Impacts of commodity prices and governance on the expansion of tropical agricultural frontiers.

Deforestation in the tropics remains a significant global challenge linked to carbon emissions and biodiversity loss. Agriculture, forestry, wildfires, and urbanization have been repeatedly identified as main drivers of tropical deforestation. Understanding the underlying mechanisms behind these direct causes is crucial to navigate the multiple tradeoffs between competing forest uses, such as food and biomass production (SDG 2), climate action (SDG 13), and life on land (SDG 15). This paper develops and implements a global-scale empirical approach to quantify two key factors affecting land use decisions at tropical forest frontiers: agricultural commodity prices and national governance. It relies on data covering the period 2004-2015 from multiple public sources, aggregated to countries and agro-ecological zones. Our analysis confirms the persistent influence of commodity prices on agricultural land expansion, especially in forest-abundant regions. Economic and environmental governance quality co-determines processes of expansion and contraction of agricultural land in the tropics, yet at much smaller magnitudes than other drivers. We derive land supply elasticities for direct use in standard economic impact assessment models and demonstrate that our results make a difference in a Computable General Equilibrium framework.

Clinical Impact and Management of Incidental Renal Findings on Pre-TAVI CT Scan from the Urologist's Perspective.

INTRODUCTION: The aim of the study was to investigate prevalence and impact of incidental renal masses (IRMs) accompanying increasing computed tomography (CT) work-up for symptomatic aortic valve stenosis (sAVS) of the elderly with regard to the relevance of urological consultation for overall survival (OS). METHODS: A retrospective analysis of pre-transcatheter aortic-valve implantations (TAVIs) CT scans of patients with sAVS (N = 1,253) harboring IRM was performed for 2014-2019. According to the clinical management, groups 1 (urologic consultation) and 2 (findings ignored) were formed and analyzed in terms of OS. RESULTS: The prevalence of IRM was 9% (119/1,253). In 19% (23/119), urological advice was sought (group 1). At baseline, group 1 showed a significantly higher rate of malignancy-specific lesions compared to 2 (p < 0.01). Other clinical parameters (e.g., age, cardiological scores, comorbidities) did not differ between groups (p > 0.05). In group 1, 4 (17%) findings were histologically confirmed, of which 3 (13%) underwent surgery. There was no significant difference in median OS at a median follow-up of 24.7 months between groups 1 and 2 with 35.7 (95% CI, 5.9; 65.4) and 47.4 months (95% CI, 33.0; 61.7), respectively (p = 0.4). In Cox regression analysis, chronic kidney disease but not urologic work-up or chronic obstructive pulmonary disease or heart failure emerged as an independent unfavorable predictor of OS (HR 2.44, 95% CI 1.37; 4.36, p = 0.003). CONCLUSION: For the first time, a TAVI population with IRM was analyzed from the urologist's perspective. Urologic co-evaluation and work-up does not confer a significant benefit in terms of OS in this particular population.

Behavioral factors driving farmers' intentions to adopt spot spraying for sustainable weed control.

Smart Farming Technologies enable plant-specific agrochemical applications which can increase the efficiency and reduce the environmental impacts of agriculture. However, the uptake of Smart Farming Technologies remains slow despite their potential to enhance sustainable transformation of food systems. The design of policies to promote sustainable agricultural technologies requires a holistic understanding of the complex set of factors driving the adoption of innovations at farm level. This study has a focus on behavioral factors, such as pro-environmental attitude, personal innovativeness and moral norms. Based on an online study conducted in Germany, structural equation modelling is applied to test the predictions of an extended version of the Theory of Planned Behavior, using spot spraying, a smart weeding technology, as an example. The results confirm theoretical predictions and show that indicators of attitude, subjective norms, and perceived behavioral control have relevant effects on farmers' adoption intentions. The extended model revealed a medium-sized (small) direct effect of moral norms on the attitude towards spot spraying (adoption intention). Personal innovativeness had a small effect on adoption intention, whereas pro-environmental attitude did not exhibit a clear direction of impact. Methodological and policy implications derived from the results are discussed noting that the inclusion of indicators for moral norms can improve the predictive power of models used in future research in this field. Overall, initiatives aimed at facilitating the exchange of opinions and related moral norms as well as collaboration among peers may contribute to voluntary sustainable innovation as it enhances adoption intentions among farmers.

Lessons from the historical dynamics of environmental law enforcement in the Brazilian Amazon.

Here, we analyze critical changes in environmental law enforcement in the Brazilian Amazon between 2000 and 2020. Based on a dataset of law enforcement indicators, we discuss how these changes explain recent Amazon deforestation dynamics. Our analysis also covers changes in the legal prosecution process and documents a militarization of enforcement between 2018 and 2022. From 2004 to 2018, 43.6 thousand land-use embargoes and 84.3 thousand fines were issued, targeting 3.3 million ha of land, and totaling USD 9.3 billion in penalties. Nevertheless, enforcement relaxed and became spatially more limited, signaling an increasing lack of commitment by the State to enforcing the law. The number of embargoes and asset confiscations dropped by 59% and 55% in 2019 and 2020, respectively. These changes were accompanied by a marked increase in enforcement expenditure, suggesting a massive efficiency loss. More importantly, the creation of so-called conciliation hearings and the centralization of legal processes in 2019 reduced the number of actual judgments and fines collected by 85% and decreased the ratio between lawsuits resulting in paid fines over filed ones from 17 to 5%. As Brazil gears up to crack-down on illegal deforestation once again, our assessment suggests urgent entry points for policy action.

Change in Splenic Volume as a Surrogate Marker for Immunotherapy Response in Patients with Advanced Urothelial and Renal Cell Carcinoma-Evaluation of a Novel Approach of Fully Automated Artificial Intelligence Based Splenic Segmentation.

BACKGROUND: In the treatment of advanced urothelial (aUC) and renal cell carcinoma (aRCC), biomarkers such as PD-1 and PD-L1 are not robust prognostic markers for immunotherapy (IO) response. Previously, a significant association between IO and a change in splenic volume (SV) was described for several tumour entities. To the best of our knowledge, this study presents the first correlation of SV to IO in aUC and aRCC. METHODS: All patients with aUC (05/2017-10/2021) and aRCC (01/2012-05/2022) treated with IO at our academic centre were included. SV was measured at baseline, 3 and 9 months after initiation of IO using an in-house developed convolutional neural network-based spleen segmentation method. Uni- and multivariate Cox regression models for overall survival (OS) and progression-free survival (PFS) were used. RESULTS: In total, 35 patients with aUC and 30 patients with aRCC were included in the analysis. Lower SV at the three-month follow-up was significantly associated with improved OS in the aRCC group. CONCLUSIONS: We describe a new, innovative artificial intelligence-based approach of a radiological surrogate marker for IO response in aUC and aRCC which presents a promising new predictive imaging marker. The data presented implicate improved OS with lower follow-up SV in patients with aRCC.

Action needed to make carbon offsets from forest conservation work for climate change mitigation.

Carbon offsets from voluntary avoided-deforestation projects are generated on the basis of performance in relation to ex ante deforestation baselines. We examined the effects of 26 such project sites in six countries on three continents using synthetic control methods for causal inference. We found that most projects have not significantly reduced deforestation. For projects that did, reductions were substantially lower than claimed. This reflects differences between the project ex ante baselines and ex post counterfactuals according to observed deforestation in control areas. Methodologies used to construct deforestation baselines for carbon offset interventions need urgent revisions to correctly attribute reduced deforestation to the projects, thus maintaining both incentives for forest conservation and the integrity of global carbon accounting.

COVID-19 in rural Africa: Food access disruptions, food insecurity and coping strategies in Kenya, Namibia, and Tanzania.

This study assesses the extent of COVID-19-related food insecurity in Kenya, Tanzania, and Namibia. Using the Household Food Insecurity Access Scale, we measure food insecurity in various dimensions and document several food access disruptions associated with the COVID-19 pandemic between April and July 2020. Furthermore, we assess the association of COVID-19 countermeasures with the adoption of various strategies in line with the coping strategies index. We rely on a unique phone survey that followed households who participated in an earlier field-based survey. First, through Ordinary Least-Squares and Probit regressions, we show a strong and statistically significant association between COVID-19 countermeasures and food access disruptions and food insecurity in each of the three countries. We then use a multivariate probit regression model to understand the use of the various coping strategies, including reducing food intake, increasing food search, and relying more on less nutritious foods. We provide evidence on the complementarities and trade-offs in using these coping strategies. COVID-19 and related lockdown measures coincided with a deleterious increase in food insecurity in rural Africa.

Exacerbated Age-Related Hippocampal Alterations of Microglia Morphology, ß-Amyloid and Lipofuscin Deposition and Presenilin Overexpression in Per1-/--Mice.

In humans, alterations of circadian rhythms and autophagy are linked to metabolic, cardiovascular and neurological dysfunction. Autophagy constitutes a specific form of cell recycling in many eukaryotic cells. Aging is the principal risk factor for the development of neurodegenerative diseases. Thus, we assume that both the circadian clock and autophagy are indispensable to counteract aging. We have previously shown that the hippocampus of Per1-/--mice exhibits a reduced autophagy and higher neuronal susceptibility to ischemic insults compared to wild type (WT). Therefore, we chose to study the link between aging and loss of clock gene Per1-/--mice. Young and aged C3H- and Per1-/--mice were used as models to analyze the hippocampal distribution of Aß42, lipofuscin, presenilin, microglia, synaptophysin and doublecortin. We detected several changes in the hippocampus of aged Per1-/--mice compared to their wild type littermates. Our results show significant alterations of microglia morphology, an increase in Aß42 deposition, overexpression of presenilin, decrease in synaptophysin levels and massive accumulation of lipofuscin in the hippocampus of 24-month-old Per1-/--mice, without alteration of adult neurogenesis. We suggest that the marked lipofuscin accumulation, Aß42 deposition, and overexpression of presenilin-2 observed in our experiments may be some of the consequences of the slowed autophagy in the hippocampus of aged Per1-/--mice. This may lead during aging to excessive accumulation of misfolded proteins which may, consequently, result in higher neuronal vulnerability.

Deforestation reduces rainfall and agricultural revenues in the Brazilian Amazon.

It has been suggested that rainfall in the Amazon decreases if forest loss exceeds some threshold, but the specific value of this threshold remains uncertain. Here, we investigate the relationship between historical deforestation and rainfall at different geographical scales across the Southern Brazilian Amazon (SBA). We also assess impacts of deforestation policy scenarios on the region's agriculture. Forest loss of up to 55-60% within 28 km grid cells enhances rainfall, but further deforestation reduces rainfall precipitously. This threshold is lower at larger scales (45-50% at 56 km and 25-30% at 112 km grid cells), while rainfall decreases linearly within 224 km grid cells. Widespread deforestation results in a hydrological and economic negative-sum game, because lower rainfall and agricultural productivity at larger scales outdo local gains. Under a weak governance scenario, SBA may lose 56% of its forests by 2050. Reducing deforestation prevents agricultural losses in SBA up to US$ 1 billion annually.

Overstated carbon emission reductions from voluntary REDD+ projects in the Brazilian Amazon.

Reducing emissions from deforestation and forest degradation (REDD+) has gained international attention over the past decade, as manifested in both United Nations policy discussions and hundreds of voluntary projects launched to earn carbon-offset credits. There are ongoing discussions about whether and how projects should be integrated into national climate change mitigation efforts under the Paris Agreement. One consideration is whether these projects have generated additional impacts over and above national policies and other measures. To help inform these discussions, we compare the crediting baselines established ex-ante by voluntary REDD+ projects in the Brazilian Amazon to counterfactuals constructed ex-post based on the quasi-experimental synthetic control method. We find that the crediting baselines assume consistently higher deforestation than counterfactual forest loss in synthetic control sites. This gap is partially due to decreased deforestation in the Brazilian Amazon during the early implementation phase of the REDD+ projects considered here. This suggests that forest carbon finance must strike a balance between controlling conservation investment risk and ensuring the environmental integrity of carbon emission offsets. Relatedly, our results point to the need to better align project- and national-level carbon accounting.

FABIO-The Construction of the Food and Agriculture Biomass Input-Output Model.

Harvested biomass is linked to final consumption by networks of processes and actors that convert and distribute food and nonfood goods. Achieving a sustainable resource metabolism of the economy is an overarching challenge which manifests itself in a number of the UN Sustainable Development Goals. Modeling the physical dimensions of biomass conversion and distribution networks is essential to understanding the characteristics, drivers, and dynamics of the socio-economic biomass metabolism. In this paper, we present the Food and Agriculture Biomass Input-Output model (FABIO), a set of multiregional supply, use and input-output tables in physical units, that document the complex flows of agricultural and food products in the global economy. The model assembles FAOSTAT statistics reporting crop production, trade, and utilization in physical units, supplemented by data on technical and metabolic conversion efficiencies, into a consistent, balanced, input-output framework. FABIO covers 191 countries and 130 agriculture, food and forestry products from 1986 to 2013. The physical supply use tables offered by FABIO provide a comprehensive, transparent, and flexible structure for organizing data representing flows of materials within metabolic networks. They allow tracing of biomass flows and embodied environmental pressures along global supply chains at an unprecedented level of product and country detail and can help to answer a range of questions regarding environment, agriculture, and trade. Here we apply FABIO to the case of cropland footprints and show the evolution of consumption-based cropland demand in China, the E.U., and the U.S.A. for plant-based and livestock-based food and nonfood products.

Emerging Evidence on the Effectiveness of Tropical Forest Conservation.

The PLOS ONE Collection "Measuring forest conservation effectiveness" brings together a series of studies that evaluate the effectiveness of tropical forest conservation policies and programs with the goal of measuring conservation success and associated co-benefits. This overview piece describes the geographic and methodological scope of these studies, as well as the policy instruments covered in the Collection as of June 2016. Focusing on forest cover change, we systematically compare the conservation effects estimated by the studies and discuss them in the light of previous findings in the literature. Nine studies estimated that annual conservation impacts on forest cover were below one percent, with two exceptions in Mexico and Indonesia. Differences in effect sizes are not only driven by the choice of conservation measures. One key lesson from the studies is the need to move beyond the current scientific focus of estimating average effects of undifferentiated conservation programs. The specific elements of the program design and the implementation context are equally important factors for understanding the effectiveness of conservation programs. Particularly critical will be a better understanding of the causal mechanisms through which conservation programs have impacts. To achieve this understanding we need advances in both theory and methods.

Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.

Deforestation in the Brazilian Amazon has dropped substantially after a peak of over 27 thousand square kilometers in 2004. Starting in 2008, the Brazilian Ministry of the Environment has regularly published blacklists of critical districts with high annual forest loss. Farms in blacklisted districts face additional administrative hurdles to obtain authorization for clearing forests. In this paper we add to the existing literature on evaluating the Brazilian anti-deforestation policies by specifically quantifying the impact of blacklisting on deforestation. We first use spatial matching techniques using a set of covariates that includes official blacklisting criteria to identify control districts. We then explore the effect of blacklisting on change in deforestation in double difference regressions with panel data covering the period from 2002 to 2012. Multiple robustness checks are conducted including an analysis of potential causal mechanisms behind the success of the blacklist. We find that the blacklist has considerably reduced deforestation in the affected districts even after controlling for the potential mechanism effects of field-based enforcement, environmental registration campaigns, and rural credit.

Post-crackdown effectiveness of field-based forest law enforcement in the Brazilian Amazon.

Regulatory enforcement of forest conservation laws is often dismissed as an ineffective approach to reducing tropical forest loss. Yet, effective enforcement is often a precondition for alternative conservation measures, such as payments for environmental services, to achieve desired outcomes. Fair and efficient policies to reducing emissions from deforestation and forest degradation (REDD) will thus crucially depend on understanding the determinants and requirements of enforcement effectiveness. Among potential REDD candidate countries, Brazil is considered to possess the most advanced deforestation monitoring and enforcement infrastructure. This study explores a unique dataset of over 15 thousand point coordinates of enforcement missions in the Brazilian Amazon during 2009 and 2010, after major reductions of deforestation in the region. We study whether local deforestation patterns have been affected by field-based enforcement and to what extent these effects vary across administrative boundaries. Spatial matching and regression techniques are applied at different spatial resolutions. We find that field-based enforcement operations have not been universally effective in deterring deforestation during our observation period. Inspections have been most effective in reducing large-scale deforestation in the states of Mato Grosso and Pará, where average conservation effects were 4.0 and 9.9 hectares per inspection, respectively. Despite regional and actor-specific heterogeneity in inspection effectiveness, field-based law enforcement is highly cost-effective on average and might be enhanced by closer collaboration between national and state-level authorities.

Mixing carrots and sticks to conserve forests in the Brazilian Amazon: a spatial probabilistic modeling approach.

Annual forest loss in the Brazilian Amazon had in 2012 declined to less than 5,000 sqkm, from over 27,000 in 2004. Mounting empirical evidence suggests that changes in Brazilian law enforcement strategy and the related governance system may account for a large share of the overall success in curbing deforestation rates. At the same time, Brazil is experimenting with alternative approaches to compensate farmers for conservation actions through economic incentives, such as payments for environmental services, at various administrative levels. We develop a spatially explicit simulation model for deforestation decisions in response to policy incentives and disincentives. The model builds on elements of optimal enforcement theory and introduces the notion of imperfect payment contract enforcement in the context of avoided deforestation. We implement the simulations using official deforestation statistics and data collected from field-based forest law enforcement operations in the Amazon region. We show that a large-scale integration of payments with the existing regulatory enforcement strategy involves a tradeoff between the cost-effectiveness of forest conservation and landholder incomes. Introducing payments as a complementary policy measure increases policy implementation cost, reduces income losses for those hit hardest by law enforcement, and can provide additional income to some land users. The magnitude of the tradeoff varies in space, depending on deforestation patterns, conservation opportunity and enforcement costs. Enforcement effectiveness becomes a key determinant of efficiency in the overall policy mix.

Environmental Income and Rural Livelihoods: A Global-Comparative Analysis.

This paper presents results from a comparative analysis of environmental income from approximately 8000 households in 24 developing countries collected by research partners in CIFOR's Poverty Environment Network (PEN). Environmental income accounts for 28% of total household income, 77% of which comes from natural forests. Environmental income shares are higher for low-income households, but differences across income quintiles are less pronounced than previously thought. The poor rely more heavily on subsistence products such as wood fuels and wild foods, and on products harvested from natural areas other than forests. In absolute terms environmental income is approximately five times higher in the highest income quintile, compared to the two lowest quintiles.

Rural income and forest reliance in highland Guatemala.

This paper estimates rural household-level forest reliance in the western highlands of Guatemala using quantitative methods. Data were generated by the way of an in-depth household income survey, repeated quarterly between November 2005 and November 2006, in 11 villages (n = 149 randomly selected households). The main sources of income proved to be small-scale agriculture (53 % of total household income), wages (19 %) and environmental resources (14 %). The latter came primarily from forests (11 % on average). In the poorest quintile the forest income share was as high as 28 %. All households harvest and consume environmental products. In absolute terms, environmental income in the top quintile was 24 times higher than in the lowest. Timber and poles, seeds, firewood and leaf litter were the most important forest products. Households can be described as 'regular subsistence users': the share of subsistence income is high, with correspondingly weak integration into regional markets. Agricultural systems furthermore use important inputs from surrounding forests, although forests and agricultural uses compete in household specialization strategies. We find the main household determinants of forest income to be household size, education and asset values, as well as closeness to markets and agricultural productivity. Understanding these common but spatially differentiated patterns of environmental reliance may inform policies aimed at improving livelihoods and conserving forests.