Modelling the impact of forest management and CO2-fertilisation on growth and demography in a Sitka spruce plantation

Afforestation and reforestation to meet 'Net Zero' emissions targets are considered a necessary policy by many countries. Their potential benefits are usually assessed through forest carbon and growth models. The implementation of vegetation demography gives scope to represent forest management and other size-dependent processes within land surface models (LSMs). In this paper, we evaluate the impact of including management within an LSM that represents demography, using both in-situ and reanalysis climate drivers at a mature, upland Sitka spruce plantation in Northumberland, UK. We compare historical simulations with fixed and variable CO2 concentrations, and with and without tree thinning implemented. Simulations are evaluated against the observed vegetation structure and carbon fluxes. Including thinning and the impact of increasing CO2 concentration ('CO2 fertilisation') gave more realistic estimates of stand-structure and physical characteristics. Historical CO2 fertilisation had a noticeable effect on the Gross Primary Productivity seasonal-diurnal cycle and contributed to approximately 7% higher stand biomass by 2018. The net effect of both processes resulted in a decrease of tree density and biomass, but an increase in tree height and leaf area index.

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) timescales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

Surface-Atmosphere Coupling Scale, the Fate of Water, and Ecophysiological Function in a Brazilian Forest

Tropical South America plays a central role in global climate. Bowen ratio teleconnects to circulation and precipitation processes far afield, and the global CO2 growth rate is strongly influenced by carbon cycle processes in South America. However, quantification of basin-wide seasonality of flux partitioning between latent and sensible heat, the response to anomalies around climatic norms, and understanding of the processes and mechanisms that control the carbon cycle remains elusive. Here, we investigate simulated surface-atmosphere interaction at a single site in Brazil, using models with different representations of precipitation and cloud processes, as well as differences in scale of coupling between the surface and atmosphere. We find that the model with parameterized clouds/precipitation has a tendency toward unrealistic perpetual light precipitation, while models with explicit treatment of clouds produce more intense and less frequent rain. Models that couple the surface to the atmosphere on the scale of kilometers, as opposed to tens or hundreds of kilometers, produce even more realistic distributions of rainfall. Rainfall intensity has direct consequences for the "fate of water," or the pathway that a hydrometeor follows once it interacts with the surface. We find that the model with explicit treatment of cloud processes, coupled to the surface at small scales, is the most realistic when compared to observations. These results have implications for simulations of global climate, as the use of models with explicit (as opposed to parameterized) cloud representations becomes more widespread.

Land-use emissions play a critical role in land-based mitigation for Paris climate targets

Scenarios that limit global warming to below 2 °C by 2100 assume significant land-use change to support large-scale carbon dioxide (CO₂) removal from the atmosphere by afforestation/reforestation, avoided deforestation, and Biomass Energy with Carbon Capture and Storage (BECCS). The more ambitious mitigation scenarios require even greater land area for mitigation and/or earlier adoption of CO₂ removal strategies. Here we show that additional land-use change to meet a 1.5 °C climate change target could result in net losses of carbon from the land. The effectiveness of BECCS strongly depends on several assumptions related to the choice of biomass, the fate of initial above ground biomass, and the fossil-fuel emissions offset in the energy system. Depending on these factors, carbon removed from the atmosphere through BECCS could easily be offset by losses due to land-use change. If BECCS involves replacing high-carbon content ecosystems with crops, then forest-based mitigation could be more efficient for atmospheric CO₂ removal than BECCS.

Land-based mitigation for meeting the Paris climate target must consider the carbon cycle impacts of land-use change. Here the authors show that when bioenergy crops replace high carbon content ecosystems, forest-based mitigation could be more effective for CO₂ removal than bioenergy crops with carbon capture and storage.

Large sensitivity in land carbon storage due to geographical and temporal variation in the thermal response of photosynthetic capacity

Plant temperature responses vary geographically, reflecting thermally contrasting habitats and long-term species adaptations to their climate of origin. Plants also can acclimate to fast temporal changes in temperature regime to mitigate stress. Although plant photosynthetic responses are known to acclimate to temperature, many global models used to predict future vegetation and climate-carbon interactions do not include this process. We quantify the global and regional impacts of biogeographical variability and thermal acclimation of temperature response of photosynthetic capacity on the terrestrial carbon (C) cycle between 1860 and 2100 within a coupled climate-carbon cycle model, that emulates 22 global climate models. Results indicate that inclusion of biogeographical variation in photosynthetic temperature response is most important for present-day and future C uptake, with increasing importance of thermal acclimation under future warming. Accounting for both effects narrows the range of predictions of the simulated global land C storage in 2100 across climate projections (29% and 43% globally and in the tropics, respectively). Contrary to earlier studies, our results suggest that thermal acclimation of photosynthetic capacity makes tropical and temperate C less vulnerable to warming, but reduces the warming-induced C uptake in the boreal region under elevated CO₂ .

Implications of improved representations of plant respiration in a changing climate

Land-atmosphere exchanges influence atmospheric CO₂. Emphasis has been on describing photosynthetic CO₂ uptake, but less on respiration losses. New global datasets describe upper canopy dark respiration (R _d) and temperature dependencies. This allows characterisation of baseline R _d, instantaneous temperature responses and longer-term thermal acclimation effects. Here we show the global implications of these parameterisations with a global gridded land model. This model aggregates R _d to whole-plant respiration R _p, driven with meteorological forcings spanning uncertainty across climate change models. For pre-industrial estimates, new baseline R _d increases R _p and especially in the tropics. Compared to new baseline, revised instantaneous response decreases R _p for mid-latitudes, while acclimation lowers this for the tropics with increases elsewhere. Under global warming, new R _d estimates amplify modelled respiration increases, although partially lowered by acclimation. Future measurements will refine how R _d aggregates to whole-plant respiration. Our analysis suggests R _p could be around 30% higher than existing estimates.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO₂ Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m^-2  yr^-1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO₂ -induced water savings to extend the growing season length. Observed interactive (CO₂  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

Gross primary production responses to warming, elevated CO2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO₂ (eCO₂ ) and warming requires accurate quantification of gross primary production (GPP), the largest flux of C in the global C cycle. We evaluated 6 years (2007-2012) of flux-derived GPP data from the Prairie Heating and CO₂ Enrichment (PHACE) experiment, situated in a grassland in Wyoming, USA. The GPP data were used to calibrate a light response model whose basic formulation has been successfully used in a variety of ecosystems. The model was extended by modeling maximum photosynthetic rate (A_max ) and light-use efficiency (Q) as functions of soil water, air temperature, vapor pressure deficit, vegetation greenness, and nitrogen at current and antecedent (past) timescales. The model fits the observed GPP well (R²  = 0.79), which was confirmed by other model performance checks that compared different variants of the model (e.g. with and without antecedent effects). Stimulation of cumulative 6-year GPP by warming (29%, P = 0.02) and eCO₂ (26%, P = 0.07) was primarily driven by enhanced C uptake during spring (129%, P = 0.001) and fall (124%, P = 0.001), respectively, which was consistent across years. Antecedent air temperature (Tair_ant ) and vapor pressure deficit (VPD_ant ) effects on A_max (over the past 3-4 days and 1-3 days, respectively) were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPD_ant suggests that atmospheric drought is important for predicting GPP under current and future climate; we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects. Finally, posterior estimates of cumulative GPP under control and eCO₂ treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data-driven GPP estimates suggest that they could be useful semi-independent data streams for validating TBMs.

Rickettsia parkeri and "Candidatus Rickettsia andeanae" in Questing Amblyomma maculatum (Acari: Ixodidae) From Mississippi

Amblyomma maculatum Koch (Acari: Ixodidae), the primary vector for Rickettsia parkeri, may also be infected with a rickettsia of unknown pathogenicity, "Candidatus Rickettsia andeanae." Infection rates with these rickettsiae vary geographically, and coinfected ticks have been reported. In this study, infection rates of R. parkeri and "Ca. R. andeanae" were evaluated, and rickettsial DNA levels quantified, in 335 questing adult A. maculatum collected in 2013 (n = 95), 2014 (n = 139), and 2015 (n = 101) from Oktibbeha County, MS. Overall infection rates of R. parkeri and "Ca. R. andeanae" were 28.7% and 9.3%, respectively, with three additional A. maculatum (0.9%) coinfected. While R. parkeri-infected ticks were detected all three years (34.7% in 2013; 13.7% in 2014; 43.6% in 2015), "Ca. R. andeanae" was not detected in 2013, and was detected at rates of 10.8% in 2014, and 15.8% in 2015. Interestingly, rickettsial DNA levels in singly-infected ticks were significantly lower in "Ca. R. andeanae"-infected ticks compared to R. parkeri-infected ticks (P < 0.0001). Thus, both infection rates and rickettsial DNA levels were higher for R. parkeri than "Ca. R. andeanae." Infection rates of R. parkeri were also higher, and "Ca. R. andeanae" lower, here compared to A. maculatum reported previously in Kansas and Oklahoma. As we continue to monitor infection rates and levels, we anticipate that understanding temporal changes will improve our awareness of human risk for spotted fever rickettsioses. Further, these data may lead to additional studies to evaluate potential interactions among sympatric Rickettsia species in A. maculatum at the population level.

Evolutionary Stability for Interactions among Kin under Quantitative Inheritance

The theory of evolutionarily stable strategies (ESS) predicts the long-term evolutionary outcome of frequency-dependent selection by making a number of simplifying assumptions about the genetic basis of inheritance. I use a symmetrized multilocus model of quantitative inheritance without mutation to analyze the results of interactions between pairs of related individuals and compare the equilibria to those found by ESS analysis. It is assumed that the fitness changes due to interactions can be approximated by the exponential of a quadratic surface. The major results are the following. (1) The evolutionarily stable phenotypes found by ESS analysis are always equilibria of the model studied here. (2) When relatives interact, one of the two conditions for stability of equilibria differs between the two models; this can be accounted for by positing that the inclusive fitness function for quantitative characters is slightly different from the inclusive fitness function for characters determined by a single locus. (3) The inclusion of environmental variance will in general change the equilibrium phenotype, but the equilibria of ESS analysis are changed to the same extent by environmental variance. (4) A class of genetically polymorphic equilibria occur, which in the present model are always unstable. These results expand the range of conditions under which one can validly predict the evolution of pairwise interactions using ESS analysis.

Bone mineral and vitamin D in Aleutian Islanders

Serum concentrations of vitamin D metabolites (chromatography) and bone mineral status (125I absorptiometry) were examined in a group of Aleutian Islanders age 40-75 from St Paul Island, Alaska. Based on 25-(OH)D (16.6 ng/ml) vitamin D status appeared adequate. However, high concentrations of 1,25-(OH)2D (44.3 pg/ml) and very low concentrations of 24,25-(OH)2D3 (0.6 ng/ml) were found. Among females, low bone mineral levels were associated with high concentrations of 1,25-(OH)2D. A low calcium intake in these Aleutians may be responsible for high concentrations of 1,25-(OH)2D and resorption of calcium from bone.

Physical growth of St. Lawrence Island Eskimos: body size, proportion, and composition

Growth patterns of body size, proportion, and composition were analyzed in 57 male and 56 female Eskimos from St. Lawrence Island in the Bering Sea, ranging in age from 1.23 through 19.82 years. Age-groups means for whites and blacks of the U.S. Health Examination Survey served as reference data. Relative to HES data, the Eskimo sample were shorter with lower values for leg length, while there were no differences from the reference values for sitting height. The Eskimos also had higher values of Quetelet's Index, the sitting height/height ratio, and the upper arm muscle circumference, while there were no differences in body weight or triceps skinfold thickness. Differences from the reference data were more pronounced in males than in females. The growth patterns for size and body proportion are in conformity with known relationships between morphology and climate.

Origins and divergence of Aleuts, Eskimos, and American Indians

The apportionment of average gene frequency differences into within and between groups of Aleuts, Eskimos and Athabascans reveals a testable model of the time of origin and differentiation of these populations. Based on the ratio of average difference between Aleuts and Eskimos, to the average difference between Bering Sea Mongoloids and Athabascans, we estimate that Athabascans diverged from Bering Sea Mongoloids at approximately 15 000 BP. The ratio of Aleut/Eskimo to Yupik/Inupiaq suggests the split between the latter occurred 5100 BP. Similarly, the within-group average gene frequency differences suggest that North American natives originated some 19 000 BP and that Bering Sea Mongoloids originated 10 200 BP. These estimates are highly concordant with independent archaeologic, linguistic and biological data.