Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project DOI Creative Commons
Stephen Sitch, Michael O’Sullivan, Eddy Robertson

et al.

Global Biogeochemical Cycles, Journal Year: 2024, Volume and Issue: 38(7)

Published: July 1, 2024

Abstract The terrestrial biosphere plays a major role in the global carbon cycle, and there is recognized need for regularly updated estimates of land‐atmosphere exchange at regional scales. An international ensemble Dynamic Global Vegetation Models (DGVMs), known as “Trends drivers scale sources sinks dioxide” (TRENDY) project, quantifies land biophysical processes biogeochemistry cycles support annual Carbon Budget assessments REgional Cycle Assessment Processes, phase 2 project. DGVMs use common protocol set driving data sets. A factorial simulations allows attribution spatio‐temporal changes surface to three primary change drivers: atmospheric CO , climate variability, Land Use Cover Changes (LULCC). Here, we describe TRENDY benchmark DGVM performance using remote‐sensing other observational data, present results contemporary period. Simulation show large sink natural vegetation over 2012–2021, attributed fertilization effect (3.8 ± 0.8 PgC/yr) (−0.58 0.54 PgC/yr). Forests semi‐arid ecosystems contribute approximately equally mean trend sink, continue dominate interannual variability. offset by net emissions from LULCC (−1.6 0.5 PgC/yr), with 1.7 0.6 PgC/yr. Despite largest gross fluxes being tropics, simulated extratropical regions.

Language: Английский

Neglected tropical diseases risk correlates with poverty and early ecosystem destruction DOI Creative Commons
Arthur Ramalho Magalhães, Cláudia Torres Codeço, Jens‐Christian Svenning

et al.

Infectious Diseases of Poverty, Journal Year: 2023, Volume and Issue: 12(1)

Published: April 10, 2023

Abstract Background Neglected tropical diseases affect the most vulnerable populations and cause chronic debilitating disorders. Socioeconomic vulnerability is a well-known important determinant of neglected diseases. For example, poverty sanitation could influence parasite transmission. Nevertheless, quantitative impact socioeconomic conditions on disease transmission risk remains poorly explored. Methods This study investigated role variables in predictive capacity models zoonoses using decade epidemiological data (2007–2018) from Brazil. Vector-borne this included dengue, malaria, Chagas disease, leishmaniasis, Brazilian spotted fever, while directly-transmitted zoonotic schistosomiasis, leptospirosis, hantaviruses. Environmental predictors were combined with infectious to build environmental socioenvironmental sets ecological niche their performances compared. Results found be as influencing estimated likelihood across large spatial scales. The combination improved overall model accuracy (or power) by 10% average ( P < 0.01), reaching maximum 18% case dengue fever. Gross domestic product was variable (37% relative importance, all individual exhibited 0.00), showing decreasing relationship indicating major factor for Loss natural vegetation cover between 2008 2018 (42% 0.05) among models, exhibiting probability, that these are especially prevalent areas where ecosystem destruction its initial stages lower when more advanced stages. Conclusions Destruction ecosystems coupled low income explain macro-scale probability Addition improves forecasts tandem variables. Our results highlight efficiently address diseases, public health strategies must target both reduction cessation forests savannas.

Language: Английский

Citations

47
Carbon storage and sequestration in a eucalyptus productive zone in the Brazilian Cerrado, using the Ca-Markov/Random Forest and InVEST models DOI
Vitor Matheus Bacani, Bruno Henrique Machado da Silva, Amanda Ayumi de Souza Amede Sato

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 444, P. 141291 - 141291

Published: Feb. 15, 2024

Language: Английский

Citations

20
Geo-spatial analysis of urbanization and environmental changes with deep neural networks: Insights from a three-decade study in Kerch peninsula DOI Creative Commons
Денис Кривогуз

Ecological Informatics, Journal Year: 2024, Volume and Issue: 80, P. 102513 - 102513

Published: Feb. 7, 2024

This study presents a comprehensive analysis of land use and cover (LULC) changes on the Kerch Peninsula over last thirty years, utilizing advanced satellite data spatial modeling techniques. The research used Landsat 5, 7 8 images to capture intricate dynamics LULC from 1990 2020. A quantitative approach was adopted, involving convolutional neural networks (CNN) for enhanced classification accuracy. methodology allowed detailed precise identification various classes, revealing significant trends transformations in region's landscape. incorporated this exploration both large-scale patterns localized changes, providing insights into drivers consequences dynamics. statistical revealed notable increase urbanized areas, coupled with decline natural ecosystems such as forests wetlands. These reflect impact sustained urban growth agricultural expansion, underscoring need informed management conservation strategies. findings contribute understanding urbanization processes their ecological implications, valuable guidance sustainable regional planning environmental protection.

Language: Английский

Citations

18
Potential for Agricultural Expansion in Degraded Pasture Lands in Brazil Based on Geospatial Databases DOI Creative Commons
Édson Luís Bolfe, D. de C. Victoria, Edson Eyji Sano

et al.

Land, Journal Year: 2024, Volume and Issue: 13(2), P. 200 - 200

Published: Feb. 6, 2024

Important public and private initiatives to map agricultural lands natural resources have been carried out in Brazil support land use planning. Some studies indicate that still has up 109.7 million hectares of cultivated pastures with some level degradation, representing around 60% the total pasturelands, estimated at 177 hectares. This study aimed gather, process, analyze publicly available databases generate quantitative spatial information about potential Brazilian degraded for expansion. We considered data related potential, restrictions imposed by special areas (indigenous Afro-Brazilian “quilombola” settlements), high biodiversity conservation priorities, infrastructure such as distance between major highways availability warehouses, current areas, made Agricultural Climate Risk Zoning. The results indicated existence approximately 28 planted intermediate severe levels degradation show crops. These could increase grains 35% relation area used 2022/23 crop season.

Language: Английский

Citations

18
Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project DOI Creative Commons
Stephen Sitch, Michael O’Sullivan, Eddy Robertson

et al.

Global Biogeochemical Cycles, Journal Year: 2024, Volume and Issue: 38(7)

Published: July 1, 2024

Abstract The terrestrial biosphere plays a major role in the global carbon cycle, and there is recognized need for regularly updated estimates of land‐atmosphere exchange at regional scales. An international ensemble Dynamic Global Vegetation Models (DGVMs), known as “Trends drivers scale sources sinks dioxide” (TRENDY) project, quantifies land biophysical processes biogeochemistry cycles support annual Carbon Budget assessments REgional Cycle Assessment Processes, phase 2 project. DGVMs use common protocol set driving data sets. A factorial simulations allows attribution spatio‐temporal changes surface to three primary change drivers: atmospheric CO , climate variability, Land Use Cover Changes (LULCC). Here, we describe TRENDY benchmark DGVM performance using remote‐sensing other observational data, present results contemporary period. Simulation show large sink natural vegetation over 2012–2021, attributed fertilization effect (3.8 ± 0.8 PgC/yr) (−0.58 0.54 PgC/yr). Forests semi‐arid ecosystems contribute approximately equally mean trend sink, continue dominate interannual variability. offset by net emissions from LULCC (−1.6 0.5 PgC/yr), with 1.7 0.6 PgC/yr. Despite largest gross fluxes being tropics, simulated extratropical regions.

Language: Английский

Citations

17