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At least 37 records · Page 2

Deforestation impacts network co-occurrence patterns of microbial communities in Amazon soils

Co-occurrence networks allow for the identification of potential associations among species, which may be important for understanding community assembly and ecosystem functions. We employed this strategy to examine prokaryotic co-occurrence patterns in the Amazon soils and the response of these patterns to land use change to pasture, with the hypothesis that altered microbial composition due to deforestation will mirror the co-occurrence patterns across prokaryotic taxa. In this study, we calculated Spearman correlations between operational taxonomic units (OTUs) as determined by 16S rRNA gene sequencing, and only robust correlations were considered for network construction (-0.80 ≥ ρ ≥ 0.80, adjusted P <0.01). The constructed network represents distinct forest and pasture components, with altered compositional and topological features. A comparative analysis between two representative modules of these contrasting ecosystems revealed novel information regarding changes to metabolic pathways related to nitrogen cycling. Our results showed that soil physicochemical properties such as temperature, C/N and H + +Al 3+ had a significant impact on prokaryotic communities, with alterations to network topologies. Taken together, changes in co-occurrence patterns and physicochemical properties may contribute to ecosystem processes including nitrification and denitrification, two important biogeochemical processes occurring in tropical forest systems.

54 ENVIRONMENTAL SCIENCES↗

Bio-Based Polyisoprene Can Mitigate Climate Change and Deforestation in Expanding Rubber Production

Biomass is a promising renewable feedstock to produce polyisoprene for the rubber industry. Through metabolic engineering, sugars derived from pretreated and hydrolyzed cellulose and hemicellulose can be directly fermented to isoprene to produce rubber. Here we investigate the life cycle environmental impact of isoprene fermentation to produce bio-polyisoprene from agricultural residues (of Zea mays L.). Results show that the greenhouse gas (GHG) intensity of bio-polyisoprene (−4.59 kg CO2e kg−1) is significantly lower than that of natural rubber (Hevea brasiliensis) and synthetic rubber (−0.79 and 2.41 kg CO2e kg−1, respectively), while supporting a circular biogenic carbon economy. We found the land use intensity of bio-polyisoprene to be 0.25 ha metric ton−1, which is 84% lower than that from rubber tree plantations. We compare the direct fermentation to isoprene results with indirect fermentation to isoprene through the intermediate, methyl butyl ether, where dehydration to isoprene is required. The direct fermentation of isoprene reduces reaction steps and unit operations, an expected outcome when employing process intensification, but our results show additional energy conservation and reduced contribution to climate change. Among the ReCiPe life cycle environmental impact metrics evaluated, air emission related impacts are high for bio-polyisoprene compared to those for natural and synthetic rubber. Those impacts can be reduced with air emission controls during production. All other metrics showed an improvement for bio-polyisoprene compared to natural and synthetic rubber.

Batten, Rahamim↗

Diazotrophs Show Signs of Restoration in Amazon Rain Forest Soils with Ecosystem Rehabilitation

Biological nitrogen fixation can be an important source of nitrogen in tropical forests that serve as a major CO 2 sink. Extensive deforestation of the Amazon is known to influence microbial communities and the biogeochemical cycles they mediate. However, it is unknown how diazotrophs (nitrogen-fixing microorganisms) respond to deforestation and subsequent ecosystem conversion to agriculture, as well as whether they can recover in secondary forests that are established after agriculture is abandoned. To address these knowledge gaps, here we combined a spatially explicit sampling approach with high-throughput sequencing of nifH genes. The main objectives were to assess the functional distance decay relationship of the diazotrophic bacterial community in a tropical forest ecosystem and to quantify the roles of various factors that drive the observed changes in the diazotrophic community structure. We observed an increase in local diazotrophic diversity (α-diversity) with a decrease in community turnover (β-diversity), associated with a shift in diazotrophic community structure as a result of the forest-to-pasture conversion. Both diazotrophic community turnover and structure showed signs of recovery in secondary forests. Changes in the diazotrophic community were primarily driven by the change in land use rather than differences in geochemical characteristics or geographic distances. The diazotroph communities in secondary forests resembled those in primary forests, suggesting that at least partial recovery of diazotrophs is possible following agricultural abandonment. IMPORTANCE The Amazon region is a major tropical forest region that is being deforested at an alarming rate to create space for cattle ranching and agriculture. Diazotrophs (nitrogen-fixing microorganisms) play an important role in supplying soil N for plant growth in tropical forests. It is unknown how diazotrophs respond to deforestation and whether they can recover in secondary forests that establish after agriculture is abandoned. Using high-throughput sequencing of nifH genes, we characterized the response of diazotrophs’ β-diversity and identified major drivers of changes in diazotrophs from forest-to-pasture and pasture-to-secondary-forest conversions. Studying the impact of land use change on diazotrophs is important for a better understanding of the impact of deforestation on tropical forest ecosystem functioning, and our results on the potential recovery of diazotrophs in secondary forests imply the possible restoration of ecosystem functions in secondary forests.

59 BASIC BIOLOGICAL SCIENCES↗

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗

Attributing land-use change carbon emissions to exported biomass

In this study, a simple, transparent and robust method is developed in which land-use change (LUC) emissions are retrospectively attributed to exported biomass products based on the agricultural area occupied for the production. LUC emissions account for approximately one-fifth of current greenhouse gas emissions. Increasing agricultural exports are becoming an important driver of deforestation. Brazil and Indonesia are used as case studies due to their significant deforestation in recent years. According to our study, in 2007, approximately 32% and 15% of the total agricultural land harvested and LUC emissions in Brazil and Indonesia respectively were due to exports. The most important exported single items with regard to deforestation were palm oil for Indonesia and bovine meat for Brazil. To reduce greenhouse gas (GHG) emissions effectively worldwide, leakage of emissions should be avoided. This can be done, for example, by attributing embodied LUC emissions to exported biomass products. With the approach developed in this study, controversial attribution between direct and indirect LUC and amortization of emissions over the product life cycle can be overcome, as the method operates on an average basis and annual level. The approach could be considered in the context of the UNFCCC climate policy instead of, or alongside with, other instruments aimed at reducing deforestation. However, the quality of the data should be improved and some methodological issues, such as the allocation procedure in multiproduct systems and the possible dilution effect through third parties not committed to emission reduction targets, should be considered. - Highlights: Black-Right-Pointing-Pointer CO{sub 2} emissions from land use changes are highly important. Black-Right-Pointing-Pointer Attribution of land use changes for products is difficult. Black-Right-Pointing-Pointer Simple and robust method is developed to attribute land use change emissions.

54 ENVIRONMENTAL SCIENCES↗

The time since land-use transition drives changes in fire activity in the Amazon-Cerrado region

Abstract Deforestation and climate change are expected to alter fire regimes along the Cerrado-Amazon transition, one of the world’s most active agricultural frontiers. Here we tested the hypothesis that the time since land-use transition (age of frontier) and agricultural intensification also drive changes in the region’s fire regimes by reducing fire probability in both drought and non-drought years. We modeled fire probability as a function of the time since land-use transitions based on MapBiomas Project datasets from 1986 to 2020. We find that, while burned area declined as pasturelands aged and croplands advanced, deforestation abruptly increased fire activity before (Amazon: 4 years; Cerrado: 3 years) and after (Amazon: 8 years; Cerrado: 7 years) land clearing for pasture, especially in the Amazon. Additionally, the combination of ignition risk, drought, and air-dryness increased the likelihood of large extents of burned areas associated with deforestation. Incorporating frontier age as a proxy for governance in fire modeling is crucial, given the ecological implications of changing fire regimes despite declining rates of fire probability. Most importantly, protecting against deforestation and preserving native vegetation are vital.

Environmental Sciences & Ecology↗

The drivers and impacts of Amazon forest degradation

Approximately 2.5 × 10 6 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year –1 ), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year –1 ). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. In conclusion, policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.

54 ENVIRONMENTAL SCIENCES↗

Ecological connectivity and habitat loss shape patterns of genetic diversity in a threatened salamander

Context The maintenance of genetic diversity is essential for preserving adaptive potential in populations, yet it is increasingly threatened by landscape alteration. The field of landscape genetics offers a framework for assessing how patch-level landscape conditions, modeled at multiple scales, influence genetic diversity. Objectives We sought to assess how local environmental features and connectivity influence genetic diversity across 74 four-toed salamander (Hemidactylium scutatum) breeding wetlands in the southeastern United States. Methods Using next-generation sequencing data and hierarchical Bayesian models, we examined genome-wide heterozygosity in relation to local landscape features and ecological connectivity. We also assessed the scale of effect of landscape features and tested for temporal lag effects. Results Genetic diversity was lower in wetlands with higher levels of historic deforestation and lower connectivity. An interaction between deforestation and connectivity indicated that deforestation had stronger negative effects in isolated wetlands but weaker effects in well-connected wetlands. Accounting for scale of effect and temporal lags was critical for detecting these relationships. Conclusions Our analyses highlight the importance of assessing the spatial scale (scale of effect) and temporal lag of landscape features to detect key drivers of genetic diversity. In line with population genetic theory, our results indicate that the genetic consequences of habitat loss do not affect populations uniformly and are most severe in isolated populations where gene flow cannot buffer against loss of diversity. Altogether, we highlight the importance of considering the interaction of habitat loss and connectivity in conservation genetic management.

Hemidactylium scutatum↗

Fire dynamics during the 20th century simulated by the Community Land Model

Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite-based estimates in terms of magnitude and spatial extent as well as interannual and seasonal variability. Long-term trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtained substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997 2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite-based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000 2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we predicted a slight downward trend in global fire emissions caused by reduced fuels as a consequence of wood harvesting and also by increases in fire suppression. The model predicted an upward trend during the last three decades of the 20th century as a result of climate variations and large burning events associated with ENSO-induced drought conditions.

09 BIOMASS FUELS↗

Harmonising the land-use flux estimates of global models and national inventories for 2000–2020

As the focus of climate policy shifts from pledges to implementation, there is a growing need to track progress on climate change mitigation at the country level, particularly for the land-use sector. Despite new tools and models providing unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO 2 fluxes between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess compliance with national climate targets under the Paris Agreement and, on the other hand, the Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to inconsistent definitions of anthropogenic CO 2 fluxes in managed forests. Countries assume larger areas of forest to be managed than BMs do, due to a broader definition of managed land in NGHGIs. Additionally, the fraction of the land sink caused by indirect effects of human-induced environmental change (e.g. fertilisation effect on vegetation growth due to increased atmospheric CO 2 concentration) on managed lands is treated as non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the CO 2 sink caused by environmental change in countries' managed forests (estimated by 16 dynamic global vegetation models, DGVMs) to the land-use fluxes from three BMs. This sum is conceptually more comparable to NGHGIs and is thus expected to be quantitatively more similar. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of regions, countries and land categories (i.e. forest land, deforestation, organic soils, other land uses). Our results confirm a large difference (6.7 GtCO 2 yr —1 ) in global land-use CO 2 fluxes between the ensemble mean of the BMs, which estimate a source of 4.8 GtCO 2 yr —1 for the period 2000–2020, and NGHGIs, which estimate a sink of —1.9 GtCO 2 yr —1 in the same period. Most of the gap is found on forest land (3.5 GtCO 2 yr —1 ), with differences also for deforestation (2.4 GtCO 2 yr —1 ), for fluxes from other land uses (1.0 GtCO 2 yr —1 ) and to a lesser extent for fluxes from organic soils (0.2 GtCO 2 yr —1 ). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (—6.4 GtCO 2 yr —1 ) to BM estimates, the gap between BMs and NGHGIs becomes substantially smaller both globally (residual gap: 0.3 GtCO 2 yr —1 ) and in most regions and countries. However, some discrepancies remain and deserve further investigation. For example, the BMs generally provide higher emissions from deforestation than NGHGIs and, when adjusted with the sink in managed forests estimated by DGVMs, yield a sink that is often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations of anthropogenic land-use fluxes, allowing for detailed comparisons between global models and national inventories at global, regional and country levels. This is crucial to increase confidence in land-use emissions estimates, support investments in land-based mitigation strategies and assess the countries' collective progress under the Global Stocktake of the Paris Agreement.

54 ENVIRONMENTAL SCIENCES↗

Emissions Scenarios, Costs, and Implementation Considerations of REDD Programs

Greenhouse gas emissions from the forestry sector are estimated to be 8.4 GtCO2-eq./year or about 17percent of the global emissions. We estimate that the cost forreducing deforestation is low in Africa and several times higher in Latin America and Southeast Asia. These cost estimates are sensitive to the uncertainties of how muchunsustainable high-revenue logging occurs, little understood transaction and program implementation costs, and barriers to implementation including governance issues. Due to lack of capacity in the affected countries, achieving reduction or avoidance of carbon emissions will require extensive REDD-plus programs. Preliminary REDD-plus Readiness cost estimates and program descriptions for Indonesia, Democratic Republic of the Congo, Ghana, Guyana and Mexico show that roughly one-third of potential REDD-plus mitigation benefits might come from avoided deforestation and the rest from avoided forest degradation and other REDD-plus activities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Update on CO2 emissions

Emissions of CO2 are the main contributor to anthropogenic climate change. Here we present updated information on their present and near-future estimates. We calculate that global CO2 emissions from fossil fuel burning decreased by 1.3% in 2009 owing to the global financial and economic crisis that started in 2008; this is half the decrease anticipated a year ago1. If economic growth proceeds as expected2, emissions are projected to increase by more than 3% in 2010, approaching the high emissions growth rates that were observed from 2000 to 20081, 3, 4. We estimate that recent CO2 emissions from deforestation and other land-use changes (LUCs) have declined compared with the 1990s, primarily because of reduced rates of deforestation in the tropics5 and a smaller contribution owing to forest regrowth elsewhere.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Climate mitigation and the future of tropical landscapes

Land use change to meet 21st Century demands for food, fuel, and fiber will occur in the context of both a changing climate as well as societal efforts to mitigate climate change. This changing natural and human environment will have large consequences for forest resources, terrestrial carbon storage and emissions, and food and energy crop production over the next century. Any climate change mitigation policies enacted will change the environment under which land-use decisions are made and alter global land use change patterns. Here we use the GCAM integrated assessment model to explore how climate mitigation policies that achieve a climate stabilization at 4.5 W m-2 radiative forcing in 2100 and value carbon in terrestrial ecosystems interact with future agricultural productivity and food and energy demands to influence land use in the tropics. The regional land use results are downscaled from GCAM regions to produce gridded maps of tropical land use change. We find that tropical forests are preserved only in cases where a climate mitigation policy that values terrestrial carbon is in place, and crop productivity growth continues throughout the century. Crop productivity growth is also necessary to avoid large scale deforestation globally and enable the production of bioenergy crops. The terrestrial carbon pricing assumptions in GCAM are effective at avoiding deforestation even when cropland must expand to meet future food demand.

54 ENVIRONMENTAL SCIENCES↗