Subsurface irradiance reflectance spectra of inland waters differing in morphometry and hydrology

A database has been established for relating subsurface irradiance reflectance, i.e. water ‘colour’, to the optical properties and water quality parameters of more than 120 Dutch inland water bodies. The concentrations of total chlorophyll-a (TChl-a = chlorophyll-a plus phaeopigment), total suspended matter and the Secchi-disc depth varied between 0.6 and 468 mg m^-3, 0.8 and 98 g m^-3, and 0.15 and 5.50 m, respectively. The water bodies represented very different water types based on morphometry and hydrology. The depth ranged from 0.4 to 40 m, and the surface area from 0.25 ha (fens in the moorland Peel) to 1200 km² (Lake IJsselmeer). The mean specific phytoplankton absorption coefficient at 676 nm was 0.013 ± 0.003 m² (mg TChl-a)^-1. The absorption by tripton and dissolved humic substances at 440 nm varied between 0.1 and 16.4 m^-1, and 0.1 and 65.5 m^-1, respectively. By using the spectral position and magnitude of the subsurface irradiance reflectance peak alone, it was possible to distinguish groups of water bodies according to a classical typology based on morphometry and hydrology. This revised version was published online in July 2006 with corrections to the Cover Date.     

In-situ fluorescence monitoring of cyanobacteria: Laboratory-based quantification of species-specific measurement accuracy

In recent years, in-situ fluorometers have been extensively deployed to monitor cyanobacteria in near real-time. Acceptable accuracy can be achieved between measured pigments and cyanobacteria biovolume provided the cyanobacteria species are known. However, cellular photosynthetic pigment content and measurement interferences are site and species specific and can dramatically affect sensor reliability. We quantified the accuracy of an in-situ fluorometer compared with traditional methods using mono- and mixed cultures of four different cyanobacterial species. We found: (1) lower pigment content in cultures in stationary phase, (2) higher precision with the sensor compared to traditional pigment quantification methods of measuring phycocyanin and chlorophyll a, (3) species-specific relationships between sensor readings and measurements related to biovolume, (4) overestimation of pigments in mixed compared with mono cultures, (5) dissolved organic matter causing a loss in signal proportional to its degree of aromaticity, and (6) potential to quantify the degree of cell lysis with a fluorescent dissolved organic matter sensor. This study has provided important new information on the strengths and limitations of fluorescence sensors. The sensor readings can provide accurate biovolume quantification and species determination for a number of bloom-forming species when sensors are properly compensated and calibrated.     

A new global 1-km dataset of percentage tree cover derived from remote sensing

Accurate assessment of the spatial extent of forest cover is a crucial requirement for quantifying the sources and sinks of carbon from the terrestrial biosphere. In the more immediate context of the United Nations Framework Convention on Climate Change, implementation of the Kyoto Protocol calls for estimates of carbon stocks for a baseline year as well as for subsequent years. Data sources from country level statistics and other ground‐based information are based on varying definitions of ‘forest’ and are consequently problematic for obtaining spatially and temporally consistent carbon stock estimates. By combining two datasets previously derived from the Advanced Very High Resolution Radiometer (AVHRR) at 1 km spatial resolution, we have generated a prototype global map depicting percentage tree cover and associated proportions of trees with different leaf longevity (evergreen and deciduous) and leaf type (broadleaf and needleleaf). The product is intended for use in terrestrial carbon cycle models, in conjunction with other spatial datasets such as climate and soil type, to obtain more consistent and reliable estimates of carbon stocks. The percentage tree cover dataset is available through the Global Land Cover Facility at the University of Maryland at http://glcf.umiacs.umd.edu .     

Effects of aggregated classifications of forest composition on estimates of evapotranspiration in a northern Wisconsin forest

Forest management presents challenges to accurate prediction of water and carbon exchange between the land surface and atmosphere, due to its alteration of forest structure and composition. We examined how forest species types in northern Wisconsin affect landscape scale water fluxes predicted from models driven by remotely sensed forest classification. A site‐specific classification was developed for the study site. Using this information and a digital soils database produced for the site we identified four key forest stand types: red pine, northern hardwoods, aspen, and forested wetland. Within these stand types, 64 trees representing 7 species were continuously monitored with sap flux sensors. Scaled stand‐level transpiration from sap flux was combined with a two‐source soil evaporation model and then applied over a 2.5 km × 3.0 km area around the WLEF AmeriFlux tower (Park Falls, Wisconsin) to estimate evapotranspiration. Water flux data at the tower was used as a check against these estimates. Then, experiments were conducted to determine the effects of aggregating vegetation types to International Geosphere– Biosphere Program (IGBP) level on water flux predictions. Taxonomic aggregation resulting in loss of species level information significantly altered landscape water flux predictions. However, daily water fluxes were not significantly affected by spatial aggregation when forested wetland evaporation was included. The results demonstrate the importance of aspen, which has a higher transpiration rate per unit leaf area than other forest species. However, more significant uncertainty results from not including forested wetland with its high rates of evaporation during wet summers.     

Combining stratification and up-scaling method-block cokriging with remote sensing imagery for sampling and mapping an erosion cover factor

When a ground and vegetation cover factor related to soil erosion is mapped with the aid of remotely sensed data, a cost-efficient sample design to collect ground data and to obtain an accurate map is required. However, the supports used to collect ground data are often smaller than the desirable pixels used for mapping, which leads to complexity in developing procedures for sample design and mapping. For these purposes, a sampling and mapping method was developed by integrating stratification and an up-scaling method in geostatistics — block cokriging with Landsat Thematic Mapper imagery. This method is based on spatial correlation and stratified sampling. It scales up not only the ground sample data but also the uncertainties associated with the data aggregation from smaller supports to larger pixels or blocks. This method uses the advantages of both stratification and block cokriging variance-based sample design, which leads to sample designs with variable grid spacing, and thus significantly increases the unit cost-efficiency of sample data in sampling and mapping. This outcome was verified by the results of this study.     

Bacterial volatiles and their action potential

During the past few years, an increasing awareness concerning the emission of an unexpected high number of bacterial volatiles has been registered. Humans sense, intensively and continuously, microbial volatiles that are released during food transformation and fermentation, e.g., the aroma of wine and cheese. Recent investigations have clearly demonstrated that bacteria also employ their volatiles during interactions with other organisms in order to influence populations and communities. This review summarizes the presently known bioactive compounds and lists the wide panoply of effects possessed by organisms such as fungi, plants, animals, and bacteria. Because bacteria often emit highly complex volatile mixtures, the determination of biologically relevant volatiles remains in its infancy. Part of the future goal is to unravel the structure of these volatiles and their biosynthesis. Nevertheless, bacterial volatiles represent a source for new natural compounds that are interesting for man, since they can be used, for example, to improve human health or to increase the productivity of agricultural products.     

Potential short-term earthquake forecasting by farm animal monitoring

Whether changes in animal behavior allow for short-term earthquake predictions has been debated for a long time. Before, during and after the 2016/2017 earthquake sequence in Italy, we deployed bio-logging tags to continuously observe the activity of farm animals (cows, dogs, and sheep) close to the epicenter of the devastating magnitude M6.6 Norcia earthquake (Oct–Nov 2016) and over a subsequent longer observation period (Jan–Apr 2017). Relating 5,304 (in 2016) and 12,948 (in 2017) earthquakes with a wide magnitude range (0.4 ≤ M ≤ 6.6) to continuously measured animal activity, we detected how the animals collectively reacted to earthquakes. We also found consistent anticipatory activity prior to earthquakes during times when the animals were in a building (stable), but not during their time on a pasture. We detected these anticipatory patterns not only in periods with high, but also in periods of low seismic activity. Earthquake anticipation times (1–20 hr) are negatively correlated with the distance between the farm and earthquake hypocenters. Our study suggests that continuous bio-logging of animal collectives has the potential to provide statistically reliable patterns of pre-seismic activity that could yield valuable insights for short-term earthquake forecasting. Based on a priori model parameters, we provide empirical threshold values for pre-seismic animal activities to be used in real-time observation stations.     

Biomechanical force in blood development: Extrinsic physical cues drive pro-hematopoietic signaling

The hematopoietic system is dynamic during development and in adulthood, undergoing countless spatial and temporal transitions during the course of one's life. Microenvironmental cues in the many unique hematopoietic niches differ, characterized by distinct soluble molecules, membrane-bound factors, and biophysical features that meet the changing needs of the blood system. Research from the last decade has revealed the importance of substrate elasticity and biomechanical force in determination of stem cell fate. Our understanding of the role of these factors in hematopoiesis is still relatively poor; however, the developmental origin of blood cells from the endothelium provides a model for comparison. Many endothelial mechanical sensors and second messenger systems may also determine hematopoietic stem cell fate, self renewal, and homing behaviors. Further, the intimate contact of hematopoietic cells with mechanosensitive cell types, including osteoblasts, endothelial cells, mesenchymal stem cells, and pericytes, places them in close proximity to paracrine signaling downstream of mechanical signals. The objective of this review is to present an overview of the sensors and intracellular signaling pathways activated by mechanical cues and highlight the role of mechanotransductive pathways in hematopoiesis.