Using Tree Rings to Predict the Response of Tree Growth to Climate Change in the Continental United States during the Twenty-First Century

In the early 1900s, tree-ring scientists began analyzing the relative widths of annual growth rings preserved in the cross sections of trees to infer past climate variations. Now, many ring-width index (RWI) chronologies, each representing a specific site and species, are archived online within the International Tree-Ring Data Bank (ITRDB). Comparing annual tree-ring-width data from 1097 sites in the continental United States to climate data, the authors quantitatively evaluated how trees at each site have historically responded to interannual climate variations. For each site, they developed a climate-driven statistical growth equation that uses regional climate variables to model RWI values. The authors applied these growth models to predict how tree growth will respond to twenty-first-century climate change, considering four climate projections. Although caution should be taken when extrapolating past relationships with climate into the future, the authors observed several clear and interesting patterns in the growth projections that seem likely if warming continues. Most notably, the models project that productivity of dominant tree species in the southwestern United States will decrease substantially during this century, especially in warmer and drier areas. In the northwest, nonlinear growth relationships with temperature may lead to warming-induced declines in growth for many trees that historically responded positively to warmer temperatures. This work takes advantage of the unmatched temporal length and spatial breath of annual growth data available within the ITRDB and exemplifies the potential of this ever-growing archive of tree-ring data to serve in meta-analyses of large-scale forest ecology

Phenology and Productivity of C₃ and C₄ Grasslands in Hawaii

Grasslands account for a large proportion of global terrestrial productivity and play a critical role in carbon and water cycling. Within grasslands, photosynthetic pathway is an important functional trait yielding different rates of productivity along environmental gradients. Recently, C₃-C₄ sorting along spatial environmental gradients has been reassessed by controlling for confounding traits in phylogenetically structured comparisons. C₃ and C₄ grasses should sort along temporal environmental gradients as well, resulting in differing phenologies and growing season lengths. Here we use 10 years of satellite data (NDVI) to examine the phenology and greenness (as a proxy for productivity) of C₃ and C₄ grass habitats, which reflect differences in both environment and plant physiology. We perform phylogenetically structured comparisons based on 3,595 digitized herbarium collections of 152 grass species across the Hawaiian Islands. Our results show that the clade identity of grasses captures differences in their habitats better than photosynthetic pathway. Growing season length (GSL) and associated productivity (GSP) were not significantly different when considering photosynthetic type alone, but were indeed different when considering photosynthetic type nested within clade. The relationship between GSL and GSP differed most strongly between C₃ clade habitats, and not between C₃-C₄ habitats. Our results suggest that accounting for the interaction between phylogeny and photosynthetic pathway can help improve predictions of productivity, as commonly used C₃-C₄ classifications are very broad and appear to mask important diversity in grassland ecosystem functions

Multi‐century stasis in C3 and C4 grass distributions across the contiguous United States since the industrial revolution

AimsUnderstanding the functional response of ecosystems to past global change is crucial to predicting performance in future environments. One sensitive and functionally significant attribute of grassland ecosystems is the percentage of species that use the C4 versus C3 photosynthetic pathway. Grasses using C3 and C4 pathways are expected to have different responses to many aspects of anthropogenic environmental change that have followed the industrial revolution, including increases in temperature and atmospheric CO2, changes to land management and fire regimes, precipitation seasonality, and nitrogen deposition. In spite of dramatic environmental changes over the past 300 years, it is unknown if the C4 grass percentage in grasslands has shifted.LocationContiguous United States of America.MethodsHere, we used stable carbon isotope data (i.e. δ13C) from 30 years of soil samples, as well as herbivore tissues that date to 1739 CE, to reconstruct coarse‐grain C3 and C4 grass composition in North American grassland sites to compare with modern vegetation. We spatially resampled these three datasets to a shared 100‐km grid, allowing comparison of δ13C values at a resolution and extent common for climate model outputs and biogeographical studies.ResultsAt this spatial grain, the bison tissue proxy was superior to the soil proxy because the soils reflect integration of local carbon inputs, whereas bison sample vegetation across landscapes. Bison isotope values indicate that historical grassland photosynthetic‐type composition was similar to modern vegetation.Main conclusionsDespite major environmental change, comparing modern plot vegetation data to three centuries of bison δ13C data revealed that the biogeographical distribution of C3 and C4 grasses has not changed significantly since the 1700s. This is particularly surprising given the expected CO2 fertilization of C3 grasses. Our findings highlight the critical importance of capturing the full range of physiological, ecological and demographical processes in biosphere models predicting future climates and ecosystems.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139065/1/jbi13061.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139065/2/jbi13061_am.pd

Assessing earth system model predictions of C-4 grass cover in North America: From the glacial era to the end of this century

Aim C-4 grasses are distinct from C-3 grasses, because C-4 grasses respond in a different manner to light, temperature, CO2 and nitrogen and often have higher resource-use efficiencies. C-3 and C-4 grasses are typically represented in earth system models (ESMs) by different plant functional types (PFTs). The ability of ESMs to capture C-4 grass biogeography and ecology across differing time periods is important to assess, given the crucial role they play in ecosystems and their divergent responses to global change. Location North America. Time periods Last Glacial Maximum (LGM), historical modern period (ca. 1850) and end of this century. Major taxa studied C-4 grasses. Methods Proxy data representing relative cover and productivity of C-4 grasses were collated, including carbon isotope ratios of soil carbon and animal grazer tissue, and vegetation plot data in undisturbed grasslands. We selected available model predictions of C-4 PFT percentage cover. Models were compared against one another and assessed against proxy data at key time points: the LGM, the historical modern period before widespread grassland conversion to agriculture, and the end of this century. Results We highlight large differences among model predictions of percentage C-4 grass cover across North America: all pairwise combinations have correlations < .5, and most are < .2. Models also do not capture spatial patterns of the percentage C-4 grass cover from proxy data, during either the LGM or the historical modern period. Models generally under-predict percentage C-4 grass cover, particularly during the historical modern period. Main conclusions Earth system models do not accurately represent the biogeography of C-4 grasses across a range of time-scales, and their outputs do not agree with one another. We suggest model improvements to represent this crucial functional type better, including more collection and greater integration of C-3 and C-4 grass trait data, explicit representations of tree-grass competition for water, and a greater focus on disturbance ecology

Tree-ring Isotopes Adjacent to Lake Superior Reveal Cold Winter Anomalies for the Great Lakes Region of North America

Tree-ring carbon isotope discrimination (Δ13C) and oxygen isotopes (δ18O) collected from white pine (Pinus strobus) trees adjacent to Lake Superior show potential to produce the first winter-specific paleoclimate reconstruction with inter-annual resolution for this region. Isotopic signatures from 1976 to 2015 were strongly linked to antecedent winter minimum temperatures (Tmin), Lake Superior peak ice cover, and regional to continental-scale atmospheric winter pressure variability including the North American Dipole. The immense thermal inertia of Lake Superior underlies the unique connection between winter conditions and tree-ring Δ13C and δ18O signals from the following growing season in trees located near the lake. By combining these signals, we demonstrate feasibility to reconstruct variability in Tmin, ice cover, and continental-scale atmospheric circulation patterns (r ≥ 0.65, P \u3c 0.001)

Evaluating spatial patterns of drought-induced tree mortality in a coastal California pine forest

In a coastal, fog-influenced forest on Santa Cruz Island in southern California, we observed mortality of Bishop pine (Pinus muricata D.Don) trees following a brief (2 year), yet intense, drought. While anecdotal evidence indicates that drought-induced Bishop pine mortality has occurred in the past in the stand we studied, this is the first attempt to capture the spatial distribution of mortality, and begin to understand the environmental drivers underlying these events. We used high spatial resolution remote sensing data to quantify the spatial extent of tree mortality using a 1 m true color aerial photograph and a 1 m LiDAR digital elevation model. We found the highest density of dead trees in the drier, more inland margins of the forest stand. We used the Random Forest decision tree algorithm to test which environmental variables (e.g., summertime cloud frequency, solar insolation, and geomorphic attributes) would best separate live and dead tree populations. We also included tree height as a variable in our analysis, which we used as a proxy for overall tree 24 size and potential rooting distribution. Based on the Random Forest analysis, we generated a map of the probability of survival. We found tree survivorship after drought was best explained by the frequency of summertime clouds, elevation, and tree height. Specifically, survivorship was greatest for larger trees (~8-10 m tall) in more foggy parts of the stand located at moderate elevation. We found that probability of survival was lowest at the inland extent of the stand where trees occur at the upper limit of their elevation range (~400 m). The coexistence of these main factors with other landscape variables help identify areas of suitable habitat for Bishop pines across the stand, and extend our understanding of this species’ distribution.Keywords: Tree mortality, Drought-stress, Random Forest, Remote Sensing, Coastal fo

Pharmacological Management of Obesity: An Endocrine Society Clinical Practice Guideline

OBJECTIVE: To formulate clinical practice guidelines for the pharmacological management of obesity. PARTICIPANTS: An Endocrine Society-appointed Task Force of experts, a methodologist, and a medical writer. This guideline was co-sponsored by the European Society of Endocrinology and The Obesity Society. EVIDENCE: This evidence-based guideline was developed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system to describe the strength of recommendations and the quality of evidence. CONSENSUS PROCESS: One group meeting, several conference calls, and e-mail communications enabled consensus. Committees and members of the Endocrine Society, the European Society of Endocrinology, and The Obesity Society reviewed and commented on preliminary drafts of these guidelines. Two systematic reviews were conducted to summarize some of the supporting evidence. CONCLUSIONS: Weight loss is a pathway to health improvement for patients with obesity-associated risk factors and comorbidities. Medications approved for chronic weight management can be useful adjuncts to lifestyle change for patients who have been unsuccessful with diet and exercise alone. Many medications commonly prescribed for diabetes, depression, and other chronic diseases have weight effects, either to promote weight gain or produce weight loss. Knowledgeable prescribing of medications, choosing whenever possible those with favorable weight profiles, can aid in the prevention and management of obesity and thus improve health

Terrestrial Planet Occurrence Rates for the Kepler GK Dwarf Sample

We measure planet occurrence rates using the planet candidates discovered by the Q1-Q16 Kepler pipeline search. This study examines planet occurrence rates for the Kepler GK dwarf target sample for planet radii, 0.75<Rp<2.5 Rearth, and orbital periods, 50<Porb<300 days, with an emphasis on a thorough exploration and identification of the most important sources of systematic uncertainties. Integrating over this parameter space, we measure an occurrence rate of F=0.77 planets per star, with an allowed range of 0.3<F<1.9. The allowed range takes into account both statistical and systematic uncertainties, and values of F beyond the allowed range are significantly in disagreement with our analysis. We generally find higher planet occurrence rates and a steeper increase in planet occurrence rates towards small planets than previous studies of the Kepler GK dwarf sample. Through extrapolation, we find that the one year orbital period terrestrial planet occurrence rate, zeta_1=0.1, with an allowed range of 0.01<zeta_1<2, where zeta_1 is defined as the number of planets per star within 20% of the Rp and Porb of Earth. For G dwarf hosts, the zeta_1 parameter space is a subset of the larger eta_earth parameter space, thus zeta_1 places a lower limit on eta_earth for G dwarf hosts. From our analysis, we identify the leading sources of systematics impacting Kepler occurrence rate determinations as: reliability of the planet candidate sample, planet radii, pipeline completeness, and stellar parameters.Comment: 19 Pages, 17 Figures, Submitted ApJ. Python source to support Kepler pipeline completeness estimates available at http://github.com/christopherburke/KeplerPORTs

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations