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AbstractDenitrification is a key process in the global nitrogen (N) cycle, causing both nitrous oxide (N2O) and dinitrogen (N2) emissions. However, estimates of seasonal denitrification losses (N2O + N2) are scarce, reflecting methodological difficulties in measuring soil‐borne N2 emissions against the high atmospheric N2 background and challenges regarding their spatio‐temporal upscaling. This study investigated N2O + N2 losses in response to N fertilizer rates (0, 100, 150, 200, and 250 kg N ha−1) on two intensively managed tropical sugarcane farms in Australia, by combining automated N2O monitoring, in situ N2 and N2O measurements using the 15N gas flux method and fertilizer 15N recoveries at harvest. Dynamic changes in the N2O/(N2O + N2) ratio (<0.01 to 0.768) were explained by fitting generalized additive mixed models (GAMMs) with soil factors to upscale high temporal‐resolution N2O data to daily N2 emissions over the season. Cumulative N2O + N2 losses ranged from 12 to 87 kg N ha−1, increasing non‐linearly with increasing N fertilizer rates. Emissions of N2O + N2 accounted for 31%–78% of fertilizer 15N losses and were dominated by environmentally benign N2 emissions. The contribution of denitrification to N fertilizer loss decreased with increasing N rates, suggesting increasing significance of other N loss pathways including leaching and runoff at higher N rates. This study delivers a blueprint approach to extrapolate denitrification measurements at both temporal and spatial scales, which can be applied in fertilized agroecosystems. Robust estimates of denitrification losses determined using this method will help to improve cropping system modeling approaches, advancing our understanding of the N cycle across scales.

Though frequently used in dendroclimatology, European larch (Larix decidua Mill.) is regularly defoliated by mass outbreaks of the larch budmoth (Zeiraphera griseana Hb., LBM). The near-cyclic growth depressions are unrelated to but possibly coincide with cold summers, which challenges signal detection on interannual timescales. LBM defoliation events cause sharp maximum latewood density declines and irregular earlywood/latewood ratios in the outbreak year, followed by one or two anomalously narrow rings. Here, we present a process-based method integrating these diverse response patterns to identify and distinguish LBM-related signals from climate-induced deviations. Application to larch sites along elevational transects in the Swiss Alps reveals the algorithm to perform better than existing extreme event detection methods, though our approach enables additional differentiation between insect- and climate-induced signatures. The new process-based multi-parameter algorithm is a suitable tool to identify different causes of growth disturbances and will therefore help to improve both tree-ring-based climate and insect defoliation reconstructions.

Frontiers in Functional Plant Ecology 14, 1216337 (2023). doi:10.3389/fpls.2023.1216337 Published by Frontiers Media, Lausanne

Klimawandel und Biodiversitätsverlust sowie Verstädterung und demografischer Wandel haben tiefgreifende Auswirkungen auf Städte und ihre Ökosysteme und damit auf die Lebensbedingungen der Mehrheit der Menschheit. Die Geschwindigkeit des Wandels und die Dringlichkeit der Folgen macht Umweltmonitoring zu einem potentiell interessanten Tool für nachhaltige und resiliente Stadtentwicklung. Der erste Artikel gibt einen Überblick über den aktuellen Stand der Fernerkundung in Bezug auf Stadtökologie und zeigt, dass Fernerkundung relevant für nachhaltige Stadtplanung ist. Es bestehen jedoch bestehen Mängel, da viele Studien nicht direkt umsetzbar sind. Der zweite Artikel zeigt, dass eine wachsende Stadt Möglichkeiten für den Ausbau der grünen Infrastruktur bieten kann. Im dritten Artikel wird untersucht, wie sich die städtische Dichte auf die Bereitstellung von Ökosystemdienstleistungen der grünen Infrastruktur auswirkt. Es wird gezeigt, dass eine hohe Siedlungsdichte nicht zwangsläufig zu einem geringeren Biodiversitätspotenzial oder einer geringeren Kühlkapazität führt. Allerdings sind dicht bebaute Gebiete mit geringer Vegetationsbedeckung besonders auf grüne Infrastruktur angewiesen. Der vierte Artikel befasst sich mit der Frage, wie naturbasierte Lösungen durch eine bessere Vernetzung der Beteiligten gestärkt werden können. Auf der Grundlage einer gezielten Literaturrecherche über Informationstechnologie zur Unterstützung sozial-ökologischer Systeme wird ein Instrument zur Entscheidungshilfe entwickelt. Dieses kombiniert ökologische und soziale Indikatoren, um Klimawandeladaption in Übereinstimmung mit den sozio-ökologischen Bedingungen entwickeln zu können. Der fünfte Artikel bietet eine grundsätzliche Perspektive zur Unterstützung der städtischen Nachhaltigkeit, die auf dem ökologischen-Trait Konzept basiert. Zusammen bieten die fünf Artikel Wege für die Fernerkundungswissenschaft und die angewandte Raumplanung für nachhaltige und resiliente Entwicklungen in Städten. Climate change and biodiversity loss, as well as urbanisation and demographic change, are major global challenges of the 21st century. These trends have profound impacts on cities and their ecosystems and thus on the living conditions of the majority of humanity. This raises the need for timely environmental monitoring supporting sustainable and resilient urban developments. The first article is an overview of the state of the art of remote sensing science in relation to urban ecology. The review found that remote sensing can contribute to sustainable urban policy, still insufficiencies remain as many studies are not directly actionable. The second article shows that a growing city can provide opportunities for an increase in green infrastructure. Here, remote sensing is used for long-term analysis of land-use in relation to urban forms in Berlin. The third article examines how urban density affects ecosystem service provision of urban green infrastructure. It is shown that residential density does not necessarily lead to poor biodiversity potential or cooling capacity. However, dense areas with low vegetation cover are particularly dependent on major green infrastructure. The fourth article explores ways to reinforce nature-based solutions by better connecting and informing stakeholders. Based on a focussed literature review on information technology supporting urban social-ecological systems, a decision support tool is developed. The tool combines indicators based on ecological diversity and performance with population density and vulnerability. This way, climate change adaptation can be developed in accordance with socio-ecological conditions. The concluding fifth article offers an outlook on a larger framework in support of urban sustainability, based on the ecological trait concept. Together the five research papers provide pathways for urban remote sensing science and applied spatial planning that can support sustainable and resilient developments in cities.

Forests interact with the local climate through a variety of biophysical mechanisms. Observational and modelling studies have investigated the effects of forested vs. non-forested areas, but the influence of forest management on surface temperature has received far less attention owing to the inherent challenges to adapt climate models to cope with forest dynamics. Further, climate models are complex and highly parameterized, and the time and resource intensity of their use limit applications. The availability of simple yet reliable statistical models based on high resolution maps of forest attributes representative of different development stages can link individual forest management practices to local temperature changes, and ultimately support the design of improved strategies. In this study, we investigate how forest management influences local surface temperature (LSTs) in Fennoscandia through a set of machine learning algorithms. We find that more developed forests are typically associated with higher LST than young or undeveloped forests. The mean multi-model estimates from our statistical system can accurately reproduce the observed LST. Relative to the present state of Fennoscandian forests, fully develop forests are found to induce an annual mean warming of 0.26 °C (0.03/0.69 °C as 5th/95th percentile), and an average cooling effect in the summer daytime from -0.85 to -0.23 °C (depending on the model). On the contrary, a scenario with undeveloped forests induces an annual average cooling of -0.29 °C (-0.61/-0.01 °C), but daytime warming in the summer that can be higher than 1 °C. A weak annual mean cooling of -0.01 °C is attributed to forest harvest from 2015 to 2018, with an increased daytime temperature in summer of about 0.04 °C. Overall, this approach is a flexible option to study effects of forest management on LST that can be applied at various scales and for alternative management scenarios, thereby helping to improve local management strategies with consideration of effects on local climate.

Satellite-derived Land Surface Temperature (LST) dynamics have been increasingly used to study various geophysical processes. This review provides an extensive overview of the applications of LST in the context of global change. By filtering a selection of relevant keywords, a total of 164 articles from 14 international journals published during the last two decades were analyzed based on study location, research topic, applied sensor, spatio-temporal resolution and scale and employed analysis methods. It was revealed that China and the USA were the most studied countries and those that had the most first author affiliations. The most prominent research topic was the Surface Urban Heat Island (SUHI), while the research topics related to climate change were underrepresented. MODIS was by far the most used sensor system, followed by Landsat. A relatively small number of studies analyzed LST dynamics on a global or continental scale. The extensive use of MODIS highly determined the study periods: A majority of the studies started around the year 2000 and thus had a study period shorter than 25 years. The following suggestions were made to increase the utilization of LST time series in climate research: The prolongation of the time series by, e.g., using AVHRR LST, the better representation of LST under clouds, the comparison of LST to traditional climate change measures, such as air temperature and reanalysis variables, and the extension of the validation to heterogenous sites.

AbstractDemand for sustainably produced biomass is expected to increase with the need to provide renewable commodities, improve resource security and reduce greenhouse gas emissions in line with COP26 commitments. Studies have demonstrated additional environmental benefits of using perennial biomass crops (PBCs), when produced appropriately, as a feedstock for the growing bioeconomy, including utilisation for bioenergy (with or without carbon capture and storage). PBCs can potentially contribute to Common Agricultural Policy (CAP) (2023–27) objectives provided they are carefully integrated into farming systems and landscapes. Despite significant research and development (R&D) investment over decades in herbaceous and coppiced woody PBCs, deployment has largely stagnated due to social, economic and policy uncertainties. This paper identifies the challenges in creating policies that are acceptable to all actors. Development will need to be informed by measurement, reporting and verification (MRV) of greenhouse gas emissions reductions and other environmental, economic and social metrics. It discusses interlinked issues that must be considered in the expansion of PBC production: (i) available land; (ii) yield potential; (iii) integration into farming systems; (iv) R&D requirements; (v) utilisation options; and (vi) market systems and the socio‐economic environment. It makes policy recommendations that would enable greater PBC deployment: (1) incentivise farmers and land managers through specific policy measures, including carbon pricing, to allocate their less productive and less profitable land for uses which deliver demonstrable greenhouse gas reductions; (2) enable greenhouse gas mitigation markets to develop and offer secure contracts for commercial developers of verifiable low‐carbon bioenergy and bioproducts; (3) support innovation in biomass utilisation value chains; and (4) continue long‐term, strategic R&D and education for positive environmental, economic and social sustainability impacts.