Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances

Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model-based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes, manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more

Assessment of carbon stores in tree biomass for two management scenarios in Russia

Accurate quantification of terrestrial carbon storage and its change is of key importance to improved understanding of global carbon dynamics. Forest management influences carbon sequestration and release patterns, and gap models are well suited for evaluating carbon storage. An individual-based gap model of forest dynamics, FAREAST, is applied across Russia to estimate aboveground carbon storage under management scenarios. Current biomass from inventoried forests across Russia is compared to model-based estimates and potential levels of biomass are estimated for a set of simplified forestry practices. Current carbon storage in eastern Russia was lower than for the northwest and south, and lower than model estimates likely due to high rates of disturbance. Model-derived carbon storage in all regions was not significantly different between the simulated ‘current’ and hypothetical ‘even-aged’ management strategies using rotations of 150 and 210 years. Simulations allowing natural maturation and harvest after 150 years show a significant increase in aboveground carbon in all regions. However, it is unlikely that forests would be left unharvested to 150 years of age to attain this condition. These applications indicate the value of stand simulators, applied over broad regions such as Russia, as tools to evaluate the effect of management regimes on aboveground carbon storage.Keywords: boreal forest, modelling, validation, biomass, carbo

Importance of Tree-and Species-Level Interactions with Wildfire, Climate, and Soils in Interior Alaska: Implications for Forest Change Under a Warming Climate

The boreal zone of Alaska is dominated by interactions between disturbances, vegetation, and soils. These interactions are likely to change in the future through increasing permafrost thaw, more frequent and intense wildfires, and vegetation change from drought and competition. We utilize an individual tree-based vegetation model, the University of Virginia Forest Model Enhanced (UVAFME), to estimate current and future forest conditions across sites within interior Alaska. We updated UVAFME for application within interior Alaska, including improved simulation of permafrost dynamics, litter decay, nutrient dynamics, fire mortality, and postfire regrowth. Following these updates, UVAFME output on species-specific biomass and stem density was comparable to inventory measurements at various forest types within interior Alaska. We then simulated forest response to climate change at specific inventory locations and across the Tanana Valley River Basin on a 2 × 2 km2 grid. We derived projected temperature and precipitation from a five-model average taken from the CMIP5 archive under the RCP 4.5 and 8.5 scenarios. Results suggest that climate change and the concomitant impacts on wildfire and permafrost dynamics will result in overall decreases in biomass (particularly for spruce (Picea spp.)) within the interior Tanana Valley, despite increases in quaking aspen (Populus tremuloides) biomass, and a resulting shift towards higher deciduous fraction. Simulation results also predict increases in biomass at cold, wet locations and at high elevations, and decreases in biomass in dry locations, under both moderate (RCP 4.5) and extreme (RCP 8.5) climate change scenarios. These simulations demonstrate that a highly detailed, species interactive model can be used across a large region within Alaska to investigate interactions between vegetation, climate, wildfire, and permafrost. The vegetation changes predicted here have the capacity to feed back to broader scale climate-forest interactions in the North American boreal forest, a region which contributes significantly to the global carbon and energy budgets

A Novel Diffuse Fraction-Based Two-Leaf Light Use Efficiency Model: An Application Quantifying Photosynthetic Seasonality across 20 AmeriFlux Flux Tower Sites

Diffuse radiation can increase canopy light use efficiency (LUE). This creates the need to differentiate the effects of direct and diffuse radiation when simulating terrestrial gross primary production (GPP). Here, we present a novel GPP model, the diffuse-fraction-based two-leaf model (DTEC), which includes the leaf response to direct and diffuse radiation, and treats maximum LUE for shaded leaves (ɛmsh defined as a power function of the diffuse fraction (Df)) and sunlit leaves (ɛmsu defined as a constant) separately. An Amazonian rainforest site (KM67) was used to calibrate the model by simulating the linear relationship between monthly canopy LUE and Df. This showed a positive response of forest GPP to atmospheric diffuse radiation, and suggested that diffuse radiation was more limiting than global radiation and water availability for Amazon rainforest GPP on a monthly scale. Further evaluation at 20 independent AmeriFlux sites showed that the DTEC model, when driven by monthly meteorological data and MODIS leaf area index (LAI) products, explained 70% of the variability observed in monthly flux tower GPP. This exceeded the 51% accounted for by the MODIS 17A2 big-leaf GPP product. The DTEC model\u27s explicit accounting for the impacts of diffuse radiation and soil water stress along with its parameterization for C4 and C3 plants was responsible for this difference. The evaluation of DTEC at Amazon rainforest sites demonstrated its potential to capture the unique seasonality of higher GPP during the diffuse radiation-dominated wet season. Our results highlight the importance of diffuse radiation in seasonal GPP simulation

Climate-Induced Boreal Forest Change: Predictions versus Current Observations

For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change

The Northern Eurasia Earth Science Partnership: An Example of Science Applied to Societal Needs

Northern Eurasia, the largest landmass in the northern extratropics, accounts for ~20% of the global land area. However, little is known about how the biogeochemical cycles, energy and water cycles, and human activities specific to this carbon-rich, cold region interact with global climate. A major concern is that changes in the distribution of land-based life, as well as its interactions with the environment, may lead to a self-reinforcing cycle of accelerated regional and global warming. With this as its motivation, the Northern Eurasian Earth Science Partnership Initiative (NEESPI) was formed in 2004 to better understand and quantify feedbacks between northern Eurasian and global climates. The first group of NEESPI projects has mostly focused on assembling regional databases, organizing improved environmental monitoring of the region, and studying individual environmental processes. That was a starting point to addressing emerging challenges in the region related to rapidly and simultaneously changing climate, environmental, and societal systems. More recently, the NEESPI research focus has been moving toward integrative studies, including the development of modeling capabilities to project the future state of climate, environment, and societies in the NEESPI domain. This effort will require a high level of integration of observation programs, process studies, and modeling across disciplines

Partitioning the Heritability of Tourette Syndrome and Obsessive Compulsive Disorder Reveals Differences in Genetic Architecture

The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained