Biogeosciences

Abstract. Recently, long filamentous bacteria have been reported conducting electrons over centimetre distances in marine sediments. These so-called cable bacteria perform an electrogenic form of sulfur oxidation, whereby long-distance electron transport links sulfide oxidation in deeper sediment horizons to oxygen reduction in the upper millimetres of the sediment. Electrogenic sulfur oxidation exerts a strong impact on the local sediment biogeochemistry, but it is currently unknown how prevalent the process is within the seafloor. Here we provide a state-of-the-art assessment of its global distribution by combining new field observations with previous reports from the literature. This synthesis demonstrates that electrogenic sulfur oxidation, and hence microbial long-distance electron transport, is a widespread phenomenon in the present-day seafloor. The process is found in coastal sediments within different climate zones (off the Netherlands, Greenland, the USA, Australia) and thrives on a range of different coastal habitats (estuaries, salt marshes, mangroves, coastal hypoxic basins, intertidal flats). The combination of a widespread occurrence and a strong local geochemical imprint suggests that electrogenic sulfur oxidation could be an important, and hitherto overlooked, component of the marine cycle of carbon, sulfur and other elements.

Abstract. Understanding how the Earth's biogeochemical cycles respond to environmental change is a prerequisite for the prediction and mitigation of the effects of anthropogenic perturbations. Microbial populations mediate key steps in these cycles, yet they are often crudely represented in biogeochemical models. Here, we show that microbial population dynamics can qualitatively affect the response of biogeochemical cycles to environmental change. Using simple and generic mathematical models, we find that nutrient limitations on microbial population growth can lead to regime shifts, in which the redox state of a biogeochemical cycle changes dramatically as the availability of a redox-controlling species, such as oxygen or acetate, crosses a threshold (a "tipping point"). These redox regime shifts occur in parameter ranges that are relevant to the present-day sulfur cycle in the natural environment and the present-day nitrogen cycle in eutrophic terrestrial environments. These shifts may also have relevance to iron cycling in the iron-containing Proterozoic and Archean oceans. We show that redox regime shifts also occur in models with physically realistic modifications, such as additional terms, chemical states, or microbial populations. Our work reveals a possible new mechanism by which regime shifts can occur in nutrient-cycling ecosystems and biogeochemical cycles, and highlights the importance of considering microbial population dynamics in models of biogeochemical cycles.

Abstract. This literature review summarizes the environmental controls governing biogenic sesquiterpene (SQT) emissions and presents a compendium of numerous SQT-emitting plant species as well as the quantities and ratios of SQT species they have been observed to emit. The results of many enclosure-based studies indicate that temporal SQT emission variations appear to be dominated mainly by ambient temperatures although other factors contribute (e.g., seasonal variations). This implies that SQT emissions have increased significance at certain times of the year, especially in late spring to mid-summer. The strong temperature dependency of SQT emissions also creates the distinct possibility of increasing SQT emissions in a warmer climate. Disturbances to vegetation (from herbivores and possibly violent weather events) are clearly also important in controlling short-term SQT emissions bursts, though the relative contribution of disturbance-induced emissions is not known. Based on the biogenic SQT emissions studies reviewed here, SQT emission rates among numerous species have been observed to cover a wide range of values, and exhibit substantial variability between individuals and across species, as well as at different environmental and phenological states. These emission rates span several orders of magnitude (10s–1000s of ng gDW-1 h−1). Many of the higher rates were reported by early SQT studies, which may have included artificially-elevated SQT emission rates due to higher-than-ambient enclosure temperatures and disturbances to enclosed vegetation prior to and during sample collection. When predicting landscape-level SQT fluxes, modelers must consider the numerous sources of variability driving observed SQT emissions. Characterizations of landscape and global SQT fluxes are highly uncertain given differences and uncertainties in experimental protocols and measurements, the high variability in observed emission rates from different species, the selection of species that have been studied so far, and ambiguities regarding controls over emissions. This underscores the need for standardized experimental protocols, better characterization of disturbance-induced emissions, screening of dominant plant species, and the collection of multiple replicates from several individuals within a given species or genus as well as a better understanding of seasonal dependencies of SQT emissions in order to improve the representation of SQT emission rates.

Abstract. Cold-water coral (CWC) reefs are heterogeneous ecosystems comprising numerous microhabitats. A typical European CWC reef provides various biogenic microhabitats (within, on and surrounding colonies of coral species such as Lophelia pertusa, Paragorgia arborea and Primnoa resedaeformis, or formed by their remains after death). These microhabitats may be surrounded and intermixed with non-biogenic microhabitats (soft sediment, hard ground, gravel/pebbles, steep walls). To date, studies of distribution of sessile fauna across CWC reefs have been more numerous than those investigating mobile fauna distribution. In this study we quantified shrimp densities associated with key CWC microhabitat categories at the Røst Reef, Norway, by analysing image data collected by towed video sled in June 2007. We also investigated shrimp distribution patterns on the local scale (<40 cm) and how these may vary with microhabitat. Shrimp abundances at the Røst Reef were on average an order of magnitude greater in biogenic reef microhabitats than in non-biogenic microhabitats. Greatest shrimp densities were observed in association with live Paragorgia arborea microhabitat (43 shrimp m−2, SD = 35.5), live Primnoa resedaeformis microhabitat (41.6 shrimp m−2, SD = 26.1) and live Lophelia pertusa microhabitat (24.4 shrimp m−2, SD = 18.6). In non-biogenic microhabitat, shrimp densities were <2 shrimp m−2. CWC reef microhabitats appear to support greater shrimp densities than the surrounding non-biogenic microhabitats at the Røst Reef, at least at the time of survey.

Abstract. Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

Abstract. In order to use the global available eddy-covariance (EC) flux dataset and remote-sensing measurements to provide estimates of gross primary productivity (GPP) at landscape (101–102 km2), regional (103–106 km2) and global land surface scales, we developed a satellite-based GPP algorithm using LANDSAT data and an upscaling framework. The satellite-based GPP algorithm uses two improved vegetation indices (Enhanced Vegetation Index – EVI, Land Surface Water Index – LSWI). The upscalling framework involves flux footprint climatology modelling and data-model fusion. This approach was first applied to an evergreen coniferous stand in the subtropical monsoon climatic zone of south China. The EC measurements at Qian Yan Zhou tower site (26°44´48" N, 115°04´13" E), which belongs to the China flux network and the LANDSAT and MODIS imagery data for this region in 2004 were used in this study. A consecutive series of LANDSAT-like images of the surface reflectance at an 8-day interval were predicted by blending the LANDSAT and MODIS images using an existing algorithm (ESTARFM: Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model). The seasonal dynamics of GPP were then predicted by the satellite-based algorithm. MODIS products explained 60% of observed variations of GPP and underestimated the measured annual GPP (= 1879 g C m−2) by 25–30%; while the satellite-based algorithm with default static parameters explained 88% of observed variations of GPP but overestimated GPP during the growing seasonal by about 20–25%. The optimization of the satellite-based algorithm using a data-model fusion technique with the assistance of EC flux tower footprint modelling reduced the biases in daily GPP estimations from about 2.24 g C m−2 day−1 (non-optimized, ~43.5% of mean measured daily value) to 1.18 g C m−2 day−1 (optimized, ~22.9% of mean measured daily value). The remotely sensed GPP using the optimized algorithm can explain 92% of the seasonal variations of EC observed GPP. These results demonstrated the potential combination of the satellite-based algorithm, flux footprint modelling and data-model fusion for improving the accuracy of landscape/regional GPP estimation, a key component for the study of the carbon cycle.

Abstract. Typhoons are very unpredictable natural disturbances to subtropical mangrove forests in Asian countries, but little information is available on how these disturbances affect ecosystem level carbon dioxide (CO2) exchange of mangrove wetlands. In this study, we examined short-term effect of frequent strong typhoons on defoliation and net ecosystem CO2 exchange (NEE) of subtropical mangroves, and also synthesized 19 typhoons during a 4-year period between 2009 and 2012 to further investigate the regulation mechanisms of typhoons on ecosystem carbon and water fluxes following typhoon disturbances. Strong wind and intensive rainfall caused defoliation and local cooling effect during the typhoon season. Daily total NEE values decreased by 26–50% following some typhoons (e.g., W28-Nockten, W35-Molave and W35-Lio-Fan), but significantly increased (43–131%) following typhoon W23-Babj and W38-Megi. The magnitudes and trends of daily NEE responses were highly variable following different typhoons, which were determined by the balance between the variances of gross ecosystem production (GEP) and ecosystem respiration (RE). Furthermore, results from our synthesis indicated that the landfall time of typhoon, wind speed and rainfall were the most important factors controlling the CO2 fluxes following typhoon events. These findings indicate that different types of typhoon disturbances can exert very different effects on CO2 fluxes of mangrove ecosystems and that typhoon will likely have larger impacts on carbon cycle processes in subtropical mangrove ecosystems as the intensity and frequency of typhoons are predicted to increase under future global climate change scenarios.

Abstract. Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc.) to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China) were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively). Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (−36%) was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%), the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements) (August–September, 2009) as well as spectral reflectance values (obtained from pansharpened GeoEye-1), both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73–100% accuracy, whereas tall A. corniculatum was correctly classified at only 53% due to its mixed vegetation stands with B. gymnorrhiza (overall classification accuracy: 85%). In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m) for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e.g. Kandelia obovata) at Gaoqiao. Despite limitations such as geometric distortion and single panchromatic band, the 42 yr old Corona declassified images are invaluable for land-use/cover change detections when compared to recent satellite data sets.

Abstract. Salt marshes and seagrass meadows can sequester and store high quantities of organic carbon (OC) in their sediments relative to other marine and terrestrial habitats. Assessing carbon stocks, carbon sources, and the transfer of carbon between habitats within coastal seascapes are each integral in identifying the role of blue carbon habitats in coastal carbon cycling. Here, we quantified carbon stocks, sources, and exchanges in seagrass meadows, salt marshes, and unvegetated sediments in six bays along the California coast. In the top 20 cm of sediment, the salt marshes contained approximately twice as much OC as seagrass meadows did, 4.92 ± 0.36 kg OC m−2 compared to 2.20 ± 0.24 kg OC m−2, respectively. Both salt marsh and seagrass sediment carbon stocks were higher than previous estimates from this region but lower than global and US-wide averages, respectively. Seagrass-derived carbon was deposited annually into adjacent marshes during fall seagrass senescence. However, isotope mixing models estimate that negligible amounts of this seagrass material were ultimately buried in underlying sediment. Rather, the vast majority of OC in sediment across sites was likely derived from planktonic/benthic diatoms and/or C3 salt marsh plants.

Abstract. Wildfires in Mediterranean Europe have been increasing in number and extension over the last decades and constitute one of the major disturbances of these ecosystems. Portugal is the country with more burnt area in the last decade and the years of 2003 and 2005 were particularly devastating, the total burned areas of 425 000 and 338 000 ha being several times higher than the corresponding average. The year of 2005 further coincided with one of the most severe droughts since early 20th century. Due to different responses of vegetation to diverse fire regimes and to the complexity of landscape structures, fires have complex effects on vegetation recovery. Remote sensing has revealed to be a powerful tool in studying vegetation dynamics and in monitoring post-fire vegetation recovery, which is crucial to land-management and to prevent erosion. The main goals of the present work are (i) to assess the accuracy of a vegetation recovery model previously developed by the authors; (ii) to assess the model's performance, namely its sensitivity to initial conditions, to the temporal length of the input dataset and to missing data; (iii) to study vegetation recovery over two selected areas that were affected by two large wildfire events in the fire seasons of 2003 and 2005, respectively. The study relies on monthly values of NDVI over 11 years (1998–2009), at 1 km × 1 km spatial resolution, as obtained by the VEGETATION instrument. According to results from sensitivity analysis, the model is robust and able to provide good estimations of recovery times of vegetation when the regeneration process is regular, even when missing data is present. In respect to the two selected burnt scars, results indicate that fire damage is a determinant factor of regeneration, as less damaged vegetation recovers more rapidly, which is mainly justified by the high coverage of Pinus pinaster over the area, and by the fact that coniferous forests tend to recover slower than transitional woodland-shrub, which tend to dominate the areas following the fire event.