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Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling

استخدام شبكات البحث لإنشاء مجموعات البيانات الشاملة اللازمة لتقييم توافر المغذيات كمحدد رئيسي لدورة الكربون الأرضية
Authors: Benjamin D. Stocker; Shilong Piao; William R. Wieder; William R. Wieder; Josep Peñuelas; Hans Lambers; Philip A. Fay; +12 Authors

Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling

Abstract

Una amplia gama de investigaciones muestra que la disponibilidad de nutrientes influye fuertemente en el ciclo del carbono (C) terrestre y da forma a las respuestas de los ecosistemas a los cambios ambientales y, por lo tanto, a las retroalimentaciones terrestres al clima. Sin embargo, nuestra comprensión de los controles de nutrientes sigue estando lejos de ser completa y mal cuantificada, al menos en parte debido a la falta de conjuntos de datos informativos, comparables y accesibles a escalas regionales a globales. Una creciente infraestructura de investigación de redes multisitio está proporcionando datos valiosos sobre flujos y existencias de C y está monitoreando sus respuestas al cambio ambiental global y midiendo las respuestas a los tratamientos experimentales. Por lo tanto, estas redes brindan una oportunidad para mejorar nuestra comprensión de las interacciones del ciclo de los nutrientes C y nuestra capacidad para modelarlas. Sin embargo, todavía falta información coherente sobre cómo interactúa el ciclo de nutrientes con los patrones del ciclo C observados. Aquí, argumentamos que complementar las mediciones del ciclo C disponibles de los sitios de monitoreo y experimentación con los datos que caracterizan la disponibilidad de nutrientes mejorará en gran medida su poder y mejorará nuestra capacidad para pronosticar futuras trayectorias del ciclo C terrestre y el clima. Por lo tanto, proponemos un conjunto de mediciones complementarias que son relativamente fáciles de realizar de forma rutinaria en cualquier sitio o experimento y que, en combinación con las observaciones del ciclo C, pueden proporcionar una caracterización sólida de los efectos de la disponibilidad de nutrientes en todos los sitios. Además, discutimos el poder de diferentes variables observables para informar la formulación de modelos y restringir sus predicciones. La mayoría de las mediciones ampliamente disponibles de la disponibilidad de nutrientes a menudo no se alinean bien con las necesidades actuales de modelado. Esto pone de relieve la importancia de fomentar la interacción entre las comunidades empírica y de modelización para establecer futuras prioridades de investigación.

Un large éventail de recherches montre que la disponibilité des nutriments influence fortement le cycle du carbone terrestre (C) et façonne les réponses des écosystèmes aux changements environnementaux et donc les rétroactions terrestres sur le climat. Néanmoins, notre compréhension des contrôles des nutriments reste loin d'être complète et mal quantifiée, du moins en partie en raison d'un manque d'ensembles de données informatifs, comparables et accessibles à l'échelle régionale et mondiale. Une infrastructure de recherche croissante de réseaux multi-sites fournit des données précieuses sur les flux et les stocks de C et surveille leurs réponses aux changements environnementaux mondiaux et mesure les réponses aux traitements expérimentaux. Ces réseaux offrent ainsi une opportunité d'améliorer notre compréhension des interactions du cycle C-nutriment et notre capacité à les modéliser. Cependant, il manque encore généralement des informations cohérentes sur la façon dont le cycle des nutriments interagit avec les modèles de cycle C observés. Ici, nous soutenons que le fait de compléter les mesures de cycle C disponibles à partir de sites de surveillance et expérimentaux par des données caractérisant la disponibilité des nutriments améliorera considérablement leur puissance et améliorera notre capacité à prévoir les trajectoires futures du cycle C terrestre et du climat. Par conséquent, nous proposons un ensemble de mesures complémentaires qui sont relativement faciles à effectuer de manière routinière sur n'importe quel site ou expérience et qui, en combinaison avec les observations du cycle C, peuvent fournir une caractérisation robuste des effets de la disponibilité des nutriments sur tous les sites. De plus, nous discutons de la puissance des différentes variables observables pour éclairer la formulation des modèles et contraindre leurs prédictions. La plupart des mesures largement disponibles de la disponibilité des nutriments ne correspondent souvent pas bien aux besoins actuels de modélisation. Cela souligne l'importance de favoriser l'interaction entre les communautés empiriques et de modélisation pour établir les futures priorités de recherche.

A wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities.

تُظهر مجموعة واسعة من الأبحاث أن توافر المغذيات يؤثر بشدة على دورة الكربون الأرضي (C) ويشكل استجابات النظام البيئي للتغيرات البيئية وبالتالي التغذية المرتدة الأرضية للمناخ. ومع ذلك، لا يزال فهمنا لضوابط المغذيات بعيدًا عن الاكتمال وقياسه الكمي ضعيفًا، ويرجع ذلك جزئيًا على الأقل إلى نقص مجموعات البيانات المفيدة والقابلة للمقارنة والتي يمكن الوصول إليها على المستويات الإقليمية والعالمية. توفر البنية التحتية البحثية المتنامية للشبكات متعددة المواقع بيانات قيمة عن تدفقات الكربون والمخزونات وترصد استجاباتها للتغير البيئي العالمي وتقيس استجاباتها للعلاجات التجريبية. وبالتالي توفر هذه الشبكات فرصة لتحسين فهمنا لتفاعلات دورة المغذيات C وقدرتنا على نمذجتها. ومع ذلك، لا تزال المعلومات المتماسكة حول كيفية تفاعل دورة المغذيات مع أنماط الدورة C المرصودة غير متوفرة بشكل عام. هنا، نجادل بأن استكمال قياسات الدورة C المتاحة من مواقع المراقبة والتجربة بالبيانات التي تميز توافر المغذيات سيعزز إلى حد كبير قوتها وسيحسن قدرتنا على التنبؤ بالمسارات المستقبلية للدورة C الأرضية والمناخ. لذلك، نقترح مجموعة من القياسات التكميلية التي يسهل إجراؤها نسبيًا بشكل روتيني في أي موقع أو تجربة والتي، جنبًا إلى جنب مع ملاحظات الدورة ج، يمكن أن توفر توصيفًا قويًا لتأثيرات توفر المغذيات عبر المواقع. بالإضافة إلى ذلك، نناقش قوة المتغيرات المختلفة التي يمكن ملاحظتها للإبلاغ عن صياغة النماذج وتقييد تنبؤاتها. غالبًا ما لا تتوافق معظم القياسات المتاحة على نطاق واسع لتوافر المغذيات بشكل جيد مع احتياجات النمذجة الحالية. وهذا يسلط الضوء على أهمية تعزيز التفاعل بين المجتمعات التجريبية والنمذجة لتحديد أولويات البحث في المستقبل.

Countries
France, Spain, Belgium, Netherlands, Netherlands
Keywords

Global vegetation models, 550, manipulation experiments, Terrestrial-Aquatic Linkages, 551, Nutrient cycle, Agricultural and Biological Sciences, Terrestrial ecosystem, Environmental Science(all), SDG 13 - Climate Action, Climate change, Environmental resource management, Global change, General Environmental Science, SDG 15 - Life on Land, Carbon-nutrient cycle interactions, Data syntheses, Global and Planetary Change, Ecology, Geography, Physics, Life Sciences, Application of Stable Isotopes in Trophic Ecology, Cycling, Carbon cycle, Chemistry, Archaeology, Physical Sciences, Public Health, Ecosystem Functioning, 570, carbon-nutrient cycle interactions, data syntheses, Soil Science, Environmental science, [SDU] Sciences of the Universe [physics], SDG 3 - Good Health and Well-being, global vegetation models, nutrients, SDG 7 - Affordable and Clean Energy, Renewable Energy, Key (lock), Biology, Ecosystem, Manipulation experiments, Sustainability and the Environment, Renewable Energy, Sustainability and the Environment, Ecosystem Structure, Environmental and Occupational Health, Public Health, Environmental and Occupational Health, Nutrients, Computer science, [SDU]Sciences of the Universe [physics], FOS: Biological sciences, Global Methane Emissions and Impacts, Environmental Science, Soil Carbon Dynamics and Nutrient Cycling in Ecosystems, Nutrient Limitation, Nutrient

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
34
Top 10%
Average
Top 10%
Green
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