Geo-climatic Factors Research Articles

Evaluation of The Safety and Efficacy of Newly Developed Domestic Allergenic Extracts for Skin Prick Testing.

Allergic disorders are common health problems worldwide with significant socio-economic impacts. The best diagnostic method using allergenic extract is the skin prick test. Regarding the effects of geo-climatic factors and allergenic extract source material quality, the aim of study was to determine the safety and efficacy of some in-house-developed allergenic extracts. Forty-five different allergenic extracts, including common regional pollen, foods, and dog and cat hair, as well as positive and negative extracts, were prepared from domestic sources using optimum extraction methods. All extracts passed stability and sterility testing, and sterile final products containing 50% glycerin in 10 and 20 w/v concentrations were used. Skin prick testing was performed on volunteers and immediate or late side effects were recorded. In total, 56 students (mean age: 21.2±2.3y, M/F ratio: 1.07) participated in this study. For inhalant allergens, all extracts except dog hair extract caused positive responses. Salsola kali (Russian thistle) and Fraxinus velutina (ash tree) were the most common grass and tree pollen extracts, respectively. Of 18 different food extracts, five, including egg white, tomato, fig, melon, and green pepper caused skin reactivity in only one person. No participant reported any immediate or late side effects, including large local reaction or systemic response. The result of the current study confirmed the safety of all our in-house-developed allergenic extracts. Regarding efficacy, almost all inhalant and five food allergens caused positive skin responses.

Spatial analysis and geoclimatic factors associated with the incidence of acute lymphoblastic leukemia in Iran during 2006–2014: An environmental epidemiological study

Background and objectivesThe present study aims to determine the cumulative incidence rate of acute lymphoblastic leukemia (ALL), the degree of spatial autocorrelation and clustering of ALL, the hotspot and coldspots of ALL and geoclimatic conditions affecting the incidence of ALL in Iran and to draw a comparison between global and local regression models. Materials and methodsIn this ecological study, an exploratory-etiologic multiple-group method has been adopted to investigate all children under 15 years of age with ALL in Iran during 2006–2014. Data analysis was performed using Mann Whitney U, Pearson correlation coefficients (PCCs), Global Moran's I, Optimized hotspot analysis (OHSA), Global Poisson regression (GPR), Geographically Weighted Poisson Regression (GWPR) at a significant level of α = 0.05. ResultsThe cumulative incidence rate of ALL was estimated at 21,315 per 100,000 Iranian children under 15 years of age. The value of Global Moran's I index was estimated 0.338 and significant (<0.001 P-value). Coldspots were observed in north and northwest of Iran and hotspots were identified in south, southwest and mid-east of Iran. In the present study, Max Temperature of Warmest Month (MTWM) and Direct Normal Irradiation (DNI) were risk factors and Precipitation of the Coldest Quarter (PCQ) and Altitude (AL) were protective factors in the incidence of ALL, even though the non-stationarity of local coefficients and local t-values was clear. GWPR, by capturing and applying spatial heterogeneity and spatial autocorrelation, had a greater performance and goodness of fit than GPR. DiscussionALL has created spatial clusters in Iran. The incidence of ALL is the result of synergistic interaction between environmental, infectious, geographical and genetic risk factors. It is recommended to use of local models in ecological studies.

Mycotoxins, Phytoestrogens and Other Secondary Metabolites in Austrian Pastures: Occurrences, Contamination Levels and Implications of Geo-Climatic Factors.

Pastures are key feed sources for dairy production and can be contaminated with several secondary metabolites from fungi and plants with toxic or endocrine-disrupting activities, which possess a risk for the health, reproduction and performance of cattle. This exploratory study aimed to determine the co-occurrences and concentrations of a wide range of mycotoxins, phytoestrogens and other secondary metabolites in grazing pastures. Representative samples of pastures were collected from 18 Austrian dairy farms (one sample per farm) between April to October 2019. After sample preparation (drying and milling) the pastures were subjected to multi-metabolite analysis using LC-MS/MS. In total, 68 metabolites were detected, including regulated zearalenone and deoxynivalenol (range: 2.16–138 and 107–505 μg/kg on a dry matter (DM) basis, respectively), modified (3-deoxynivalenol-glucoside, HT-2-glucoside) and emerging Fusarium mycotoxins (e.g., enniatins), ergot alkaloids and Alternaria metabolites along with phytoestrogens and other metabolites. Aflatoxins, fumonisins, T-2 toxin, HT-2 toxin and ochratoxins were not detected. Of the geo-climatic factors and botanical diversity investigated, the environment temperature (average of 2 pre-sampling months and the sampling month) was the most influential factor. The number of fungal metabolites linearly increased with increasing temperatures and temperatures exceeding 15 °C triggered an exponential increment in the concentrations of Fusarium and Alternaria metabolites and ergot alkaloids. In conclusion, even though the levels of regulated mycotoxins detected were below the EU guidance levels, the long-term exposure along with co-occurrence with modified and emerging mycotoxins might be an underestimated risk for grazing and forage-fed livestock. The one-year preliminary data points out a dominant effect of environmental temperature in the diversity and contamination level of fungal metabolites in pastures.

Geo-climatic factors weaken the effectiveness of phytoplankton diversity as a water quality indicator in a large sediment-laden river

The study aims to determine whether phytoplankton diversity can be used as an indicator of water quality in large-scale sediment-laden rivers with heterogeneous environmental conditions. We hypothesized that environmental factors, such as sediment load, water surface slope, and precipitation, may impact the effectiveness of using phytoplankton diversity as a water quality indicator. To test this hypothesis, the Yellow River was selected for phytoplankton diversity and water quality assessments. We measured water quality parameters, calculated phytoplankton diversity indices, and collected data on geo-climatic variables at 130 sampling points in the Yellow River mainstream over two seasons (spring and autumn) in 2019. The results of the water quality assessment based on phytoplankton diversity indices were compared with those based on water quality index (WQI). Correlation analysis, multiple stepwise regression, distance-based redundancy analysis, and regression modeling were used to explore the biogeographical patterns and drivers of phytoplankton diversity. According to the WQI, the water quality gradually deteriorated from the source to the estuary of the river. Three biodiversity indices (Margalef, Pielou, and Shannon-Wiener) indicated that the water quality varied dynamically in the middle reaches of the river. The actual relationships between the biodiversity indices and WQI did not fit well with the standard curves of water quality classification based on the respective biodiversity indices and WQI. Variation partitioning analysis indicated that water quality parameters, such as sediment and nutrient load, were the dominant drivers of variation in phytoplankton diversity in most cases, with the contribution ranging from 11.0% to 25.7%. Geo-climatic factors, such as water surface slope and annual mean precipitation, also affected phytoplankton diversity, with the contribution reaching 27.8%. Therefore, in sediment-laden rivers with a large geographical span and complex environment, phytoplankton diversity cannot be used as a suitable water quality indicator, albeit it can reflect habitat changes to a certain extent.

ESTIMATION OF DAILY ENERGY GAIN OF SOLAR TRACKING SURFACES BASED ON GEOGRAPHIC POSITION

The performance of solar systems depends on the effective incident solar energy on the capture surface. This factor is dependent on the geographic position, the orientation of the surface, atmospheric conditions, and other geo-climatic factors. Solar trackers, typically uni- and biaxial, are used to optimize the capture of solar radiation via movement of the plane of incidence of these devices. A reliable estimation of the energy gain of these trackers with respect to a fixed surface facilitates more accurate analyses of the feasibility, operation, and maintenance of solar ventures. In this work, a method for estimating the relative energy gain of uni- and biaxial solar trackers is developed. This approach applies to locations between the Arctic Circle and the Antarctic Circle, using geographic coordinates and the altitude of the location of interest, providing daily results throughout the year. Unlike empirical results or case studies, the proposed method applies to any location and has a low error. It can be implemented using iterative algorithms with a low computational cost and can be easily utilized by researchers and technicians in the field.

County-level USA: No Robust Relationship between Geoclimatic Variables and Cognitive Ability

Using a sample of ~3,100 U.S. counties, we tested geoclimatic explanations for why cognitive ability varies across geography. These models posit that geoclimatic factors will strongly predict cognitive ability across geography,even when a variety of common controls appear in the regression equations.Our results generally do not support UV radiation (UVR) based or other geoclimatic models. Specifically, although UVR alone predicted cognitive ability at the U.S. county-level (β = -.33), its validity was markedly reduced in the presence of climatic and demographic covariates (β = -.16), and was reduced even further with a spatial lag (β = -.10). For climate models,average temperature remained a significant predictor in the regression equation containing a spatial lag (β = .35). However, the effect was in the wrong direction relative to typical cold weather hypotheses. Moreover,when we ran the analyses separately by race/ethnicity, no consistent pattern appeared in the models containing the spatial lag. Analyses of gap sizes across counties were also generally inconsistent with predictions from the UVR model. Instead, results seemed to provide support for compositional models.

Genetic stability of Larix olgensis provenances planted in different sites in northeast China

Larix olgensis, also known locally as Changbai larch, is one of the most important timber species in northeast China. In order to widely expand the plantation of this species, the genetic stability and adaptability of the provenances must be analyzed through provenance tests. In this study, growth traits and survival rate (SR) of 10 L. olgensis provenances planted in four representative sites were investigated and analyzed. The results of ANOVA and AMMI analyses showed that the environment effect was a predominant source of variation. The average diameter at breast height (DBH) of different provenances at the four sites ranged from 14.65 to 28.51 cm. The stand volume also varied among provenances planted at different sites mainly due to variation in SR and DBH. The phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV) and repeatability (hP2) for DBH in different sites ranged from 12.47% to 17.79%, from 2.94% to 3.83% and from 0.49 to 0.63, respectively. The correlation analysis showed that there were highly significant positive correlations among DBH, survival rate, and stand volume, and they all not correlated with geoclimatic factors of provenances original sites. However, they were significantly positively correlated with longitude and precipitation of the trial sites. Significant negative correlations were observed between SR and latitude and with equivalent latitude. According to AMMI biplots, four provenances were regarded as the most stable and relatively high-yielding provenances across environments. These provenances could be used as the preferred materials for the establishment of large-scale plantations in the future.

Effects of geoclimatic factors on the variability in Pinus pinea cone, seed, and seedling traits in Turkey native habitats

BackgroundStone pine (Pinus pinea L.) is harvested for its edible kernels. It is an important forest tree species, and also plays an important role in afforestation. Successful afforestation activities strongly depend on the quality of seeds and seedlings. Five eastern native populations of stone pine were analyzed, in terms of their geographical and climatic parameters, in order to identify their cone, seed, pine nut, and seedling traits. With this regard, we aimed to contribute to the reforestation, yield, and breeding of this species.ResultsAll native populations occur in the sub-humid bioclimatic zone, according to Emberger’s bioclimatic classification, ranging 74.7–63.2 of Emberger’s Q Index value (Q), which synthesizes humidity and temperature, with lower values indicating more arid conditions. With regard to geographical factors, altitude was found to have the greatest effect on cone diameter and seed weight, while there was a weak correlation of cone, seed, and pine nut dimension with longitude and latitude. In terms of climatic factors, Q and mean of the maximum temperature of June, July, and August (ME) were found to be the main drivers behind significant effects in cone, seed, and pine nut morphometric traits. The most negative effect on seed number cone−1 (r: − 0.897), pine nut number cone−1 (r: − 0.923), pine nut yield (r: − 0.903), and pine nut weight (r: − 0.878) was Q, whereas cone diameter, seed length, and seed weight were positively correlated with the ME (r: 0.939, r: 0.889, and r: 0.866, respectively). Cone and seed diameter and seed weight increased with decreasing summer drought index (r: − 0.806, r: − 0.846, and r: − 0.866, respectively). Rainfall in the June of the third year prior to harvest time (RJ) had a negative effect on the percentage of sound seeds per cone. Annual rainfall in the third year prior to harvest time (AR) significantly affected pine nut weight (r: 0.889), although rainfall during summer had a negative effect. The empty seed ratio of the different populations ranged from 20 to 68%, while considering all populations, the empty seed ratio was 46%.ConclusionsThe study suggests that the Q Index and ME should be taken into account to determine cone to pine nut yield. With this regard, plantations of stone pine should be established on sub-humid areas and Q values should not exceed 75.

Genetically modified crops in India: Experiments with Bt Cotton to explore the road ahead

Abstract The success of genetically modified crops (GMCs), claimed to hold solution to impending environmental problems, depends on land holdings, agroclimatic and geoclimatic conditions, food preferences and sociocultural factors. The direct and indirect impacts of these crops on human health, ecology and environment have not been evaluated on long-term basis. In India, with rich background of farming, GMCs remain a minor change. Introduction of first GMC, Bt Cotton (BC), showed varied response throughout the country. New GMCs like Bt Brinjal and GM Mustard approved for open-field trials in the country were marred under contentious debate and were never approved for commercial cultivation. The current research article aims to study the ecological implications of only GMC available for experimentation in India, BC. A three-phase study carried out as field survey, glass dome experiments and open-field trials compared the BC and conventional cotton (CC) plants with extensive experimentation of ecological parameters including vegetation diversity, insect diversity, plant morphology and infestation intensity. Results highlighted the better morphological characteristics of BC over CC, while infestation studies showed 40% survival rate of insect pest on BC for which it is genetically modified. High electrical conductivity and low organic matter content in the BC soil samples as compared to CC soil samples were indicative of impact of Bt toxins in soil but need further in-depth soil studies to reach scientifically valid results. The current research article substantiates the environmental concerns raised against GMCs especially BC in the country. Its objective is to trigger more research in this direction, so that the technology of GMCs is utilized for the benefit of humankind.

Local environmental, geo-climatic and spatial factors interact to drive community distributions and diversity patterns of stream benthic algae, macroinvertebrates and fishes in a large basin, Northeast China

Understanding processes and mechanisms driving patterns of species distribution and diversity is a vital theme in community ecology and conservation biology. There has been a continuous increase in studies focusing on diversity patterns in freshwater ecosystems during the last few decades. However, comparative studies of species distributions, diversity patterns and underlying processes across trophic levels remain limited. The unique characteristics of the study area (i.e. Hun-Tai River in Northeast China) generates a wide range of environmental conditions to advance our understanding of what drives community assembly and diversity pattern of three stream organism groups. We applied variance partitioning (VPA) to correlate community compositions with environmental and spatial factors to infer stochastic and deterministic assembly processes, respectively. Linear regression (LR) models were used to identify the main drivers of species richness and local contributions to beta diversity (LCBD) as a function of different factors, including local environmental (e.g., in situ parameters, hydrology, nutrients), geo-climatic variables (e.g., land use, topography, climate) and spatial factors. Results indicated that species compositions of stream biota showed significant correlations with local environmental, geo-climatic and spatial factors. VPA demonstrated that both paradigms (i.e. deterministic and stochastic processes) interact to influence the biota distributions with stochastic process contributing more than deterministic process. In addition, the strongest stochastic process was found in fishes (10%), followed by benthic algae and macroinvertebrates with the same effects (8%). Notably, geo-climatic factors explained a substantial fraction of species composition, richness and beta diversity, although their effects were partially manifested via local and spatial variables. We demonstrate the relative importance of both stochastic and deterministic processes in shaping community composition and biodiversity of three stream organism groups in a large basin. This emphasizes the need to move beyond observed patterns and consider metacommunity theory into river management and conservation practices.

Effects of geographical and climatic factors on cystic echinococcosis in south-western Iran.

Cystic echinococcosis (CE) is caused by the larval form of Echinococcus granulosus that can cause serious health and economic problems in the endemic foci. CE is globally distributed in various climatic conditions from circumpolar to tropical latitudes. Iran is an important endemic area with a spectrum of weather conditions. The aim of this study was to determine the effects of geo-climatic factors on the distribution of livestock CE in south-western Iran (SWI) in 2016 to 2018. Data of livestock CE were retrieved from veterinary organizations of four provinces of SWI. The geo-climatic factors, including mean annual temperature (MAT), minimum MAT (MinMAT), maximum MAT (MaxMAT), mean annual rainfall (MAR), elevation, mean annual evaporation (MAE), sunny hours, wind speed, mean annual humidity (MAH), slope, frost days and land cover, were analysed using geographical information systems (GIS) approaches. The statistical analysis showed that MAR, frost days, elevation, slope and semi-condensed forest land cover were positively and MAE, MAT, MaxMAT, MinMAT and salt and salinity land cover were negatively correlated with CE occurrence. MAE was shown to be a predictive factor in the stepwise linear logistic regression model. In short, the current GIS-based study found that areas with lower evaporation were the main CE risk zones, though those with lower temperature and higher rainfall, altitude and slope, especially where covered with or in close proximity of semi-condensed forest, should be prioritized for consideration by health professionals and veterinarians for conducting control programmes in SWI.

Colonial Origins, Property Rights, and the Organization of Agricultural Production: The Us Midwest and Argentine Pampas Compared

We examine the origins, persistence, and economic consequences of institutional structures of agricultural production. We compare farms in the Argentine Pampas and US Midwest, regions of similar potential input and output mixes. The focus is on 1910-1914, during the international grain trade boom and when census data are available. The Midwest was characterized by small farms and family labor. Land was a commercial asset and traded routinely. The Pampas was characterized by large landholdings and use of external labor. Land was a source of status and held across generations. Status attributes could not be easily monetized for trade, reducing market exchange, limiting entry, and hindering farm restructuring. Differing land property rights followed from English and Spanish colonial and post-independence policies. Geo-climatic factors cannot explain dissimilarities in farm sizes, tenancy, and output mixes, suggesting institutional constraints. Midwest farmers also were more responsive to exogenous signals. There is evidence of moral hazard on Pampas farms. Conjectures on long-term development are provided.

The Spatial Distribution of Population in Spain: An Anomaly in European Perspective

We exploit the GEOSTAT 2011 population grid with a very high 1-km2 resolution to document that Spain presents the lowest density of settlements among European countries. We uncover that this anomaly cannot be accounted for by adverse geographic and climatic conditions. Using techniques from spatial econometrics, we identify the clusters that exhibit the lowest densities within Spain after controlling for geo-climatic factors: these areas mainly belong to Teruel, Zaragoza, Ciudad Real, Albacete, Sevilla and Asturias. We also explore the attributes that characterize the municipalities located in these low-density areas: larger population losses during the 1950-1991 rural exodus, higher shares of local-born inhabitants, longer distances to the province capital, higher shares of population employed in agriculture, and larger increases in regionalist vote after the Great Recession.

Associations between Water, Sanitation and Hygiene (WASH) and trachoma clustering at aggregate spatial scales, Amhara, Ethiopia

BackgroundTrachoma is the leading infectious cause of blindness globally. The WHO has recommended the SAFE (Surgery, Antibiotics, Facial cleanliness and Environmental improvements) strategy to eliminate trachoma as a public health problem. The F and E arms of the strategy will likely be important for sustained disease reductions, yet more evidence is needed detailing relationships between hygiene, sanitation and trachoma in areas with differing endemicity. This study addressed whether the regional differences in water, sanitation, and hygiene (WASH) variables were associated with the spatial distribution of trachomatous inflammation-follicular (TF) among children aged 1 to 9 years in the Amhara National Regional State of Ethiopia.MethodsData from 152 multi-stage cluster random trachoma surveys were used to understand the degree of clustering of trachoma on two spatial scales (district and village) in Amhara using a geographical information system and the Getis-Ord Gi* (d) statistic for local clustering. Trained and certified graders examined children for the clinical signs of trachoma using the WHO simplified system. Socio-demographic, community, and geoclimatic factors thought to promote the clustering of the disease were included as covariates in a logistic regression model.ResultsThe mean district prevalence of TF among children aged 1 to 9 years in Amhara was 25.1% (standard deviation = 16.2%). The spatial distribution of TF was found to exhibit global spatial dependency with neighboring evaluation units at both district and village level. Specific clusters of high TF were identified at both the district and the village scale of analysis using weighted estimates of the prevalence of the disease. Increased prevalence of children without nasal and ocular discharge as well as increased prevalence of households with access to a water source within 30 minutes were statistically significantly negatively associated with clusters of high TF prevalence.ConclusionsWater access and facial cleanliness were important factors in the clustering of trachoma within this hyperendemic region. Intensified promotion of structural and behavioral interventions to increase WASH coverage may be necessary to eliminate trachoma as a public health problem in Amhara and perhaps other hyper-endemic settings.

Gastrointestinal nematodes in sheep of cutting under grazing regime

Sheep breeding is practiced in practically all the continents, the wide diffusion of the species is due mainly to its power of adaptation. Due to geoclimatic factors, tropical and subtropical countries stand out and settle in the agricultural scenario, and Brazil does not become an exception in this market. Brazil, because it has a considerable part of the herd produced in pasture, which is one of the economic and practical ways of producing and offering bulky ruminants, is one of the main meat producers at one of the lowest production costs. Tropical and subtropical climates, in addition to favoring optimal conditions for the production and development of agricultural and livestock sectors, such as pasture and ruminant farming, also provide favorable conditions for the development and survival of gastrointestinal nematodes. Negative performance of the animals, especially the sheep. Gastrointestinal nematodes, when uncontrolled, can cause 30 to 40% losses in animal performance, especially in the development of young animals and reproductive matrices that are the most sensitive categories, and which are closely related to the growth of the stock. The main nematodes that affect the small ruminants and of greater economic importance for the exploitation of sheep are: Haemonchus contortus and Trichostrongylus axei, both located in the abomasum; Trichostrongylus colubriformis, Strongyloides papillousus, Cooperia sp. and Bunostomum trigonocephalum, in the small intestine and Oesophagostomum columbianum, Trichuris ovis, T. globulosa and Skrjabinema sp., in the large intestine. Morphophysiological characteristics of forage plants such as foliar structure, habit of growth and green mass production, associated to climatic factors, may be factors that influence the permanence of the different stages of free life of the gastrointestinal nematodes in the environment, pastures that do not provide lightning in the lower stratum of the clumps and soils, provide shading and humidity and may potentiate the reinfection of the animals.

Значение финансово-экономических, геоклиматических и технологических факторов для здравоохранения

Значение финансово-экономических, геоклиматических и технологических факторов для здравоохранения

Variation in seed and seedling traits and their relations to geo-climatic factors among populations in Yunnan Pine (Pinus yunnanensis)

Differences in seed germination and seedling growth among populations of Pinus yunnanensis Franch. were quantified to provide information for use in the regeneration, reforestation, and improvement of this species. Seed germination and seedling growth traits at the nursery stage were investigated at the population level. We evaluated relationships between pairs of measured traits as well as the association between measured traits and geo-climatic variables including longitude, latitude, elevation, temperature and precipitation. Seedling growth showed significant differences although a low magnitude of variation was found in the seed germination traits among the populations. Some populations with strong and stable growth (e.g., the Baoshan population) may be selected as superior seed sources for regeneration and reforestation. Germination percentage was negatively correlated with elevation, and positively with precipitation. In addition, germination index, vigor index and seedling height were positively correlated with precipitation. Seed germination index, cotyledon number and length, and seedling diameter were significantly and positively correlated with seed weight. Strong correlations between pairs of traits will be helpful in early evaluations for the selection of certain prominent traits.

Disentangling the effects of land use and geo-climatic factors on diversity in European freshwater ecosystems

Land use effects are considered among the main stressors on freshwater biodiversity, with up to 80% of land in Europe under intensive use. Here, we address the impact of arable and urban landscapes on taxon richness, Shannon–Wiener diversity, taxon rareness and taxonomic distinctness of eleven organism groups encompassing vertebrates, invertebrates and plants, occurring in five freshwater ecosystem types across Europe: rivers, floodplains, lakes, ponds and groundwater. In addition, nine geo-climatic descriptors (e.g. latitude, longitude, precipitation) were used to disentangle land use effects from those of natural drivers of biodiversity. Using a variance partitioning scheme based on boosted regression trees and generalised linear regression modelling, we sought: (i) to partition the unique, shared and unexplained variation in the metrics explained by both groups of descriptor variables, (ii) to quantify the contribution of each descriptor variable to biodiversity variation in the most parsimonious regression model and (iii) to identify interactions of land use and natural descriptors. The variation in biodiversity uniquely described by land use was consistently low across both ecosystem types and organism groups. In contrast, geo-climatic descriptors uniquely, and jointly with land use, explained significantly more variance in all 39 biodiversity metrics tested. Regression models revealed significant interactions between geo-climatic descriptors and land use for a third of the models, with interactions accounting for up to 17% of the model's deviance. However, no consistent patterns were observed related to the type of biodiversity metric and organism group considered. Subdividing data according to the strongest geo-climatic gradient in each dataset aimed to reduce the strength of natural descriptors relative to land use. Although data sub-setting can highlight land use effects on freshwater biodiversity, sub-setting our data often failed to produce stronger land use effects. There was no increase in spatial congruence in the subsets, suggesting that the observed land use effects were not dependent on the spatial extent of the subsets. Our results confirm significant joint effects of, and interactions between, land use and natural environmental descriptors on freshwater biodiversity, across ecosystem types and organism groups. This has implications for biodiversity monitoring. First, the combined analysis of anthropogenic and natural descriptors is a prerequisite for the analysis of human threats to biodiversity. Second, geo-climatically, but not necessarily geographically more homogeneous datasets can help unmask the role of anthropogenic descriptors. And third, whole community-based biodiversity metrics (including taxon richness) are not ideal indicators of anthropogenic effects on biodiversity at broad scales.

Effects of Geoclimatic Factors on Soil Water, Nitrogen, and Foliar Properties of Douglas-Fir Plantations in the Pacific Northwest

Soil water and nitrogen (N) availability drive Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) growth and productivity in the Pacific Northwest, but the methods for accurate assessment and modeling of soil water and N availability are not well developed. The objectives of this study were to identify geoclimatic factors that effectively predict soil water content, N availability, and foliar properties and correlate these factors with productivity of 71 Douglas-fir plantations in Oregon, Washington, and British Columbia. Boosted regression tree models were used to compare the performance of both mapped and field-measured variables, as well as various combinations of variables from these two general sources, while allowing for nonlinear relationships. Linear relationships between predictor and site productivity variables were tested using Pearson correlations. Fine, deep soils had the highest summer volumetric soil water content and contained high total soil N. Forest floor carbon/nitrogen (C/N) ratios were highly related to plant-available N, presumably due to climatic limitations on decomposition. Foliar N concentration was associated with plant-available N variables, whereas needle area was related to factors describing soil water-holding capacity. Douglas-fir site productivity and fertilizer response were related to the measured soil and foliar variables but were most strongly related to surface soil and forest floor C/N ratios.

An Evaluation of Industrial Facilities Defects in Selected Industrial Estates in Lagos State, Nigeria

The study appraised the state of industrial facilities in selected industrial estates established between 1957 and 1981 in Lagos State by examining the nature and causes of facilities’ defects in the selected industrial estates. The buildings sampled were load bearing sandcrete block wall (1%), concrete framed structure (83%) and steel framed structure (16%). Data were sourced using structured questionnaire administered on the staff of maintenance department of 35 building materials and plastic manufacturing industries purposively selected and located in 18 industrial estates. Data obtained were analyzed using descriptive statistic. The study found the structural elements of the buildings, i.e. foundations, beams, walls, and floors satisfactory. Using the mean response analysis, the result showed that the most severe factors responsible for industrial facilities’ defects were combined effects of geo-climatic factors (2.35), combined effects of biological agencies (2.15), corrosion (1.98), and physical aggression on the facilities (1.71).