The role of fires for tundra-forest transition in northwest Siberia

<p>Transition of arctic vegetation from tundra to shrubs and forest is an important process influencing global carbon budget. Transition is predicted due to warming and prolongation of the growing season but observations show that it is slower than expected. Fires are disturbances that could trigger a shift of biomes.</p><p>We studied the transition of dry tundra to forest and woodland in northwest Siberia for burned and background sites within the time interval of 60 years. We used meteorological data to estimate potential shifts in vegetation based on a bioclimatic model. To investigate fire and vegetation dynamics, we used historical and modern satellite imagery (Corona KH-4b, Landsat-5,7,8, Resurs-P, SPOT-6,7). We performed comparative analysis of vegetation using high-resolution satellite data from different years.</p><p>The growing season length increased by 20 days and the mean temperature of the growing season increased by 1°C making climatic conditions suitable for trees. We showed that ca 40% of the total study area experienced fires at least once during the last 60 years. Within this period, shift from dry tundra to tree-dominated vegetation occurred in 6-15% of the area in the non-disturbed sites compared to 40-85% of the area in the burned sites.</p>

Potential Range of Bulbocodium versicolor (Ker-Gawl.) Spreng. (Colchicaceae, Liliopsida) in Russia

The article presents a bioclimatic model of the potential range of Bulbocodium versicolor in European Russia. To build the model, we analyzed a matrix containing 166 B. versicolor localities in the studied region; the analysis was carried out in the SDMtoolbox program using the climatic paramaters from the WorldClim open database. The model demonstrates that, given the available dataset on the modern climatic conditions, B. versicolor may occur in a wider geographical range comprising, at the very least, the Belgorod, Voronezh, Volgograd, Lipetsk, Penza, Rostov and Saratov provinces. Also, within European Russia, the most favorable conditions for B. versicolor are found in most of the Voronezh and Volgograd provinces as well as in some areas of the Right Bank and Left Bank of the Volga River adjacent to the Volga Upland (in the Saratov province). The maximum occurrence probability is 70–100% while the average occurrence probability is 40– 60%. The maximum contribution to the model is made by the precipitation of the warmest and most humid quarter (June–August); a smaller contribution is made by the average temperature of the coldest (December–February) and warmest (June – August) quarters as well as by the average annual precipitation. The least contribution is made by the precipitation of the most humid month (July) and the driest quarter (March–May). Finally, we conclude that bioclimatic model facilitates a better understanding of the geographical distribution of the species in question.

TERMAL COMFORT IN THE CITY OF BIJELJINA, FOR THE PERIOD 2009 – 2018 DEFINED BY WGBT

In paper are presented results of bioclimatic model Wet bulbe globe temperature (WBGT) for the area ofthe city of Bijeljina, for the period of 10 years, from 2009 to 2018. The city is located in the north eastpart of Bosnia and Herzegovina and has a moderate continental climate. Results were obtained bycalculation of meteorological data in software program Biklima 2.6. They show the presence of all fivevalues defined with the WBGT index. Results differ in during the year, and seasons and have differentnumber of days with the Unlimited (<18) being the most common value and Activity should be stopped(>30) the least presence. Some years have the high number of high values (over 30) and present apotential danger for a human organism if exposed to physical activities. Number of consecutive days withhigh value rises and presents danger for human organism.

Empirical Model of Thermal Comfort for Medium-Sized Cities in Subtropical Climate

The present study sought to elaborate an empirical model of thermal comfort for medium-sized cities in subtropical climate, based on a cross-sectional survey in the city of Santa Maria, state of Rio Grande do Sul, Brazil. The research was based on the collection of meteorological, subjective and individual data collected simultaneously in August 2015, January and July 2016, which were submitted to multiple linear regression for the elaboration of the Bioclimatic Model for Subtropical Medium-Sized Cities (MBCMS). The proposed model was validated through a normality test, obtained by the measure of obliquity and kurtosis of the distribution, heteroscedasticity and covariance, as well as by the comparison between already traditional models in the literature, such as PET, SET and PMV, which were calibrated to the study area, and the results observed for MBCMS. The results presented high multiple R-squared and adjusted R-squared, 0.928 and 0.925, respectively, for the proposed model, as well as an F-statistic of 447.6. In the validation, the MBCMS presented R equal to 0.83 and an accuracy score 60% more efficient than the PET, SET and PMV indexes.

Monitoring canopy and air temperature of dominant vegetation in tropical semi-arid using bioclimatic model

Typical vegetation of arid environments consists of few dominant species highly threatened by climate change. Jurema preta (Mimosa tenuiflora (Willd.) Poiret) is one of these successful species that now is dominant in extensive semiarid areas in the world. The development of a simple bioclimatic model using climate change scenarios based on optimistic and pessimistic predictions of the Intergovernmental Panel on Climate Change (IPCC) shown as a simple tool to predict possible responses of dominant species under dry land conditions and low functional biodiversity. The simple bioclimatic model proved satisfactory in creating climate change scenarios and impacts on the canopy temperature of Jurema preta in semiarid Brazil. The bioclimatic model was efficient to obtain spatially relevant estimations of air temperature from determinations of the surface temperature using satellite images. The model determined that the average difference of 5oC between the air temperature and the leaf temperature for Jurema preta, and an increase of 3oC in air temperature, promote an increase of 2oC in leaf temperature. It leads to disturbances in vital physiological mechanisms in the leaf, mainly the photosynthesis and efficient use of water.

Predicting global geographical distribution of Lolium rigidum (rigid ryegrass) under climate change

SUMMARYLolium rigidum L. (rigid ryegrass) is one of the most extensive and harmful weeds in winter cereal crops. A bioclimatic model for this species was developed using CLIMEX. The model was validated with records from North America and Oceania and used to assess the global potential distribution of L. rigidum under the current climate and under two climate change scenarios. Both scenarios represent contrasting temporal patterns of economic development and carbon dioxide (CO2) emissions. The projections under current climatic conditions indicated that L. rigidum does not occupy the full extent of the climatically suitable area available to it. Under future climate scenarios, the suitable potential area increases by 3·79% in the low-emission CO2 scenario and by 5·06% under the most extreme scenario. The model's projection showed an increase in potentially suitable areas in North America, Europe, South America and Asia; while in Africa and Oceania it indicated regression. These results provide the necessary knowledge for identifying and highlighting the potential invasion risk areas and for establishing the grounds on which to base the planning and management measures required.

The Influence of Abiotic Factors on an Invasive Pest of Pulse Crops,Sitona lineatus(L.) (Coleoptera: Curculionidae), in North America

Pea leaf weevil,Sitona lineatus(L.), native to Europe and North Africa, has been introduced into many other countries around the world, including the USA and Canada. Adults are oligophagous pests on leguminaceous plants.Sitona lineatuswas first recorded in Canada in 1997, near Lethbridge, Alberta. Since then, it has spread north in Alberta and west into Saskatchewan in 2007. Bioclimatic simulation models were used to predict the distribution and extent of establishment ofS. lineatusin Canada based on its current geographic range, phenology, relative abundance, and empirical data. The study identified areas in Canada that are at risk for future establishment ofS. lineatusand developed a better understanding of climate effects. Climate change projections (General Circulation Models) were then imposed on the bioclimatic model ofS. lineatus. Bioclimatic model output varied for each of the three General Circulation Models. In terms of suitability for pest establishment (Ecoclimatic Index), the NCAR273 CCSM climate data resulted in the most significant shift northward.

A bioclimatic model for forecasting olive yield

SUMMARYThe aim of the present study was to develop a hierarchical bioclimatic model for forecasting olive crop yields in the Alentejo region of south-eastern Portugal. The model was estimated for three different developmental stages: (1) at flowering, using only the regional pollen index (RPI); (2) at fruit growth using RPI and a plant water requirements index (PWRI) and (3) at fruit maturing using RPI plus a water requirements index plus a phytopathological index (PPI). Olive airborne pollen was sampled from 1999 to 2007, using a Cour trap installed in Reguengos de Monsaraz. The meteorological parameters used in the calculation of the post-flowering indices corresponded to data from a meteorological station located near the airborne sampling point. At the flowering stage, 0·66 of the regional olive yield can be explained by the RPI with an average deviation between observed and predicted production of 0·15 for the forecast model internal validation and of 0·19 for the cross-validation. The addition of the variable PWRI to the forecasting model explained an additional 0·26 of the variation, while the PPI explained an additional 0·05. The final bioclimatic model, with all the three variables tested, explained 0·97 of the regional olive fruit yield being the average deviation between observed and predicted production of 0·04 for the internal validation of the model and of 0·07 for the external validation. The hierarchical nature of this bioclimatic model, along three different development stages, enabled the prediction to be updated as the growing season progressed.