Biome Productivity Research Articles

Potential evaporation at eddy-covariance sites across the globe

Abstract. Potential evaporation (Ep) is a crucial variable for hydrological forecasting and drought monitoring. However, multiple interpretations of Ep exist, which reflect a diverse range of methods to calculate it. A comparison of the performance of these methods against field observations in different global ecosystems is urgently needed. In this study, potential evaporation was defined as the rate of terrestrial evaporation (or evapotranspiration) that the actual ecosystem would attain if it were to evaporate at maximal rate for the given atmospheric conditions. We use eddy-covariance measurements from the FLUXNET2015 database, covering 11 different biomes, to parameterise and inter-compare the most widely used Ep methods and to uncover their relative performance. For each of the 107 sites, we isolate days for which ecosystems can be considered unstressed, based on both an energy balance and a soil water content approach. Evaporation measurements during these days are used as reference to calibrate and validate the different methods to estimate Ep. Our results indicate that a simple radiation-driven method, calibrated per biome, consistently performs best against in situ measurements (mean correlation of 0.93; unbiased RMSE of 0.56 mm day−1; and bias of −0.02 mm day−1). A Priestley and Taylor method, calibrated per biome, performed just slightly worse, yet substantially and consistently better than more complex Penman-based, Penman–Monteith-based or temperature-driven approaches. We show that the poor performance of Penman–Monteith-based approaches largely relates to the fact that the unstressed stomatal conductance cannot be assumed to be constant in time at the ecosystem scale. On the contrary, the biome-specific parameters required by simpler radiation-driven methods are relatively constant in time and per biome type. This makes these methods a robust way to estimate Ep and a suitable tool to investigate the impact of water use and demand, drought severity and biome productivity.

Productivity, organism size, and the trophic structure of the major terrestrial biomes

I present a hypothesis suggesting that terrestrial biomes' productivity determines the size of the major organisms and plant physiognomy in them and consequently determines their trophic structure. I suggest a more comprehensive set of patterns over current hypotheses, which consider productivity alone. Based on my hypothesis, I predict that the number of trophic levels decreases with increasing productivity from four in hot deserts to two in productive grasslands and that there are three to four trophic levels in all types of forested biomes. I also suggest that productivity is the limiting factor for the number of trophic levels at the lower end of the terrestrial productivity gradient, herbivore size is the limiting factor at intermediate productivities, and plant physiognomy is the limiting factor in the high productivity range. This contradicts existing hypotheses that predict either an increase (Am Nat 118:240–261, 1981; Am Nat 155:703–723, 2000) or no change (Am Nat 142:379–411, 1993) in the number of trophic levels with the increase in biome productivity.

Ecosystem as a text: information analysis of the global vegetation pattern

Let us consider a text, which is written in the English language. At the zero level of perception (or description), we know only the number of symbols ( n=29: 26 letters, 1 blank, 1 comma and 1 full stop). Then the information per symbol I (0) log 2 29≈4.85 bits. At the second level of perception we take into account the frequencies of the symbols (letters); then I (1)≈4.03 bits. At the next levels we take into account double, triple, etc. correlations, i.e., words of two letters, three letters, etc., so that the information per letter are I (2)/2≈3.32 bits, I (3)/3≈3.10 bits,…. The redundancy of information, R ( i) , and its cost, C ( i) , are equal to R (0)=0, R (1)=0.15, R (2)=0.30, R (3)=0.35, and C (0)=1, C (1)=1.18, C (2)=1.43, C (3)=1.54. Let us consider a description of the global vegetation pattern (GVP). At the zero level of description we have a number of significant biomes or vegetation types, n. In accordance with Bazilevich n=30, then I (0) log 2 30≈4.9 bits. At the second level we take into account the relative areas covered by biomes. Then I (1)≈4.41 bits, R 1=0.1, and C 1=1.11. At the next level of description we consider the spatial correlations between different pairs of biomes, then I (2)/2≈3.6 bits, R 2=0.265, and C 2=1.36. Note that in addition to their areas, the biomes are also characterised by three parameters: annual productivity P i , living biomass B i and dead organic matter D i . Weighting them in relation to biome area σ i we define the frequencies p i P =P iσ i/ ∑ i=1 30 P iσ i,p i B =B iσ i/ ∑ i=1 30 B iσ i and p i D =D iσ i/ ∑ i=1 30 D iσ i . The description in terms of productivity, living or dead organic matter can be considered as description at the first level with information per letter defined as (I (1)) P, B, D =− ∑ i=1 n p i P, B, D log 2 p i P, B, D . Then (1) for productivity: ( I (1)) P=3.61 bits, C 2 P=1.32, R 2 P=0.24; (2) for living biomass: ( I (1)) B=3.27 bits, C 2 B=1.5, R 2 B=0.33; (3) for dead organic matter: ( I (1)) D=4.13 bits, C 2 D=1.17, R 2 D=0.16. One can see that information about the biome productivity, living biomass and dead organic matter is more valuable than the information about the biome areas distribution. Information about the distribution of living biomass has the maximal cost ( C 2 B=1.5).

Temporal and spatial variations of terrestrial biomes and carbon storage since 13 000 yr BP in Europe: Reconstruction from pollen data and statistical models

Statistical models calibrated from field measurement data are used to reconstruct the past terrestrial carbon (C) storage from pollen data for the last 13 000 yr BP in Europe. The pollen-based climatic and biome reconstructions provide the input data for these statistical models, i.e., annual mean temperature, total annual precipitation, annual actual evapotranspiration, annual potential evapotranspiration and biome type with a spatial resolution of 0.5°×0.5° longitude/latitude. Our reconstructions indicate that the last 13 000 yr BP were characterized in Europe by variations of terrestrial biome and net primary productivity (NPP) at various temporal and spatial scales. For the considered region, our results also suggest that changes in climate have significantly altered the distribution of terrestrial biomes and affected the uptake of CO2 for NPP. However, these changes did not translate into significant C storage change in potential terrestrial biosphere during the Holocene. The largest decrease of terrestrial C storage (compared to modern levels) is found during the late-Glacial period mainly due to the persistence of ice sheets and the small extension of forest.