Portable Vis-NIR und MIR Spektroskopie zur Erfassung von Bodeneigenschaften im Labor und im Gelände: Ergebnisse einer Fallstudie an Lößböden der Querfurter Platte (Sachsen-Anhalt)

Laborbasierte spektroskopische Verfahren im nahen Infrarot (inklusive dem sichtbaren Bereich; Vis-NIR, 400 – 2500 nm) und im mittleren Infrarot (MIR, 2500 – 25000 nm) stellen erprobte Methoden zur quantitativen Erfassung verschiedenster Bodeneigenschaften in Ergänzung zur klassischen Laboranalytik dar. Im MIR-Bereich hat sich als Technik die DRIFT („Diffuse Reflectance Infrared Fourier Transform“)-Spektroskopie etabliert, die, vergleichbar mit der Vis-NIR Spektroskopie, wenig Aufwand bei der Probenaufbereitung erfordert. Im Gegensatz zum Vis-NIR Bereich fehlen im MIR-Bereich Fallstudien mit „in-situ“ Messungen, da portable FTIR-Spektrometer erst seit wenigen Jahren verfügbar sind. Die vorliegende Untersuchung trägt hier zum Lückenschluss bei. Für 100 Ackerstandorte der Querfurter Platte (Tschernoseme der Mitteldeutschen Trockengebiete) wurden mit portablen Vis-NIR und MIR-Geräten (ASD FieldSpec-4 Wide-Res Feldpektroradiometer mit „Contact Probe“; aktives Agilent 4300 Handheld FTIR-Spektrometer mit „Diffuse Reflectance Sample Interface“) in-situ Messungen durchgeführt. Zusätzlich erfolgten eine Probennahme und erneute spektrale Vermessung der aufbereiteten Proben (gemahlen und luftgetrocknet) im Labor; nasschemisch wurden Referenzwerte für den gesamten und den organischen Kohlenstoff, Gesamt-Stickstoffgehalte und ph-Werte ermittelt. Auf dieser Datenbasis werden folgende Fragestellungen behandelt: 1) Vergleich beider Techniken hinsichtlich ihrer Potenziale zur Quantifizierung der genannten Bodengrößen (sowohl im Labor als auch im Gelände) mit verschiedenen multivariaten Kalibrationsansätzen (insbesondere Partial Least Squares Regression mit und ohne Spektralvariablenselektion); 2) Bewertung von Limitationen beider Techniken bei der praktischen Durchführung von Geländemessungen; 3) Möglichkeiten zur synergistischen Nutzung beider Spektralbereiche für eine verbesserte Abschätzung der Bodeneigenschaften

Associations for Citizen Science: Regional Knowledge, Global Collaboration

Since 2012, three organizations advancing the work of citizen science practitioners have arisen in different regions: The primarily US-based but globally open Citizen Science Association (CSA), the European Citizen Science Association (ECSA), and the Australian Citizen Science Association (ACSA). These associations are moving rapidly to establish themselves and to develop inter-association collaborations. We consider the factors driving this emergence and the significance of this trend for citizen science as a field of practice, as an area of scholarship, and for the culture of scientific research itself

Einsatz der Nahinfrarotspektroskopie zur Abschätzung von allgemeinen und biologischen Bodeneigenschaften

Infrarotspektroskopie im sichtbaren und nahen Infrarotbereich (vis-NIRS) ist eine etablierte Methode zur Abschätzung der Gehalte an organischem Kohlenstoff (SOC) und Stickstoff (N) in Böden. Weniger Information ist hinsichtlich einer Eignung für bodenbiologische Eigenschaften vorhanden. Ziele waren die Untersuchung der Eignung der vis-NIRS zur Abschätzung von allgemeinen Bodeneigenschaften (SOC, N, pH, Textur) und Enzymaktivitäten für unterschiedliche Standorte. Chemometrische Auswertungen wurden mit der PLS (partial least squares)-Regression durchgeführt. Unabhängige Validierungen zeigten, dass vis-NIRS erwartungsgemäß gut geeignet zur Abschätzung von SOC- und N-Gehalten war, während die Abschätzungen von pH und Texturklassen variabel waren. Die Abschätzungen von Enzymaktivitäten konnten mittels Regressionen aus den allgemeinen Bodeneigenschaften mit ähnlicher Genauigkeit abgeschätzt werden wie aus den Infrarotdaten, so dass wir keinen Nutzen der vis-NIRS zur direkten Abschätzung von Enzymaktivitäten sehen

Innovation in citizen science – perspectives on science-policy advances

Citizen science is growing as a field of research with contributions from diverse disciplines, promoting innovation in science, society, and policy. Inter- and transdisciplinary discussions and critical analyses are needed to use the current momentum to evaluate, demonstrate, and build on the advances that have been made in the past few years. This paper synthesizes results of discussions at the first international citizen science conference of the European Citizen Science Association (ECSA) in 2016 in Berlin, Germany, and distills major points of the discourse into key recommendations. To enhance innovation in science, citizen science needs to clearly demonstrate its scientific benefit, branch out across disciplines, and foster active networking and new formats of collaboration, including true co-design with participants. For fostering policy advances, it is important to embrace opportunities for policy-relevant monitoring and policy development and to work with science funders to find adequate avenues and evaluation tools to support citizen science. From a society angle it is crucial to engage with societal actors in various formats that suit participants and to evaluate two-way learning outcomes as well as to develop the transformative role of science communication. We hope that these key perspectives will promote citizen science progress at the science-society-policy interface

ECSA's Characteristics of Citizen Science: Explanation Notes

This explanation document provides an interpretation of and explanation for the characteristics document, which was kept short to make it useful to different stakeholders. In this document, the characteristics document is represented, with the original text in blue and an explanation in black

Remote sensing of geomorphodiversity linked to biodiversity — part III: traits, processes and remote sensing characteristics

Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well as the constraints of monitoring the diversity of geomorphology using RS, are discussed. RS-aided techniques that can be used for monitoring geomorphodiversity in regimes with changing land-use intensity are presented. Further, new approaches of geomorphic traits that enable the monitoring of geomorphodiversity through the valorisation of RS data from multiple missions are discussed as well as the ecosystem integrity approach. Likewise, the approach of monitoring the five characteristics of geomorphodiversity recording with RS is discussed, as are existing approaches for recording spectral geomorhic traits/ trait variation approach and indicators, along with approaches for assessing geomorphodiversity. It is shown that there is no comparable approach with which to define and record the five characteristics of geomorphodiversity using only RS data in the literature. Finally, the importance of the digitization process and the use of data science for research in the field of geomorphology in the 21st century is elucidated and discussed

Contours of Citizen Science: A Vignette Study

Citizen science has expanded rapidly over the past decades. Yet, defining citizen science and its boundaries remained a challenge, and this is reflected in the literature - for example in the proliferation of typologies and definitions. There is a need for identifying areas of agreement and disagreement within the citizen science practitioners community on what should be considered as citizen science activity. This paper describes the development and results of a survey that examined this issue, through the use of vignettes - short case descriptions that describe an activity, while asking the respondents to rate the activity on a scale from ‘not citizen science’ (0%) to ‘citizen science’ (100%). The survey included 50 vignettes, of which 5 were developed as clear cases of not-citizen science activities, 5 as widely accepted citizen science activities, and the others addressing 10 factors and 61 sub-factors that can lead to controversy about an activity. The survey has attracted 333 respondents, who provided over 5,100 ratings. The analysis demonstrates the plurality of understanding of what citizen science is and calls for an open understanding of what activities are included in the field

A global spectral library to characterize the world's soil

Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for future generations. To this end, we developed and analyzed a global soil visible-near infrared (vis-NIR) spectral library. It is currently the largest and most diverse database of its kind. We show that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability. We also show the usefulness of the global spectra for predicting soil attributes such as soil organic and inorganic carbon, clay, silt, sand and iron contents, cation exchange capacity, and pH. Using wavelets to treat the spectra, which were recorded in different laboratories using different spectrometers and methods, helped to improve the spectroscopic modelling. We found that modelling a diverse set of spectra with a machine learning algorithm can find the local relationships in the data to produce accurate predictions of soil properties. The spectroscopic models that we derived are parsimonious and robust, and using them we derived a harmonized global soil attribute dataset, which might serve to facilitate research on soil at the global scale. This spectroscopic approach should help to deal with the shortage of data on soil to better understand it and to meet the growing demand for information to assess and monitor soil at scales ranging from regional to global. New contributions to the library are encouraged so that this work and our collaboration might progress to develop a dynamic and easily updatable database with better global coverage. We hope that this work will reinvigorate our community's discussion towards larger, more coordinated collaborations. We also hope that use of the database will deepen our understanding of soil so that we might sustainably manage it and extend the research outcomes of the soil, earth and environmental sciences towards applications that we have not yet dreamed of