The effects of stand characteristics on the understory vegetation in Quercus petraea and Q. cerris dominated forests

The shelterwood system used in Hungary has many effects on the composition and structure of the herb layer. The aim of our study was to identify the main variables that affect the occurence of herbs and seedlings in Turkey oak-sessile oak (Quercus cerris and Q. petraea) stands. The study was carried out in the Bükk mountains, Hungary. 122 sampling plots were established in 50-150 year old oak forests, where we studied the species composition and structure of the understorey and overstorey. The occurence of herbs was affected by canopy closure, the heterogenity and patchiness of the stand, the slope and the east-west component of the aspect. The composition of saplings was significantly explained by the ratio of the two major oak species in the stand and the proximity of the adult plants. An important result for forest management was that sessile oaks were able to regenerate almost only where they were dominant in the overstorey

INFLUENCES OF WATERSHED URBANIZATION AND INSTREAM HABITAT ON MACROINVERTEBRATES IN COLD WATER STREAMS 1

We analyzed data from riffle and snag habitats for 39 small cold water streams with different levels of watershed urbanization in Wisconsin and Minnesota to evaluate the influences of urban land use and instream habitat on macroinvertebrate communities. Multivariate analysis indicated that stream temperature and amount of urban land use in the watersheds were the most influential factors determining macroinvertebrate assemblages. The amount of watershed urbanization was nonlinearly and negatively correlated with percentages of Ephemeroptera-Plecoptera-Trichoptera (EPT) abundance, EPT taxa, filterers, and scrapers and positively correlated with Hilsenhoff biotic index. High quality macroinvertebrate index values were possible if effective imperviousness was less than 7 percent of the watershed area. Beyond this level of imperviousness, index values tended to be consistently poor. Land uses in the riparian area were equal or more influential relative to land use elsewhere in the watershed, although riparian area consisted of only a small portion of the entire watershed area. Our study implies that it is extremely important to restrict watershed impervious land use and protect stream riparian areas for reducing human degradation on stream quality in low level urbanizing watersheds. Stream temperature may be one of the major factors through which human activities degrade cold-water streams, and management efforts that can maintain a natural thermal regime will help preserve stream quality.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72139/1/j.1752-1688.2003.tb03701.x.pd

Statistical Challenges in Estimating Past Climate Changes

We review the statistical methods currently in use to estimate past changes in climate. These methods encompass the full gamut of statistical modeling approaches, ranging from simple regression up to nonparametric spatiotemporal Bayesian models. Often the full inferential challenge is broken down into many submodels each of which may involve multiple stochastic components, and occasionally mechanistic or process‐based models too. We argue that many of the traditional approaches are simplistic in their structure, handling, and presentation of uncertainty, and that newer models (which incorporate mechanistic aspects alongside statistical models) provide an exciting research agenda for the next decade. We hope that policy‐makers and those charged with predicting future climate change will increasingly use probabilistic paleoclimate reconstructions to calibrate their forecasts, learn about key natural climatological parameters, and make appropriate decisions concerning future climate change. Remarkably few statisticians have involved themselves with paleoclimate reconstruction, and we hope that this article inspires more to take up the challenge

Photosynthetic traits of Sphagnum and feather moss species in undrained, drained and rewetted boreal spruce swamp forests

Peer reviewe

Diffusion tensor imaging of Parkinson's disease, multiple system atrophy and progressive supranuclear palsy: a tract-based spatial statistics study

Although often clinically indistinguishable in the early stages, Parkinson's disease (PD), Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP) have distinct neuropathological changes. The aim of the current study was to identify white matter tract neurodegeneration characteristic of each of the three syndromes. Tract-based spatial statistics (TBSS) was used to perform a whole-brain automated analysis of diffusion tensor imaging (DTI) data to compare differences in fractional anisotropy (FA) and mean diffusivity (MD) between the three clinical groups and healthy control subjects. Further analyses were conducted to assess the relationship between these putative indices of white matter microstructure and clinical measures of disease severity and symptoms. In PSP, relative to controls, changes in DTI indices consistent with white matter tract degeneration were identified in the corpus callosum, corona radiata, corticospinal tract, superior longitudinal fasciculus, anterior thalamic radiation, superior cerebellar peduncle, medial lemniscus, retrolenticular and anterior limb of the internal capsule, cerebral peduncle and external capsule bilaterally, as well as the left posterior limb of the internal capsule and the right posterior thalamic radiation. MSA patients also displayed differences in the body of the corpus callosum corticospinal tract, cerebellar peduncle, medial lemniscus, anterior and superior corona radiata, posterior limb of the internal capsule external capsule and cerebral peduncle bilaterally, as well as the left anterior limb of the internal capsule and the left anterior thalamic radiation. No significant white matter abnormalities were observed in the PD group. Across groups, MD correlated positively with disease severity in all major white matter tracts. These results show widespread changes in white matter tracts in both PSP and MSA patients, even at a mid-point in the disease process, which are not found in patients with PD

PIT telemetry as a method to study the habitat requirements of fish populations: application to native and stocked trout movements

Passive integrated transponder (PIT) technology was used to study the behaviour of fishes during the summer season in two headwater streams of northeastern Portugal. A total of 71 PIT tags (12 mm long x 2.1 mm diameter) were surgically implanted in 1+ stocked (39) and native (32) brown trout of two size classes (< 20.0 and ≥ 20.0 cm). Eight independent antennae, connected to a multi-point decoder (MPD reader) unit, were placed in different microhabitats, selected randomly every three days during the observation period (29 August to 9 September in Baceiro stream and 19 September to 4 October in Sabor stream). The results confirmed this method as a suitable labour efficient tool to assess the movement and habitat use of sympatric stocked and native trout populations. About 76.9% of stocked and 59.4% of native PIT tagged trouts were detected. Multivariate techniques (CCA, DFA and classification tree) showed a separation in habitat use between the two sympatric populations. Stocked trout mainly used the microhabitats located in the middle of the channel with higher depths and without cover. Furthermore, these fishes displayed a greater mobility and a diel activity pattern different to native trout populations

Globally sparse PLS regression

Volume 56 ; Print ISBN : 978-1-4614-8282-6Partial least squares (PLS) regression combines dimensionality reduction and prediction using a latent variable model. It provides better predictive ability than principle component analysis by taking into account both the independent and re- sponse variables in the dimension reduction procedure. However, PLS suffers from over-fitting problems for few samples but many variables. We formulate a new criterion for sparse PLS by adding a structured sparsity constraint to the global SIMPLS optimization. The constraint is a sparsity-inducing norm, which is useful for selecting the important variables shared among all the components. The optimization is solved by an augmented Lagrangian method to obtain the PLS components and to perform variable selection simultaneously. We propose a novel greedy algorithm to overcome the computation difficulties. Experiments demonstrate that our approach to PLS regression attains better performance with fewer selected predictor