Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)

Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple "big-leaf" approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1°. While the photosynthetic capacity parameter (Vc;max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity

Climate Change and the Future of California's Endemic Flora

The flora of California, a global biodiversity hotspot, includes 2387 endemic plant taxa. With anticipated climate change, we project that up to 66% will experience >80% reductions in range size within a century. These results are comparable with other studies of fewer species or just samples of a region's endemics. Projected reductions depend on the magnitude of future emissions and on the ability of species to disperse from their current locations. California's varied terrain could cause species to move in very different directions, breaking up present-day floras. However, our projections also identify regions where species undergoing severe range reductions may persist. Protecting these potential future refugia and facilitating species dispersal will be essential to maintain biodiversity in the face of climate change

Crop growth and irrigation interact to influence surface fluxes in a regional climate-cropland model (WRF3.3-CLM4crop)

© 2015 Springer-Verlag Berlin Heidelberg In this study, we coupled Version 4.0 of the Community Land Model that includes crop growth and management (CLM4crop) into the Weather Research and Forecasting (WRF) model Version 3.3 to better represent interactions between climate and agriculture. We evaluated the performance of the coupled model (WRF3.3-CLM4crop) by comparing simulated crop growth and surface climate to multiple observational datasets across the continental United States. The results showed that although the model with dynamic crop growth overestimated leaf area index (LAI) and growing season length, interannual variability in peak LAI was improved relative to a model with prescribed crop LAI and growth period, which has no environmental sensitivity. Adding irrigation largely improved daily minimum temperature but the RMSE is still higher over irrigated land than non-irrigated land. Improvements in climate variables were limited by an overall model dry bias. However, with addition of an irrigation scheme, soil moisture and surface energy flux partitioning were largely improved at irrigated sites. Irrigation effects were sensitive to crop growth: the case with prescribed crop growth underestimated irrigation water use and effects on temperature and overestimated soil evaporation relative to the case with dynamic crop growth in moderately irrigated regions. We conclude that studies examining irrigation effects on weather and climate using coupled climate–land surface models should include dynamic crop growth and realistic irrigation schemes to better capture land surface effects in agricultural regions

Improving sustainable tropical forest management with voluntary carbon markets

Purpose: Due to a rapidly changing climate, voluntary carbon markets are gaining momentum and should be leveraged to improve and expand tropical sustainable forest management plans, limiting carbon emissions and enhancing critical carbon sinks. By sequestering more carbon than any other terrestrial ecosystem — ~1 Pg C yr−1 — tropical forests provide crucial natural climate solutions and opportunities in the evolving voluntary carbon market. Methods: Here, we argue that some issues with the current sustainable management of tropical forests can be addressed using carbon-focused sustainable forest management (SFM + C) to leverage financial resources for tropical forest carbon storage and sequestration. We suggest an extended harvest cycle in SFM + C and calculate an associated potential increase in aboveground carbon stocks of commercial timber of 1.26 Mg C ha−1 after each cycle in the Brazilian Amazon. Results: The additional carbon storage due to a longer harvest cycle can generate carbon credits worth 152.6 (SD 9.2) US dollars per hectare in 40 years. Considering an average cost of 180 BRL per m3 of commercial timber delivered to the sawmill, an SFM + C plan with a 40-year cycle could generate 28.7% (SD 2.5) more profit than 35-year cycles by combining timber and carbon revenues. Conclusion: A robust carbon price could incentivize the further extension of harvest cycles, providing a monetary return that offsets the opportunity cost intrinsic to harvesting under longer cycles. Finally, we highlight research needs to support tropical SFM + C, which can be part of a global collective effort to limit global warming to below 2 °C above pre-industrial levels

Bacterial endophyte communities in Pinus flexilis are structured by host age, tissue type, and environmental factors

Background and aims: Forest tree microbiomes are important to forest dynamics, diversity, and ecosystem processes. Mature limber pines (Pinus flexilis) host a core microbiome of acetic acid bacteria in their foliage, but the bacterial endophyte community structure, variation, and assembly across tree ontogeny is unknown. The aims of this study were to test if the core microbiome observed in adult P. flexilis is established at the seedling stage, if seedlings host different endophyte communities in root and shoot tissues, and how environmental factors structure seedling endophyte communities. Methods: The 16S rRNA gene was sequenced to characterize the bacterial endophyte communities in roots and shoots of P. flexilis seedlings grown in plots at three elevations at Niwot Ridge, Colorado, subjected to experimental treatments (watering and heating). The data was compared to previously sequenced endophyte communities from adult tree foliage sampled in the same year and location. Results: Seedling shoots hosted a different core microbiome than adult tree foliage and were dominated by a few OTUs in the family Oxalobacteraceae, identical or closely related to strains with antifungal activity. Shoot and root communities significantly differed from each other but shared major OTUs. Watering but not warming restructured the seedling endophyte communities. Conclusions: The results suggest differences in assembly and ecological function across conifer life stages. Seedlings may recruit endophytes to protect against fungi under increased soil moisture

Conifer seedling recruitment across a gradient from forest to alpine tundra: Effects of species, provenance, and site

Background: Seedling germination and survival is a critical control on forest ecosystem boundaries, such as at the alpine-treeline ecotone. In addition, while it is known that species respond individualistically to the same suite of environmental drivers, the potential additional effect of local adaptation on seedling success has not been evaluated. Aims: To determine whether local adaptation may influence the position and movement of forest ecosystem boundaries, we quantified conifer seedling recruitment in common gardens across a subalpine forest to alpine tundra gradient at Niwot Ridge, Colorado, USA. Methods: We studied Pinus flexilis and Picea engelmannii grown from seed collected locally at High (3400 m a.s.l.) and Low (3060 m a.s.l.) elevations. We monitored emergence and survival of seeds sown directly into plots and survival of seedlings germinated indoors and transplanted after snowmelt. Results: Emergence and survival through the first growing season was greater for P. flexilis than P. engelmannii and for Low compared with High provenances. Yet survival through the second growing season was similar for both species and provenances. Seedling emergence and survival tended to be greatest in the subalpine forest and lowest in the alpine tundra. Survival was greater for transplants than for field-germinated seedlings. Conclusions: These results suggest that survival through the first few weeks is critical to the establishment of natural germinants. In addition, even small distances between seed sources can have a significant effect on early demographic performance - a factor that has rarely been considered in previous studies of tree recruitment and species range shifts. © 2013 The work of C. Castanha, M.S. Torn, and L.M. Kueppers was conducted at Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231 with the U.S. Department of Energy. The U.S. Government retains, and the publisher, by accepting the article for publication, acknowledges, that the U.S. Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. Government purposes. The work of M.J. Germino at the U.S. Geological Survey was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. B. Weibel waives her copyright in the work but not her status as co-author of the work

Separating the effects of phenology and diffuse radiation on gross primary productivity in winter wheat

Gross primary productivity (GPP) has been reported to increase with the fraction of diffuse solar radiation, for a given total irradiance. The correlation between GPP and diffuse radiation suggests effects of diffuse radiation on canopy light-use efficiency, but potentially confounding effects of vegetation phenology have not been fully explored. We applied several approaches to control for phenology, using 8 years of eddy-covariance measurements of winter wheat in the U.S. Southern Great Plains. The apparent enhancement of daily GPP due to diffuse radiation was reduced from 260% to 75%, after subsampling over the peak growing season or by subtracting a 15 day moving average of GPP, suggesting a role of phenology. The diffuse radiation effect was further reduced to 22% after normalizing GPP by a spectral reflectance index to account for phenological variations in leaf area index LAI and canopy photosynthetic capacity. Canopy photosynthetic capacity covaries with diffuse fraction at a given solar irradiance at this site because both factors are dependent on day of year or solar zenith angle. Using a two-leaf Sun-shaded canopy radiative transfer model, we confirmed that the effects of phenological variations in photosynthetic capacity can appear qualitatively similar to the effects of diffuse radiation on GPP and therefore can be difficult to distinguish using observations. The importance of controlling for phenology when inferring diffuse radiation effects on GPP raises new challenges and opportunities for using radiation measurements to improve carbon cycle models

Representing winter wheat in the Community Land Model (version 4.5)

Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land-atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange of CO2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35% during the spring growing season. The model accurately simulated the interannual variation in yield at the USARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %