ◽  
Vasilis Dakos ◽  
Sonia Kéfi
Keyword(s):  
Global Environmental Change ◽  
Early Response ◽  
Ecological Systems ◽  
Ecological Communities ◽  
Independent Components ◽  
Global Environmental ◽  
Overall Stability ◽  
Dynamical Simulations ◽  
The Stability ◽  
The Relationship

Understanding the stability of ecological communities is a matter of increasing importance in the context of global environmental change. Yet it has proved to be a challenging task. Different metrics are used to assess the stability of ecological systems, and the choice of one metric over another may result in conflicting conclusions. Although each of the multitude of metrics is useful for answering a specific question about stability, the relationship among metrics is poorly understood. Such lack of understanding prevents scientists from developing a unified concept of stability. Instead, by investigating these relationships we can unveil how many dimensions of stability there are (i.e., in how many independent components stability metrics can be grouped), which should help build a more comprehensive concept of stability. Here we simultaneously measured 27 stability metrics frequently used in ecological studies. Our approach is based on dynamical simulations of multispecies trophic communities under different perturbation scenarios. Mapping the relationships between the metrics revealed that they can be lumped into 3 main groups of relatively independent stability components: early response to pulse, sensitivities to press, and distance to threshold. Selecting metrics from each of these groups allows a more accurate and comprehensive quantification of the overall stability of ecological communities. These results contribute to improving our understanding and assessment of stability in ecological communities.

Sign in / Sign up

Export Citation Format

Share Document