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Can Joint Carbon and Biodiversity Management in Tropical Agroforestry Landscapes Be Optimized?
(2012)
Managing ecosystems for carbon storage may also benefit biodiversity conservation, but such a potential 'win-win' scenario has not yet been assessed for tropical agroforestry landscapes. We measured above-and below-ground carbon stocks as well as the species richness of four groups of plants and eight of animals on 14 representative plots in Sulawesi, Indonesia, ranging from natural rainforest to cacao agroforests that have replaced former natural forest. The conversion of natural forests with carbon stocks of 227-362 Mg C ha\(^{-1}\) to agroforests with 82-211 Mg C ha\(^{-1}\) showed no relationships to overall biodiversity but led to a significant loss of forest-related species richness. We conclude that the conservation of the forest-related biodiversity, and to a lesser degree of carbon stocks, mainly depends on the preservation of natural forest habitats. In the three most carbon-rich agroforestry systems, carbon stocks were about 60% of those of natural forest, suggesting that 1.6 ha of optimally managed agroforest can contribute to the conservation of carbon stocks as much as 1 ha of natural forest. However, agroforestry systems had comparatively low biodiversity, and we found no evidence for a tight link between carbon storage and biodiversity. Yet, potential win-win agroforestry management solutions include combining high shade-tree quality which favours biodiversity with cacao-yield adapted shade levels.
Background
Severe COVID-19 induced acute respiratory distress syndrome (ARDS) often requires extracorporeal membrane oxygenation (ECMO). Recent German health insurance data revealed low ICU survival rates. Patient characteristics and experience of the ECMO center may determine intensive care unit (ICU) survival. The current study aimed to identify factors affecting ICU survival of COVID-19 ECMO patients.
Methods
673 COVID-19 ARDS ECMO patients treated in 26 centers between January 1st 2020 and March 22nd 2021 were included. Data on clinical characteristics, adjunct therapies, complications, and outcome were documented. Block wise logistic regression analysis was applied to identify variables associated with ICU-survival.
Results
Most patients were between 50 and 70 years of age. PaO\(_{2}\)/FiO\(_{2}\) ratio prior to ECMO was 72 mmHg (IQR: 58–99). ICU survival was 31.4%. Survival was significantly lower during the 2nd wave of the COVID-19 pandemic. A subgroup of 284 (42%) patients fulfilling modified EOLIA criteria had a higher survival (38%) (p = 0.0014, OR 0.64 (CI 0.41–0.99)). Survival differed between low, intermediate, and high-volume centers with 20%, 30%, and 38%, respectively (p = 0.0024). Treatment in high volume centers resulted in an odds ratio of 0.55 (CI 0.28–1.02) compared to low volume centers. Additional factors associated with survival were younger age, shorter time between intubation and ECMO initiation, BMI > 35 (compared to < 25), absence of renal replacement therapy or major bleeding/thromboembolic events.
Conclusions
Structural and patient-related factors, including age, comorbidities and ECMO case volume, determined the survival of COVID-19 ECMO. These factors combined with a more liberal ECMO indication during the 2nd wave may explain the reasonably overall low survival rate. Careful selection of patients and treatment in high volume ECMO centers was associated with higher odds of ICU survival.