Short-term response of the Ca cycle of a montane forest in Ecuador to low experimental CaCl2 additions

The tropical montane forests of the E Andean cordillera in Ecuador receive episodic Sahara- dust inputs particularly increasing Ca deposition. We added CaCl2 to isolate the effect of Ca deposition by Sahara dust to tropical montane forest from the simultaneously occurring pH effect. We examined components of the Ca cycle at four control plots and four plots with added Ca (2 × 5 kg ha?1 Ca annually as CaCl2) in a random arrangement. Between August 2007 and December 2009 (four applications of Ca), we determined Ca concentrations and fluxes in litter leachate, mineral soil solution (0.15 and 0.30 m depths), throughfall, and fine litterfall and Al con- centrations and speciation in soil solutions. After 1 y of Ca addition, we assessed fine-root bio- mass, leaf area, and tree growth. Only < 3% of the applied Ca leached below the acid organic layer (pH 3.5?4.8). The added CaCl2 did not change electrical conductivity in the root zone after 2 y. In the second year of fertilization, Ca retention in the canopy of the Ca treatment tended to decrease relative to the control. After 2 y, 21% of the applied Ca was recycled to soil with throughfall and litterfall. One year after the first Ca addition, fine-root biomass had decreased significantly. Decreasing fine-root biomass might be attributed to a direct or an indirect beneficial effect of Ca on the soil decomposer community. Because of almost complete association of Al with dissolved organic matter and high free Ca2+ : Al3+ activity ratios in solution of all plots, Al toxicity was unlikely. We conclude that the added Ca was retained in the system and had benefi- cial effects on some plants.

Directed seed dispersal by bellbirds in a tropical cloud forest

A fundamental goal of plant population ecology is to understand the consequences for plant fitness of seed dispersal by animals. Theories of seed dispersal and tropical forest regeneration suggest that the advantages of seed dispersal for most plants are escape from seed predation near the parent tree and colonization of vacant sites, the locations of which are unpredictable in space and time. Some plants may gain in fitness as a fortuitous consequence of disperser behavior if certain species of dispersers nonrandomly place seeds in sites predictably favorable for seedling establishment. Such patterns of directed dispersal by vertebrates long have been suggested but never demonstrated for tropical forest trees. Here we report the pattern of seed distribution and 1-year seedling survival generated by five species of birds for a neotropical, shade-tolerant tree. Four of the species dispersed seeds to sites near the parent trees with microhabitat characteristics similar to those at random locations, whereas the fifth species, a bellbird, predictably dispersed seeds under song perches in canopy gaps. The pattern of seedling recruitment was bimodal, with a peak near parent trees and a second peak, corresponding to bellbird song perches, far (>40 m) from parent trees. Seedling survival was higher for seeds dispersed by bellbirds than by the other species, because of a reduction in seedling mortality by fungal pathogens in gaps. Thus, bellbirds play a significant role in seed dispersal by providing directed dispersal to favorable sites and therefore may influence plant recruitment patterns and species diversity in Neotropical forests.

Validation of the Item-Attribute Matrix in TIMSS-Mathematics Using Multiple Regression and the LSDM

The purposes of this study were (1) to validate of the item-attribute matrix using two levels of attributes (Level 1 attributes and Level 2 sub-attributes), and (2) through retrofitting the diagnostic models to the mathematics test of the Trends in International Mathematics and Science Study (TIMSS), to evaluate the construct validity of TIMSS mathematics assessment by comparing the results of two assessment booklets. Item data were extracted from Booklets 2 and 3 for the 8th grade in TIMSS 2007, which included a total of 49 mathematics items and every student's response to every item. The study developed three categories of attributes at two levels: content, cognitive process (TIMSS or new), and comprehensive cognitive process (or IT) based on the TIMSS assessment framework, cognitive procedures, and item type. At level one, there were 4 content attributes (number, algebra, geometry, and data and chance), 3 TIMSS process attributes (knowing, applying, and reasoning), and 4 new process attributes (identifying, computing, judging, and reasoning). At level two, the level 1 attributes were further divided into 32 sub-attributes. There was only one level of IT attributes (multiple steps/responses, complexity, and constructed-response). Twelve Q-matrices (4 originally specified, 4 random, and 4 revised) were investigated with eleven Q-matrix models (QM1 ~ QM11) using multiple regression and the least squares distance method (LSDM). Comprehensive analyses indicated that the proposed Q-matrices explained most of the variance in item difficulty (i.e., 64% to 81%). The cognitive process attributes contributed to the item difficulties more than the content attributes, and the IT attributes contributed much more than both the content and process attributes. The new retrofitted process attributes explained the items better than the TIMSS process attributes. Results generated from the level 1 attributes and the level 2 attributes were consistent. Most attributes could be used to recover students' performance, but some attributes' probabilities showed unreasonable patterns. The analysis approaches could not demonstrate if the same construct validity was supported across booklets. The proposed attributes and Q-matrices explained the items of Booklet 2 better than the items of Booklet 3. The specified Q-matrices explained the items better than the random Q-matrices.

Lake-effect snow as the dominant control of mesic-forest distribution in Michigan, USA

1Recent studies demonstrated the sensitivity of northern forest ecosystems to changes in the amount and duration of snow cover at annual to decadal time scales. However, the consequences of snowfall variability remain uncertain for ecological variables operating at longer time scales, especially the distributions of forest communities. 2The Great Lakes region of North America offers a unique setting to examine the long-term effects of variable snowfall on forest communities. Lake-effect snow produces a three-fold gradient in annual snowfall over tens of kilometres, and dramatic edaphic variations occur among landform types resulting from Quaternary glaciations. We tested the hypothesis that these factors interact to control the distributions of mesic (dominated by Acer saccharum, Tsuga canadensis and Fagus grandifolia) and xeric forests (dominated by Pinus and Quercus spp.) in northern Lower Michigan. 3We compiled pre-European-settlement vegetation data and overlaid these data with records of climate, water balance and soil, onto Landtype Association polygons in a geographical information system. We then used multivariate adaptive regression splines to model the abundance of mesic vegetation in relation to environmental controls. 4Snowfall is the most predictive among five variables retained by our model, and it affects model performance 29% more than soil texture, the second most important variable. The abundance of mesic trees is high on fine-textured soils regardless of snowfall, but it increases with snowfall on coarse-textured substrates. Lake-effect snowfall also determines the species composition within mesic forests. The weighted importance of A. saccharum is significantly greater than of T. canadensis or F. grandifolia within the lake-effect snowbelt, whereas T. canadensis is more plentiful outside the snowbelt. These patterns are probably driven by the influence of snowfall on soil moisture, nutrient availability and fire return intervals. 5Our results imply that a key factor dictating the spatio-temporal patterns of forest communities in the vast region around the Great Lakes is how the lake-effect snowfall regime responds to global change. Snowfall reductions will probably cause a major decrease in the abundance of ecologically and economically important species, such as A. saccharum.

Bariatric surgery in women of child-bearing age, timing between an operation and birth, and associated perinatal complications

Thesis (Master's)--University of Washington, 2016-06

Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm

The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.

Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Modeling the age of tropical moist forest fragments in heavily-cleared lowland landscapes of Colombia

Increasingly, large areas of native tropical forests are being transformed into a mosaic of human dominated land uses with scattered mature remnants and secondary forests. In general, at the end of the land clearing process, the landscape will have two forest components: a stable component of surviving mature forests, and a dynamic component of secondary forests of different ages. As the proportion of mature forests continues to decline, secondary forests play an increasing role in the conservation and restoration of biodiversity. This paper aims to predict and explain spatial and temporal patterns in the age of remnant mature and secondary forests in lowland Colombian landscapes. We analyse the age distributions of forest fragments, using detailed temporal land cover data derived from aerial photographs. Ordinal logistic regression analysis was applied to model the spatial dynamics of mature and secondary forest patches. In particular, the effect of soil fertility, accessibility and auto-correlated neighbourhood terms on forest age and time of isolation of remnant patches was assessed. In heavily transformed landscapes, forests account for approximately 8% of the total landscape area, of which three quarters are comprised of secondary forests. Secondary forest growth adjacent to mature forest patches increases mean patch size and core area, and therefore plays an important ecological role in maintaining landscape structure. The regression models show that forest age is positively associated with the amount of neighbouring forest, and negatively associated with the amount of neighbouring secondary vegetation, so the older the forest is the less secondary vegetation there is adjacent to it. Accessibility and soil fertility also have a negative but variable influence on the age of forest remnants. The probability of future clearing if current conditions hold is higher for regenerated than mature forests. The challenge of biodiversity conservation and restoration in dynamic and spatially heterogeneous landscape mosaics composed of mature and secondary forests is discussed. (c) 2004 Elsevier B.V. All rights reserved.

Habitat selection and breeding success in a forest-nesting Alcid, the marbled murrelet, in two landscapes with different degrees of forest fragmentation

We studied habitat selection and breeding success in marked populations of a protected seabird (family Alcidae), the marbled murrelet (Brachyramphus marmoratus), in a relatively intact and a heavily logged old-growth forest landscape in south-western Canada. Murrelets used old-growth fragments either proportionately to their size frequency distribution (intact) or they tended to nest in disproportionately smaller fragments (logged). Multiple regression modelling showed that murrelet distribution could be explained by proximity of nests to landscape features producing biotic and abiotic edge effects. Streams, steeper slopes and lower elevations were selected in both landscapes, probably due to good nesting habitat conditions and easier access to nest sites. In the logged landscape, the murrelets nested closer to recent clearcuts than would be expected. Proximity to the ocean was favoured in the intact area. The models of habitat selection had satisfactory discriminatory ability in both landscapes. Breeding success (probability of nest survival to the middle of the chick rearing period), inferred from nest attendance patterns by radio-tagged parents, was modelled in the logged landscape. Survivorship was greater in areas with recent clearcuts and lower in areas with much regrowth, i.e. it was positively correlated with recent habitat fragmentation. We conclude that marbled murrelets can successfully breed in old-growth forests fragmented by logging.

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

The importance of forest area and configuration relative to local habitat factors for conserving forest mammals: A case study of koalas in Queensland, Australia

The loss and fragmentation of forest habitats by human land use are recognised as important factors influencing the decline of forest-dependent fauna. Mammal species that are dependent upon forest habitats are particularly sensitive to habitat loss and fragmentation because they have highly specific habitat requirements, and in many cases have limited ability to move through and utilise the land use matrix. We addressed this problem using a case study of the koala (Phascolarctos cinereus) surveyed in a fragmented rural-urban landscape in southeast Queensland, Australia. We applied a logistic modelling and hierarchical partitioning analysis to determine the importance of forest area and its configuration relative to site (local) and patch-level habitat variables. After taking into account spatial auto-correlation and the year of survey, we found koala occurrence increased with the area of all forest habitats, habitat patch size and the proportion of primary Eucalyptus tree species; and decreased with mean nearest neighbour distance between forest patches, the density of forest patches, and the density of sealed roads. The difference between the effect of habitat area and configuration was not as strong as theory predicts, with the configuration of remnant forest becoming increasingly important as the area of forest habitat declines. We conclude that the area of forest, its configuration across the landscape, as well as the land use matrix, are important determinants of koala occurrence, and that habitat configuration should not be overlooked in the conservation of forest-dependent mammals, such as the koala. We highlight the implications of these findings for koala conservation. (c) 2006 Elsevier Ltd. All rights reserved.

Parameterized Link Functions in Generalized Linear Random Effect Models: a Case Study on Breast Cancer Treatment

In non-linear random effects some attention has been very recently devoted to the analysis ofsuitable transformation of the response variables separately (Taylor 1996) or not (Oberg and Davidian 2000) from the transformations of the covariates and, as far as we know, no investigation has been carried out on the choice of link function in such models. In our study we consider the use of a random effect model when a parameterized family of links (Aranda-Ordaz 1981, Prentice 1996, Pregibon 1980, Stukel 1988 and Czado 1997) is introduced. We point out the advantages and the drawbacks associated with the choice of this data-driven kind of modeling. Difficulties in the interpretation of regression parameters, and therefore in understanding the influence of covariates, as well as problems related to loss of efficiency of estimates and overfitting, are discussed. A case study on radiotherapy usage in breast cancer treatment is discussed.

Hurricane disturbance and recovery of energy balance, CO2 fluxes and canopy structure in a mangrove forest of the Florida Everglades

Eddy covariance (EC) estimates of carbon dioxide (CO2) fluxes and energy balance are examined to investigate the functional responses of a mature mangrove forest to a disturbance generated by Hurricane Wilma on October 24, 2005 in the Florida Everglades. At the EC site, high winds from the hurricane caused nearly 100% defoliation in the upper canopy and widespread tree mortality. Soil temperatures down to -50 cm increased, and air temperature lapse rates within the forest canopy switched from statically stable to statically unstable conditions following the disturbance. Unstable conditions allowed more efficient transport of water vapor and CO2 from the surface up to the upper canopy layer. Significant increases in latent heat fluxes (LE) and nighttime net ecosystem exchange (NEE) were also observed and sensible heat fluxes (H) as a proportion of net radiation decreased significantly in response to the disturbance. Many of these impacts persisted through much of the study period through 2009. However, local albedo and MODIS (Moderate Resolution Imaging Spectro-radiometer) data (the Enhanced Vegetation Index) indicated a substantial proportion of active leaf area recovered before the EC measurements began 1 year after the storm. Observed changes in the vertical distribution and the degree of clumping in newly emerged leaves may have affected the energy balance. Direct comparisons of daytime NEE values from before the storm and after our measurements resumed did not show substantial or consistent differences that could be attributed to the disturbance. Regression analyses on seasonal time scales were required to differentiate the storm's impact on monthly average daytime NEE from the changes caused by interannual variability in other environmental drivers. The effects of the storm were apparent on annual time scales, and CO2 uptake remained approximately 250 g C m-2 yr-1 lower in 2009 compared to the average annual values measured in 2004-2005. Dry season CO2 uptake was relatively more affected by the disturbance than wet season values. Complex leaf regeneration dynamics on damaged trees during ecosystem recovery are hypothesized to lead to the variable dry versus wet season impacts on daytime NEE. In contrast, nighttime CO2 release (i.e., nighttime respiration) was consistently and significantly greater, possibly as a result of the enhanced decomposition of litter and coarse woody debris generated by the storm, and this effect was most apparent in the wet seasons compared to the dry seasons. The largest pre- and post-storm differences in NEE coincided roughly with the delayed peak in cumulative mortality of stems in 2007-2008. Across the hurricane-impacted region, cumulative tree mortality rates were also closely correlated with declines in peat surface elevation. Mangrove forest-atmosphere interactions are interpreted with respect to the damage and recovery of stand dynamics and soil accretion processes following the hurricane.

Summertime Influences of Tidal Energy Advection on the Surface Energy Balance in a Mangrove Forest

Mangrove forests are ecosystems susceptible to changing water levels and temperatures due to climate change as well as perturbations resulting from tropical storms. Numerical models can be used to project mangrove forest responses to regional and global environmental changes, and the reliability of these models depends on surface energy balance closure. However, for tidal ecosystems, the surface energy balance is complex because the energy transport associated with tidal activity remains poorly understood. This study aimed to quantify impacts of tidal flows on energy dynamics within a mangrove ecosystem. To address the research objective, an intensive 10-day study was conducted in a mangrove forest located along the Shark River in the Everglades National Park, FL, USA. Forest–atmosphere turbulent exchanges of energy were quantified with an eddy covariance system installed on a 30-m-tall flux tower. Energy transport associated with tidal activity was calculated based on a coupled mass and energy balance approach. The mass balance included tidal flows and accumulation of water on the forest floor. The energy balance included temporal changes in enthalpy, resulting from tidal flows and temperature changes in the water column. By serving as a net sink or a source of available energy, flood waters reduced the impact of high radiational loads on the mangrove forest. Also, the regression slope of available energy versus sink terms increased from 0.730 to 0.754 and from 0.798 to 0.857, including total enthalpy change in the water column in the surface energy balance for 30-min periods and daily daytime sums, respectively. Results indicated that tidal inundation provides an important mechanism for heat removal and that tidal exchange should be considered in surface energy budgets of coastal ecosystems. Results also demonstrated the importance of including tidal energy advection in mangrove biophysical models that are used for predicting ecosystem response to changing climate and regional freshwater management practices.

Burned Area Mapping in the North American Boreal Forest Using Terra-MODIS LTDR (2001–2011): A Comparison with the MCD45A1, MCD64A1 and BA GEOLAND-2 Products

An algorithm based on a Bayesian network classifier was adapted to produce 10-day burned area (BA) maps from the Long Term Data Record Version 3 (LTDR) at a spatial resolution of 0.05° (~5 km) for the North American boreal region from 2001 to 2011. The modified algorithm used the Brightness Temperature channel from the Moderate Resolution Imaging Spectroradiometer (MODIS) band 31 T31 (11.03 μm) instead of the Advanced Very High Resolution Radiometer (AVHRR) band T3 (3.75 μm). The accuracy of the BA-LTDR, the Collection 5.1 MODIS Burned Area (MCD45A1), the MODIS Collection 5.1 Direct Broadcast Monthly Burned Area (MCD64A1) and the Burned Area GEOLAND-2 (BA GEOLAND-2) products was assessed using reference data from the Alaska Fire Service (AFS) and the Canadian Forest Service National Fire Database (CFSNFD). The linear regression analysis of the burned area percentages of the MCD64A1 product using 40 km × 40 km grids versus the reference data for the years from 2001 to 2011 showed an agreement of R2 = 0.84 and a slope = 0.76, while the BA-LTDR showed an agreement of R2 = 0.75 and a slope = 0.69. These results represent an improvement over the MCD45A1 product, which showed an agreement of R2 = 0.67 and a slope = 0.42. The MCD64A1, BA-LTDR and MCD45A1 products underestimated the total burned area in the study region, whereas the BA GEOLAND-2 product overestimated it by approximately five-fold, with an agreement of R2 = 0.05. Despite MCD64A1 showing the best overall results, the BA-LTDR product proved to be an alternative for mapping burned areas in the North American boreal forest region compared with the other global BA products, even those with higher spatial/spectral resolution