Hemlock Legacy Project (HeLP): A paleoecological requiem for eastern hemlock

Eastern North American forests have effectively lost two major tree species (American chestnut and American elm) in the last 100 years and two more, eastern and Carolina hemlock, will be functionally extinct over much of their ranges within a couple of decades. The loss of eastern hemlock is of particular concern because hemlock is: (1) a foundation species; (2) one of the longest-lived tree species over much of temperate eastern North America; and (3) sensitive to climatic variation and ecosystem disturbance, making it an ideal species for the reconstruction of environmental history. Unlike American chestnut, we have a small window of opportunity to salvage environmental histories from hemlock before they are lost. In this progress report, we review the extensive body of science derived from this paleoenvironmental archive and urge scientists from eastern North America to sample and archive old-growth hemlock while living and dead material remain. Here we describe a community-based approach to salvaging paleoenvironmental archives that could serve as a model for collections from other foundation species currently threatened by exotic forests pests and pathogens (e.g. whitebark pine, ash). The approach supports Schlesinger’s (2010) call for ‘translational ecology’ by building connections between scientists, students, environmental NGOs, and land managers focused on old-growth forests

Spatially Heterogeneous Estimates of Fire Frequency in Ponderosa Pine Forests of Washington, USA

Many fire history studies have evaluated the temporal nature of fire regimes using fire interval statistics calculated from fire scars. More recently, researchers have begun to evaluate the spatial properties of past fires as well. In this paper, we describe a technique for investigating spatio-temporal variability using a geographic information system (GIS). We used a dataset of fire-scarred trees collected from four sites in eastern Washington, USA, ponderosa pine (Pinus ponderosa C. Lawson) forests. The patterns of past fires recorded by individual trees (points) were converted to two-dimensional representations of fire with inverse distance weighting (IDW) in a GIS. A map overlay approach was then used to extract a fine-grained, spatially explicit reconstruction of fire frequency at the four sites. The resulting classified maps can supplement traditional fire interval statistics and fire atlas data to provide detailed, spatially heterogeneous estimates of fire frequency. Such information can reveal ecological relationships between fire and the landscape, and provide managers with an improved spatial perspective on fire frequency that can inform risk evaluations, fuels reduction efforts, and the allocation of fire-fighting resources

Privatization, Drought, and Fire Exclusion in the Tuul River Watershed, Mongolia

Global wildfire frequency and extent are expected to increase under projected climate change in the twenty-first century, yet little is known about how human activities might affect this trend. In central Mongolia, there has been a 2.5°C rise in spring and summer temperatures during the last 40 years and a decrease in moisture availability during the latter half of the twentieth century. Concurrently, Mongolia has experienced multiple shifts in socioeconomic systems during the twentieth century, most notably the establishment of a Soviet-backed communist economy in the 1920s and a rapid transition to privatization in the 1990s. Observed records of fire in the late twentieth century suggested that fire activity had increased, but no long-term data existed to place these trends in a historical context. Our objective was to identify spatial and temporal patterns in fire occurrence in the forest-steppe ecotone of the Tuul River watershed in the context of changing climatic and social conditions since 1875. We used fire-scarred trees to reconstruct past fire occurrence during the period 1875–2009. Our results indicate a significant association between human activity and fire occurrence independent of climatic variables. The greatest evidence for an anthropogenic fire regime exists following the transition to a free market economy during the early 1990s when land-use intensification near the capital city of Ulaanbaatar resulted in fire exclusion. We emphasize the importance of including socio-political variables in global models of wildfire potential, particularly where fuels limit fire activity

Evaluating The Effect Of Alternative Carbon Allocation Schemes In A Land Surface Model (Clm4.5) On Carbon Fluxes, Pools And Turnover In Temperate Forests

How carbon (C) is allocated to different plant tissues (leaves, stem and roots) determines C residence time and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and Leaf Area Index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a Land Surface Model (LSM), the Community Land Model (CLM4.5). We ran CLM for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: i) Dynamic C allocation scheme (named D-CLM ) with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual Net Primary Production (NPP). ii) An alternative dynamic C allocation scheme (named D-Litton ), where, similar to (i) C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem and coarse roots iii–iv) Two fixed C allocation schemes, one representative of observations in evergreen (named F-Evergreen ) and the other of observations in deciduous forests (named F-Deciduous ). D-CLM generally overestimated Gross Primary Production (GPP) and ecosystem respiration, and underestimated Net Ecosystem Exchange (NEE). In D-CLM, initial aboveground biomass in 1980 was largely overestimated (between 10527 and 12897 g Cm-2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g Cm-2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM overestimated LAI in both evergreen and deciduous sites because the leaf C-LAI relationship in the model did not match the observed leaf C-LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic Cstem/Cleaf ratios and strongly reduced the overestimation of initial aboveground biomass, and aboveground NPP for deciduous forests by D-CLM. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. That could be done by addressing some of the current model assumptions about C allocation and the associated parameter uncertainty. Our results highlight the importance of using aboveground biomass data to evaluate and constrain the C allocation scheme in the model, and in particular, the sensitivity to the stem turnover rate. Revising these will be critical to improving long-term C processes in LSMs, and improve their projections of biomass accumulation in forests

Pluvials, droughts, the Mongol Empire, and modern Mongolia

Although many studies have associated the demise of complex societies with deteriorating climate, few have investigated the connection between an ameliorating environment, surplus resources, energy, and the rise of empires. The 13th-century Mongol Empire was the largest contiguous land empire in world history. Although drought has been proposed as one factor that spurred these conquests, no high-resolution moisture data are available during the rapid development of the Mongol Empire. Here we present a 1,112-y tree-ring reconstruction of warm-season water balance derived from Siberian pine (Pinus sibirica) trees in central Mongolia. Our reconstruction accounts for 56% of the variability in the regional water balance and is significantly correlated with steppe productivity across central Mongolia. In combination with a gridded temperature reconstruction, our results indicate that the regional climate during the conquests of Chinggis Khan’s (Genghis Khan’s) 13th-century Mongol Empire was warm and persistently wet. This period, characterized by 15 consecutive years of above-average moisture in central Mongolia and coinciding with the rise of Chinggis Khan, is unprecedented over the last 1,112 y. We propose that these climate conditions promoted high grassland productivity and favored the formation of Mongol political and military power. Tree-ring and meteorological data also suggest that the early 21st-century drought in central Mongolia was the hottest drought in the last 1,112 y, consistent with projections of warming over Inner Asia. Future warming may overwhelm increases in precipitation leading to similar heat droughts, with potentially severe consequences for modern Mongolia

Comparing Tree‐Ring and Permanent Plot Estimates of Aboveground Net Primary Production in Three Eastern U.S. Forests

Forests account for a large portion of sequestered carbon, much of which is stored as wood in trees. The rate of carbon accumulation in aboveground plant material, or aboveground net primary productivity (aNPP), quantifies annual to decadal variations in forest carbon sequestration. Permanent plots are often used to estimate aNPP but are usually not annually resolved and take many years to develop a long data set. Tree rings are a unique and infrequently used source for measuring aNPP, and benefit from fine spatial (individual trees) and temporal (annual) resolution. Because of this precision, tree rings are complementary to permanent plots and the suite of tools used to study forest productivity. Here we evaluate whether annual estimates of aNPP developed from tree rings approximate estimates derived from colocated permanent plots. We studied a lowland evergreen (Howland, Maine), mixed deciduous (Harvard Forest, Massachusetts), and mixed mesophytic (Fernow, West Virginia) forest in the eastern United States. Permanent plots at the sites cover an area of 2–3 ha, and we use these areas as benchmarks indicative of the forest stand. We simulate random draws of permanent plot subsets to describe the distribution of aNPP estimates given a sampling area size equivalent to the tree-ring plots. Though mean tree-ring aNPP underestimates permanent plot aNPP slightly at Howland and Fernow and overestimates at Harvard Forest when compared with the entire permanent plot, it is within the 95% confidence interval of the random draws of equal-sized sampling area at all sites. To investigate whether tree-ring aNPP can be upscaled to the stand, we conducted a second random draw of permanent plot subsets simulating a twofold increase in sampling area. aNPP estimates from this distribution were not significantly different from results of the initial sampling area, though variance decreased as sampling area approaches stand area. Despite several concerns to consider when using tree rings to reconstruct aNPP (e.g., upscaling, allometric, and sampling uncertainties), the benefits are apparent, and we call for the continued application of tree rings in carbon cycle studies across a broader range of species diversity, productivity, and disturbance histories to fully develop this potential

Comparing Tree-Ring And Permanent Plot Estimates Of Aboveground Net Primary Production In Three Eastern U.S. Forests

Forests account for a large portion of sequestered carbon, much of which is stored as wood in trees. The rate of carbon accumulation in aboveground plant material, or aboveground net primary productivity (aNPP), quantifies annual to decadal variations in forest carbon sequestration. Permanent plots are often used to estimate aNPP but are usually not annually resolved and take many years to develop a long data set. Tree rings are a unique and infrequently used source for measuring aNPP, and benefit from fine spatial (individual trees) and temporal (annual) resolution. Because of this precision, tree rings are complementary to permanent plots and the suite of tools used to study forest productivity. Here we evaluate whether annual estimates of aNPP developed from tree rings approximate estimates derived from colocated permanent plots. We studied a lowland evergreen (Howland, Maine), mixed deciduous (Harvard Forest, Massachusetts), and mixed mesophytic (Fernow, West Virginia) forest in the eastern United States. Permanent plots at the sites cover an area of 2-3 ha, and we use these areas as benchmarks indicative of the forest stand. We simulate random draws of permanent plot subsets to describe the distribution of aNPP estimates given a sampling area size equivalent to the tree-ring plots. Though mean tree-ring aNPP underestimates permanent plot aNPP slightly at Howland and Fernow and overestimates at Harvard Forest when compared with the entire permanent plot, it is within the 95% confidence interval of the random draws of equal-sized sampling area at all sites. To investigate whether tree-ring aNPP can be upscaled to the stand, we conducted a second random draw of permanent plot subsets simulating a twofold increase in sampling area. aNPP estimates from this distribution were not significantly different from results of the initial sampling area, though variance decreased as sampling area approaches stand area. Despite several concerns to consider when using tree rings to reconstruct aNPP (e.g., upscaling, allometric, and sampling uncertainties), the benefits are apparent, and we call for the continued application of tree rings in carbon cycle studies across a broader range of species diversity, productivity, and disturbance histories to fully develop this potential

Synergistic Effects of Climate Change and Grazing on Net Primary Production of Mongolian Grasslands

In arid and semi-arid regions, grassland degradation has become a major environmental and economic problem, but little information is available on the response of grassland productivity to both climate change and grazing intensity. By developing a grazing module in a process-based ecosystem model, the dynamic land ecosystem model (DLEM), we explore the roles of climate change, elevated CO2, and varying grazing intensities in affecting aboveground net primary productivity (ANPP) across different grassland sites in Mongolia. Our results show that both growing season precipitation totals and average temperature exert important controls on annual ANPP across six sites over a precipitation gradient, explaining 65% and 45% of the interannual variations, respectively. Interannual variation in ANPP, measured as the ratio of standard deviation among years to long-term mean, increased from 9.5 to 18.9% to 23.9–32.5% along a gradient of high to low precipitation. Historical grazing resulted in a net reduction in ANPP across all sites ranging from 2% to 15.4%. Our results further show that grassland ANPP can be maintained at a grazing intensity of 1.0 and 0.5 sheep/ha at wet and dry sites, respectively, indicating that dry sites are more vulnerable to grazing compared to wet sites. In addition, precipitation use efficiency (PUE) decreased while nitrogen use efficiency (NUE) increased across a gradient of low to high precipitation. However, grazing resulted in a net reduction in both PUE and NUE by 47% and 67% across all sites. Our results indicate that seasonal precipitation totals, average temperatures and grazing are important regulators of grassland ANPP in Mongolia. These results have important implications for grassland productivity in semi-arid regions in Central Asia and beyond

Integrating Herbivore Population Dynamics Into a Global Land Biosphere Model: Plugging Animals Into the Earth System

Mammalian herbivores are an essential component of grassland and savanna ecosystems, and with feedbacks to the climate system. To date, the response and feedbacks of mammalian herbivores to changes in both abiotic and biotic factors are poorly quantified and not adequately represented in the current global land surface modeling framework. In this study, we coupled herbivore population dynamics in a global land model (the Dynamic Land Ecosystem Model, DLEM 3.0) to simulate populations of horses, cattle, sheep, and goats, and their responses to changes in multiple environmental factors at the site level across different continents during 1980–2010. Simulated results show that the model is capable of reproducing observed herbivore population dynamics across all sites for these animal groups. Our simulation results also indicate that during this period, climate extremes led to a maximum mortality of 27% of the total herbivores in Mongolia. Across all sites, herbivores reduced aboveground net primary productivity (ANPP) and heterotrophic respiration (Rh) by 14% and 15%, respectively (p \u3c 0.05). With adequate parameterization, the model can be used for historical assessment and future prediction of mammalian herbivore populations and their relevant impacts on biogeochemical cycles. Our simulation results demonstrate a strong coupling between primary producers and consumers, indicating that inclusion of herbivores into the global land modeling framework is essential to better understand the potentially large effect of herbivores on carbon cycles in grassland and savanna ecosystems