Robust permanence for ecological equations with internal and external feedbacks.

PubMed

Patel, Swati; Schreiber, Sebastian J

2018-07-01

Species experience both internal feedbacks with endogenous factors such as trait evolution and external feedbacks with exogenous factors such as weather. These feedbacks can play an important role in determining whether populations persist or communities of species coexist. To provide a general mathematical framework for studying these effects, we develop a theorem for coexistence for ecological models accounting for internal and external feedbacks. Specifically, we use average Lyapunov functions and Morse decompositions to develop sufficient and necessary conditions for robust permanence, a form of coexistence robust to large perturbations of the population densities and small structural perturbations of the models. We illustrate how our results can be applied to verify permanence in non-autonomous models, structured population models, including those with frequency-dependent feedbacks, and models of eco-evolutionary dynamics. In these applications, we discuss how our results relate to previous results for models with particular types of feedbacks.

Confounding factors in determining causal soil moisture-precipitation feedback

NASA Astrophysics Data System (ADS)

Tuttle, Samuel E.; Salvucci, Guido D.

2017-07-01

Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.

A minimal mathematical model combining several regulatory cycles from the budding yeast cell cycle.

PubMed

Sriram, K; Bernot, G; Képès, F

2007-11-01

A novel topology of regulatory networks abstracted from the budding yeast cell cycle is studied by constructing a simple nonlinear model. A ternary positive feedback loop with only positive regulations is constructed with elements that activates the subsequent element in a clockwise fashion. A ternary negative feedback loop with only negative regulations is constructed with the elements that inhibit the subsequent element in an anticlockwise fashion. Positive feedback loop exhibits bistability, whereas the negative feedback loop exhibits limit cycle oscillations. The novelty of the topology is that the corresponding elements in these two homogeneous feedback loops are linked by the binary positive feedback loops with only positive regulations. This results in the emergence of mixed feedback loops in the network that displays complex behaviour like the coexistence of multiple steady states, relaxation oscillations and chaos. Importantly, the arrangement of the feedback loops brings in the notion of checkpoint in the model. The model also exhibits domino-like behaviour, where the limit cycle oscillations take place in a stepwise fashion. As the aforementioned topology is abstracted from the budding yeast cell cycle, the events that govern the cell cycle are considered for the present study. In budding yeast, the sequential activation of the transcription factors, cyclins and their inhibitors form mixed feedback loops. The transcription factors that involve in the positive regulation in a clockwise orientation generates ternary positive feedback loop, while the cyclins and their inhibitors that involve in the negative regulation in an anticlockwise orientation generates ternary negative feedback loop. The mutual regulation between the corresponding elements in the transcription factors and the cyclins and their inhibitors generates binary positive feedback loops. The bifurcation diagram constructed for the whole system can be related to the different events of the cell cycle in terms of dynamical system theory. The checkpoint mechanism that plays an important role in different phases of the cell cycle are accounted for by silencing appropriate feedback loops in the model.

Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review

DOE PAGES

Klein, Stephen A.; Hall, Alex; Norris, Joel R.; ...

2017-10-24

Here, the response to warming of tropical low-level clouds including both marine stratocumulus and trade cumulus is a major source of uncertainty in projections of future climate. Climate model simulations of the response vary widely, reflecting the difficulty the models have in simulating these clouds. These inadequacies have led to alternative approaches to predict low-cloud feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low clouds and the “cloud-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the cloud-controlling factors change with climate warming,more » one can predict low-cloud feedbacks without using any model simulation of low clouds. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-cloud feedback. Recent studies using this approach predict that the tropical low-cloud feedback is positive mainly due to the observation that reflection of solar radiation by low clouds decreases as temperature increases, holding all other cloud-controlling factors fixed. The positive feedback from temperature is partially offset by a negative feedback from the tendency for the inversion strength to increase in a warming world, with other cloud-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low clouds to the global mean cloud feedback is 0.25 ± 0.18 W m –2 K –1 (90% confidence interval), suggesting it is very unlikely that tropical low clouds reduce total global cloud feedback. Because the prediction of positive tropical low-cloud feedback with this approach is consistent with independent evidence from low-cloud feedback studies using high-resolution cloud models, progress is being made in reducing this key climate uncertainty.« less

Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Stephen A.; Hall, Alex; Norris, Joel R.

Here, the response to warming of tropical low-level clouds including both marine stratocumulus and trade cumulus is a major source of uncertainty in projections of future climate. Climate model simulations of the response vary widely, reflecting the difficulty the models have in simulating these clouds. These inadequacies have led to alternative approaches to predict low-cloud feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low clouds and the “cloud-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the cloud-controlling factors change with climate warming,more » one can predict low-cloud feedbacks without using any model simulation of low clouds. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-cloud feedback. Recent studies using this approach predict that the tropical low-cloud feedback is positive mainly due to the observation that reflection of solar radiation by low clouds decreases as temperature increases, holding all other cloud-controlling factors fixed. The positive feedback from temperature is partially offset by a negative feedback from the tendency for the inversion strength to increase in a warming world, with other cloud-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low clouds to the global mean cloud feedback is 0.25 ± 0.18 W m –2 K –1 (90% confidence interval), suggesting it is very unlikely that tropical low clouds reduce total global cloud feedback. Because the prediction of positive tropical low-cloud feedback with this approach is consistent with independent evidence from low-cloud feedback studies using high-resolution cloud models, progress is being made in reducing this key climate uncertainty.« less

Modeling trial by trial and block feedback in perceptual learning

PubMed Central

Liu, Jiajuan; Dosher, Barbara; Lu, Zhong-Lin

2014-01-01

Feedback has been shown to play a complex role in visual perceptual learning. It is necessary for performance improvement in some conditions while not others. Different forms of feedback, such as trial-by-trial feedback or block feedback, may both facilitate learning, but with different mechanisms. False feedback can abolish learning. We account for all these results with the Augmented Hebbian Reweight Model (AHRM). Specifically, three major factors in the model advance performance improvement: the external trial-by-trial feedback when available, the self-generated output as an internal feedback when no external feedback is available, and the adaptive criterion control based on the block feedback. Through simulating a comprehensive feedback study (Herzog & Fahle 1997, Vision Research, 37 (15), 2133–2141), we show that the model predictions account for the pattern of learning in seven major feedback conditions. The AHRM can fully explain the complex empirical results on the role of feedback in visual perceptual learning. PMID:24423783

Uncertain soil moisture feedbacks in model projections of Sahel precipitation

NASA Astrophysics Data System (ADS)

Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra

2017-06-01

Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.