Change Detection Memory in Rhesus Monkeys and Humans

Visual short-term memory (VSTM) is the storage of visual information over a brief time period (usually a few seconds or less). Over the past decade, the most popular task for studying VSTM in humans has been the change detection task. In this task, subjects must remember several visual items per trial in order to identify a change following a brief delay interval. Results from change detection tasks have shown that VSTM is limited; humans are only able to accurately hold a few visual items in mind over a brief delay. However, there has been much debate in regard to the structure or cause of these limitations. The two most popular conceptualizations of VSTM limitations in recent years have been the fixed-capacity model and the continuous-resource model. The fixed-capacity model proposes a discrete limit on the total number of visual items that can be stored in VSTM. The continuous-resource model proposes a continuous-resource that can be allocated among many visual items in VSTM, with noise in item memory increasing as the number of items to be remembered increases. While VSTM is far from being completely understood in humans, even less is known about VSTM in non-human animals, including the rhesus monkey (Macaca mulatta). Given that rhesus monkeys are the premier medical model for humans, it is important to understand their VSTM if they are to contribute to understanding human memory. The primary goals of this study were to train and test rhesus monkeys and humans in change detection in order to directly compare VSTM between the two species and explore the possibility that direct species comparison might shed light on the fixed-capacity vs. continuous-resource models of VSTM. The comparative results suggest qualitatively similar VSTM for the two species through converging evidence supporting the continuous-resource model and thereby establish rhesus monkeys as a good system for exploring neurophysiological correlates of VSTM.

Collaborative Conversations for Change: A SolutionFocused Approach to Family Centered Practice

The renewed interest in Family Centered Practice, prompted by the funding of Family Preservation and Support Programs, has created a need for training practitioners at a number of different levels and for a variety of roles. This paper will describe a training program for Family Centered Practice. Building on an empowerment model, the author presents an approach for working with families and children that views the tragedies of the past as resources, rather than the major cause of present problems. Collaborative Conversations for Change adapts the solution-focused therapy model to nontherapy roles that are required for a program to be family centered. Although these roles are not therapy, they are nevertheless therapeutic and reinforce clients' strengths. These collaborative conversations, however brief they may be, recognize that the client is the expert on his/her pain and struggles and the practitioner is the expert on assisting her/him plan change. Additionally, illustrations from a cross-cultural perspective demonstrate the utility of collaborative conversation in enhancing cultural competence.

Is there a common pattern of future gas-phase air pollution in Europe under diverse climate change scenarios?

Climate change alone influences future levels of tropospheric ozone and their precursors through modifications of gas-phase chemistry, transport, removal, and natural emissions. The goal of this study is to determine at what extent the modes of variability of gas-phase pollutants respond to different climate change scenarios over Europe. The methodology includes the use of the regional modeling system MM5 (regional climate model version)-CHIMERE for a target domain covering Europe. Two full-transient simulations covering from 1991–2050 under the SRES A2 and B2 scenarios driven by ECHO-G global circulation model have been compared. The results indicate that the spatial patterns of variability for tropospheric ozone are similar for both scenarios, but the magnitude of the change signal significantly differs for A2 and B2. The 1991–2050 simulations share common characteristics for their chemical behavior. As observed from the NO2 and α-pinene modes of variability, our simulations suggest that the enhanced ozone chemical activity is driven by a number of parameters, such as the warming-induced increase in biogenic emissions and, to a lesser extent, by the variation in nitrogen dioxide levels. For gas-phase pollutants, the general increasing trend for ozone found under A2 and B2 forcing is due to a multiplicity of climate factors, such as increased temperature, decreased wet removal associated with an overall decrease of precipitation in southern Europe, increased photolysis of primary and secondary pollutants as a consequence of lower cloudiness and increased biogenic emissions fueled by higher temperatures.

Land use change and nitrogen feedbacks constrain the trajectory of the land carbon sink

Our understanding of Earth's carbon climate system depends critically upon interactions between rising atmospheric CO2, changing land use, and nitrogen limitation on vegetation growth. Using a global land model, we show how these factors interact locally to generate the global land carbon sink over the past 200 years. Nitrogen constraints were alleviated by N2 fixation in the tropics and by atmospheric nitrogen deposition in extratropical regions. Nonlinear interactions between land use change and land carbon and nitrogen cycling originated from three major mechanisms: (i) a sink foregone that would have occurred without land use conversion; (ii) an accelerated response of secondary vegetation to CO2 and nitrogen, and (iii) a compounded clearance loss from deforestation. Over time, these nonlinear effects have become increasingly important and reduce the present-day net carbon sink by ~40% or 0.4 PgC yr−1.

Recent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate change

Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.

Paleoclimate data-model comparison and the role of climate forcings over the past 1500 years

The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.

Declining pine growth in Central Spain coincides with increasing diurnal temperature range since the 1970s

Growing evidence suggests environmental change to be most severe across the semi-arid subtropics, with past, present and projected drying of the Mediterranean Basin posing a key multidisciplinary challenge. Consideration of a single climatic factor, however, often fails to explain spatiotemporal growth dynamics of drought-prone ecosystems. Here, we present annually resolved and absolutely dated ring width measurements of 871 Scots pines (Pinus sylvestris) from 18 individual plot sites in the Central Spanish Pinar Grande forest reserve. Although comprising tree ages from 6 to 175 years, this network correlates surprisingly well with the inverse May–July diurnal temperature range (r = 0.84; p < 0.00011956–2011). Ring width extremes were triggered by pressure anomalies of the North Atlantic Oscillation, and the long-term growth decline coincided with Iberian-wide drying since the mid-1970s. Climate model simulations not only confirm this negative trend over the last decades but also project drought to continuously increase over the 21st century. Associated ecological effects and socio-economic consequences should be considered to improve adaptation strategies of agricultural and forest management, as well as biodiversity conservation and ecosystem service.

Quantitative MRI of spinal cord injury in a rat model: Correlative studies

Serial quantitative and correlative studies of experimental spinal cord injury (SCI) in rats were conducted using three-dimensional magnetic resonance imaging (MRI). Correlative measures included morphological histopathology, neurobehavioral measures of functional deficit, and biochemical assays for N-acetyl-aspartate (NAA), lactate, pyruvate, and ATP. A spinal cord injury device was characterized and provided a reproducible injury severity. Injuries were moderate and consistent to within $\pm$20% (standard deviation). For MRI, a three-dimensional implementation of the single spin-echo FATE (Fast optimum angle, short TE) pulse sequence was used for rapid acquisition, with a 128 x 128 x 32 (x,y,z) matrix size and a 0.21 x 0.21 x 1.5 mm resolution. These serial studies revealed a bimodal characteristic in the evolution in MRI pathology with time. Early and late phases of SCI pathology were clearly visualized in $T\sb2$-weighted MRI, and these corresponded to specific histopathological changes in the spinal cord. Centralized hypointense MRI regions correlated with evidence of hemorrhagic and necrotic tissue, while surrounding hyperintense regions represented edema or myelomalacia. Unexpectedly, $T\sb2$-weighted MRI pathology contrast at 24 hours after injury appeared to subside before peaking at 72 hours after injury. This change is likely attributable to ongoing secondary injury processes, which may alter local $T\sb2$ values or reduce the natural anisotropy of the spinal cord. MRI, functional, and histological measures all indicated that 72 hours after injury was the temporal maximum for quantitative measures of spinal cord pathology. Thereafter, significant improvement was seen only in neurobehavioral scores. Significant correlations were found between quantitated MRI pathology and histopathology. Also, NAA and lactate levels correlated with behavioral measures of the level of function deficit. Asymmetric (rostral/caudal) changes in NAA and lactate due to injury indicate that rostral and caudal segments from the injury site are affected differently by the injury. These studies indicate that volumetric quantitation of MRI pathology from $T\sb2$-weighted images may play an important role in early prediction of neurologic deficit and spinal cord pathology. The loss of $T\sb2$ contrast at 24 hours suggests MR may be able to detect certain delayed mechanisms of secondary injury which are not resolved by histopathology or other radiological modalities. Furthermore, in vivo proton magnetic resonance spectroscopy (MRS) studies of SCI may provide a valuable addition source of information about changes in regional spinal cord lactate and NAA levels, which are indicative of local metabolic and pathological changes. ^

Valuation of ecosystem goods and services. Part 2: Implications of unpredictable novel change

This is the second part of a two-part paper which offers a new approach to the valuation of ecosystem goods and services. In the first part a simple pre-industrial model was introduced to show how the interdependencies between the three subsystems, society, economy and nature, influence values, and how values change over time. In this second part the assumption of perfect foresight is dropped. I argue that due to novelty and complexity ex ante unpredictable change occurs within the three subsystems society, economy and nature. Again the simple pre-industrial model, which was introduced in part 1, serves as a simple paradigm to show how unpredictable novel change limits the possibility to derive accurate estimates of values.

Psychiatric severity and behavior change in alcoholism

Individuals who are diagnosed with a chronic mental illness and an alcohol use disorder comprise a high risk population that challenges the mental health care system. Effective treatment for the dually diagnosed, who are characterized by heterogeneity in their psychiatric diagnoses, their substance use patterns, and their current degree of dysfunction, presents a challenge. Several integrated treatment models have been developed that attempt to concurrently treat patients' psychiatric and substance abuse problems. At this point in the development of these "dual diagnosis" programs, treatment planning is hindered by a lack of knowledge about the relation of psychiatric severity to the process of recovery from alcohol abuse and dependence.^ The present study sought to advance the field's understanding of the relation between psychiatric severity and the process of behavior change through an examination of the relation between dimensions of psychiatric severity and Prochaska and DiClemente's Transtheoretical Model (TTM) constructs. The TTM, which focuses on identifying the processes of change that appear to underlie the modification of addictive behaviors, provides a way of conceptualizing and measuring specific elements relevant to the desired behavior change. Knowledge of the relation between these constructs and psychiatric severity will enable treatment planners to develop dual diagnosis programs which target clients' needs with a much higher level of specificity.^ One hundred-thirty two alcohol dependent patients in a dual diagnosis treatment program were assessed on psychiatric severity (defined as number of symptoms and level of distress resulting from symptoms) and the Transtheoretical Model constructs. The constructs include stages and processes of change for alcohol use, alcohol decisional balance, and alcohol abstinence self-efficacy. Results indicate that the TTM variable of "temptation to drink" is most strongly related to psychiatric severity: the more psychiatric distress a person is experiencing, the more he or she is tempted to drink. The "cons" of drinking were also related to psychiatric severity, indicating that participants who were experiencing more psychiatric distress also endorsed as important a higher number of the negative aspects of drinking.^ Additional aims of this investigation were to determine whether participants' scores on the Transtheoretical Model variables were associated with their: (a) severity of drinking, defined as frequency, quantity and consequences of use, (b) previous psychiatric and substance abuse treatment episodes, and (c) functional impairment. Associations were found among these variables and each of the key constructs of the Transtheoretical Model. Each association is explored in detail and implications for treatment programming are discussed. ^

PREDICTIVE VARIABLES FOR WEIGHT CHANGE 2 YEARS FOLLOWING PARTICIPATION IN A WEIGHT LOSS INTERVENTION PROGRAM

A historical prospective study was designed to assess the man weight status of subjects who participated in a behavioral weight reduction program in 1983 and to determine whether there was an association between the dependent variable weight change and any of 31 independent variables after a 2 year follow-up period. Data was obtained by abstracting the subjects records and from a follow-up questionnaire administered 2 years following program participation. Five hundred nine subjects (386 females and 123 males) of 1460 subjects who participated in the program, completed and returned the questionnaire. Results showed that mean weight was significantly different (p < 0.001) between the measurement at baseline and after a 2 year follow-up period. The mean weight loss of the group was 5.8 pounds, 10.7 pounds for males and 4.2 pounds for females after a 2 year follow-up period. A total of 63.9% of the group, 69.9% of males and 61.9% of females were still below their initial weight after the 2 year follow-up period. Sixteen of the 31 variables assessed utilizing bivariate analyses were found to be significantly (p (LESSTHEQ) 0.05) associated with weight change after a 2 year follow-up period. These variables were then entered into a multivariate linear regression model. A total of 37.9% of the variance of the dependent variable, weight change, was accounted for by all 16 variables. Eight of these variables were found to be significantly (p (LESSTHEQ) 0.05) predictive of weight change in the stepwise multivariate process accounting for 37.1% of the variance. These variables included: Two baseline variables (percent over ideal body weight at enrollment and occupation) and six follow-up variables (feeling in control of eating habits, percent of body weight lost during treatment, frequency of weight measurement, physical activity, eating in response to emotions, and number of pounds of weight gain needed to resume a diet). It was concluded that a greater amount of emphasis should be placed on the six follow-up variables by clinicians involved in the treatment of obesity, and by the subjects themselves to enhance their chances of success at long-term weight loss. ^

Drivers of collaboration to mitigate climate change: An illustration of Swiss climate policy over 15 years

Climate change mitigation policy is driven by scientific knowledge and involves actors from the international, national and local decision-making levels. This multi-level and cross-sectoral context requires collaborative management when designing mitigation solutions over time and space. But collaboration in general policymaking settings, and particularly in the complex domain of climate mitigation, is not an easy task. This paper addresses the question of what drives collaboration among collective actors involved in climate mitigation policy. We wish to investigate whether common beliefs or power structures influence collaboration among actors. We adopt a longitudinal approach to grasp differences between the early and more advanced stages of mitigation policy design. We use survey data to investigate actors’ collaboration, beliefs and power, and apply a Stochastic Actor-oriented Model for network dynamics to three subsequent networks in Swiss climate policy between 1995 and 2012. Results show that common beliefs among actors, as well as formal power structures, have a higher impact on collaboration relations than perceived power structures. Furthermore, those effects hold true for decision-making about initial mitigation strategies, but less so for the implementation of those measures.

Decadal Variability in the Northeast Pacific in a Physical-Ecosystem Model: Role of Mixed Layer Depth and Trophic Interactions

A basin-wide interdecadal change in both the physical state and the ecology of the North Pacific occurred near the end of 1976. Here we use a physical-ecosystem model to examine whether changes in the physical environment associated with the 1976-1977 transition influenced the lower trophic levels of the food web and if so by what means. The physical component is an ocean general circulation model, while the biological component contains 10 compartments: two phytoplankton, two zooplankton, two detritus pools, nitrate, ammonium, silicate, and carbon dioxide. The model is forced with observed atmospheric fields during 1960-1999. During spring, there is a similar to 40% reduction in plankton biomass in all four plankton groups during 1977-1988 relative to 1970-1976 in the central Gulf of Alaska (GOA). The epoch difference in plankton appears to be controlled by the mixed layer depth. Enhanced Ekman pumping after 1976 caused the halocline to shoal, and thus the mixed layer depth, which extends to the top of the halocline in late winter, did not penetrate as deep in the central GOA. As a result, more phytoplankton remained in the euphotic zone, and phytoplankton biomass began to increase earlier in the year after the 1976 transition. Zooplankton biomass also increased, but then grazing pressure led to a strong decrease in phytoplankton by April followed by a drop in zooplankton by May: Essentially, the mean seasonal cycle of plankton biomass was shifted earlier in the year. As the seasonal cycle progressed, the difference in plankton concentrations between epochs reversed sign again, leading to slightly greater zooplankton biomass during summer in the later epoch.

A model-data comparison of Holocene timberline changes in the Swiss Alps reveals past and future drivers of mountain forest dynamics

Mountain vegetation is strongly affected by temperature and is expected to shift upwards with climate change. Dynamic vegetation models are often used to assess the impact of climate on vegetation and model output can be compared with paleobotanical data as a reality check. Recent paleoecological studies have revealed regional variation in the upward shift of timberlines in the Northern and Central European Alps in response to rapid warming at the Younger Dryas/Preboreal transition ca. 11700years ago, probably caused by a climatic gradient across the Alps. This contrasts with previous studies that successfully simulated the early Holocene afforestation in the (warmer) Central Alps with a chironomid-inferred temperature reconstruction from the (colder) Northern Alps. We use LandClim, a dynamic landscape vegetation model to simulate mountain forests under different temperature, soil and precipitation scenarios around Iffigsee (2065m a.s.l.) a lake in the Northwestern Swiss Alps, and compare the model output with the paleobotanical records. The model clearly overestimates the upward shift of timberline in a climate scenario that applies chironomid-inferred July-temperature anomalies to all months. However, forest establishment at 9800 cal. BP at Iffigsee is successfully simulated with lower moisture availability and monthly temperatures corrected for stronger seasonality during the early Holocene. The model-data comparison reveals a contraction in the realized niche of Abies alba due to the prominent role of anthropogenic disturbance after ca. 5000 cal. BP, which has important implications for species distribution models (SDMs) that rely on equilibrium with climate and niche stability. Under future climate projections, LandClim indicates a rapid upward shift of mountain vegetation belts by ca. 500m and treeline positions of ca. 2500m a.s.l. by the end of this century. Resulting biodiversity losses in the alpine vegetation belt might be mitigated with low-impact pastoralism to preserve species-rich alpine meadows.

Past and future carbon fluxes from land use change, shifting cultivation and wood harvest

Carbon emissions from anthropogenic land use (LU) and land use change (LUC) are quantified with a Dynamic Global Vegetation Model for the past and the 21st century following Representative Concentration Pathways (RCPs). Wood harvesting and parallel abandonment and expansion of agricultural land in areas of shifting cultivation are explicitly simulated (gross LUC) based on the Land Use Harmonization (LUH) dataset and a proposed alternative method that relies on minimum input data and generically accounts for gross LUC. Cumulative global LUC emissions are 72 GtC by 1850 and 243 GtC by 2004 and 27–151 GtC for the next 95 yr following the different RCP scenarios. The alternative method reproduces results based on LUH data with full transition information within <0.1 GtC/yr over the last decades and bears potential for applications in combination with other LU scenarios. In the last decade, shifting cultivation and wood harvest within remaining forests including slash each contributed 19% to the mean annual emissions of 1.2 GtC/yr. These factors, in combination with amplification effects under elevated CO2, contribute substantially to future emissions from LUC in all RCPs.