Modelling the effects of topographic heterogeneity on distribution of Nitraria tangutorum Bobr. species in deserts using LiDAR-data.

Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. Many hot issues can be investigated in desert ecosystems, including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence index, and solar insolation). Species Distribution Models (SDMs) can be used to understand these relationships. We used data acquired from the important desert plant Nitraria tangutorum Bobr. communities and desert topographic factors extracted from LiDAR (Light Detection and Ranging) data of one square kilometer in the inner Mongolia region of China to develop SDMs. We evaluated the performance of SDMs developed with a variety of both the parametric and nonparametric algorithms (Bioclimatic Modelling (BIOCLIM), Domain, Mahalanobi, Generalized Linear Model, Generalized Additive Model, Random Forest (RF), and Support Vector Machine). The area under the receiver operating characteristic curve was used to evaluate these algorithms. The SDMs developed with RF showed the best performance based on the area under curve (0.7733). We also produced the Nitraria tangutorum Bobr. distribution maps with the best SDM and suitable habitat area of the Domain model. Based on the suitability map, we conclude that Nitraria tangutorum Bobr. is more suited to southern part with 0-20 degree slopes at an elevation of approximately 1010 m. This is the first attempt of modelling the effects of topographic heterogeneity on the desert species distribution on a small scale. The presented SDMs can have important applications for predicting species distribution and will be useful for preparing conservation and management strategies for desert ecosystems on a small scale.

Modeling stand biomass for Moso bamboo forests in Eastern China.

Stand biomass models can be used as basic decision-making tools in forest management planning. The Moso bamboo (Phyllostachys pubescens) forest, a major forest system in tropical and subtropical regions, represents a substantial carbon sink, slowing down the rise of greenhouse gas concentrations in the earth's atmosphere. Bamboo stand biomass models are important for the assessment of the contribution of carbon to the terrestrial ecosystem. We constructed a stand biomass model for Moso bamboo using destructively sampled data from 45 sample plots that were located across the Yixing state-owned farm in Jiangsu Province, China. Among several bamboo stand variables used as predictors in the stand biomass models, mean diameter at breast height (MDBH), mean height (MH), and canopy density (CD) of bamboo contributed significantly to the model. To increase the model's accuracy, we introduced the effects of bamboo forest block as a random effect into the model through mixed-effects modeling. The mixed-effects model described a large part of stand biomass variation (R2 = 0.6987), significantly higher than that of the ordinary least squares regression model (R2 = 0.5748). Our results show an increased bamboo stand biomass with increasing MH and CD, confirming our model's biological logic. The proposed stand biomass model may have important management implications; for example, it can be combined with other bamboo models to estimate bamboo canopy biomass, carbon sequestration, and bamboo biomass at different growth stages.

Two-level mixed-effects height to crown base model for moso bamboo (Phyllostachys edulis) in Eastern China.

Height to crown base (HCB) is an important predictor variable for forest growth and yield models and is of great significance for bamboo stem utilization. However, existing HCB models built so far on the hierarchically structured data are for arbor forests, and not applied to bamboo forests. Based on the fitting of data acquired from 38 temporary sample plots of Phyllostachys edulis forests in Yixing, Jiangsu Province, we selected the best HCB model (logistic model) from among six basic models and extended it by integrating predictor variables, which involved evaluating the impact of 13 variables on HCB. Block- and sample plot-level random effects were introduced to the extended model to account for nested data structures through mixed-effects modeling. The results showed that bamboo height, diameter at breast height, total basal area of all bamboo individuals with a diameter larger than that of the subject bamboo, and canopy density contributed significantly more to variation in HCB than other variables did. Introducing two-level random effects resulted in a significant improvement in the accuracy of the model. Different sampling strategies were evaluated for response calibration (model localization), and the optimal strategy was identified. The prediction accuracy of the HCB model was substantially improved, with an increase in the number of bamboo samples in the calibration. Based on our findings, we recommend the use of four randomly selected bamboo individuals per sample to provide a compromise between measurement cost, model use efficiency, and prediction accuracy.

Constructing two-level nonlinear mixed-effects crown width models for Moso bamboo in China.

Bamboo crown width (CW) is a reliable index for evaluating growth, yield, health and vitality of bamboo, and light capture ability and carbon fixation efficiency of bamboo forests. Based on statistical results produced from fitting the eight basic growth functions using data from 1374 Phyllostachys pubescens in Yixing, Jiangsu Province, China, this study identified the most suitable function (logistic function) to construct a two-level mixed effects (NLME) CW model with the forest block and sample plot-level effects included as random effects in the model. Four methods for selecting sample bamboos per sample plot (largest bamboo, medium-sized bamboo, smallest bamboo, and randomly selected bamboos) and eight sample sizes (1-8 selected bamboos per sample plot) were evaluated to calibrate our NLME CW model. Using diameter at breast height (DBH), height to crown base (HCB), arithmetic mean diameter at breast height (MDBH), and height (H) as predictor variables, the model produced the best fit statistics (Max R2, min RMSE, and TRE). This model was further improved by introducing random effects at two levels. The results showed a positive correlation of CW with HCB and DBH and a negative correlation with H. The smallest two bamboo poles per sample plot used to estimate the random effects of the NLME model provided a satisfactory compromise regarding measurement cost, model efficiency, and prediction accuracy. The presented NLME CW model may guide effective management and carbon estimation of bamboo forests.

Aboveground carbon of community-managed Chirpine (Pinus roxburghii Sarg.) forests of Nepal based on stand types and geographic aspects.

On a global scale, about 15.5% of forests are administered through community-based forestry programs that offer the opportunity for enhanced carbon sequestration while maintaining the supply of more traditional goods and services such as cooking fuels, animal fodder and bedding. A challenge in community forest (CF) management is to realize their carbon value without compromising their role in the provision of these traditional goods and services. In this study of CF dominated by Pinus roxburghii in the Phalebas region of Nepal, the impacts of stand composition and geographic aspect on aboveground forest carbon is investigated as a means to optimize CF management for both traditional values and for emerging carbon market values. The aboveground carbon of mixed and monospecific stands of Pinus roxburghii was estimated using a combination of destructive sampling and species-specific allometric equations. On average, monospecific stands contained 106.2 Mg C ha-1 in aboveground tree biomass, significantly more than mixed stands at 73.1 Mg C ha-1 (p = 0.022). Similarly, stands growing on northern aspects (northeast 124.8 Mg C ha-1, northwest 100.9 Mg C ha-1) stored significantly more carbon (p = 0.002) than southern aspects (southeast 75.3 Mg C ha-1, southwest 57.6 Mg C ha-1), reflecting the more favorable growing conditions of northern aspects. These results suggest monospecific stands planted on northern aspects may be best suited for management to achieve carbon benefits, whilst mixed-species stands on southern aspects may be better suited for biodiversity conservation and supporting livelihoods. To maintain and increase carbon value, community forestry may need to implement nutrient return practices to limit the impact of sustained nutrient removals on stand productivity.

Windbreak Efficiency in Agricultural Landscape of the Central Europe: Multiple Approaches to Wind Erosion Control.

Windbreak is one of the key factors for making the agriculture systems successful through reduced wind erosion, improved microclimate, increased biodiversity, and production potentiality of timber and agricultural crops. Even though windbreak occupies only a small part of agricultural landscape, its advantages on the ecological and economical perspective are quite high. This study evaluated the effects of three windbreak types on the wind erosion control in relation to their structural diversities, wind-speed reduction, and optical porosities in the central part of the Czech Republic. Diversity in the windbreak was evaluated based on its species diversity, vertical structure, spatial pattern, and complexities. Wind speed was measured at the different distances on the leeward side of the windbreak and one station placed on the windward side as a control. Windbreak characteristics were described by terrestrial photogrammetry method using the values of optical porosity. The timber volume of the windbreaks with rich biodiversity species ranged from 224 to 443 m3 ha-1height of the windbreak on the. Results of the windbreak efficiency showed significantly closer relationship between optical porosity and structural indices. The optical porosity significantly correlated with wind-speed reduction, especially in the lower part of the windbreak. A significant dependency of the windbreak efficiency on the tree dominant height was also observed for each windbreak type. The most significant effect on the wind-speed reduction in terms of structural indices had total diversity index and Arten-profile index describing vertical structures, which are recommended together with the optical porosity to evaluate the windbreak efficiency in controlling wind erosion.

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.).

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi's competition index (HCI-spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models.

Solid phase synthesis of anthraquinone peptides and their evaluation as topoisomerase I inhibitors.

Anthraquinone peptide derivatives have previously been shown to inhibit the enzyme topoisomerase I (topo I), a pharmaceutical target for the prevention of malignant carcinomas. A highly efficient procedure for the attachment of the anthraquinone moiety to the N-terminus of a peptide on a solid support is reported. This methodology provides a convenient method for the synthesis of labelled peptides, with potential applications for chemotherapy, DNA detection and protein purification. As the synthetic strategy utilizes the solid phase, it should also be amenable to the generation of combinatorial libraries. The utility of the method by synthesizing a pool of peptides and assaying for topo I inhibition is demonstrated.

Topoisomerase enzymes as therapeutic targets for cancer chemotherapy.

The topoisomerase enzymes are essential for DNA metabolism, where they act to adjust the number of supercoils in DNA, a key requirement in the cellular processes of transcription and replication. Their enzymatic mechanism creates transient nicks (type I) or breaks (type II) in the double stranded DNA polymer, allowing DNA to be converted between topological isomers. Humans possess both types of topoisomerase enzymes, however the two types utilize very different enzymatic mechanisms. Both type I and type II topoisomerases have been identified as clinically important targets for cancer chemotherapy and their inhibitors are central components in many therapeutic regimes. Over the course of the last 30 years inhibitors with extensive structural diversity have been developed through a combination of drug screening and rational design programs. Simultaneously much emphasis has been placed upon establishing the mechanisms of action of both classes of topoisomerase enzyme. Crucial structural insights have come from the crystal structure of topoisomerase I, while modelling comparisons are beginning to map out a possible framework for topoisomerase II action. This review discusses these recent advances in the fields of enzyme mechanism and inhibitor design. We also address the development of drug resistance and dose-limiting side effects as well as cover alternative methods in drug delivery.

Effects of nociceptin and analogues of nociceptin upon spontaneous dorsal root activity recorded from an in vitro preparation of rat spinal cord.

The 17 amino acid peptide nociceptin has been implicated in pain modulation in the central nervous system. The effects of bath applied nociceptin, and some analogues of nociceptin, upon spontaneous lumbar dorsal root activity have been investigated in an isolated preparation of rat spinal cord. Nociceptin was found to reversibly depress spontaneous dorsal root activity at concentrations of 1.0 microM and 10.0 microM (IC50 2.0 microM), whereas acetyl-nociceptin at concentrations up to 10 microM had no detectable effect. Omission of the last four amino acids (nociceptin 1-13), increased the potency of the effect upon dorsal root activity by approximately 100-fold (IC50 30 nM), but activity was lost when only the first seven amino acids of the nociceptin molecule (nociceptin 1-7) were tested.

Hypoxic ventilatory response changes of men and women 6 to 7 days after climbing from 2100 m to 4350 m altitude and after descent.

To test the hypothesis that the changes in hypoxic ventilatory response (HVR) of men and women mountaineers on induction to HA by trekking is not influenced by gender, isocapnic HVR as DeltaV(E)/DeltaSa(O2) was studied in eight men and eight women mountaineering trainees initially at 2100 m, then during 6 to 7 days of sojourn at 4350 m, and retested again on return to 2100 m. Results indicated that HVR at 2100 m increased significantly at 4350 m in both sexes, and the values reverted to baseline level within 4 to 5 days between leaving high altitude (4350 m) and restudy at 2100 m. No sex differences were observed at 2100- or at 4350-m altitude, indicating that men and women have a similar level of chemosensitive response as measured by HVR during induction to HA.