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The gap between the limited human sense of how living entities change over time and the ways in which living systems change is one of the most potent uncertainties in ecological knowledge. This gap remains a significant source of problems and errors for those working with the transformations of living systems. This article foregrounds Mary Catherine Bateson's cybernetic practice of working with narratives in order to cultivate better understanding and responses to change, at the level of both societies and individuals. To do so, I investigate some significant moments, encounters and projects that connect her practice to the ecological ideas of her father, Gregory Bateson and situate their ideas on abduction, metaphor, recursion and narrative within broader discussions of ecological change. The Batesons did not seek a particular attitudinal change towards the transformation of selves, cities and worlds but rather sought to change the very understanding of what an attitude towards change should be, a distinction that is worth pondering given the challenges of attending to change within the present ecological crisis. [ABSTRACT FROM AUTHOR]

Change in music therapy is often modeled linearly. In linear analysis, change is represented as the difference between the scores recorded before and after treatment, where changes in the input are proportional to the output. However, changes in complex systems are often not linear and depend on time. We propose Dynamic Systems Theory (DST) as a means to overcome the shortcomings of linear analysis and enrich the study of change in music therapy. This article aims to introduce and critically discuss the applications of DST in music therapy, focusing on its theoretical and methodological aspects. DST offers a meta-framework to model nonlinear change in music therapy, considering time as continuous. The application of DST can further enhance the understanding of how music therapy works, the shape of the change, and how the relevant therapeutic processes within music therapy support therapeutic change. An introduction to DST theory is provided along with its history, implications, assessment methods, statistical analyses, mathematical modeling, and implementation examples in music therapy research. [ABSTRACT FROM AUTHOR]

A method of establishing a prediction model of the greenhouse temperature based on time-series analysis and the boosting tree model is proposed, aiming at the problem that the temperature of a greenhouse cannot be accurately predicted owing to nonlinear changes in the temperature of the closed ecosystem of a greenhouse featuring modern agricultural technology and various influencing factors. This model comprehensively considers environmental parameters, including humidity inside and outside the greenhouse, air pressure inside and outside the greenhouse, and temperature outside the greenhouse, as well as time-series changes, to make a more accurate prediction of the temperature in the greenhouse. Experiments show that the R2 determination coefficients of different prediction models are improved and the mean square error and mean absolute error are reduced after adding time-series features. Among the models tested, LightGBM performs best, with the mean square error of the prediction results of the model decreasing by 18.61% after adding time-series features. Comparing with the support vector machine, radial basis function neural network, back-propagation neural network, and multiple linear regression model after adding time-series features, the mean square error is 11.70% to 29.12% lower. Furthermore, the fitting degree of LightGBM is the best among the models. The prediction results of LightGBM therefore have important application value in greenhouse temperature control. [ABSTRACT FROM AUTHOR]

It is common to see urban land expansion worldwide, and its characteristics, mechanisms, and effects are widely known. As socio-economic transition and the change of land use policies may reverse the trend of urban expansion, in-depth research on the process of urban land use change is required. Through a process perspective, this paper reveals the change paths, development stages, and spatial patterns of urban residential land use with data from 323 cities in China from 2009 to 2016. The results show that: (1) theoretically, urban residential land use change can be divided into four development stages: an initial stage (Ⅰ), a rapid development stage (Ⅱ), a transition stage (Ⅲ), and a later stage of transition (Ⅳ). The rate of land use change is low—increase—decrease—approaching zero. (2) In about 68.7% of China's cities, urban residential land is experiencing a transition, shifting from accelerating growth to decelerating growth. Given the distinctive transition process, it has been suggested that urban planning and land use policies should give timely responses to the new trends and spatial differences. [ABSTRACT FROM AUTHOR]

Recent work attributing decadal regime changes in temperature to radiative forcing is extended to atmospheric moisture. Temperature, and specific and relative humidity (T, q, RH) from the HadISDH data set were analyzed for regime shifts using the bivariate test. Most shifts in q and T for global and northern hemisphere (NH), and tropical land occurred within a year of each other. Only one shift of q was recorded in the southern hemisphere (SH). RH increased in the NH in 1990–91 and decreased in a series of shifts from the late 1990s, while in the SH decreased from 2001. The tropics have remained neutral, shifting negative over land and positive over the ocean. The global decreases in 2001 and 2011 was −0.56%. Global RH from 32 climate models from the CMIP5 RCP4.5 archive all contained regime shifts but only 4 reached or exceeded the observed decreases by 2100, the earliest in 2056. Regime shifts in RH and fire danger over Australia are consistent with the SH decreases in RH, shifting within one year of global fire season length in 2002, showing that impacts are also being underestimated by current analyses. Methods for nonlinear attribution and the contributing processes for nonlinear change are discussed. These results show that developing a better understanding of nonlinear change in moisture-related climate risk is an urgent task. [ABSTRACT FROM AUTHOR]

Background: A common critique of adventure education research methodology is the overreliance on pre-/post-study designs to measure change. Purpose: This paper compares and contrasts two methods of data analysis on the same adventure education data set to show how these distinct approaches provide starkly different results and interpretation. Methodology/Approach: Using secondary data analysis, we employ a longitudinal data set of the social skill development of urban middle school students who participated in an adventure education program over the course of three academic years. First, change was assessed using a pre-/post-design by a traditional analysis of variance (ANOVA). Next, change was assessed with a six-wave, longitudinal design using multilevel modeling. Findings/Conclusions: Results show that the multilevel modeling approach revealed nonlinear change in the social skill development of middle school students, resulting in more accurate, nuanced estimation of change in social skill development than the ANOVA approach. Implications: The use of longitudinal data and multilevel modeling can be a useful methodological approach and statistical tool for adventure education researchers to not only address the criticisms of quantitative research in adventure education, but more importantly, provide a more thorough understanding of the impact of adventure education on human development. [ABSTRACT FROM AUTHOR]

A method of establishing a prediction model of the greenhouse temperature based on time-series analysis and the boosting tree model is proposed, aiming at the problem that the temperature of a greenhouse cannot be accurately predicted owing to nonlinear changes in the temperature of the closed ecosystem of a greenhouse featuring modern agricultural technology and various influencing factors. This model comprehensively considers environmental parameters, including humidity inside and outside the greenhouse, air pressure inside and outside the greenhouse, and temperature outside the greenhouse, as well as time-series changes, to make a more accurate prediction of the temperature in the greenhouse. Experiments show that the R2 determination coefficients of different prediction models are improved and the mean square error and mean absolute error are reduced after adding time-series features. Among the models tested, LightGBM performs best, with the mean square error of the prediction results of the model decreasing by 18.61% after adding time-series features. Comparing with the support vector machine, radial basis function neural network, back-propagation neural network, and multiple linear regression model after adding time-series features, the mean square error is 11.70% to 29.12% lower. Furthermore, the fitting degree of LightGBM is the best among the models. The prediction results of LightGBM therefore have important application value in greenhouse temperature control.

It is common to see urban land expansion worldwide, and its characteristics, mechanisms, and effects are widely known. As socio-economic transition and the change of land use policies may reverse the trend of urban expansion, in-depth research on the process of urban land use change is required. Through a process perspective, this paper reveals the change paths, development stages, and spatial patterns of urban residential land use with data from 323 cities in China from 2009 to 2016. The results show that: (1) theoretically, urban residential land use change can be divided into four development stages: an initial stage (Ⅰ), a rapid development stage (Ⅱ), a transition stage (Ⅲ), and a later stage of transition (Ⅳ). The rate of land use change is low—increase—decrease—approaching zero. (2) In about 68.7% of China’s cities, urban residential land is experiencing a transition, shifting from accelerating growth to decelerating growth. Given the distinctive transition process, it has been suggested that urban planning and land use policies should give timely responses to the new trends and spatial differences.

Recent work attributing decadal regime changes in temperature to radiative forcing is extended to atmospheric moisture. Temperature, and specific and relative humidity (T, q, RH) from the HadISDH data set were analyzed for regime shifts using the bivariate test. Most shifts in q and T for global and northern hemisphere (NH), and tropical land occurred within a year of each other. Only one shift of q was recorded in the southern hemisphere (SH). RH increased in the NH in 1990–91 and decreased in a series of shifts from the late 1990s, while in the SH decreased from 2001. The tropics have remained neutral, shifting negative over land and positive over the ocean. The global decreases in 2001 and 2011 was −0.56%. Global RH from 32 climate models from the CMIP5 RCP4.5 archive all contained regime shifts but only 4 reached or exceeded the observed decreases by 2100, the earliest in 2056. Regime shifts in RH and fire danger over Australia are consistent with the SH decreases in RH, shifting within one year of global fire season length in 2002, showing that impacts are also being underestimated by current analyses. Methods for nonlinear attribution and the contributing processes for nonlinear change are discussed. These results show that developing a better understanding of nonlinear change in moisture-related climate risk is an urgent task.

Exploring the impact of climate change on drought under changing environmental conditions is crucial for agriculture, ecology, and human society. To evaluate the role of climate change on drought, this study selected the Songnen Plain (SNP) in Northeast China as a study area in which to quantify the relative contributions of climatic variables to the drought trend in accordance with the Standardized Precipitation and Evapotranspiration Index (SPEI). A series of SPEI-based numerical experiments, using combinations of observational and nonlinear detrended climatic variable data series, was used as a synthetic approach with which to analyze the relative impact of the individual climatic variables. Results indicated that drought on the SNP has been mitigated marginally during 1961–2016, mainly during spring, winter, the growing season, and on the annual timescale. Significant trends were detected in relation to temperature, sunshine duration, and wind speed, and these variables had differing roles in drought evolution. An increasing trend in temperature was found to aggravate drought tendency at all investigated timescales; however, decreasing trends in net radiation and wind speed offset the drought tendency caused by rising temperature. The positive contribution of wind speed was larger than the negative contribution of temperature, especially in areas around 46°N. Although the change of precipitation was not significant, it promoted drought mitigation on the SNP in spring, winter, the growing season, and on the annual timescale. The analysis framework used in this study was shown useful for improving understanding of the relationship between climate change and drought evolution, and it could prove helpful in providing rational and regulatory policy strategies regarding drought relief.

Drug-proton antiporters (DHA) play an important role in multi-drug resistance, utilizing the proton-motive force to drive the expulsion of toxic molecules, including antibiotics and drugs. DHA transporters belong to the major facilitator superfamily (MFS), members of which deliver substrates by utilizing the alternating access model of transport. However, the transport process is still elusive. Here, we report the structures of SotB, a member of DHA1 family (TCDB: 2.A.1.2) from Escherichia coli. Four crystal structures of SotB were captured in different conformations, including substrate-bound occluded, inward-facing, and inward-open states. Comparisons between the four structures reveal nonlinear rigid-body movements of alternating access during the state transition from inward-open to occluded conformation. This work not only reveals the conformational dynamics of SotB but also deepens our understanding of the alternating access mechanism of MFS transporters. • Visualizing dynamic alternating access cycle is important for understanding the transport mechanism of MFS transporters. • Crystal structure of SotB in complex with IPTG presents a substrate-bound occlude conformation. • Crystal structures of SotB in different conformations. • Four structures comparison reveals the nonlinear conformational changes from an inward-open to an occluded state. [ABSTRACT FROM AUTHOR]

This study tested the complex relationship among the perceived benefit from and cost of condom use, self-efficacy and condom use among adolescents as a nonlinear dynamic process. Participants were 12th graders in public Bahamian high schools who reported having had sex and frequency of condom use. Results revealed that the perceived benefit and perceived cost as asymmetry variables were significantly associated with condom use (p < 0.001) after controlling for covariates. The association was bifurcated by the variable self-efficacy (p < 0.001). Furthermore, the cusp model was better than linear and logistic regression models in predicting the dynamic changes in condom use behavior, judged by the AIC and BIC, and R2 criteria. These results suggest that adolescent condom use may follow a nonlinear rather than linear dynamic process. Emphasizing bifurcation variables such as self-efficacy that promote sudden change could be essential to strengthen current evidence-based intervention programs in encouraging condom use. [ABSTRACT FROM AUTHOR]

How the pattern of the Earth’s surface warming will change under global warming represents a fundamental question for our understanding of the climate system with implications for regional projections. Despite the importance of this problem there have been few analyses of nonlinear local temperature change as a function of global warming. Individual climate models project nonlinearities, but drivers of nonlinear local change are poorly understood. Here, I present a framework for the identification and quantification of local nonlinearities using a time-slice analysis of a multi-model ensemble. Accelerated local warming is more likely over land than ocean per unit global warming. By examining changes across the model ensemble, I show that models that exhibit summertime drying over mid-latitude land regions, such as in central Europe, tend to also project locally accelerated warming relative to global warming, and vice versa. A case study illustrating some uses of this framework for nonlinearity identification and analysis is presented for north-eastern Australia. In this region, model nonlinear warming in summertime is strongly connected to changes in precipitation, incoming shortwave radiation, and evaporative fraction. In north-eastern Australia, model nonlinearity is also connected to projections for El Niño. Uncertainty in nonlinear local warming patterns contributes to the spread in regional climate projections, so attempts to constrain projections are explored. This study provides a framework for the identification of local temperature nonlinearities as a function of global warming and analysis of associated drivers under prescribed global warming levels.

In the face of growing human impacts on ecosystems, scientists and managers recognize the need to better understand thresholds and nonlinear dynamics in ecological systems to help set management targets. However, our understanding of the factors that drive threshold dynamics, and when and how rapidly thresholds will be crossed is currently limited in many systems. In spite of these limitations, there are approaches available to practitioners today—including ecosystem monitoring, statistical methods to identify thresholds and indicators, and threshold-based adaptive management—that can be used to help avoid ecological thresholds or restore systems that have crossed them. We briefly review the current state of knowledge and then use real-world examples to demonstrate how resource managers can use available approaches to avoid crossing ecological thresholds. We also highlight new tools and indicators being developed that have the potential to enhance our ability to detect change, predict when a system is approaching an ecological threshold, or restore systems that have already crossed a tipping point.

Educational organizations, public schools in particular, are seen as being notoriously inert and resistant to change. While school reform efforts are widespread, educational outcomes such as high school graduation rates and achievement in reading and math continue to show disparity between socioeconomic groups. Why is educational change so hard to accomplish? This article approaches the question from two perspectives: the school reform literature that identifies the factors inhibiting change in school systems, and the literature on complex dynamical systems (CDS), which facilitates understanding of the dynamics underlying inertia and transformation. The need is articulated for empirical research that focuses on reform as an implementation process, to provide further insight in what we know about its impact on educational outcomes. [ABSTRACT FROM AUTHOR]

Although the nonlinear dynamical systems (NDS) paradigm has been highly influential in psychology, economics and the life sciences, its impact in the field of education has been disturbingly modest, particularly in the interface between research and policy, where linear cause and effect relationships are typically presumed when the impact of interventions and educational reform on the behavior of children and adults is measured. This reduction of the educational process to simple input - output relationships without examining the constituent changes in great detail produces significant gaps in our knowledge about the effectiveness of educational initiatives, an issue that has been acknowledged in the research literature as the 'black box problem. ' This paper approaches the black box problem from an NDS perspective and proposes that investigating the self-organizing process in the educational system may help address these gaps. [ABSTRACT FROM AUTHOR]

An interval estimation procedure for proportion of explained observed variance in latent curve analysis is discussed, which can be used as an aid in the process of choosing between linear and nonlinear models. The method allows obtaining confidence intervals for the R 2 indexes associated with repeatedly followed measures in longitudinal studies. In addition to facilitating evaluation of local model fit, the approach is helpful for purposes of differentiating between plausible models stipulating different patterns of change over time, and in particular in empirical situations characterized by large samples and high statistical power. The procedure is also applicable in cross-sectional studies, as well as with general structural equation models. The method is illustrated using data from a nationally representative study of older adults. [ABSTRACT FROM AUTHOR]

The transference relationship within the psychodynamic process was conceived of as a self-organizing system under the assumption that patient and therapist instability trajectories prove similar. Nine patients and therapists each rated their experience of the therapeutic interaction (Intrex, SASB) over the course of therapy (29 to 35 sessions). A measure of instability was calculated for these ratings across the resulting time series. The degree of synchronicity (correlation) and the correspondence of instability levels (measure of difference) were calculated for each patient-therapist dyad. Destabilization of ratings was highly synchronous and the level of destabilization corresponded highly in successful therapies. Destabilization in non-successful cases showed low synchronicity and/or therapist ratings proved more instable. The results suggest that systematically including a measure of instability and associations between patient and therapist ratings may prove fruitful in process research. [ABSTRACT FROM PUBLISHER]

The authors developed a concept that applies self-organization theory to psychodynamic principles. According to this concept, episodes of temporary destabilization represent a precondition for abrupt changes within the therapeutic process. The authors examined six courses of therapy (patients diagnosed with depression and personality disorder). After each therapy session, patients rated their experience of the therapeutic interaction. A measure of instability was used to identify episodes of destabilization with respect to patients' interaction experience throughout the process. Episodes of pronounced destabilization occurred in the four courses of therapy that showed better therapy outcomes. These episodes were characterized by temporary strong deteriorations in interaction experience (negative peaks). Three of the four courses showed subsequent discontinuous improvements to a higher level of interaction. Results indicate that the systematic inclusion of a measure of instability is worthwhile in investigations of discontinuous changes. This method allows the theoretical assumptions of the psychodynamic approach to be tested. [ABSTRACT FROM AUTHOR]

Organizational fields undergo upheavals. Shifting industry boundaries, new network forms, emerging sectors, and volatile ecosystems have become the stuff of everyday organizational life. Curiously, profound changes of this sort receive scant attention in organization theory and research. Researchers acknowledge fieldwide flux, emergence, convergence, and collapse, but sidestep direct investigations of the causes and dynamic processes, leaving these efforts to political scientists and institutional economists. We attribute this neglect to our field's philosophical, theoretical, and methodological fealty to the precepts of equilibrium and linearity. We argue that ingrained assumptions and habituated methodologies dissuade organizational scientists from grappling with problems to which these ideas and tools do not apply. Nevertheless, equilibrium and linearity are assumptions of social theory, not facts of social life. Drawing on four empirical studies of organizational fields in flux, we suggest new intellectual perspectives and methodological heuristics that may facilitate investigation of fields that are far from equilibrium. We urge our colleagues to transcend the general linear model, and embrace ideas like field configuration, complex adaptive systems, self-organizing networks, and autocatalytic feedback. We recommend conducting natural histories of organizational fields, and paying especially close attention to turning points when fields are away from equilibrium and discontinuous changes are afoot. [ABSTRACT FROM AUTHOR]

Predictions of the effects of climate change on the extent of forests, savannas and deserts are usually based on simple response models derived from actual vegetation distributions. In this review, we show two major problems with the implicitly assumed straightforward cause–effect relationship. Firstly, several studies suggest that vegetation itself may have considerable effects on regional climate implying a positive feedback, which can potentially lead to large-scale hysteresis. Secondly, vegetation ecologists have found that effects of plants on microclimate and soils can cause a microscale positive feedback, implying that critical precipitation conditions for colonization of a site may differ from those for disappearance from that site. We argue that it is important to integrate these nonlinearities at disparate scales in models to produce more realistic predictions of potential effects of climate change and deforestation. [ABSTRACT FROM AUTHOR]

Dynamic birefringence of the linear optical amplifier (LOA) is theoretically and experimentally investigated. Significant nonlinear variations of the state of polarization with the input power and bias current of the LOA have been found. Based on this nonlinear change of the state of polarization, an all-optical 2R regenerator is demonstrated. Under static operation, an extinction ratio (ER) improvement of 15 dB has been obtained for an input ER of 5 dB. With a degraded input signal, a receiver sensitivity improvement of over 3 dB at a bit-error rate (BER) of 10-9 has been found for 2.5 Gb/s. For 10 Gb/s, zero power penalty is observed. Significant improvements of ER for both 2.5 and 10 Gb/s are obtained. [ABSTRACT FROM PUBLISHER]

• A statistic framework and nonlinear detrend method are used in this study. • The relative contributions of climate variability on drought are quantified. • The dependence of drought trend on climate change varies in region and timescale. Exploring the impact of climate change on drought under changing environmental conditions is crucial for agriculture, ecology, and human society. To evaluate the role of climate change on drought, this study selected the Songnen Plain (SNP) in Northeast China as a study area in which to quantify the relative contributions of climatic variables to the drought trend in accordance with the Standardized Precipitation and Evapotranspiration Index (SPEI). A series of SPEI-based numerical experiments, using combinations of observational and nonlinear detrended climatic variable data series, was used as a synthetic approach with which to analyze the relative impact of the individual climatic variables. Results indicated that drought on the SNP has been mitigated marginally during 1961–2016, mainly during spring, winter, the growing season, and on the annual timescale. Significant trends were detected in relation to temperature, sunshine duration, and wind speed, and these variables had differing roles in drought evolution. An increasing trend in temperature was found to aggravate drought tendency at all investigated timescales; however, decreasing trends in net radiation and wind speed offset the drought tendency caused by rising temperature. The positive contribution of wind speed was larger than the negative contribution of temperature, especially in areas around 46°N. Although the change of precipitation was not significant, it promoted drought mitigation on the SNP in spring, winter, the growing season, and on the annual timescale. The analysis framework used in this study was shown useful for improving understanding of the relationship between climate change and drought evolution, and it could prove helpful in providing rational and regulatory policy strategies regarding drought relief. [ABSTRACT FROM AUTHOR]