Individual Growth Models Research Articles

F3: Simulating spatiotemporal forest change from field inventory, remote sensing, growth modeling, and management actions

Abstract Contemporary forest management requires highly-detailed, spatially-contiguous, multi-temporal, and scenarios-comparable forest conditions. Field inventories and individual-tree models often contain highly-detailed data and allow for long-term complex scenarios comparison, but the information is only at sampled locations and lacks complete spatial coverage. Forest landscape models (FLMs) provide landscape-level spatiotemporal data, but the details that are important to land managers are often lost in the generalized outputs. We developed a modeling framework, F3, to integrate FIA (Forest Inventory and Analysis) plots, the Forest Vegetation Simulator (FVS), and FastEmap (Field And SatelliTe for Ecosystem MAPping) to simulate spatiotemporal forest change under natural succession and vegetation management. F3 extrapolates the details of forest inventory plots and individual-tree model outputs to a spatially-contiguous landscape by fusing tree-list field measurements, individual tree growth and yield models, remote sensing and environmental geospatial datasets. F3 allows for area-specific management action simulations. F3 compares FVS results with field measurements for temporal accuracy assessment and uses a leave-one-out cross-validation for spatial accuracy assessment. F3 adopts parallel computation techniques to implement the modeling in an automatic and efficient manner. The proof of concept of F3 was demonstrated in Tahoe National Forest (TNF) showing spatiotemporal changes on six forest structural metrics (quadratic mean diameter, basal area, biomass, habitat suitability index, canopy cover, and coarse woody debris) under natural succession, regeneration-cut, and thinning scenarios for the years 2014–2114 at a 30 m resolution. F3 can be used for initializing FLMs and for analyzing a wide range of ecosystem services; however, the under-representation of certain forest types in the FIA plot data set, the modeling bias from FVS, and choice of FastEmap covariates contribute to major uncertainties in the framework.

Rapid changes in age and size at maturity in Lake Erie yellow perch (Perca flavescens) are not explained by harvest

Harvest can change phenotypic traits of populations through immediate demographic consequences, evolutionary responses to harvest selection, or developmental responses by individuals. This study investigated the plastic phenotypic effects of harvest on size and age at maturity in a commercially exploited freshwater fish. We tested an individual growth and life history plasticity model using lagged correlations incorporating how harvesting fish ages 2 and older influenced the abundance of juvenile fish, resource availability, individual growth rates, and carry-over responses in age and size at maturity. Our test used cohort data for Lake Erie yellow perch (Perca flavescens). Age and size at maturity fluctuated widely and rapidly across 23 cohorts between 1991 and 2013, suggesting phenotypic plasticity contributed strongly to maturation dynamics. The changes in maturity could not be explained by responses to harvest, as expected under the plasticity model. In Lake Erie, age and size at maturity in yellow perch appear to be responding to other drivers, such as harvest-induced dynamics of other fish stocks or ecosystem changes that are independent of harvest.

Habit, a Feasibility Trial to Improve Hydroxyurea Adherence, Improves Quality of Life in Youth with Sickle Cell Disease

Background: Daily hydroxyurea (HU) adherence is often suboptimal for youth with sickle cell disease (SCD). Adolescence is a critical time to improve HU adherence as youth assume greater responsibility for medication self-management. While QOL is higher among youth prescribed HU compared to those who are not,1little is known about how participation in an intervention to improve HU adherence is related to self- and parent-proxy reported QOL.Methods: We conducted a 2-site randomized controlled feasibility trial with 2:1 randomization, “Hydroxyure Adherence for Personal Best in Sickle Cell Treatment: HABIT,” to estimate the effect of a community health worker (CHW) intervention for youth-parent dyads, augmented by tailored text messages, on HU adherence in youth 10-18 years of age with SCD.2 The secondary outcomes, reported here, were: generic QOL (PedsQL; total score and 4 subscales); disease-specific QOL (PedsQL SCD Module; total score and 9 additional subscales), and youth-parent concordance regarding self-management responsibility (Sickle Cell Family Responsibility Scale, adapted from the Diabetes Family Responsibility Questionnaire). Each outcome was measured at 0, 3 and 6 months. Descriptive statistics were used to profile each measure including a Cronbach alpha to assess scale reliability in this sample. A minimally clinically important difference (MCID) was computed for each total and subscale score as a criterion to assess clinically meaningful improvements. A linear individual growth model incorporating group assignment and time was used to examine the difference in each outcome over time. Where outcomes achieved statistical significance (p<0.05), we compared the intervention group's absolute score change from 0 to 6 months to the MCID to assess a clinically meaningful change. Data were analyzed using SAS 9.4 (Cary, NC) statistical software.Results: Of 48 eligible dyads, 28 (youth age 14.3±2.6 years, 50% Hispanic) participated (18 intervention dyads, 10 control dyads), with 10.7% attrition. The intervention was feasible (58% enrolled), acceptable to dyads and demonstrated a trend to HU adherence improvement at 4 months.3 Cronbach alphas ranged between 0.71 and 0.97 for parent and youth measures. Incorporating group assignment and time, intervention youth reported improved generic QOL total score (p=0.04; change 9.2 [95% CI 5.7, 12.7]) and its emotional subscale (p=0.034; change 14.4 [95% CI 10.2, 18.6]), 3 disease-specific QOL subscales: worry I (p=0.009; 26.1 [95% CI 18.0, 34.2), emotions (p=0.01; change 33.0 [95% CI 23.8, 42.2]), and communication I (p=0.048; change 15.3 [95% CI 8.5, 22.1]), and a trend for improved dyad concordance regarding self-management responsibility at 3 months (p=0.07; change 1.6 [95% CI 1.0, 2.2]). In each case, score improvement exceeded its MCID. No differences were found in parent-proxy reported QOL measures.Conclusions: HABIT improved two generic and three disease-specific youth-reported QOL outcomes in the psychosocial domain. Whether QOL improvement stemmed from greater HU adherence, CHW support and/or improved dyad self-management concordance is uncertain. These findings add to a growing body of research examining effects of interventions on QOL outcomes in youth with SCD. To confirm these findings, a multi-site HABIT randomized controlled trial powered to test intervention efficacy is planned.

Deterministic Models of Growth and Mortality for Jack Pine in Boreal Forests of Western Canada

We developed individual tree deterministic growth and mortality models for jack pine (Pinus banksiana Lamb.) using data from permanent sample plots in Alberta, Saskatchewan and Manitoba, Canada. Height and diameter increment equations were fitted using nonlinear mixed effects models. Logistic mixed models were used to estimate jack pine survival probability based on tree and stand characteristics. The resulting models showed that (1) jack pine growth is significantly influenced by competition; (2) competitive effects differ between species groups; and (3) survival probability is affected by tree size and growth, stand composition, and stand density. The estimated coefficients of selected growth and mortality functions were implemented into the Mixedwood Growth Model (MGM) and the simulated predictions were evaluated against independently measured data. The validation showed that the MGM can effectively model jack pine trees and stands, providing support for its use in management planning.

Prototype Individual Growth Model For Inpatient Recovery of Motor Function in Persons Recovering From Stroke

To describe recovery trajectories of motor functioning during inpatient rehabilitation following stroke with a prototype individual growth curve (IGC) model.

An imputation/copula-based stochastic individual tree growth model\xa0for mixed species Acadian forests: a case study using the Nova Scotia permanent sample plot network

BackgroundA novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection system.Methods The Nova Scotia, Canada permanent sample plot network is used as a case study to develop and test the modelling approach. Predictions from this model are compared to predictions from the Acadian variant of the Forest Vegetation Simulator, a widely used statistical individual tree growth and yield model.ResultsDiameter and height growth rates were predicted with error rates consistent with those produced using statistical models. Mortality and ingrowth error rates were higher than those observed for diameter and height, but also were within the bounds produced by traditional approaches for predicting these rates. Ingrowth species composition was very poorly predicted. The model was capable of reproducing a wide range of stand dynamic trajectories and in some cases reproduced trajectories that the statistical model was incapable of reproducing. ConclusionsThe model has potential to be used as a benchmarking tool for evaluating statistical and process models and may provide a mechanism to separate signal from noise and improve our ability to analyze and learn from large regional datasets that often have underlying flaws in sample design.

Possibilities and limitations of individual-tree growth models – A review on model evaluations

Summary Individual-tree growth models are the new standard for modeling growth and yield. Their main purpose is to simulate future forest management scenarios but they can also be used to predict wood quality, rockfall protection or habitat quality. Individual tree growth models may consist of different models but core models are diameter increment, height increment, crown ratio (often used as a predictor for increment) and mortality. The model differentiation is based on how these four models include tree age (size), competition and site. Four common growth simulators in Central Europe are BWIN, Moses, Prognaus and Silva. These four models are commonly deployed to simulate 30 years of growth, but a prospective application is the simulation of a whole rotation period (80–150 years). It is therefore crucial to understand the possibilities and limitations of these models by evaluating them. This review paper summarizes the statistical and emergent properties’ evaluation results for these models. Statistical evaluations focus on individual models of a simulator, whereas the evaluation of emergent properties evaluates the entire simulator, by testing if the models conform to known principles of stand growth. Further, the meaning of these evaluation results for the development and improvement of individual-tree growth models is discussed.

Individual tree diameter increment model for natural Betula platyphylla forests based on meteorological factors

Based on the 212 re-measured permanent plots for natural Betula platyphylla fore-sts in Daxing'an Mountains and Xiaoxing'an Mountains and 30 meteorological stations data, an individual tree growth model based on meteorological factors was constructed. The differences of stand and meteorological factors between Daxing'an Mountains and Xiaoxing'an Mountains were analyzed and the diameter increment model including the regional effects was developed by dummy variable approach. The results showed that the minimum temperature (Tg min) and mean precipitation (Pg m) in growing season were the main meteorological factors which affected the diameter increment in the two study areas. Tg min and Pg m were positively correlated with the diameter increment, but the influence strength of Tg min was obviously different between the two research areas. The adjusted coefficient of determination (Ra2) of the diameter increment model with meteorological factors was 0.56 and had an 11% increase compared to the one without meteorological factors. It was concluded that meteorological factors could well explain the diameter increment of B. platyphylla. Ra2 of the model with regional effects was 0.59, and increased by 18% compared to the one without regional effects, and effectively solved the incompatible problem of parameters between the two research areas. The validation results showed that the individual tree diameter growth model with regional effect had the best prediction accuracy in estimating the diameter increment of B. platyphylla. The mean error, mean absolute error, mean error percent and mean prediction error percent were 0.0086, 0.4476, 5.8% and 20.0%, respectively. Overall, dummy variable model of individual tree diameter increment based on meteorological factors could well describe the diameter increment process of natural B. platyphylla in Daxing'an Mountains and Xiaoxing'an Mountains.

Developing a framework for growth modelling in a managed southern black beech forest

BackgroundA model of individual tree growth using simple predictors in a managed black beech (Fuscospora solandri (Hook.f.) Heenan & Smissen) forest could provide a useful tool for predicting future stand characteristics.MethodsData from permanent sample plots were used to develop a framework for modelling individual tree growth in Woodside forest, a managed black beech forest in north Canterbury (New Zealand). We tested three mixed-effect models to identify effects of sites, treatment (thinnings), individual tree size and competition on tree growth rates.ResultsA power function amended with variables specifying stand basal area and thinning treatment was best suited for black beech, explaining about 55% of the variation in growth rates. Treatment history (thinnings), as well as the individual tree size and the stand basal area, strongly affected tree diameter growth. Only 3% of the variation in diameter growth rates was explained by plot-specific effect which was less than observed in earlier studies.ConclusionsAll predictor variables (management history, individual tree diameter and stand basal area) are quite simple to measure in the field and could be easily used to predict diameter increments in managed or unmanaged forests. A limitation of our study was that available growth data in Woodside were from small plots, focused on a small number of trees and a narrow range of diameters. However, our results are a good starting point, providing a promising framework for further modelling of tree growth in Woodside forest from new permanent plot data.

Efficient modelling of foliage distribution and crown dynamics in monolayer tree species.

In response to the computational limitations of individual leaf-based tree growth models, this article presents a new approach for the efficient characterisation of the spatial distribution of foliage in monolayered trees in terms of 2D foliage surfaces. Much like the recently introduced 3D leaf area density, this concept accommodates local crown plasticity, which is a common weak point in large-scale growth models. Recognizing phototropism as the predominant driver of spatial crown expansion, we define the local light gradient on foliage surfaces. We consider the partial differential equation describing the evolution of a curve expanding along the light gradient and present an explicit solution. The article concludes with an illustration of the incorporation of foliage surfaces in a simple tree growth model for European beech (Fagus sylvatica L.), and discusses perspectives for applications in functional-structural models.

Modelling individual tree diameter growth for Norway spruce in the Czech Republic using a generalized algebraic difference approach

Individual tree-based growth models precisely describe the growth of individual trees irrespective of stand complexity. These models are more useful than the stand-based growth models for effective management of forests. We developed an individual tree diameter growth model for Norway spruce (Picea abies /Linnaeus/ H. Karsten) using permanent research plot data collected from Krkonoše National Park in the Czech Republic. The model was tested against a part of the Czech National Forest Inventory (NFI) data that originated from the western region of the country. Among various models derived by a generalized algebraic difference approach (GADA), the GADA model derived from the Chapman-Richards function best suited to our data. Tree-specific parameters unique to each growth series, which describe tree-specific growth conditions, were estimated simultaneously with global parameters common to all growth series using the iterative nested regressions. The model described most of the variations in diameter growth for model calibration data (R&lt;sup&gt;2&lt;/sup&gt;&lt;sub&gt;adj&lt;/sub&gt; = 0.9901, RMSE = 0.5962), leaving no significant trends in the residuals. A test against NFI data also confirms that the model is precise enough for predictions of diameter growth for ranges of site quality, tree size, age, and growth condition. The model also possesses biologically desirable properties because it produces the curves with growth rates and asymptotes that increase with increasing site quality. The GADA model is path-invariant and therefore applicable for both forward and backward predictions, meaning that the model can precisely predict diameter growth at any past ages of the trees.

Individual tree biomass equations and growth models sensitive to climate variables for Larix spp. in China

Climate change has increased the need of information on amount of forest biomass. The biomass and carbon storage for larch (Larix spp.) in large geographic regions in China were failed to be accurately estimated from current biomass equations, because they were usually based on a few sample trees on local sites, generally incompatible to volume estimation, and not additive between components and total biomass. China needs reliable biomass estimation of the important species in the whole country. This study was based on the mensuration data of above- and belowground biomass from 600 and 198 destructive sample trees of larch from four regions in China, respectively. The main purpose was to develop compatible individual tree equations on both national and regional levels for above- and belowground biomass, biomass conversion factor and root-to-shoot ratio, using the nonlinear error-in-variable simultaneous equation approach. In addition, diameter at breast height (D) and tree height (H) growth models were also developed, and effects of key climate variables on biomass variation and growth process were analyzed. The results showed that mean prediction errors (MPEs) of regional aboveground biomass models were from 3.86 to 7.52%, and total relative errors (TREs) are within ±3%; and for regional belowground biomass equations, the MPEs are from 9.91 to 28.85%, and the TREs are within ±4%. The above- and belowground biomass and D- and H-growth were significantly related to mean annual temperature and mean annual precipitation. The biomass equations and growth models developed in this paper will provide good basis for estimating and predicting biomass of larch forests in China.

Modeling individual tree height growth of Norway spruce and Scots pine from national forest inventory data in Norway

ABSTRACTWe developed individual tree height growth models for Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.) in Norway based on national forest inventory data. Potential height growth is based on existing dominant height growth models and reduced due to competition by functions developed in this study. Three spatially explicit and two spatially non-explicit competition indices were tested. Distance effects and diameter ratio effects were estimated from the data simultaneously with parameters of the potential modifier functions. Large height measurement errors in the national forest inventory data caused large residual variation of the models. However, the effects of competition on height growth were significant and plausible. The potential modifier functions show that height growth of dominant trees is largely unaffected by competition. Only at higher levels of competition, height growth is reduced as a consequence of competition. However, Scots pine also reduced height growth at very low levels of competition. Distance effects in the spatially explicit competition indices indicated that the closest neighbors are most important for height growth. However, for Scots pine also competitors at larger distance affected height growth. The five competition indices tested in this study explained similar proportions of the variation in relative height growth. Given that unbiased predictions can only be expected for the same plot size, we recommend a spatially explicit index, which describes the distance function with a negative exponential, for use in growth simulators.

Distance-independent tree basal area growth models for Norway spruce, Douglas-fir and Japanese larch in Southern Belgium

This paper presents new harmonized distance-independent individual tree basal area growth models for Norway spruce, Douglas-fir and Japanese larch in pure even-aged stands in Southern Belgium. The selected model was originally developed for Norway spruce and Douglas-fir in neighboring France. New formulations are proposed for some of the model components in order to lower the number of fitted parameters and facilitate the fitting procedure. The resulting models integrate the most recent corresponding top-height growth models and use four simple and usually collected explanatory variables: stand age, top-height, total basal area and tree girth at breast height. The modified formulations maintain similar fitting performances and make it easier to interpret the influence of the explanatory variables on tree growth. Parameters estimates were fitted on thousands of growth measurements gathered from several monitoring plots, forest management inventories and silvicultural field experiments that represent the wide range of site conditions and of forest management scenarios applied to coniferous stands in Southern Belgium. Cross-validation of the models revealed no bias and highlighted their consistent behavior over the entire range of girth at breast height, age, top-height, site index and density represented in our dataset. Combining utility and robust performances, these models represent useful forest management tools, purposely ideal for forest simulation software development. Moreover, the flexibility and generic capabilities of the model formulation should make it easily adjustable for other species in even-aged stands.

Development and evaluation of an individual tree growth and yield model for the mixed species forest of the Adirondacks Region of New York, USA

Growth and yield models are important tools for forest planning. Due to its geographic location, topology, and history of management, the forests of the Adirondacks Region of New York are unique and complex. However, only a relatively limited number of growth and yield models have been developed and/or can be reasonably extended to this region currently. In this analysis, 571 long–term continuous forest inventory plots with a total of 10 – 52 years of measurement data from four experimental forests maintained by the State University of New York College of Environmental Science and Forestry and one nonindustrial private forest were used to develop an individual tree growth model for the primary hardwood and softwood species in the region. Species–specific annualized static and dynamic equations were developed using the available data and the system was evaluated for long–term behavior. Equivalence tests indicated that the Northeast Variant of the Forest Vegetation Simulator (FVS–NE) was biased in its estimation of tree total and bole height, diameter and height increment, and mortality for most species examined. In contrast, the developed static and annualized dynamic, species–specific equations performed quite well given the underlying variability in the data. Long–term model projections were consistent with the data and suggest a relatively robust system for prediction. Overall, the developed growth model showed reasonable behavior and is a significant improvement over existing models for the region. The model also highlighted the complexities of forest dynamics in the region and should help improve forest planning efforts there.

Modelling diameter growth, mortality and recruitment of trees in miombo woodlands of Tanzania

Miombo woodlands cover large areas in Tanzania but very little reliable data on forest dynamics for the woodlands exist. The main objective of this study was to develop a model system describing such dynamics based on easily measurable tree variables. Individual tree diameter growth and mortality models, and area-based recruitment models were developed. The modelling was based on data from 117 permanent sample plots established between 1997 and 2009 on seven sites in the Iringa and Manyara regions. The data set comprised 2 314 trees at establishment and 4 758 observations of individual tree growth, and covered a large number of species (141). Based on diameter growth and by using a model-based clustering procedure, three tree species groups were developed. Several model forms with different independent variables were tested. Simple and robust models with few independent variables, which agreed with expected biological behaviour, were finally selected. Although biological behaviour was the principal model selection criterion, the models also performed well statistically. The developed model system, which is the first of its kind for miombo woodlands in Africa, may be used to develop a decision-support tool for practical forest management planning in the country.

Modelling the effect of size-asymmetric competition on size inequality: Simple models with two plants

The concept of size asymmetry in resource competition among plants, in which larger individuals obtain a disproportionate share of contested resources, appears to be very straightforward, but the effects of size asymmetry on growth and size variation among individuals have proved to be controversial. It has often been assumed that competition among individual plants in a population has to be size-asymmetric to result in higher size inequality than in the absence of competition, but here we question this inference. Using very simple, individual-based models, we investigate how size symmetry of competition affects the development in size inequality between two competing plants and show that increased size inequality due to competition is not always strong evidence for size-asymmetric competition. Even absolute symmetric competition, in which all plants receive the same amount of resources irrespective of their sizes, can, under some assumptions, result in higher size inequality than when competition is absent. We demonstrate our approach by applying it to data from a greenhouse experiment investigating the size symmetry of belowground competition between pairs of Triticum aestivum (wheat) plants. The effects of size symmetry/asymmetry on size inequality are dependent on (1) the individual plant growth model, (2) the parameters of the growth model that are affected by competition and (3) the initial sizes and growth rates. Across a range of reasonable assumptions, very general patterns that have been considered evidence for or against size-asymmetric competition do not always hold. Our results emphasize the need for explicit growth models, even very simple ones, for making inferences about the effects of competition on plant growth and size inequality.

Traits controlling body size in copepods: separating general constraints from species-specific strategies

A new synthesis of laboratory measurements of food-saturated development and growth across diverse copepod taxa was conducted in a theoretical framework that distinguishes general allometric constraints on copepod physiology from contingent strategies that correlate with size for other reasons. After temperature correction, the allometry of growth rate is inconsistent between the ontogeny of Calanus spp., where it follows the classic -0.3 power-law scaling, and a broader spectrum of adult size Wa(0.3 to 2000 μg C, Oithona spp. to Neocalanus spp.), across which the classic scaling appears to represent only an upper limit. Over the full size spectrum, after temperature correction, a growth rate g0 relative to the -0.3 power law correlates with adult size better than does relative (temperature-corrected) development rate u0; in contrast, at a finer scale of diversity (among Calanus spp., or among large (>50 μg C) calanoids in general), u0 is the better correlate with adult size and the effect of g0 is insignificant. Across all these scales, the ratio of relative growth and development rates g0/u0 is a better predictor of adult size than g0 or u0 alone, consistent with a simple model of individual growth.

Analysis of depression trajectory patterns using collaborative learning

BackgroundDepression is a common, complex, and dynamic mental disorder. Mitigating depression has become a national health priority as it affects 1 out of 10 American adults and is the most common mental illness seen in primary care. The emerging use of electronic health record (EHR) provides an unprecedented information infrastructure to understand depression trajectories. ObjectiveWe aim to effectively analyze patterns in the collected depression trajectories of a treatment population and compare several methods to predict individual trajectories for monitoring treatment outcomes. MethodsOur data includes longitudinal Patient Health Questionnaire (PHQ)-9 scores over 4 years for assessing depression severity from the Mental Health Research Network. We analyzed > 3,000 patients with at least six PHQ-9 observations who have ongoing treatment. We used smoothing splines to model individual depression trajectories. We then used K-means clustering and collaborative modeling (CM) to identify subgroup patterns. We further predicted the individuals’ PHQ-9 scores based on depression trajectories learnt from individual growth model (IGM), mixed effect model (MEM), CM, and similarity-based CM (SCM), and compared their predictive performances. ResultsWe found five broad trajectory patterns in the ongoing treatment population: stable high, stable low, fluctuating moderate, an increasing and a decreasing group. For prediction, the root mean square error (rMSE) in the testing set for IGM, MEM, CM, and SCM are 12.53, 5.91, 5.18, and 3.21. LimitationsOur EHR data provide limited information on patients’ demographic, socioeconomic, and other clinical factors that may be relevant to improve model performances. ConclusionWe established a trajectory-based framework for depression assessment and prognosis that is adaptable to model population heterogeneity using EHR data. Collaborative modeling outperformed other established methods.

Predictors of and health- and fall-related program outcomes resulting from complete and adequate doses of a fall risk reduction program.

Falls are dangerous and costly for older adults. The A Matter of Balance/Volunteer Lay Leader (AMOB/VLL) program is an evidence-based fall risk reduction program that could help reduce this burden. This study introduced a door-through-door transportation program to improve program delivery (N=126). Characteristics predicting completion of all eight AMOB/VLL sessions were identified using logistic regression. Individual growth models were employed to determine the immediate, intermediate, and long-term goal outcomes resulting from receiving an adequate dose of the program (five to eight sessions). Self-restriction of activities due to fear of falling (OR 5.04, 95% CI 1.86-13.69) and a lower frequency of moderate and vigorous physical activity (OR 1.14, 95% CI 1.04-1.27) were significantly predictive of receiving a complete dose. Three outcome goals were significant, including (1) immediate-improved self-efficacy of managing medications and treatments, (2) intermediate-reduced activity limitations, and (3) intermediate-reduced physical disability. Self-restriction of activities due to a fear of falling and physical activity levels may be simple and effective screening questions to prevent AMOB/VLL attrition. In our study, those who did receive the program improved on a specific type of self-efficacy and on self-reported physical functioning.