Parameters and equations of winter-chilling models [53] used to simulate the timing of dormancy break, budbreak and flowering.

<p>Daily chilling and forcing states calculated from daily mean temperature (T_mean) and curve shape parameters a = 0.005 and c = 2.8. The same forcing equation applies to budbreak and flowering. The critical forcing state at which budburst occurs is calculated from the chilling state and curve shape parameters: co1 = 176 and co2 = 0.015.</p

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions

<div><p>The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.</p></div

Changes in cumulative growing season GDD (1^st April to 31^st October) calculated from baseline (1960–90) weather generator runs, daily historic weather data (1960–2011) and future climate weather generator runs using three emissions scenarios (low, middle and high emissions from left to right) and time periods.

<p>Baseline quantile box plots calculated from 9,000 30-year time sequences; future box plots from 1,000 30-year time sequences.</p

Mean budbreak and flowering times under different climate conditions using two types of phenology model: (i) spring warming budbreak and flowering models [58, 60, 62], and (ii) winter chilling (vernalization) models [53].

<p>Mean budbreak and flowering times under different climate conditions using two types of phenology model: (i) spring warming budbreak and flowering models [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141218#pone.0141218.ref058" target="_blank">58</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141218#pone.0141218.ref060" target="_blank">60</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141218#pone.0141218.ref062" target="_blank">62</a>], and (ii) winter chilling (vernalization) models [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141218#pone.0141218.ref053" target="_blank">53</a>].</p

Risk profiles of adverse flowering weather (defined as 10 or more of the 14 days after flowering with daily mean temperatures <15°C or >5mm precipitation) under baseline (blue) and three future time periods (green 2010–39, purple 2040–69, red 2070–89) for low, medium and high emissions scenarios (from left to right).

<p>Dotted lines indicate the mean budbreak date, calculated using a spring warming models [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141218#pone.0141218.ref060" target="_blank">60</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141218#pone.0141218.ref062" target="_blank">62</a>], and the corresponding risk of adverse flowering weather under each scenario and time period.</p

Mean seasonal growing degree days, measures of late frost risk and of adverse flowering weather under different climate scenarios.

<p>Late frost risk expressed as (i) probability of a frost day (minimum temperature < = 0°C) after budbreak; (ii) mean number of these frost days, and (iii) mean accumulated degree days under 2°C after budbreak. Adverse flowering weather defined as a mean daily temperature <15°C or total precipitation>5mm and expressed as (i) the probability of 10 or more adverse days during the 7 days before and after flowering, and (ii) mean number of adverse days during the same 15 day period. The timing of budbreak and flowering calculated using spring warming models.</p

Parameters & forcing equation for spring warming models [58, 60, 62] used to simulate the timing of budbreak, flowering and veraison.

<p>The same forcing equation, using different starting times and base temperatures and where <i>T</i>_<i>mean</i> is the mean temperature of day <i>t</i>, applies to all three phenophases.</p

Modelled times of budbreak, flowering and veraison (from bottom to top) calculated from baseline (1960–90) weather generator runs, daily observed weather (1960–2011) and future climate weather generator runs using three emissions scenarios (low, middle and high emissions from left to right) and time periods.

<p>Modelled times of budbreak, flowering and veraison (from bottom to top) calculated from baseline (1960–90) weather generator runs, daily observed weather (1960–2011) and future climate weather generator runs using three emissions scenarios (low, middle and high emissions from left to right) and time periods.</p

Ethylene Transposition: Ruthenium Hydride Catalyzed Intramolecular <i>trans</i>-Silylvinylation of Internal Alkynes

A highly selective intramolecular <i>trans</i>-silylvinylation of internal alkynes catalyzed by RuHCl­(CO)­(SIMes)­(PPh₃) has been accomplished. The use of methyl vinyl ketone as an additive increased the efficiency of this transformation. This process was used to successfully form five-, six-, and seven-membered oxasilacycles by a formal anti-exo-dig cyclization

Signals of Climate Change in Butterfly Communities in a Mediterranean Protected Area

<div><p>The European protected-area network will cease to be efficient for biodiversity conservation, particularly in the Mediterranean region, if species are driven out of protected areas by climate warming. Yet, no empirical evidence of how climate change influences ecological communities in Mediterranean nature reserves really exists. Here, we examine long-term (1998–2011/2012) and short-term (2011–2012) changes in the butterfly fauna of Dadia National Park (Greece) by revisiting 21 and 18 transects in 2011 and 2012 respectively, that were initially surveyed in 1998. We evaluate the temperature trend for the study area for a 22-year-period (1990–2012) in which all three butterfly surveys are included. We also assess changes in community composition and species richness in butterfly communities using information on (a) species’ elevational distributions in Greece and (b) Community Temperature Index (calculated from the average temperature of species' geographical ranges in Europe, weighted by species' abundance per transect and year). Despite the protected status of Dadia NP and the subsequent stability of land use regimes, we found a marked change in butterfly community composition over a 13 year period, concomitant with an increase of annual average temperature of 0.95°C. Our analysis gave no evidence of significant year-to-year (2011–2012) variability in butterfly community composition, suggesting that the community composition change we recorded is likely the consequence of long-term environmental change, such as climate warming. We observe an increased abundance of low-elevation species whereas species mainly occurring at higher elevations in the region declined. The Community Temperature Index was found to increase in all habitats except agricultural areas. If equivalent changes occur in other protected areas and taxonomic groups across Mediterranean Europe, new conservation options and approaches for increasing species’ resilience may have to be devised.</p></div