A GIS-based Approach for Modeling the Spatial and Temporal Development of Night-time Lights

One of the few directly observable indicators of human activity in spatially explicit form are night-time satellite imagery data. Nocturnal lighting can be regarded as one of the defining features of concentrated human activity, such as flaring of natural gas in oil field

Biomass turnover time in terrestrial ecosystems halved by land use

The terrestrial carbon cycle is not well quantified1. Biomass turnover time is a crucial parameter in the global carbon cycle2–4, and contributes to the feedback between the terrestrial carbon cycle and climate2–7. Biomass turnover time varies substantially in time and space, but its determinants are not well known8,9, making predictions of future global carbon cycle dynamics uncertain5,10–13. Land use—the sum of activities that aim at enhancing terrestrial ecosystem services14—alters plant growth15 and reduces biomass stocks16, and is hence expected to aect biomass turnover. Here we explore land-use-induced alterations of biomass turnover at the global scale by comparing the biomass turnover of the actual vegetation with that of a hypothetical vegetation state with no land use under current climate conditions. We find that, in the global average, biomass turnover is 1.9 times faster with land use. This acceleration aects all biomes roughly equally, but with large dierences between land-use types. Land conversion, for example fromforests to agricultural fields, is responsible for59%of the acceleration; the use of forestsand natural grazing land accounts for 26% and 15% respectively. Reductions in biomass stocks are partly compensated by reductions in net primary productivity. We conclude that land use significantly and systematically aects the fundamental trade-off between carbon turnover and carbon stocks

Challenges and opportunities in mapping land use intensity globally

Future increases in land-based production will need to focus more on sustainably intensifying existing production systems. Unfortunately, our understanding of the global patterns of land use intensity is weak, partly because land use intensity is a complex, multidimensional term, and partly because we lack appropriate datasets to assess land use intensity across broad geographic extents. Here, we review the state of the art regarding approaches for mapping land use intensity and provide a comprehensive overview of available global-scale datasets on land use intensity. We also outline major challenges and opportunities for mappinglanduseintensityfor cropland, grazing, and forestry systems, and identify key issues for future research.Peer Reviewe

Reply to: Soils need to be considered when assessing the impacts of land-use change on carbon sequestration

Industrial Ecolog

EXIOBASE 3: Developing a time series of detailed environmentally extended multi-regional input-output tables

Environmentally extended multiregional input-output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the System of Environmental-Economic Accounting (SEEA) with a high sectorial detail matched with multiple social and environmental satellite accounts. In this paper, we present the latest developments realized with EXIOBASE 3—a time series of EE MRIO tables ranging from 1995 to 2011 for 44 countries (28 EU member plus 16 major economies) and five rest of the world regions. EXIOBASE 3 builds upon the previous versions of EXIOBASE by using rectangular supply-use tables (SUTs) in a 163 industry by 200 products classification as the main building blocks. In order to capture structural changes, economic developments, as repor ted by national statistical agencies, were imposed on the available, disaggregated SUTs from EXIOBASE 2. These initial estimates were further refined by incorporating detailed data on energy, agricultural production, resource extraction, and bilateral trade. EXIOBASE 3 inherits the high level of environmental stressor detail from its precursor, with further improvement in the level of detail for resource extraction. To account for the expansion of the European Union (EU), EXIOBASE 3 was developed with the full EU28 country set (including the new member state Croatia). EXIOBASE 3 provides a unique tool for analyzing the dynamics of environmental pressures of economic activities over time

Global priority areas for ecosystem restoration

Extensive ecosystem restoration is increasingly seen as being central to conserving biodiversity1 and stabilizing the climate of the Earth2. Although ambitious national and global targets have been set, global priority areas that account for spatial variation in benefits and costs have yet to be identified. Here we develop and apply a multicriteria optimization approach that identifies priority areas for restoration across all terrestrial biomes, and estimates their benefits and costs. We find that restoring 15% of converted lands in priority areas could avoid 60% of expected extinctions while sequestering 299 gigatonnes of CO2—30% of the total CO2 increase in the atmosphere since the Industrial Revolution. The inclusion of several biomes is key to achieving multiple benefits. Cost effectiveness can increase up to 13-fold when spatial allocation is optimized using our multicriteria approach, which highlights the importance of spatial planning. Our results confirm the vast potential contributions of restoration to addressing global challenges, while underscoring the necessity of pursuing these goals synergistically.Fil: Strassburg, Bernardo B. N.. Pontifícia Universidade Católica do Rio de Janeiro; Brasil. Universidade Federal do Rio de Janeiro; BrasilFil: Iribarrem, Alvaro. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Beyer, Hawthorne L.. The University of Queensland; Australia. University of Queensland; AustraliaFil: Cordeiro, Carlos Leandro. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Crouzeilles, Renato. Universidade Federal do Rio de Janeiro; Brasil. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Jakovac, Catarina C.. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Braga Junqueira, André. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Lacerda, Eduardo. Pontifícia Universidade Católica do Rio de Janeiro; Brasil. Universidade Federal Fluminense; BrasilFil: Latawiec, Agnieszka E.. University of East Anglia; Reino Unido. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Balmford, Andrew. University of Cambridge; Estados UnidosFil: Brooks, Thomas M.. University Of The Philippines Los Banos; Filipinas. Institute For Marine And Antarctic Studies; Australia. International Union For Conservation Of Nature And Natural Resources; SuizaFil: Butchart, Stuart H. M.. University of Cambridge; Estados UnidosFil: Chazdon, Robin L.. University Of The Sunshine Coast; Australia. University of Connecticut; Estados UnidosFil: Erb, Karl-Heinz. Universitat Fur Bodenkultur Wien; AustriaFil: Brancalion, Pedro. Universidade de Sao Paulo; BrasilFil: Buchanan, Graeme. Royal Society For The Protection Of Birds; Reino UnidoFil: Cooper, David. Secretariat Of The Convention On Biological Diversity; CanadáFil: Díaz, Sandra Myrna. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Donald, Paul F.. University of Cambridge; Estados UnidosFil: Kapos, Valerie. United Nations Environment Programme World Conservation Monitoring Centre; Reino UnidoFil: Leclère, David. International Institute For Applied Systems Analysis, Laxenburg; AustriaFil: Miles, Lera. United Nations Environment Programme World Conservation Monitoring Centre; Reino UnidoFil: Obersteiner, Michael. Oxford Social Sciences Division; Reino Unido. International Institute For Applied Systems Analysis, Laxenburg; AustriaFil: Plutzar, Christoph. Universitat Fur Bodenkultur Wien; Austria. Universidad de Viena; AustriaFil: de M. Scaramuzza, Carlos Alberto. International Institute For Sustainability; BrasilFil: Scarano, Fabio R.. Universidade Federal do Rio de Janeiro; BrasilFil: Visconti, Piero. International Institute For Applied Systems Analysis, Laxenburg; Austri

High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany

The dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Two main types of data are currently used to map stocks, night-time lights (NTL) from Earth-observing (EO) satellites and cadastral information. We present an alternative approach for broad-scale material stock mapping based on freely available high-resolution EO imagery and OpenStreetMap data. Maps of built-up surface area, building height, and building types were derived from optical Sentinel-2 and radar Sentinel-1 satellite data to map patterns of material stocks for Austria and Germany. Using material intensity factors, we calculated the mass of different types of buildings and infrastructures, distinguishing eight types of materials, at 10 m spatial resolution. The total mass of buildings and infrastructures in 2018 amounted to ∼5 Gt in Austria and ∼38 Gt in Germany (AT: ∼540 t/cap, DE: ∼450 t/cap). Cross-checks with independent data sources at various scales suggested that the method may yield more complete results than other data sources but could not rule out possible overestimations. The method yields thematic differentiations not possible with NTL, avoids the use of costly cadastral data, and is suitable for mapping larger areas and tracing trends over time

Characteristics and drivers of forest cover change in the post-socialist era in Croatia: evidence from a mixed-methods approach

© 2016, Springer-Verlag Berlin Heidelberg.Extensive forests in Croatia represent an important biological and economic resource in Europe. They are characterised by heterogeneity in forest management practices dating back to the socialist planned economy of the pre-1991 era. In this study we investigated the difference in rates of deforestation and reforestation in private- and state-owned forests during the post-socialist period and the causal drivers of change. The selected region of Northern Croatia is characterised by a high percentage of privately owned forests with minimal national monitoring and control. We used a mixed-methods approach which combines remote sensing, statistical modelling and a household-based questionnaire survey to assess the rates of forest cover change and factors influencing those changes. The results show that predominantly privately owned forests in Northern Croatia have recorded a net forest loss of 1.8 % during the 1991–2011 period, while Croatia overall is characterised by a 10 % forest cover increase in predominantly state-owned forests. Main factors influencing forest cover changes in private forests are slope, altitude, education structure, population age and population density. The results also show that the deforestation in private forests is weakening overall, mostly due to the continuation of the de-agrarisation and de-ruralisation processes which began during socialism

Towards an integrated model of socioeconomic biodiversity drivers, pressures and impacts. A feasibility study based on three European long-term socio-ecological research platforms

Effective policies to slow the rate of anthropogenic biodiversity loss should reduce socioeconomic pressures on biodiversity, either directly or by modifying their underlying socioeconomic driving forces. The design of such policies is currently hampered by the limited understanding of socioeconomic drivers of and pressures on biodiversity as well as by lacking data, indicators and models. In order to improve understanding of these issues we here propose a conceptual model of socioeconomic biodiversity drivers and pressures. The model is based on the drivers-pressures-impacts-states-responses (DPSIR) scheme and on the socioeconomic metabolism approach. The aim of the model is to guide research aimed at improving our understanding of socioeconomic biodiversity pressures and drivers and to serve as a basis for the development of formal, quantitative models in that field. Based on three European long-term socio-ecological research (LTSER) platforms, we analyze the model's applicability and suitability as well as data availability and research needs. These platforms are the Danube Delta Wetland System in Romania, the Doñana in Spain and the Eisenwurzen in Austria. An empirical analysis of the relationship between the human appropriation of net primary production (HANPP) and breeding bird richness in the Eisenwurzen demonstrates the ability of HANPP to provide a link between socioeconomic pressures/drivers and biodiversity. The analysis of the case studies underlines the potential utility of the conceptual model to guide future research into socioeconomic biodiversity drivers and pressures. However, considerable investments in monitoring and reconstruction of past trajectories as well as in model development will be required before mathematical (computer) models of the interrelation processes between society and ecosystems can be successfully deployed. © 2008 Elsevier B.V. All rights reserved.Peer Reviewe