A 700-year paleoecological record of boreal ecosystem responses to climatic variation from Alaska

Recent observations and model simulations have highlighted the sensitivity of the forest - tundra ecotone to climatic forcing. In contrast, paleoecological studies have not provided evidence of tree-line fluctuations in response to Holocene climatic changes in Alaska, suggesting that the forest - tundra boundary in certain areas may be relatively stable at multicentennial to millennial time scales. We conducted a multiproxy study of sediment cores from an Alaskan lake near the altitudinal limits of key boreal-forest species. Paleoecological data were compared with independent climatic reconstructions to assess ecosystem responses of the forest - tundra boundary to Little Ice Age (LIA) climatic. uctuations. Pollen, diatom, charcoal, macrofossil, and magnetic analyses provide the first continuous record of vegetation -. re - climate interactions at decadal to centennial time scales during the past 700 years from southern Alaska. Boreal-forest diebacks characterized by declines of Picea mariana, P. glauca, and tree Betula occurred during the LIA ( AD 1500 - 1800), whereas shrubs ( Alnus viridis, Betula glandulosa/nana) and herbaceous taxa (Epilobium, Aconitum) expanded. Marked increases in charcoal abundance and changes in magnetic properties suggest increases in. re importance and soil erosion during the same period. In addition, the conspicuous reduction or disappearance of certain aquatic ( e. g., Isoetes, Nuphar, Pediastrum) and wetland ( Sphagnum) plants and major shifts in diatom assemblages suggest pronounced lake-level. uctuations and rapid ecosystem reorganization in response to LIA climatic deterioration. Our results imply that temperature shifts of 1 - 2 degrees C, when accompanied by major changes in moisture balance, can greatly alter high-altitudinal terrestrial, wetland, and aquatic ecosystems, including conversion between boreal-forest tree line and tundra. The climatic and ecosystem variations in our study area appear to be coherent with changes in solar irradiance, suggesting that changes in solar activity contributed to the environmental instability of the past 700 years.

Physiological Responses to Environmental Variation in Intertidal Red Algae: Does Thallus Morphology Matter?

Morphological variation within and among many species of algae show correlated life history traits. The trade-offs of Life history traits among different morphs are presumed to be determined by morphology. Form-function hypotheses also predict that algae of different morphological groups exhibit different tolerances to physiological stress, whereas algae within a morphological group respond similarly to stress. We tested this hypothesis by comparing photosynthetic and respiratory responses to variation in season, light, temperature, desiccation and freezing among the morphologically similar fronds of Chondrus crispus and Mastocarpus stellatus and the alternate stage crust of M. stellatus. Physiological differences between fronds of the 2 species and crusts and fronds were consistent with their patterns of distribution and abundance in the intertidal zone. However, there was no clear relationship between algal morphology and physiological response to environmental variation. These results suggest that among macroalgae the correlation between Life history traits and morphology is not always causal. Rather, the link between life history traits and morphology is constrained by the extent to which physiological characteristics codetermine these features.

Drought-induced shift of a forest–woodland ecotone: Rapid landscape response to climate variation

In coming decades, global climate changes are expected to produce large shifts in vegetation distributions at unprecedented rates. These shifts are expected to be most rapid and extreme at ecotones, the boundaries between ecosystems, particularly those in semiarid landscapes. However, current models do not adequately provide for such rapid effects—particularly those caused by mortality—largely because of the lack of data from field studies. Here we report the most rapid landscape-scale shift of a woody ecotone ever documented: in northern New Mexico in the 1950s, the ecotone between semiarid ponderosa pine forest and piñon–juniper woodland shifted extensively (2 km or more) and rapidly (<5 years) through mortality of ponderosa pines in response to a severe drought. This shift has persisted for 40 years. Forest patches within the shift zone became much more fragmented, and soil erosion greatly accelerated. The rapidity and the complex dynamics of the persistent shift point to the need to represent more accurately these dynamics, especially the mortality factor, in assessments of the effects of climate change.

Managing from the inside out:drawing on 'receptivity' to explain variation in strategy implementation

With the rise of 'New Public Management' (NPM), government policy has encouraged public-sector organizations to downsize and outsource their services. There is, however, local variation in the use of outsourcing - this is 'managing from the inside out'. This paper draws on the notion of receptivity for organizational change to explain variation in strategy implementation. Four receptivity factors are identified which seem to explain the success of two contrasting English local government outsourcing strategies: ideological vision, leading change, institutional politics and implementation capacity. The organization level of change is interconnected with two other levels of change (the public service and environment levels) to illustrate the dynamic nature of change.

Hydrological Response of East China to the Variation of East Asian Summer Monsoon

Copyright © 2016 Fuxing Li et al.The sensitivity of hydrologic variables in East China, that is, runoff, precipitation, evapotranspiration, and soil moisture to the fluctuation of East Asian summer monsoon (EASM), is evaluated by the Mann-Kendall correlation analysis on a spatial resolution of 1/4° in the period of 1952-2012. The results indicate remarkable spatial disparities in the correlation between the hydrologic variables and EASM. The regions in East China susceptible to hydrological change due to EASM fluctuation are identified. When the standardized anomaly of intensity index of EASM (EASMI) is above 1.00, the runoff of Haihe basin has increased by 49% on average, especially in the suburb of Beijing and Hebei province where the runoff has increased up to 105%. In contrast, the runoff in the basins of Haihe and Yellow River has decreased by about 27% and 17%, respectively, when the standardized anomaly of EASMI is below -1.00, which has brought severe drought to the areas since mid-1970s. The study can be beneficial for national or watershed agencies developing adaptive water management strategies in the face of global climate change.

A geostatistical analysis of soil, vegetation, and image data characterizing land surface variation

The elucidation of spatial variation in the landscape can indicate potential wildlife habitats or breeding sites for vectors, such as ticks or mosquitoes, which cause a range of diseases. Information from remotely sensed data could aid the delineation of vegetation distribution on the ground in areas where local knowledge is limited. The data from digital images are often difficult to interpret because of pixel-to-pixel variation, that is, noise, and complex variation at more than one spatial scale. Landsat Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de La Terre (SPOT) image data were analyzed for an area close to Douna in Mali, West Africa. The variograms of the normalized difference vegetation index (NDVI) from both types of image data were nested. The parameters of the nested variogram function from the Landsat ETM+ data were used to design the sampling for a ground survey of soil and vegetation data. Variograms of the soil and vegetation data showed that their variation was anisotropic and their scales of variation were similar to those of NDVI from the SPOT data. The short- and long-range components of variation in the SPOT data were filtered out separately by factorial kriging. The map of the short-range component appears to represent the patterns of vegetation and associated shallow slopes and drainage channels of the tiger bush system. The map of the long-range component also appeared to relate to broader patterns in the tiger bush and to gentle undulations in the topography. The results suggest that the types of image data analyzed in this study could be used to identify areas with more moisture in semiarid regions that could support wildlife and also be potential vector breeding sites.

Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction

Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.

No-reference image quality assessment in contourlet domain

The target of no-reference (NR) image quality assessment (IQA) is to establish a computational model to predict the visual quality of an image. The existing prominent method is based on natural scene statistics (NSS). It uses the joint and marginal distributions of wavelet coefficients for IQA. However, this method is only applicable to JPEG2000 compressed images. Since the wavelet transform fails to capture the directional information of images, an improved NSS model is established by contourlets. In this paper, the contourlet transform is utilized to NSS of images, and then the relationship of contourlet coefficients is represented by the joint distribution. The statistics of contourlet coefficients are applicable to indicate variation of image quality. In addition, an image-dependent threshold is adopted to reduce the effect of content to the statistical model. Finally, image quality can be evaluated by combining the extracted features in each subband nonlinearly. Our algorithm is trained and tested on the LIVE database II. Experimental results demonstrate that the proposed algorithm is superior to the conventional NSS model and can be applied to different distortions. © 2009 Elsevier B.V. All rights reserved.

Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.