Terrestrial ecosystems from space: a review of earth observation products for macroecology applications

Aim Earth observation (EO) products are a valuable alternative to spectral vegetation indices. We discuss the availability of EO products for analysing patterns in macroecology, particularly related to vegetation, on a range of spatial and temporal scales. Location Global. Methods We discuss four groups of EO products: land cover/cover change, vegetation structure and ecosystem productivity, fire detection, and digital elevation models. We address important practical issues arising from their use, such as assumptions underlying product generation, product accuracy and product transferability between spatial scales. We investigate the potential of EO products for analysing terrestrial ecosystems. Results Land cover, productivity and fire products are generated from long-term data using standardized algorithms to improve reliability in detecting change of land surfaces. Their global coverage renders them useful for macroecology. Their spatial resolution (e.g. GLOBCOVER vegetation, 300 m; MODIS vegetation and fire, ≥ 500 m; ASTER digital elevation, 30 m) can be a limiting factor. Canopy structure and productivity products are based on physical approaches and thus are independent of biome-specific calibrations. Active fire locations are provided in near-real time, while burnt area products show actual area burnt by fire. EO products can be assimilated into ecosystem models, and their validation information can be employed to calculate uncertainties during subsequent modelling. Main conclusions Owing to their global coverage and long-term continuity, EO end products can significantly advance the field of macroecology. EO products allow analyses of spatial biodiversity, seasonal dynamics of biomass and productivity, and consequences of disturbances on regional to global scales. Remaining drawbacks include inter-operability between products from different sensors and accuracy issues due to differences between assumptions and models underlying the generation of different EO products. Our review explains the nature of EO products and how they relate to particular ecological variables across scales to encourage their wider use in ecological applications.

Estimating interchannel observation-error correlations for IASI radiance data in the Met Office system

The optimal utilisation of hyper-spectral satellite observations in numerical weather prediction is often inhibited by incorrectly assuming independent interchannel observation errors. However, in order to represent these observation-error covariance structures, an accurate knowledge of the true variances and correlations is needed. This structure is likely to vary with observation type and assimilation system. The work in this article presents the initial results for the estimation of IASI interchannel observation-error correlations when the data are processed in the Met Office one-dimensional (1D-Var) and four-dimensional (4D-Var) variational assimilation systems. The method used to calculate the observation errors is a post-analysis diagnostic which utilises the background and analysis departures from the two systems. The results show significant differences in the source and structure of the observation errors when processed in the two different assimilation systems, but also highlight some common features. When the observations are processed in 1D-Var, the diagnosed error variances are approximately half the size of the error variances used in the current operational system and are very close in size to the instrument noise, suggesting that this is the main source of error. The errors contain no consistent correlations, with the exception of a handful of spectrally close channels. When the observations are processed in 4D-Var, we again find that the observation errors are being overestimated operationally, but the overestimation is significantly larger for many channels. In contrast to 1D-Var, the diagnosed error variances are often larger than the instrument noise in 4D-Var. It is postulated that horizontal errors of representation, not seen in 1D-Var, are a significant contributor to the overall error here. Finally, observation errors diagnosed from 4D-Var are found to contain strong, consistent correlation structures for channels sensitive to water vapour and surface properties.

Impact of strong deep ocean stratification on the glacial carbon cycle

During the Last Glacial Maximum, the climate was substantially colder and the carbon cycle was clearly different from the late Holocene. According to proxy data deep oceanic δ13C was very low, and the atmospheric CO2 concentration also reduced. Several mechanisms have been proposed to explain these changes, but none can fully explain the data, especially the very low deep ocean δ13C values. Oceanic core data show that the deep ocean was very cold and salty, which would lead to enhanced deep ocean stratification. We show that such an enhanced stratification in the coupled climate model CLIMBER-2 helps get very low deep oceanic δ13C values. Indeed the simulated δ13C reaches values as low as −0.8‰ in line with proxy data evidences. Moreover it increases the oceanic carbon reservoir leading to a small, yet robust, atmospheric CO2 drop of approximately 10 ppm.

Thermobaric control of gravitational potential energy generation by diapycnal mixing in the deep ocean

Sources and sinks of gravitational potential energy (GPE) play a rate-limiting role in the large scale ocean circulation. A key source is turbulent diapycnal mixing, whereby irre- versible mixing across isoneutral surfaces is enhanced by turbulent straining of these surfaces. This has motivated international observational efforts to map diapycnal mixing in the global ocean. However, in order to accurately relate the GPE supplied to the large scale circulation by diapycnal mixing to the mixing energy source, it is first necessary to determine the ratio, ξ , of the GPE generation rate to the available potential energy dissipation rate associated with turbulent mixing. Here, the link between GPE and hydro- static pressure is used to derive the GPE budget for a com- pressible ocean with a nonlinear equation of state. The role of diapycnal mixing is isolated and from this a global cli- matological distribution of ξ is calculated. It is shown that, for a given source of mixing energy, typically three times as much GPE is generated if the mixing takes place in bottom waters rather than in the pycnocline. This is due to GPE destruction by cabbelling in the pycnocline, as opposed to thermobaric enhancement of GPE generation by diapycnal mixing in the deep ocean.

Superhumps: confronting theory with observation

We review the theory and observations related to the "superhump" precession of eccentric accretion discs in close binary systems. We agree with earlier work, although for different reasons, that the discrepancy between observation and dynamical theory implies that the effect of pressure in the disc cannot be neglected. We extend earlier work that investigates this effect to include the correct expression for the radius at which resonant orbits occur. Using analytic expressions for the accretion disc structure, we derive a relationship between the period excess and mass ratio with the pressure effects included. This is compared to the observed data, recently derived results for detailed integration of the disc equations and the equivalent empirically derived relations and used to predict values for the mass ratio based on measured values of the period excess for 88 systems.

In at the Deep End. Impressions of farming in a year gaining experience: 1952-3; 1978-85

The book describes a wide variety of students’ experiences in their practical year prior to entering University to study BSc Agriculture. Until comparatively recently it was the normal requirement for all such students, whether or not they already had home farming experience, to gain a full year’s experience of practical agriculture – and to write a report thereon. This record of 41 students’ reports of the pre-entry year begins with Paul’s own experience in the early 1950s before 41 reports from 30 or more years ago. The essays provide compelling and fascinating stories, well-articulated with clear acknowledgement for most part of the humanity and the warmth with which each student was treated by farmers and farm workers alike, despite the difference in both age and experience (considerable!). [This summary is an extract from the full overview which is archived here together with the book.]

Simulated last glacial maximum D14Catm and the deep glacial ocean carbon reservoir

∆14Catm has been estimated as 420 ± 80‰ (IntCal09) during the Last Glacial Maximum (LGM) compared to preindustrial times (0‰), but mechanisms explaining this difference are not yet resolved. ∆14Catm is a function of both cosmogenic production in the high atmosphere and of carbon cycling and partitioning in the Earth system. 10Be-based reconstructions show a contribution of the cosmogenic production term of only 200 ± 200‰ in the LGM. The remaining 220‰ have thus to be explained by changes in the carbon cycle. Recently, Bouttes et al. (2010, 2011) proposed to explain most of the difference in pCO2atm and δ13C between glacial and interglacial times as a result of brine-induced ocean stratification in the Southern Ocean. This mechanism involves the formation of very saline water masses that contribute to high carbon storage in the deep ocean. During glacial times, the sinking of brines is enhanced and more carbon is stored in the deep ocean, lowering pCO2atm. Moreover, the sinking of brines induces increased stratification in the Southern Ocean, which keeps the deep ocean well isolated from the surface. Such an isolated ocean reservoir would be characterized by a low ∆14C signature. Evidence of such 14C-depleted deep waters during the LGM has recently been found in the Southern Ocean (Skinner et al. 2010). The degassing of this carbon with low ∆14C would then reduce ∆14Catm throughout the deglaciation. We have further developed the CLIMBER-2 model to include a cosmogenic production of 14C as well as an interactive atmospheric 14C reservoir. We investigate the role of both the sinking of brine and cosmogenic production, alongside iron fertilization mechanisms, to explain changes in ∆14Catm during the last deglaciation. In our simulations, not only is the sinking of brine mechanism consistent with past ∆14C data, but it also explains most of the differences in pCO2atm and ∆14Catm between the LGM and preindustrial times. Finally, this study represents the first time to our knowledge that a model experiment explains glacial-interglacial differences in pCO2atm, δ13C, and ∆14C together with a coherent LGM climate.

Observation impact in data assimilation: the effect of non-Gaussian observation error.

Data assimilation methods which avoid the assumption of Gaussian error statistics are being developed for geoscience applications. We investigate how the relaxation of the Gaussian assumption affects the impact observations have within the assimilation process. The effect of non-Gaussian observation error (described by the likelihood) is compared to previously published work studying the effect of a non-Gaussian prior. The observation impact is measured in three ways: the sensitivity of the analysis to the observations, the mutual information, and the relative entropy. These three measures have all been studied in the case of Gaussian data assimilation and, in this case, have a known analytical form. It is shown that the analysis sensitivity can also be derived analytically when at least one of the prior or likelihood is Gaussian. This derivation shows an interesting asymmetry in the relationship between analysis sensitivity and analysis error covariance when the two different sources of non-Gaussian structure are considered (likelihood vs. prior). This is illustrated for a simple scalar case and used to infer the effect of the non-Gaussian structure on mutual information and relative entropy, which are more natural choices of metric in non-Gaussian data assimilation. It is concluded that approximating non-Gaussian error distributions as Gaussian can give significantly erroneous estimates of observation impact. The degree of the error depends not only on the nature of the non-Gaussian structure, but also on the metric used to measure the observation impact and the source of the non-Gaussian structure.

Estimating correlated observation error statistics using an ensemble transform Kalman filter

For certain observing types, such as those that are remotely sensed, the observation errors are correlated and these correlations are state- and time-dependent. In this work, we develop a method for diagnosing and incorporating spatially correlated and time-dependent observation error in an ensemble data assimilation system. The method combines an ensemble transform Kalman filter with a method that uses statistical averages of background and analysis innovations to provide an estimate of the observation error covariance matrix. To evaluate the performance of the method, we perform identical twin experiments using the Lorenz ’96 and Kuramoto-Sivashinsky models. Using our approach, a good approximation to the true observation error covariance can be recovered in cases where the initial estimate of the error covariance is incorrect. Spatial observation error covariances where the length scale of the true covariance changes slowly in time can also be captured. We find that using the estimated correlated observation error in the assimilation improves the analysis.

Effects of action observation on corticospinal excitability: muscle specificity, direction, and timing of the mirror response

Many human behaviours and pathologies have been attributed to the putative mirror neuron system, a neural system that is active during both the observation and execution of actions. While there are now a very large number of papers on the mirror neuron system, variations in the methods and analyses employed by researchers mean that the basic characteristics of the mirror response are not clear. This review focuses on three important aspects of the mirror response, as measured by modulations in corticospinal excitability: (1) muscle specificity, (2) direction, and (3) timing of modulation. We focus mainly on electromyographic (EMG) data gathered following single-pulse transcranial magnetic stimulation (TMS), because this method provides precise information regarding these three aspects of the response. Data from paired-pulse TMS paradigms and peripheral nerve stimulation (PNS) are also considered when we discuss the possible mechanisms underlying the mirror response. In this systematic review of the literature, we examine the findings of 85 TMS and PNS studies of the human mirror response, and consider the limitations and advantages of the different methodological approaches these have adopted in relation to discrepancies between their findings. We conclude by proposing a testable model of how action observation modulates corticospinal excitability in humans. Specifically, we propose that action observation elicits an early, non-specific facilitation of corticospinal excitability (at around 90 ms from action onset), followed by a later modulation of activity specific to the muscles involved in the observed action (from around 200 ms). Testing this model will greatly advance our understanding of the mirror mechanism and provide a more stable grounding on which to base inferences about its role in human behaviour.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

The hidden organic carbon in deep mineral soils

Aims Current estimates of soil organic carbon (SOC) are based largely on surficial measurements to depths of 0.3 to 1 m. Many of the world’s soils greatly exceed 1 m depth and there are numerous reports of biological activity to depths of many metres. Although SOC storage to depths of up to 8 m has been previously reported, the extent to which SOC is stored at deeper depths in soil profiles is currently unknown. This paper aims to provide the first detailed analysis of these previously unreported stores of SOC. Methods Soils from five sites in the deeply weathered regolith in the Yilgarn Craton of south-western Australia were sampled and analysed for total organic carbon by combustion chromatography. These soils ranged between 5 and 38 m (mean 21 m) depth to bedrock and had been either recently reforested with Pinus pinaster or were under agriculture. Sites had a mean annual rainfall of between 399 and 583 mm yr−1. Results The mean SOC concentration across all sites was 2.30 ± 0.26 % (s.e.), 0.41 ± 0.05 % and 0.23 ± 0.04 % in the surface 0.1, 0.1–0.5 and 0.5 to 1.0 m increments, respectively. The mean value between 1 and 5 m was 0.12 ± 0.01 %, whereas between 5 and 35 m the values decreased from 0.04 ± 0.002 % to 0.03 ± 0.003 %. Mean SOC mass densities for each of the five locations varied from 21.8–37.5 kg C m−2, and were in toto two to five times greater than would be reported with sampling to a depth of 0.5 m. Conclusions This finding may have major implications for estimates of global carbon storage and modelling of the potential global impacts of climate change and land-use change on carbon cycles. The paper demonstrates the need for a reassessment of the current arbitrary shallow soil sampling depths for assessing carbon stocks, a revision of global SOC estimates and elucidation of the composition and fate of deep carbon in response to land use and climate change

Commensalism in an agroecosystem: hydraulic redistribution by deep-rooted legumes improves survival of a droughted shallow-rooted legume companion

We investigated commensalism of water use among annual shallow-rooted and perennial deep-rooted pasture legumes by examining the effect of hydraulic lift by Cullen pallidum (N.T.Burb.) J.W.Grimes and Medicago sativa on growth, survival and nutrient uptake of Trifolium subterraneum L. A vertically split-root design allowed separate control of soil water in top and bottom soil. Thirty-five days after watering ceased in the top tube, but soil remained at field capacity in the bottom tube, an increase in shallow soil water content by hydraulic lift was 5.6 and 5.9 g kg−1 soil overnight for C. pallidum and M. sativa, respectively. Trifolium subterraneum in this treatment maintained higher leaf water potentials (with M. sativa) or exhibited a slower decline (with C. pallidum) than without companion perennial plants; and shoot biomass of T. subterraneum was 56% (with C. pallidum) and 67% (with M. sativa) of that when both top and bottom tubes were at field capacity. Uptake of rubidium (a potassium analog) and phosphorus by T. subterraneum was not facilitated by hydraulic lift. Interestingly, phosphorus content was threefold greater, and shoot biomass 1.5–3.3-fold greater when T. subterraneum was interplanted with C. pallidum compared with M. sativa, although dry weight of C. pallidum was much greater than that of M. sativa. This study showed that interplanting with deep-rooted perennial legumes has benefited the survival of T. subterraneum.