Life and the five biological laws : lessons for global change models and sustainability

Life on Earth is the result of a continuous accumulation of information by combination and innovation using endo- (inside the organism) and exosomatic (outside the organism) energy. Sustenance occurs through cycles of life and death. We here define five life laws for these vital processes. These processes cannot exceed natural limits of size and rates because they are constrained by space, matter and energy; biology builds on what is possible within these physicochemical limits. Learning from the way nature deals with the accumulation of information, the limits of size and the rates at which life can acquire and expend energy and resources for maintenance, growth and competition will help us to model and manage our environmental future and sustainabilit

Natural carbon solutions are not large or fast enough

Response letter: we thank Griscom et al. for their thoughtful letter to the editor (https://doi.org/10.1111/gcb.14612), responding to our paper (Baldocchi & Penuelas, 2019, https://doi.org/10.1111/gcb.14559) and expressing the opinion "we need both natural and energy solutions to stabilize our climate." We agree with tha

Evaluation of forest canopy models for estimating isoprene emissions

During the summer of 1992, isoprene emissions were measured in a mixed deciduous forest near Oak Ridge, Tennessee. Measurements were aimed at the experimental scale-up of emissions from the leaf level to the forest canopy to the mixed layer. Results from the scale-up study are compared to different canopy models for determining the leaf microclimate as input to isoprene emission algorithms. These include (1) no canopy effects, (2) a simple vertical scaling canopy model with a leaf energy balance, and (3) a numerical canopy model which accounts for leaf-sun geometries, photosynthesis, respiration, transpiration, and gas transport in the canopy. Initial evaluation of the models was based upon a standard emission rate factor of 90 μgC g-1 hr-1 (0.42 nmol g-1 s-1) taken from leaf cuvette measurements and a biomass density factor of 203 g m-2 taken from biomass surveys and a flux footprint analysis. The results indicated that predicted fluxes were consistent among the models to within approximately ±20%, but that the models overestimated the mean flux by about a factor of 2 and overestimated the maximum observed flux by 30 to 50%. Adjusting the standard emission factor and biomass density each downward by 20% yielded predicted means approximately 20% greater than the observed means and predicted maxima approximately 25% less than the observed maxima. Accounting for changes in biomass density as a function of direction upwind of the tower improved the overall model performance

Influence of sun zenith angle on canopy clumping and the resulting impacts on photosynthesis

Addressing the impact of vegetation architecture on shortwave radiation transfer in land surface models is important for accurate weather forecasting, carbon budget estimates, and climate predictions. This paper investigates to what extent it is possible to retrieve structural parameters of two different parameterization schemes from direct transmittance derived from digital hemispherical photography and 3D radiative transfer modeling for two study sites with different vegetation canopy architectures. Neglecting the representation of 3D canopy structure in radiative transfer schemes leads to significant errors in shortwave radiation partitioning (up to 3.5 times more direct transmittance in the 3D model). Structural parameters, referred to as whole canopy ‘clumping indices’, were obtained in order to evaluate the impact of angular variation in clumping on shortwave radiation transfer. Impacts on photosynthesis were evaluated at site level with the UKESM land surface model, JULES. A comparison between flux tower derived and modeled photosynthesis indicates that considering zenith angular variations of structural parameters in the radiative transfer scheme of the UKESM land surface model significantly improves photosynthesis prediction in light limited ecosystems (from RMSE = 2.91 mol CO2.m-2.s-1 to RMSE = 1.51 mol CO2.m-2.s-1, 48% smaller), typically with enhanced photosynthesis from bottom layers

Protecting climate with forests

Policies for climate mitigation on land rarely acknowledge biophysical factors, such as reflectivity, evaporation, and surface roughness. Yet such factors can alter temperatures much more than carbon sequestration does, and often in a conflicting way. We outline a framework for examining biophysical factors in mitigation policies and provide some best-practice recommendations based on that framework. Tropical projects-avoided deforestation, forest restoration, and afforestation-provide the greatest climate value, because carbon storage and biophysics align to cool the Earth. In contrast, the climate benefits of carbon storage are often counteracted in boreal and other snow-covered regions, where darker trees trap more heat than snow does. Managers can increase the climate benefit of some forest projects by using more reflective and deciduous species and through urban forestry projects that reduce energy use. Ignoring biophysical interactions could result in millions of dollars being invested in some mitigation projects that provide little climate benefit or, worse, are counter-productive

On the use of MODIS EVI to assess gross primary productivity of North American ecosystems

[1] Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remote‐sensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remote‐sensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remote‐sensing data

Looking deeper into the soil : biophysical controls and seasonal lags of soil CO2 production and efflux

Author Posting. © Ecological Society of America, 2010. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecological Applications 20 (2010): 1569–1582, doi:10.1890/09-0693.1.We seek to understand how biophysical factors such as soil temperature (Ts), soil moisture (θ), and gross primary production (GPP) influence CO2 fluxes across terrestrial ecosystems. Recent advancements in automated measurements and remote-sensing approaches have provided time series in which lags and relationships among variables can be explored. The purpose of this study is to present new applications of continuous measurements of soil CO2 efflux (F0) and soil CO2 concentrations measurements. Here we explore how variation in Ts, θ, and GPP (derived from NASA's moderate-resolution imaging spectroradiometer [MODIS]) influence F0 and soil CO2 production (Ps). We focused on seasonal variation and used continuous measurements at a daily timescale across four vegetation types at 13 study sites to quantify: (1) differences in seasonal lags between soil CO2 fluxes and Ts, θ, and GPP and (2) interactions and relationships between CO2 fluxes with Ts, θ, and GPP. Mean annual Ts did not explain annual F0 and Ps among vegetation types, but GPP explained 73% and 30% of the variation, respectively. We found evidence that lags between soil CO2 fluxes and Ts or GPP provide insights into the role of plant phenology and information relevant about possible timing of controls of autotrophic and heterotrophic processes. The influences of biophysical factors that regulate daily F0 and Ps are different among vegetation types, but GPP is a dominant variable for explaining soil CO2 fluxes. The emergence of long-term automated soil CO2 flux measurement networks provides a unique opportunity for extended investigations into F0 and Ps processes in the near future.Data collection was possible thanks to NASA, the NSF Center for Embedded Networked Sensing (CCR-0120778), DOE (DE-FG02-03ER63638), CONACyT, UCMEXUS, NSF (EF-0410408), NSF-LTER, KAKENHI (12878089 and 13480150), the Academy of Finland (213093), the Austrian Science Fund (FWF, P18756-B16), the Kearney Foundation, the Canadian Foundation for Climate and Atmospheric Sciences (CFCAS), and the Natural Science and Engineering Research Council of Canada (NSERC). R. Vargas was supported by grant DEB-0639235 during the preparation of this manuscript