Influence of climatic variables on crown condition in pine forests of Northern Spain

Producción CientíficaThe aim of this study was to find relationships between crown condition and some climatic parameters to identify which are those having a main influence on crown condition, and how this influence is shown in the tree (crown transparency), and to contribute to the understanding of how these parameters will affect under future climate change scenarios

How perilous are broad-scale correlations with environmental variables?

Many studies correlate geographic variation of biotic variables (e.g., species ranges, species richness, etc.) with variation in environmental variables (climate, topography, history). Often, the resulting correlations are interpreted as evidence of causal links. However, both the dependent and independent variables in these analyses are strongly spatially structured. Several studies have suggested that spatially structured variables may be significantly correlated with one another despite the absence of a causal link between them. In this study we ask: if two variables are spatially structured, but causally unrelated, how strong is the expected correlation between them? As a specific example, we consider the correlations between broad-scale variation in gamma species richness and climatic variables. Are these correlations likely to be statistical artefacts? To answer these questions, we randomly generated pseudo-climatic variables that have the same range and spatial autocorrelation as temperature and precipitation in the Americas. We related mammal and bird species richness both to the real and the pseudo-climatic variables. We also observed the correlations among pseudo-climate simulations. Correlations among randomly generated, spatially unstructured, variables are very small. In contrast, the median correlations between spatially structured variables are near r2=0.1 – 0.3, and the 95% confidence limits extend to r2=0.6 – 0.7. Viewing this as a null expectation, given spatially structured variables, it is worth nothing that published richness–climate correlations are typically marginally stronger than these values. However, many other published richness–environment correlations would fail this test. Tests of the “predictive ability” of a correlation cannot reliably distinguish correlations due to spatial structure from causal relationships. Our results suggest a three-part update of Tobler’s “First Law of Geography”: #1) Everything in geography that is spatially structured will be collinear. #2) Near things are more related than distant things. #3) The more strongly spatially structured two variables are, the stronger the collinearity between them will be

Effect of climate and geography on worldwide fine resolution economic activity

Geography, including climatic factors, have long been considered potentially important elements in shaping socio-economic activities, alongside other determinants, such as institutions. Here we demonstrate that geography and climate variables satisfactorily explain the worldwide economic activity as measured by the per capita Gross Cell Product (GCP-PC) at a fine geographical resolution, typically much higher than country average. A 1° by 1° GCPPC dataset has been key for establishing and testing a direct relationship between 'local' geography/climate and GCP-PC. Not only have we tested the geography and climate hypothesis using many possible explanatory variables, importantly we have also predicted and reconstructed GCP-PC worldwide by retaining the most significant predictors. While this study confirms that latitude is the most important predictor for GCP-PC when taken in isolation, the accuracy of the GCP-PC prediction is greatly improved when other factors mainly related to variations in climatic variables, rather than average climatic conditions as typically used, are considered. However, latitude diminishes in importance when only the wealthier parts of the globe are considered. This work points to specific features of the climate system which explain economic activity, such as the variability in air pressure. Implications of these findings range from an improved understanding of why socio-economically better-off societies are geographically placed where they are in the present, past and future to informing where new economic activities could be established in order to yield favourable economic outcomes based on geography and climate conditions

New results on the influence of climate on the distribution of population and economic activity

This paper applies G-Econ+, an updated version of the G-Econ database by Nordhaus, to analyze the influence of climatic and geographic factors on the geographic distribution of population and economic activity. I discuss options for improved treatment of several statistical problems associated with G-Econ, which are not addressed adequately in the original G-Econ analysis. Reanalysis of key results from the original G-Econ analysis corrects some surprising results therein. Extensive sensitivity analysis determines the robustness of the relationship between climatic factors and economic activity across alternative central estimators. Further analysis assesses revealed climatic preferences of population, the effects of climate parameters on different quantiles of economic variables, and synergies between temperature and precipitation. I find that population density has a much stronger influence on output density than output per capita. Furthermore, least developed countries are located in a climatic zone where all indicators of economic activity decline with increasing temperature.Climate; macroeconomics; population; cross-sectional analysis; G-Econ

A REVIEW AND EVALUATION OF WEATHER-CROP YIELD MODELS

The purpose of this paper is the relatively limited one of reviewing the literature for models which develop specific relationships between climatic variables and crop yields. Following a review of recent weather-crop yield modeling efforts we evaluate these models and suggest some conceptual models and data base improvements if we are to adequately project the impacts on crop production of expected future climatic change. Our review and evaluation centers on weather-crop yield models applicable to the central grain belt of the U.S., mainly the Corn Belt and Great Plains production regions.Crop Production/Industries,

Hydrological controls on river network connectivity

This study proposes a probabilistic approach for the quantitative assessment of reach- and network-scale hydrological connectivity as dictated by river flow space–time variability. Spatial dynamics of daily streamflows are estimated based on climatic and morphological features of the contributing catchment, integrating a physically based approach that accounts for the stochasticity of rainfall with a water balance framework and a geomorphic recession flow analysis. Ecologically meaningful minimum stage thresholds are used to evaluate the connectivity of individual stream reaches, and other relevant network-scale connectivity metrics. The framework allows a quantitative description of the main hydrological causes and the ecological consequences of water depth dynamics experienced by river networks. The analysis shows that the spatial variability of local-scale hydrological connectivity is strongly affected by the spatial and temporal distribution of climatic variables. Depending on the underlying climatic settings and the critical stage threshold, loss of connectivity can be observed in the headwaters or along the main channel, thereby originating a fragmented river network. The proposed approach provides important clues for understanding the effect of climate on the ecological function of river corridors

A review of potential physical impacts on harbours in the Mediterranean Sea under climate change

The final publication is available at Springer via http://dx.doi.org/10.1007/s10113-016-0972-9The potential impact of climate change on port operations and infrastructures has received much less attention than the corresponding impact for beach systems. However, ports have always been vulnerable to weather extremes and climate change could enhance such occurrences at timescales comparable to the design lifetime of harbour engineering structures. The analysis in this paper starts with the main climatic variables affecting harbour engineering and exploitation. It continues with a review of the available projections for such variables first at global scale and then at a regional scale (Catalan coast in the western Mediterranean) as a study case for similar environments in the planet. The detailed assessment of impacts starts from downscaled projections for mean sea level and wave storms (wind not considered in the paper). This is followed by an analysis of the port operations and infrastructure performance that are relevant from a climate perspective. The key climatic factors here considered are relative sea level, wave storm features (height, period, direction and duration) and their combined effect, which is expected to produce the highest impacts. The paper ends with a discussion and some examples of analyses aiming at port adaptation to future climate change.Peer ReviewedPostprint (author's final draft

Nature Relation Between Climatic Variables and Cotton Production

This study investigated the effect of climatic variables on flower and boll production and retention in cotton (Gossypium barbadense). Also, this study investigated the relationship between climatic factors and production of flowers and bolls obtained during the development periods of the flowering and boll stage, and to determine the most representative period corresponding to the overall crop pattern. Evaporation, sunshine duration, relative humidity, surface soil temperature at 1800 h, and maximum air temperature, are the important climatic factors that significantly affect flower and boll production. The least important variables were found to be surface soil temperature at 0600 h and minimum temperature. There was a negative correlation between flower and boll production and either evaporation or sunshine duration, while that correlation with minimum relative humidity was positive. Higher minimum relative humidity, short period of sunshine duration, and low temperatures enhanced flower and boll formation

Activity schedule and foraging in Protopolybia sedula (Hymenoptera, Vespidae)

Protopolybia sedula is a social swarming wasp, widely spread throughout many countries in the Americas, including most of Brazil. Despite its distribution, studies of its behavioral ecology are scarce. This study aimed to describe its foraging activity and relation to climatic variables in the city of Juiz de Fora in southeastern Brazil. Three colonies were under observation between 07:00 and 18:00 during April 2012, January 2013, and March 2013. Every 30 minutes, the number of foragers leaving and returning to the colony was registered along with air temperature and relative humidity. Activity began around 07:30¸ increased between 10:30 and 14:30, and ended around 18:30. A mean of 52.7 exits and 54 returns were measured every 30 minutes. The daily mean values were 1,107 ± 510.6 exits and 1,135 ± 854.8 returns. Only one colony showed a significant correlation between forager exits and temperature (rs = 0.8055; P \u3c 0.0001) and between exits and relative humidity (rs = -0.7441; P = 0.0001). This paper shows that climatic variables are likely to have little control on the foraging rhythm of P. sedula when compared to other species, suggesting the interaction of other external and internal factors as stimuli of species foraging behavio

Possible Impacts of Climate Change on Mediterranean Irrigated Farming Systems

In the agricultural sector, climate change (CC) affects multiple weather variables at different stages of crop cycles. CC may influence the mean level or affect the distribution of events (e.g., rainfall, temperature). This work evaluates the economic impact of CC-related changes in multiple climatic components, and the resulting uncertainty. For this purpose, a three-stage discrete stochastic programming model is used to represents farm sector of an irrigated area of Italy and to examine the influence of CC on rainfall and on maximum temperature. These variables affect the availability of water for agriculture and the water requirements of irrigated crops. The states of nature, and their change, are defined more broadly than in previous analyses; this allows examining the changes of more climatic variables and crops cultivation. The effect of CC is obtained by comparing the results of scenarios that represent the climatic conditions in the current situation and in the future. The results show that the agricultural sector would seek to lower costs by modifying patterns of land use, farming practices and increasing the use groundwater. The overall economic impact of these changes is small and due primarily to the reduced availability of water in the future. The temperature increase is, in fact, largely offset by the effects of the increase in CO2 levels, which boosts the yield of main crops of the irrigated zone. Therefore, availability and water management becomes a crucial factor to offset the increase of evapotranspiration and of water stress resulting from the increase of temperature. However, the costs of CC are very high for some types of farming, which suffer a large reduction in income.discrete stochastic programming model, climate change, water availability, irrigation requirements, Farm Management, Resource /Energy Economics and Policy,