Forest microclimates and climate change: importance, drivers and future research agenda

Forest microclimates contrast strongly with the climate outside forests. To fully understand and better predict how forests' biodiversity and functions relate to climate and climate change, microclimates need to be integrated into ecological research. Despite the potentially broad impact of microclimates on the response of forest ecosystems to global change, our understanding of how microclimates within and below tree canopies modulate biotic responses to global change at the species, community and ecosystem level is still limited. Here, we review how spatial and temporal variation in forest microclimates result from an interplay of forest features, local water balance, topography and landscape composition. We first stress and exemplify the importance of considering forest microclimates to understand variation in biodiversity and ecosystem functions across forest landscapes. Next, we explain how macroclimate warming (of the free atmosphere) can affect microclimates, and vice versa, via interactions with land-use changes across different biomes. Finally, we perform a priority ranking of future research avenues at the interface of microclimate ecology and global change biology, with a specific focus on three key themes: (1) disentangling the abiotic and biotic drivers and feedbacks of forest microclimates; (2) global and regional mapping and predictions of forest microclimates; and (3) the impacts of microclimate on forest biodiversity and ecosystem functioning in the face of climate change. The availability of microclimatic data will significantly increase in the coming decades, characterizing climate variability at unprecedented spatial and temporal scales relevant to biological processes in forests. This will revolutionize our understanding of the dynamics, drivers and implications of forest microclimates on biodiversity and ecological functions, and the impacts of global changes. In order to support the sustainable use of forests and to secure their biodiversity and ecosystem services for future generations, microclimates cannot be ignored.Peer reviewe

Acute and Chronic Effects of Particles on Hospital Admissions in New-England

Background: Many studies have reported significant associations between exposure to $PM_{2.5}$ and hospital admissions, but all have focused on the effects of short-term exposure. In addition all these studies have relied on a limited number of $PM_{2.5}$ monitors in their study regions, which introduces exposure error, and excludes rural and suburban populations from locations in which monitors are not available, reducing generalizability and potentially creating selection bias. Methods Using our novel prediction models for exposure combining land use regression with physical measurements (satellite aerosol optical depth) we investigated both the long and short term effects of $PM_{2.5}$ exposures on hospital admissions across New-England for all residents aged 65 and older. We performed separate Poisson regression analysis for each admission type: all respiratory, cardiovascular disease (CVD), stroke and diabetes. Daily admission counts in each zip code were regressed against long and short-term $PM_{2.5}$ exposure, temperature, socio-economic data and a spline of time to control for seasonal trends in baseline risk. Results: We observed associations between both short-term and long-term exposure to $PM_{2.5}$ and hospitalization for all of the outcomes examined. In example, for respiratory diseases, for every10-µg/m$^3$ increase in short-term $PM_{2.5}$ exposure there is a 0.70 percent increase in admissions (CI = 0.35 to 0.52) while concurrently for every10-µg/m$^3$ increase in long-term $PM_{2.5}$ exposure there is a 4.22 percent increase in admissions (CI = 1.06 to 4.75). Conclusions: As with mortality studies, chronic exposure to particles is associated with substantially larger increases in hospital admissions than acute exposure and both can be detected simultaneously using our exposure models

Estimating PM 2.5 concentrations in Xi'an City using a generalized additive model with multi-source monitoring data

© 2015 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi'an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5

Effecten ontwerp Klimaatakkoord.

FdR – Publicaties niet-programma gebonde

Constraints on the presence of post-perovskite in Earth's lowermost mantle from tomographic-geodynamic model comparisons

Lower mantle tomography models consistently feature an increase in the ratio of shear-wave velocity (VS) to compressional-wave velocity (VP) variations and a negative correlation between shear-wave and bulk-sound velocity (VC) variations. These seismic characteristics, also observed in the recent SP12RTS model, have been interpreted to be indicative of large-scale chemical variations. Other explanations, such as the lower mantle post-perovskite (pPv) phase, which would not require chemical heterogeneity, have been explored less. Constraining the origin of these seismic features is important, as geodynamic simulations predict a fundamentally different style of mantle convection under both scenarios. Here, we investigate to what extent the presence of pPv explains the observed high VS/VP ratios and negative VS–VC correlation globally. We compare the statistical properties of SP12RTS with the statistics of synthetic tomography models, derived from both thermal and thermochemical models of 3-D global mantle convection. We convert the temperature fields of these models into seismic velocity structures using mineral physics lookup tables with and without pPv. We account for the limited tomographic resolution of SP12RTS using its resolution operator for both VS and VP structures. This allows for direct comparisons of the resulting velocity ratios and correlations. Although the tomographic filtering significantly affects the synthetic tomography images, we demonstrate that the effect of pPv remains evident in the ratios and correlations of seismic velocities. We find that lateral variations in the presence of pPv have a dominant influence on the VS/VP ratio and VS–VC correlation, which are thus unsuitable measures to constrain the presence of large-scale chemical variations in the lowermost mantle. To explain the decrease in the VS/VP ratio of SP12RTS close to the CMB, our results favour a pPv-bearing CMB region, which has implications for the stability field of pPv in the Earth's mantle

Constraints on the presence of post-perovskite in Earth's lowermost mantle from tomographic-geodynamic model comparisons

Lower mantle tomography models consistently feature an increase in the ratio of shear-wave velocity (VS) to compressional-wave velocity (VP) variations and a negative correlation between shear-wave and bulk-sound velocity (VC) variations. These seismic characteristics, also observed in the recent SP12RTS model, have been interpreted to be indicative of large-scale chemical variations. Other explanations, such as the lower mantle post-perovskite (pPv) phase, which would not require chemical heterogeneity, have been explored less. Constraining the origin of these seismic features is important, as geodynamic simulations predict a fundamentally different style of mantle convection under both scenarios. Here, we investigate to what extent the presence of pPv explains the observed high VS/VP ratios and negative VS–VC correlation globally. We compare the statistical properties of SP12RTS with the statistics of synthetic tomography models, derived from both thermal and thermochemical models of 3-D global mantle convection. We convert the temperature fields of these models into seismic velocity structures using mineral physics lookup tables with and without pPv. We account for the limited tomographic resolution of SP12RTS using its resolution operator for both VS and VP structures. This allows for direct comparisons of the resulting velocity ratios and correlations. Although the tomographic filtering significantly affects the synthetic tomography images, we demonstrate that the effect of pPv remains evident in the ratios and correlations of seismic velocities. We find that lateral variations in the presence of pPv have a dominant influence on the VS/VP ratio and VS–VC correlation, which are thus unsuitable measures to constrain the presence of large-scale chemical variations in the lowermost mantle. To explain the decrease in the VS/VP ratio of SP12RTS close to the CMB, our results favour a pPv-bearing CMB region, which has implications for the stability field of pPv in the Earth's mantle

Probing Composition and Molecular Mobility in Thin Spherical Films Using Nuclear Magnetic Resonance Measurements of Diffusion

The composition and molecular mobility within thin spherical liquid films have been investigated using nuclear magnetic resonance (NMR) diffusion measurements. These films were formed either on the surface of pores inside a sponge at low saturation or by adsorbed water on the outside of urea prills during caking. Using pulsed field gradient (PFG) NMR experiments, the molecular mobility within these liquid films was determined through analysis of the conditional probability density for displacement (propagator). Molecular diffusion coefficients were determined for films in the sponge and prill systems by fitting the experimental propagators using a model for diffusion on an array of isotropically distributed infinite planes. By comparing these diffusion coefficients with bulk diffusion coefficients for a range of concentrations of urea solutions (2.1 M, 6.2 M and saturated), it was possible to optimize the PFG experimental parameters to enable accurate determination of molecular diffusion in these spherical liquid films. Determination of the diffusion coefficients for a range of urea solutions in the sponge enabled identification of the composition of the film that formed on the surface of the urea prills. Analysis of these data showed that the liquid layers are composed of saturated urea solution covering the surface of the prills, with an estimated layer thickness on the order of 10–5 m. The shape of the propagators indicated the adsorbed water was uniformly distributed over the surface of the urea prills, rather than primarily in the meniscus between particles, which agrees with dye visualization experiments on a pair of urea prills during caking. This work provides the first quantitative measurements of diffusion in thin spherical films, which is a key parameter for determining what controls the presence and rate of bonding between adjacent particle surfaces