Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA-TV)

Tropical forests are a key determinant of the functioning of the Earth system, but remain a major source of uncertainty in carbon cycle models and climate change projections. In this study, we present an updated land model (LM3PPA-TV) to improve the representation of tropical forest structure and dynamics in Earth system models (ESMs). The development and parameterization of LM3PPA-TV drew on extensive datasets on tropical tree traits and long-term field censuses from Barro Colorado Island (BCI), Panama. The model defines a new plant functional type (PFT) based on the characteristics of shade-tolerant, tropical tree species, implements a new growth allocation scheme based on realistic tree allometries, incorporates hydraulic constraints on biomass accumulation, and features a new compartment for tree branches and branch fall dynamics. Simulation experiments reproduced observed diurnal and seasonal patterns in stand-level carbon and water fluxes, as well as mean canopy and understory tree growth rates, tree size distributions, and stand-level biomass on BCI. Simulations at multiple sites captured considerable variation in biomass and size structure across the tropical forest biome, including observed responses to precipitation and temperature. Model experiments suggested a major role of water limitation in controlling geographic variation forest biomass and structure. However, the failure to simulate tropical forests under extreme conditions and the systematic underestimation of forest biomass in Paleotropical locations highlighted the need to incorporate variation in hydraulic traits and multiple PFTs that capture the distinct floristic composition across tropical domains. The continued pressure on tropical forests from global change demands models which are able to simulate alternative successional pathways and their pace to recovery. LM3PPA-TV provides a tool to investigate geographic variation in tropical forests and a benchmark to continue improving the representation of tropical forests dynamics and their carbon storage potential in ESMs.

Urban heat island: Aerodynamics or imperviousness?

More than half of the world's population now live in cities, which are known to be heat islands. While daytime urban heat islands (UHIs) are traditionally thought to be the consequence of less evaporative cooling in cities, recent work sparks new debate, showing that geographic variations of daytime UHI intensity were largely explained by variations in the efficiency with which urban and rural areas convect heat from the land surface to the lower atmosphere. Here, we reconcile this debate by demonstrating that the difference between the recent finding and the traditional paradigm can be explained by the difference in the attribution methods. Using a new attribution method, we find that spatial variations of daytime UHI intensity are more controlled by variations in the capacity of urban and rural areas to evaporate water, suggesting that strategies enhancing the evaporation capability such as green infrastructure are effective ways to mitigate urban heat.

The impact of anthropogenic land use and land cover change on regional climate extremes

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

Confronting terrestrial biosphere models with forest inventory data

Efforts to test and improve terrestrial biosphere models (TBMs) using a variety of data sources have become increasingly common. Yet, geographically extensive forest inventories have been under-exploited in previous model-data fusion efforts. Inventory observations of forest growth, mortality, and biomass integrate processes across a range of timescales, including slow timescale processes such as species turnover, that are likely to have important effects on ecosystem responses to environmental variation. However, the large number (thousands) of inventory plots precludes detailed measurements at each location, so that uncertainty in climate, soil properties, and other environmental drivers may be large. Errors in driver variables, if ignored, introduce bias into model-data fusion. We estimated errors in climate and soil drivers at U.S. Forest Inventory and Analysis (FIA) plots, and we explored the effects of these errors on model-data fusion with the Geophysical Fluid Dynamics Laboratory LM3V dynamic global vegetation model. When driver errors were ignored or assumed small at FIA plots, responses of biomass production in LM3V to precipitation and soil available water capacity appeared steeper than the corresponding responses estimated from FIA data. These differences became nonsignificant if driver errors at FIA plots were assumed to be large. Ignoring driver errors when optimizing LM3V parameter values yielded estimates for fine-root allocation that were larger than biometric estimates, which is consistent with the expected direction of bias. To explore whether complications posed by driver errors could be circumvented by relying on intensive study sites where driver errors are small, we performed a power analysis. To accurately quantify the response of biomass production to spatial variation in mean annual precipitation within the eastern United States would require at least 40 intensive study sites, which is larger than the number of sites typically available for individual biomes in existing plot networks. Driver errors may be accommodated by several existing model-data fusion approaches, including hierarchical Bayesian methods and ensemble filtering methods; however, these methods are computationally expensive. We propose a new approach, in which the TBM functional response is fit directly to the driver-error-corrected functional response estimated from data, rather than to the raw observations.

Regions of Strong Coupling Between Soil Moisture and Precipitation

Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a lack of observational data and by the model dependence of computational estimates. To counter the second limitation, a dozen climate-modeling groups have recently performed the same highly controlled numerical experiment as part of a coordinated comparison project. This allows a multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Potential benefits of this estimation may include improved seasonal rainfall forecasts.

Chromosomal location and genetic mapping of the mismatch repair gene homologs MSH2, MSH3, and MSH6 in rye and wheat

The efficiency of homeologous recombination is influenced by mismatch repair genes in bacteria, yeast, and mammals. To elucidate a possible role of these genes in homeologous pairing and cross-compatibility in plants, gene probes of wheat (Triticum aestivum) specific for the mismatch repair gene homologues MSH2, MSH3, and MSH6 were used to map them to their genomic positions in rye (Secale cereale). Whereas MSH2 was mapped to the short arm of chromosome 1R, MSH3 was mapped to the long arm of chromosome 2R and MSH6 to the long arm of chromosome 5R. Southern blots with nullisomic-tetrasomic (NT) lines of wheat indicated the presence of the sequences on the respective homeologous group of wheat chromosomes. Additionally, an MSH6-specific homologue could also be detected on homoeologous group 3 of wheat. However, in the well-known, highly homoeologous pairing wheat mutant ph1b the MSH6-specific sequence is not within the deleted part of chromosome 5BL, indicating that the pairing phenotype is not due to a loss of one of the mismatch repair genes tested.

RFLP mapping of a gene for hairy leaf sheath using a recombinant line from Hordeum vulgare L. ×Hordeum bulbosum L. cross

A gene conditioning hairy leaf sheath character, which was derived from Hordeum bulbosum and designated Hsb, was mapped using a cross between Hordeum vulgare and a H. vulgare/H. bulbosum recombinant line. The Hsb locus was tagged relative to eight RFLP markers detecting three loci on the distal part of chromosome 4HL. The map position suggests that Hsb of H. bulbosum is homoeologous to the gene Hp1 of rye (Secale cereale), which pleiotropically governs the traits hairy leaf sheath and hairy peduncle. It is proposed that the recombination break point between H. vulgare and H. bulbosum chromosomes occured at a position homoeologous compared with the 4L/5L translocation in Triticeae genomes, and may reflect a hot spot for chromosome breakage.Key words: Hordeum vulgare, Hordeum bulbosum, comparative mapping, hairy leaf sheath, RFLP.

Molecular mapping of two dwarfing genes differing in their GA response on chromosome 2H of barley

The two recessive dwarfing mutants gai (GA-ins) and gal (GA-less), differing in their response to exogenously applied gibberellic acid (GA(3)), were mapped in the centromere region and on the long arm, respectively, of the barley chromosome 2H. The gene gai, which determines reduced plant height and GA insensitivity pleiotropically, was found to co-segregate with the two RFLP markers Xmwg2058 and Xmwg2287. Both markers are known to map close to the centromere. The GA-sensitive dwarfing gene gal was found to be linked to the three co-segregating RFLP markers Xmwg581, Xmwg882 and Xmwg2212 (proximal) and XksuG5 (distal) by 3.6 and 9.5. cM, respectively. The distance between the two mutant loci was estimated to be about 55 cM. Homoeologous relationships between the dwarfing genes within the Triticeae are discussed.