Using species traits to guide conservation actions under climate change

Few assessments of species vulnerability to climate change used to inform conservation management consider the intrinsic traits that shape species’ capacity to respond to climate change. This omission is problematic as it may result in management actions that are not optimised for the long-term persistence of species as climates shift. We present a tool for explicitly linking data on plant species’ life history traits and range characteristics to appropriate management actions that maximise their capacity to respond to climate change. We deliberately target data on easily measured and widely available traits (e.g. dispersal syndrome, height, longevity) and range characteristics (e.g. range size, climatic/soil niche breadth), to allow for rapid comparison across many species. We test this framework on 1237 plants, categorising species on the basis of their potential climate change risk as related to four factors affecting their response capacity: reproduction, movement capability, abiotic niche specialisation and spatial coverage. Based on these four factors, species were allocated risk scores, and these were used to test the hypothesis that the current protection status under national legislation and related management actions capture species response capacity to climate change. Our results indicate that 20% of the plant species analysed (242 species) are likely to have a low capacity to respond to climate change based on the traits assessed, and are therefore at high risk. Of the 242 high risk species, only 10% (24 species) are currently listed for protection under conservation legislation. Importantly, many management plans for these listed species fail to address the capacity of species to respond to climate change with appropriate actions: 70% of approved management plans do not include crucial actions which may improve species’ ability to adapt to climate change. We illustrate how the use of easily attainable traits associated with ecological and evolutionary responses to changing environmental conditions can inform conservation actions for plant species globally.     

Regionalisation of population growth projections in coastal exposure analysis

Large-area coastal exposure and impact analysis has focussed on using sea-level rise (SLR) scenarios and has placed little emphasis on socioeconomic scenarios, while neglecting spatial variations of population dynamics. We use the Dynamic Interactive Vulnerability Assessment (DIVA) Framework to assess the population exposed to 1 in 100-year coastal flood events under different population scenarios, that are consistent with the shared socioeconomic pathways (SSPs); and different SLR scenarios, derived from the representative concentration pathways (RCPs); and analyse the effect of accounting for regionalised population dynamics on population exposure until 2100. In a reference approach, we use homogeneous population growth on national level. In the regionalisation approaches, we test existing spatially explicit projections that also account for urbanisation, coastal migration and urban sprawl. Our results show that projected global exposure in 2100 ranges from 100 million to 260 million, depending on the combination of SLR and population scenarios and method used for regionalising the population projections. The assessed exposure based on the regionalised approaches is higher than that derived from the reference approach by up to 60 million people (39%). Accounting for urbanisation and coastal migration leads to an increase in exposure, whereas considering urban sprawl leads to lower exposure. Differences between the reference and the regionalised approaches increase with higher SLR. The regionalised approaches show highest exposure under SSP5 over most of the twenty-first century, although total population in SSP5 is the second lowest overall. All methods project the largest absolute growth in exposure for Asia and relative growth for Africa.     

Real Data Assimilation Using the Local Ensemble Transform Kalman Filter (LETKF) System for a Global Non-hydrostatic NWP model on the Cubed-sphere

An ensemble data assimilation system using the 4-dimensional Local Ensemble Transform Kalman Filter is implemented to a global non-hydrostatic Numerical Weather Prediction model on the cubed-sphere. The ensemble data assimilation system is coupled to the Korea Institute of Atmospheric Prediction Systems Package for Observation Processing, for real observation data from diverse resources, including satellites. For computational efficiency in a parallel computing environment, we employ some advanced software engineering techniques in the handling of a large number of files. The ensemble data assimilation system is tested in a semi-operational mode, and its performance is verified using the Integrated Forecast System analysis from the European Centre for Medium-Range Weather Forecasts. It is found that the system can be stabilized effectively by additive inflation to account for sampling errors, especially when radiance satellite data are additionally used.     

Joint Impacts of SSTA in Tropical Pacific and Indian Oceans on Variations of the WPSH

Using the NCEP/NCAR reanalysis and HadISST sea surface temperature (SST) data, the joint effects of the tropical Indian Ocean and Pacific on variations of area of the summertime western Pacific subtropical high (WPSH) for period 1980–2016 are investigated. It is demonstrated that the central tropical Indian Ocean (CTI) and central equatorial Pacific (CEP) are two key oceanic regions that affect the summertime WPSH. During autumn and winter, warm SST anomalies (SSTAs) in CEP force the Walker circulation to change anomalously, resulting in divergence anomalies over the western Pacific and Maritime Continent (MC). Due to the Gill-type response, the abnormal anticyclonic circulation is generated over the western Pacific and South China Sea (SCS). In the subsequent spring, the warm SSTAs in CEP weaken, while the SST over CTI demonstrates a lagged response to Pacific SSTA. The warm CTISSTA and CEP-SSTA cooperate with the eastward propagation of cold Kelvin waves in the western Pacific, leading to the eastward shift of the abnormal divergence center that originally locates at the western Pacific and MC. The anticyclone forced by this divergence subsequently moves eastward, leading to the intensification of the negative vorticity there. Meanwhile, warm SSTA in CTI triggers eastward propagating Kelvin waves, which lead to easterly anomalies over the equatorial Indian Ocean and Indonesia, being favorable for maintenance and intensification of the anticyclone over the SCS and western Pacific. The monsoonal meridional–vertical circulation strengthens, which is favorable for the intensification of the WPSH. Using SSTA over the two key oceanic regions as predictors, a multiple regression model is successfully constructed for prediction of WPSH area. These results are useful for our better understanding the variation mechanisms of WPSH and better predicting summer climate in East Asia.     

Influence of the Boreal Summer Intraseasonal Oscillation on Extreme Temperature Events in the Northern Hemisphere

The impact of the boreal summer intraseasonal oscillation (BSISO) on extreme hot and cool events was investigated, by analyzing the observed and reanalysis data for the period from 1983 to 2012. It is found that the frequency of the extreme events in middle and high latitudes is significantly modulated by the BSISO convection in the tropics, with a 3–9-day lag. During phases 1 and 2 when the BSISO positive rainfall anomaly is primarily located over a northwest–southeast oriented belt extending from India to Maritime Continent and a negative rainfall anomaly appears in western North Pacific, the frequency of extreme hot events is 40% more than the frequency of non-extreme hot events. Most noticeable increase appears in midlatitude North Pacific (north of 40°N) and higher-latitude polar region.Two physical mechanisms are primarily responsible for the change of the extreme frequency. First, an upper-tropospheric Rossby wave train (due to the wave energy propagation) is generated in response to a negative heating anomaly over tropical western North Pacific in phases 1 and 2. This wave train consists of a strong high pressure anomaly center northeast of Japan, a weak low pressure anomaly center over Alaska, and a strong high pressure anomaly center over the western coast of United States. Easterly anomalies to the south of the two strong midlatitude high pressure centers weaken the climatological subtropical jet along 40°N, which is accompanied by anomalous subsidence and warming in North Pacific north of 40°N. Second, an enhanced monsoonal heating over South Asia and East Asia sets up a transverse monsoonal overturning circulation, with large-scale ascending (descending) anomalies over tropical Indian (Pacific) Ocean. Both the processes favor more frequent extreme hot events in higher-latitude Northern Hemisphere. An anomalous atmospheric general circulation model is used to confirm the tropical heating effect.     

Preface

Climate change is one of the most challenging issues faced by human beings. Although many remarkable achievements have been made in climate change research,there is still a tremendous amount of uncertainty in     

The Role of Planetary Boundary-Layer Parameterizations in the Air Quality of an Urban Area with Complex Topography

The effect of different planetary boundary-layer (PBL) parameterization schemes on the spatial distribution of atmospheric pollution over the complex topography of the greater Athens area is investigated. Four PBL schemes originally implemented in a numerical meteorological model and a fifth one simulating the urban effect are examined. Two different atmospheric conditions are analyzed; a typical summer and a typical winter pollution episode. The relative importance of chemical and physical processes of the pollution predictions is discussed using process analysis. It is revealed that, for primary pollutants, a local scheme seems more adequate to represent the maximum observed concentrations while, completely different in structure, a non-local scheme reproduces the mean observed values in the basin. Concerning secondary pollutants, peak concentration differences, due to the different PBL schemes, are smoothed out. Nevertheless, the PBL scheme selection shapes the horizontal and the vertical extension of maximum values. The non-local and semi non-local schemes are superior to the others, favouring strong vertical mixing and transport towards the surface. The stronger turbulence accommodated effectively by the semi non-local urban scheme enhances ozone production along the sea-breeze axis and preserves the high ozone concentrations during the nighttime hours in the urban core.     

Parameterization of Sheared Convective Entrainment in the First-Order Jump Model: Evaluation Through Large-Eddy Simulation

In this note, two different approaches are used to estimate the entrainment-flux to surface-flux ratio for a sheared convective boundary layer (CBL); both are derived under the framework of the first-order jump model (FOM). That suggested by Sun and Wang (SW approach) has the advantage that there is no empirical constant included, though the dynamics are described in an implicit manner. The second, which was proposed by Kim et al. and Pino et al. (KP approach), explicitly characterizes the dynamics of the sheared entrainment, but uncertainties are induced through the empirical constants. Their performances in parameterizing the CBL growth rate are compared and discussed, and a new value of the parameter A ₃ in the KP approach is suggested. Large-eddy simulation (LES) data are employed to test both approaches: simulations are conducted for the CBL growing under varying conditions of surface roughness, free-atmospheric stratification, and wind shear, and data used when the turbulence is in steady state. The predicted entrainment rates in each case are tested against the LES data. The results show that the SW approach describes the evolution of the sheared CBL quite well, and the KP approach also reproduces the growth of the CBL reasonably, so long as the value of A ₃ is modified to 0.6.     

Respiration of Recently-Fixed Plant Carbon Dominates Mid-Winter Ecosystem CO2 Production in Sub-Arctic Heath Tundra

Arctic ecosystems could provide a substantial positive feedback to global climate change if warming stimulates below-ground CO₂ release by enhancing decomposition of bulk soil organic matter reserves.Ecosystem respiration during winter is important in this context because CO₂ release from snow-covered tundra soils is a substantial component of annual net carbon (C) balance, and because global climate models predict that the most rapid rises in regional air temperature will occur in the Arctic during winter. In this manipulative field study, the relative contributions of plant and bulk soil organic matter C pools to ecosystem CO₂ production in mid-winter were investigated. We measured CO₂ efflux rates in Swedish sub-arctic heath tundra from control plots and from plots that had been clipped in the previous growing season to disrupt plant activity. Respiration derived from recently-fixed plant C (i.e., plant respiration, and respiration associated with rhizosphere exudates and decomposition of fresh litter) was the principal source of CO₂ efflux, while respiration associated with decomposition of bulk soil organic matter was low, and appeared relatively insensitive to temperature. These results suggest that warmer mid-winter temperatures in the Arctic may have a much greater impact on the cycling of recently-fixed, plant-associated C pools than on the depletion of tundra bulk soil C reserves, and consequently that there is a low potential for significant initial feedbacks from arctic ecosystems to climate change during mid-winter.     

On rising temperature trends of Karachi in Pakistan

Karachi is the largest city of Pakistan. The temperature change in Karachi is studied in this research by analyzing the time series data of mean maximum temperature (MMxT), mean minimum temperature (MMiT) and mean annual temperature (MAT) from 1947 to 2005 (59 years). Data is analyzed in three parts by running linear regression and by taking anomalies of all time periods: (a) whole period from 1947–2005; (b) phase one 1947–1975 and (c) phase two 1976–2005. During 1947 to 2005 MMxT has increased about 4.6°C, MMiT has no change and MAT has increased 2.25°C. During 1947–1975, MMxT increased 1.9°C, in this period there is − 1.3°C decrease in MMiT and MAT has raised upto 0.3°C. During 1976–2005, the MMxT, MMiT and MAT increased 2.7°C, 1.2°C and 1.95°C, respectively. The analysis shows significantly the role of extreme vulnerability of MMxT in rising the temperature of Karachi than the MMiT.