Window technique for climate trend analysis

Climatic characteristics are affected by various systematic and occasional impacts: besides the changes in the observing system (locations of the stations of the meteorological network, instruments, observing procedures), the possible local-scale and global natural and antropogenic impacts on climatic conditions should be taken into account. Apart from the predictability problems, the phenomenological analysis of the climatic variability and the determination of past persistent climatic anomalies are significant problems, among other aspects, as evidence of the possible anomalous behavior of climate or for climate impact studies. In this paper, a special technique for the identification of such shifts in the observational series is presented. The existence of these significant shorter or longer term changes in the mean characteristics for the properly selected adjoining periods of time is the necessary condition for the formation of any more or less unidirectional climatic trends. Actually, the window technique is based on a complete set of orthogonal functions. The sensitivity of the proposed model on its main parameters is also investigated. This method is applied for hemispheric and Hungarian data series of the mean annual surface temperature.Contribution to Clima Locarno — Past and Present Climate Dynamics; Conference September 1990, Swiss Academy of Sciences — National Climate Program     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Evaluation of methods of spatial interpolation for monthly rainfall data over the state of Rio de Janeiro,Brazil

Five deterministic methods of spatial interpolation of monthly rainfall were compared over the state of Rio de Janeiro, southeast Brazil. The methods were the inverse distance weight (IDW), nearest neighbor (NRN), triangulation with linear interpolation (TLI), natural neighbor (NN), and spline tension (SPT). A set of 110 weather stations was used to test the methods. The selection of stations had two criteria: time series longer than 20 years and period of data from 1960 to 2009. The methods were evaluated using cross-validation, linear regression between values observed and interpolated, root mean square error (RMSE), coefficient of determination (r ²), coefficient of variation (CV, %), and the Willmott index of agreement (d). The results from different methods are influenced by the meteorological systems and their seasonality, as well as by the interaction with the topography. The methods presented higher precision (r ²) and accuracy (d, RMSE) during the summer and transition to autumn, in comparison with the winter or spring months. The SPT had the highest precision and accuracy in relation to other methods, in addition to having a good representation of the spatial patterns expected for rainfall over the complex terrain of the state and its high spatial variability.     

Changing human-environment interactions in medium mountains: the Apuseni Mts (Romania) as a case study

The study of human-environment relationships in mountain areas is important for both theoretical and practical reasons, as many mountain areas suffer similar problems, such as depopulation, unemployment and natural hazards. Medium mountains constitute a special case within mountains, because they are more populated but less attractive as tourist destinations than high mountains. In this context, the Apuseni Mts (Romania) are considered as a case study. In this paper, we apply GIS-based, quantitative methods to characterize the strength and dynamics of human-environment interactions, taking into consideration some environmental factors (elevation, relative height, slope, river distance, lithology, land cover, natural attractions) as well as historical population and recent tourism data. We found that population density has strong (r ²>0.8) relationships with all relief factors (elevation, relative height, slope, river distance), and that best-fit functions are nonlinear. We outlined the varying demographic scenarios by elevation zones and interpreted the historically switching sign of population change versus elevation relationship. We demonstrated that lithology also has an impact on the spatial distribution of population, although it is not independent from the relief effect. The land cover of the mainly cultural landscape is very strongly correlated with relief parameters (especially slope), which suggests good adaptation. We pointed out the dominance of karst objects in the natural tourism potential of the Apuseni Mts and also explored further components of real tourism (spas, heritage, towns). Finally, we concluded that the environmental settings investigated do in fact constrain the spatial framework of society, but socio-economic changes in history can be explained from the side of society, which conforms to the theory of cultural possibilism.     

Comparison of ecophysiological characteristics between introduced and indigenous mangrove species in China

Due to its rapid growth, the introduced mangrove species Sonneratia apetala from Bangladesh has been widely used in mangrove restoration in southeastern China since 1985. As an indigenous mangrove species in Hainan, China, Sonneratia caseolaris was also planted in Guangdong Province for afforestation purposes. Both species have developed well in their new habitats, but their ecophysiological differences with the native mangrove species have not been studied. In this study, leaf gas exchange, water and nitrogen use efficiencies of two Sonneratia species were compared with those of selected native mangrove species (Avicennia marina, Aegiceras corniculatum, Kandelia candel, and Excoecaria agallocha) in Hainan and Shenzhen. The introduced S. apetala maintained lower carbon assimilation rate (A) and photosynthetic nitrogen use efficiency (PNUE) than the indigenous S. caseolaris. In Shenzhen, the two introduced Sonneratia had comparable photosynthetic rates and water use efficiency (WUE) with the native mangrove species, except that PNUE in S. caseolaris was significantly higher than in the native mangrove species. The two Sonneratia species showed significant overlap in PNUE and long-term WUE. Photosynthetic parameters derived from leaf photosynthetic light–response curves and A–C_i curves also suggested lower carbon assimilation capacities for the introduced Sonneratia than for the native mangrove species in both study sites. The lower light compensation point (LCP) of two introduced Sonneratia in both study sites also indicated a better adaptation to a low light regime than the native mangrove species. The results of photosynthetic capacities indicated that the introduced mangrove species have little competitive advantage over local native mangrove species in their respective new habitats.     

Microbial community dynamics and biodegradation of polycyclic aromatic hydrocarbons in polluted marine sediments in Hong Kong

Dynamics of microbial community and biodegradation of polycyclic aromatic hydrocarbons (PAHs) in polluted marine sediments, artificially spiked with a mixture of PAHs (fluorene, phenanthrene, fluoranthene and pyrene), were examined for a period of 60 days. Microbial communities were characterised by bacterial counts, ester-linked fatty acid methyl ester (EL-FAME) analysis and denaturing gradient gel electrophoresis (DGGE). A noted reduction in species diversity occurred only in the high PAH level treatment at onset. Both EL-FAME and DGGE demonstrated a marked shift in microbial community, in all the PAH level treatments, afterwards, with increases in the number of fatty acid degraders, the relative abundance of fatty acid biomarkers for gram-negative bacteria and a decrease in species diversity. The shift was also accompanied by the significant decrease in PAH concentrations. By the end of the experiment, diversity indices, based on both approaches, recovered when PAH concentrations declined to their background levels, except in the high PAH level treatment.     

Trophic modeling of the Northern Humboldt Current Ecosystem, Part II: Elucidating ecosystem dynamics from 1995 to 2004 with a focus on the impact of ENSO

The Northern Humboldt Current Ecosystem is one of the most productive in the world in terms of fish production. Its location near to the equator permits strong upwelling under relatively low winds, thus creating optimal conditions for the development of plankton communities. These communities ultimately support abundant populations of grazing fish such as the Peruvian anchoveta, Engraulis ringens. The ecosystem is also subject to strong inter-annual environmental variability associated with the El Niño Southern Oscillation (ENSO), which has major effects on nutrient structure, primary production, and higher trophic levels. Here our objective is to model the contributions of several external drivers (i.e. reconstructed phytoplankton changes, fish immigration, and fishing rate) and internal control mechanisms (i.e. predator-prey) to ecosystem dynamics over an ENSO cycle. Steady-state models and time-series data from the Instituto del Mar del Perú (IMARPE) from 1995 to 2004 provide the base data for simulations conducted with the program Ecopath with Ecosim. In simulations all three external drivers contribute to ecosystem dynamics. Changes in phytoplankton quantity and composition (i.e. contribution of diatoms and dino- and silicoflagellates), as affected by upwelling intensity, were important in dynamics of the El Niño of 1997–98 and the subsequent 3 years. The expansion and immigration of mesopelagic fish populations during El Niño was important for dynamics in following years. Fishing rate changes were the most important of the three external drivers tested, helping to explain observed dynamics throughout the modeled period, and particularly during the post-El Niño period. Internal control settings show a mix of predator–prey control settings; however a “wasp-waist” control of the ecosystem by small pelagic fish is not supported.     

West Nile virus in American crows (Corvus brachyrhynchos) in Canada: projecting the influence of climate change

The present study examined the influence of climate change on the spread of West Nile virus (WNV) in Canada among American crows (Corvus brachyrhynchos) by first identifying the significant climatic and environmental determinants of positive WNV cases in American crow specimens from 2009 to 2013. Using this information, we projected climate change scenarios on the potential spread of WNV in American crow species in Canada for three time periods: 2015–2039, 2040–2069, and 2070–2099. Using bird specimen, meteorological and land-use data, the statistical association between positive WNV cases in American crows and the environment was assessed by means of a general linear mixed model. Statistical results revealed that temperature and precipitation were significantly related to positive cases of WNV in American crows. Thus, climate change projections of summer mean temperature averages were projected for the three time periods. Climate change scenarios were created and imported into Quantum Geographic Information System (QGIS) and an algorithm was applied using the raster calculator to spatially delineate current and future areas of risk. Spatial analyses revealed that increased warming in the near future may increase the latitudinal extension of WNV in American crows in Canada.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

Geospatial analysis between the environment and past incidences of West Nile virus in bird specimens in Ontario,Canada

Over recent years, the prevalence of the West Nile virus (WNV) in Canada has greatly increased due to various factors including changes in feeding behavior among WNV vectors. To understand whether changes in climate are a significant factor, the association between the environment and cases of WNV-infected bird specimens from 2009 to 2012 in Ontario, Canada, was examined using SAS and Quantum Geographic Information Systems (QGIS). Through a generalized linear mixed analysis, monthly totals of cooling degree days (CDD) and a two-way interaction between maximum temperature (Tmax) and precipitation were significantly positively associated to past incidences of WNV; while Tmax, precipitation, and a two-way interaction between CDD and precipitation were significantly negatively associated to past incidences of WNV. With the effects of increased warming, locations at higher latitudes in Canada may soon be at risk to WNV, as a positive case of WNV in a bird specimen was found close to the near north of Ontario in 2012.