Large-scale commodity agriculture exacerbates the climatic impacts of Amazonian deforestation

In the Amazon rainforest, land use following deforestation is diverse and dynamic. Mounting evidence indicates that the climatic impacts of forest loss can also vary considerably, depending on specific features of the affected areas. The size of the deforested patches, for instance, was shown to modulate the characteristics of local climatic impacts. Nonetheless, the influence of different types of land use and management strategies on the magnitude of local climatic changes remains uncertain. Here, we evaluated the impacts of large-scale commodity farming and rural settlements on surface temperature, rainfall patterns, and energy fluxes. Our results reveal that changes in land–atmosphere coupling are induced not only by deforestation size but also, by land use type and management patterns inside the deforested areas. We provide evidence that, in comparison with rural settlements, deforestation caused by large-scale commodity agriculture is more likely to reduce convective rainfall and increase land surface temperature. We demonstrate that these differences are mainly caused by a more intensive management of the land, resulting in significantly lower vegetation cover throughout the year, which reduces latent heat flux. Our findings indicate an urgent need for alternative agricultural practices, as well as forest restoration, for maintaining ecosystem processes and mitigating change in the local climates across the Amazon basin.

During the past 50 y, ∼20% of the Amazon forest has been lost to deforestation (1, 2). These changes in the land surface have affected the functioning of ecosystems and the climate in ways we are only starting to understand. Deforestation size, for instance, is a potential factor defining the magnitude and characteristics of changes in local climate associated with forest loss (3, 4). There is also evidence that the different land uses that follow deforestation can regulate the magnitude of changes in surface energy balance and water cycle (5). Historically, there has been large variation in the characteristics and causes of deforestation (1, 6–9). In the area known as the “arc of deforestation,” two major processes have contributed to forest loss: government-supported rural settlements and expansion of market-focused large-scale agriculture (hereinafter referred to as “commodity agriculture”) (10, 11). Deforestation caused by these two types of farming systems has distinct characteristics, and each can have several variants.Rural settlements are generally associated with government colonization projects, migratory flow incentives, and the construction of new roads (7). In areas dominated by rural settlements, small properties with plots ranging from 25 to 100 ha are predominant (8, 9, 12). However, medium-sized properties ranging from 250 to 1,000 ha and farms larger than 1,000 ha may also occur. Activities inside these areas are characterized by livestock production (extensive pastures), small-scale crop production, and family farming (13). The establishment of small farms along main highways and secondary roads results in the well-known “fish bone” deforestation pattern.Forest areas taken by large-scale commodity agriculture represent a more recent stage of occupation, usually associated with spontaneous and economical migration but also, with changes in land use policies and market conditions (14). Agricultural activities aimed at commodity crop plantation are in general productive and often technologically advanced. The most common commodity crops in the Amazon region are soybean, maize, sorghum, and cotton. Nonetheless, forests are typically not converted directly into croplands, with pastures often used as a transitory land use. Permanent mid- to large-scale cattle ranching also occurs, although many of these areas are being rapidly converted into croplands (6, 14–16). Farm sizes can reach several thousand hectares. Properties are, therefore, bigger and more isolated, in comparison with rural settlements (13).Given the different characteristics of commodity agriculture and rural settlements, the spatiotemporal patterns of land cover biophysical properties can also differ considerably. In general, commodity crops cultivation involves an intensive use of the land, sometimes with two or more harvests per year (17). Hence, rapid changes in the vegetation cover, albedo, and evapotranspiration (ET) can occur (5, 18). On the other hand, in areas where small-scale pastures and agriculture are prevalent, the biophysical properties of the land surface are expected to vary less, given the less intensive use of the land (e.g., associated with family farming and agroforestry). Furthermore, modeling studies suggest that the type of vegetation involved in land cover conversions is important in determining the sign of the land change impacts (19). However, empirical studies are crucially needed to better understand how different land uses across the Amazon region affect the local and regional climate.Tropical deforestation has deep impacts on biophysical processes (1, 20–22), contributing to amplifying diurnal temperature variability (1.95 ± 0.08 °C) as well as increasing mean air temperature (∼1 °C) (23). The causes of increase in temperature are dominated by nonradiative mechanisms, in particular a decrease in latent heat flux (LE) (24). The cooling effects of albedo increase due to deforestation are in most cases outweighed by the warming effects of decreasing ET, leading to net warming (23–25).The impacts of Amazon deforestation on rainfall patterns are not yet fully understood (4). In the initial phases of deforestation, vegetation loss was shown to increase regional cloudiness and precipitation (3). In comparison with deforested areas, the greater humidity over forests leads to more convective available potential energy, which makes the atmospheric boundary layer more unstable (26). Conversely, small deforestation patches showed more active shallow convection, explaining the higher frequency of shallow clouds over deforested areas (26). However, it is unclear how these mechanisms change as deforested areas increase and land cover becomes more uniform. One hypothesis is that convective lifting mechanisms will lose force, and shallow clouds over deforested areas will no longer be favored. Modeling studies indicate that this shift is already happening in some parts of the Amazon, where deforestation has reached a point in which thermally dominated regime has declined, leading to a more dynamically driven hydroclimatic regime (27). A dynamically driven regime becomes dominant when differences in surface roughness between forest and forest clearings start to play a larger role in the atmospheric response, in comparison with the differences in the surface energy partitioning (28).As observational and modeling studies indicate that land use and management can play an important role in the climate system, overlooking these landscape heterogeneities can hinder an adequate response to the threats posed by human activities (29). Clarifying the climatic impacts of different land uses in the Amazon is crucial to foster informed plans for sustainable land management, in particular those aiming at strategies for climate change mitigation, maintenance of ecological functioning, and guarantying provision of essential ecosystem services. Here, we hypothesize that forest conversion to large-scale commodity agriculture is more detrimental to local climate than conversion to rural settlements. To test this hypothesis, we first evaluated whether or not land uses associated with commodity agriculture and rural settlements lead to quantitatively distinguishable land cover spatiotemporal patterns in regions with similar deforestation rates (1985 to 2018) and total deforested area in 2018. Next, we collected empirical evidence on how forest clearing associated with these two causes has affected local rainfall, surface temperature, and LE.     

Reductions in emissions from deforestation from Indonesia’s moratorium on new oil palm,timber, and logging concessions

To reduce greenhouse gas emissions from deforestation, Indonesia instituted a nationwide moratorium on new license areas (“concessions”) for oil palm plantations, timber plantations, and logging activity on primary forests and peat lands after May 2011. Here we indirectly evaluate the effectiveness of this policy using annual nationwide data on deforestation, concession licenses, and potential agricultural revenue from the decade preceding the moratorium. We estimate that on average granting a concession for oil palm, timber, or logging in Indonesia increased site-level deforestation rates by 17–127%, 44–129%, or 3.1–11.1%, respectively, above what would have occurred otherwise. We further estimate that if Indonesia’s moratorium had been in place from 2000 to 2010, then nationwide emissions from deforestation over that decade would have been 241–615 MtCO₂e (2.8–7.2%) lower without leakage, or 213–545 MtCO₂e (2.5–6.4%) lower with leakage. As a benchmark, an equivalent reduction in emissions could have been achieved using a carbon price-based instrument at a carbon price of $3.30–7.50/tCO₂e (mandatory) or $12.95–19.45/tCO₂e (voluntary). For Indonesia to have achieved its target of reducing emissions by 26%, the geographic scope of the moratorium would have had to expand beyond new concessions (15.0% of emissions from deforestation and peat degradation) to also include existing concessions (21.1% of emissions) and address deforestation outside of concessions and protected areas (58.7% of emissions). Place-based policies, such as moratoria, may be best thought of as bridge strategies that can be implemented rapidly while the institutions necessary to enable carbon price-based instruments are developed.Reducing deforestation in Indonesia can contribute to climate-change mitigation at a globally significant scale. Estimates of annual greenhouse gas emissions from deforestation in Indonesia and the associated degradation of peat soils ranged from 0.32 to 1.91 GtCO₂e during 2000–2010 (1–6) (SI Appendix, Fig. S1) relative to a global total of 40–49 GtCO₂e from 2000 to 2010 (7). Deforestation in Indonesia is largely driven by the expansion of profitable and legally sanctioned oil palm and timber plantations and logging operations (5, 8–13). National and provincial governments zone areas of forest land to be logged or converted to plantation agriculture, and then district governments issue licenses to individual companies for these purposes (“concessions”) (14, 15). Substantial deforestation occurs outside of legally sanctioned concession areas as well.In May 2010, the national government of Indonesia announced a moratorium prohibiting district governments from granting new concession licenses (16, 17). The moratorium covered licenses for three types of activities: (i) conversion of primary forests and peat lands to oil palm plantations (oil palm concessions); (ii) conversion of primary forests and peat lands to fast-growing tree plantations for pulp and paper (timber concessions); and (iii) logging of commercially valuable tree species within forests (logging concessions). The moratorium was enacted in the context of a national strategy for reducing emissions from deforestation (REDD+) (18), a national target of reducing greenhouse gas emissions projected to 2020 by 26–41% while increasing gross domestic product by 7% per year (19), and a $1 billion bilateral cooperative agreement with Norway on reducing emissions from deforestation (20). The moratorium came into force in May 2011 (21) and was extended in May 2013 for an additional 2 y (22).The moratorium was conceived as both a stepping-stone to reforming Indonesia’s complex forest tenure system and a mechanism for reducing deforestation in its own right (23). The moratorium has been criticized for not covering secondary (i.e., logged) forests, for providing potential loopholes for food and energy security, for periodic downward revisions to the total moratorium area, for leaving a grace period between the announcement and the implementation of the moratorium during which licenses could still be obtained, and for not curtailing deforestation within existing concessions (24–27). Furthermore it has been noted that Indonesia’s deforestation rate has continued an upward trend from 2000 through 2012, even after the implementation of the moratorium in 2011 (28, 29). However, the effectiveness of the moratorium in reducing emissions from deforestation has yet to be quantified. Deforestation in recent years might have been even higher in the absence of a moratorium.Here we have evaluated the effectiveness of the moratorium policy by analyzing annual nationwide data on deforestation, the boundaries and license dates of concessions, and potential agricultural revenue from 2000 to 2010, the decade preceding the moratorium. The decade preceding the moratorium is ideal for scenario analysis because we can’t know where concessions would have been designated post-2011 without a moratorium, but we do know where pre-2010 concessions would not have been with a moratorium. Thus, we are able to construct a counterfactual scenario in which the moratorium policy in its current form was applied over the previous decade, and compare emissions under this simulated scenario to the emissions that actually occurred.We first answered the question: How much did the designation of a concession increase local (grid cell-level) deforestation above what would have occurred there without a concession? We used panel econometric techniques to control for potentially confounding geographic and time-variant factors and to construct upper and lower bounds around the magnitude of the treatment effect. Next, we answered the question: How much lower would Indonesia’s emissions from deforestation have been from 2000 to 2010 if no new concessions had been granted on primary forests and peat lands during that period? We aggregated estimates of local (grid cell-level) land-use change to the national level, accounted for geographic displacement of deforestation caused by market feedbacks (“leakage”), and applied grid cell-specific carbon emission factors for deforestation and peat degradation. Finally, we answered the question: At what carbon price would a price-based instrument have achieved an equivalent reduction in emissions over the same time period? We compared the estimated emission reductions from the place-based moratorium policy with the estimated emission reductions from a hypothetical carbon price-based instrument, adapting the Open Source Impacts of REDD+ Incentives Spreadsheet (OSIRIS) Indonesia model (4). We examined both a mandatory carbon price-based instrument (e.g., a cap-and-trade or symmetric tax-and-subsidy program) and a voluntary carbon price-based instrument (e.g., a project-level REDD+ program with business-as-usual reference levels).With this paper we contribute to several literatures. First, we expand the literature on quasi-experimental evaluation of the causal impact of conservation measures (30), such as protected areas (31–33), payment-for-ecosystem-services programs (33, 34), logging concessions (35), and clearing bans (36), to include agricultural concessions. Even though agricultural concessions are used to legally sanction deforestation on at least 150 million hectares of forest in at least 12 countries (37), and curtailing the expansion of such concessions represents a potentially promising policy for reducing emissions from deforestation, the effects of agricultural concessions on deforestation have only been estimated obliquely in econometric studies exploring other topics (4, 38, 39). Additionally, to our knowledge our paper is the first to transform area-based treatment effects to emissions-based treatment effects. Second, our paper is rare in that it uses panel data and techniques. Nearly all previous spatially explicit econometric studies of land-use change have necessarily relied upon cross-sectional analyses because of data availability constraints. In a meta-analysis of 117 such studies (40), only three have previously used panel methods (39, 41, 42). This paper is at the forefront of what is likely to be a proliferation of panel econometric analyses enabled by the recent availability of reliable, annual, globally consistent data on patterns of forest loss (28). Third, our paper is rare in that it calibrates the effect of land-use designations empirically. Nearly all previous land-use change scenario analyses have assumed idealized perfect effectiveness of conservation measures or complete conversion without such measures. A recent review of this literature found that only 1 of 71 peer-reviewed studies explicitly incorporated the difference in probable threat between reserved and nonreserved scenarios (43). Finally, our paper is to our knowledge the first to compare the effectiveness of place-based policies with alternative carbon price-based instruments for climate change mitigation within a landscape.     

Actor-specific contributions to the deforestation slowdown in the Brazilian Amazon

Annual deforestation rates in the Brazilian Amazon fell by 77% between 2004 and 2011, yet have stabilized since 2009 at 5,000–7,000 km². We provide the first submunicipality assessment, to our knowledge, of actor-specific contributions to the deforestation slowdown by linking agricultural census and remote-sensing data on deforestation and forest degradation. Almost half (36,158 km²) of the deforestation between 2004 and 2011 occurred in areas dominated by larger properties (>500 ha), whereas only 12% (9,720 km²) occurred in areas dominated by smallholder properties (<100 ha). In addition, forests in areas dominated by smallholders tend to be less fragmented and less degraded. However, although annual deforestation rates fell during this period by 68–85% for all actors, the contribution of the largest landholders (>2,500 ha) to annual deforestation decreased over time (63% decrease between 2005 and 2011), whereas that of smallholders went up by a similar amount (69%) during the same period. In addition, the deforestation share attributable to remote areas increased by 88% between 2009 and 2011. These observations are consistent across the Brazilian Amazon, regardless of geographical differences in actor dominance or socioenvironmental context. Our findings suggest that deforestation policies to date, which have been particularly focused on command and control measures on larger properties in deforestation hotspots, may be increasingly limited in their effectiveness and fail to address all actors equally. Further reductions in deforestation are likely to be increasingly costly and require actor-tailored approaches, including better monitoring to detect small-scale deforestation and a shift toward more incentive-based conservation policies.By 2012, some 749,987 km² of forest, or about 20% of the original forest extent of the Brazilian Legal Amazon (BLA), had been cleared (1). Large areas of the remaining forests have been severely degraded and fragmented by logging, fire, and overhunting (2). The combined effects of deforestation and forest degradation threaten the maintenance of critical ecosystem services, including carbon storage and sequestration and the conservation of hydrological cycles, as well as the protection of globally significant biodiversity (2, 3). Much of the land already cleared for farming is poorly used (4), and despite the economic growth often associated with converting forests to farmland, many inhabitants of the Amazon continue to live in poverty (5).The BLA has experienced a dramatic slowdown in annual deforestation rates in the last decade, with a decrease of 83.5% by 2012, the lowest year on record, decreasing from a peak of 27,772 km² in 2004 (1). This slowdown has been driven by a combination of policy interventions, private sector initiatives, and market conditions (6). In 2004, in response to rising deforestation levels, the Brazilian federal government launched an interministerial process, the Action Plan for the Protection and Control of Deforestation in the Amazon (PPCDAm), encompassing a diverse set of policy interventions with three broad lines of action: land tenure regularization and the creation of new reserves (with about 500,000 km² of new reserves being created between 2004 and 2011) (7); increased land use monitoring and enforcement (supported by Brazil’s world-leading deforestation monitoring system) (8); and the promotion of more sustainable agricultural production systems (9, 10). This process, in turn, gave rise to a number of linked policy interventions, including the Critical Municipalities Program, which suspended access to agricultural credit and markets for the 36 most-deforesting municipalities (6). These government efforts to curb deforestation, particularly through command-and-control measures, are widely recognized as having played a key role in reducing deforestation (8, 11). That said, other regional initiatives and changes have also played important roles. These include the soy and beef moratoria of 2006 and 2009, driven by intense campaigning from nongovernmental actors; increased private sector engagement in responsible land-use practices (6); and market changes, including oscillations in the price of agricultural commodities and a periodic weakening of the dollar (8). However, since 2009, deforestation rates have stabilized at 5,000–7,000 km², and there was a relative annual increase in deforestation (+28%) in 2013 for the first time since 2008. Although annual rates of deforestation are still among the lowest levels recorded since monitoring began in 1988, the decline in deforestation reductions calls into question the continued effectiveness of current policy measures. Set against the national target of an 80% reduction (on a 1996–2005 baseline) by 2020, Brazil still needs to reduce annual deforestation rates to 3,800 km² from the more than 5,000 km² cleared in 2013 (8). Moreover, although deforestation rates have fallen, rates of forest degradation from selective logging, fire, and fragmentation have remained high or are increasing in many areas, threatening the ecological functioning and integrity of many remaining areas of forest (12).To achieve further reductions in deforestation and forest degradation, it is vital to have an in-depth understanding of the relative contributions of different types of actors to total deforestation and forest degradation, as well as how such contributions have changed during the deforestation slowdown period. Agricultural frontier expansion in the Amazon is a dynamic process in which land-use decisions are shaped by factors that are often specific to different actor groups. These actor differences include the availability of assets, cultural backgrounds, household life cycles, access to markets and technologies, and power relationships (13). Improving our understanding of the link between different actor groups and patterns of deforestation and forest degradation can help identify possible improvements in existing forest conservation and regional sustainable development policies.To date, two approaches have been used to understand the contribution of different actors to deforestation in the Amazon. First, actor contributions to deforestation have been assessed by linking data on land use change with data on land tenure on the scale of individual properties. However, this work has been restricted to relatively small geographical areas (14–16), and the findings are hard to generalize. Second, regional assessments have been conducted for the entire BLA by combining agricultural census data and remote sensing analyses aggregated at the scale of municipalities (13, 17), or by using the size of deforested patches as a proxy for the spatial distribution of deforestation activities of different actor groups (18, 19). Although these approaches address the entire BLA, they deal with relatively large geographic units. Thus, both approaches are limited in their ability to provide a reliable assessment of actor-specific contributions to deforestation for such a highly heterogeneous socioecological system as the Brazilian Amazon, which comprises more than 5 million km² and a diverse array of land-users (20).Here, we provide the first submunicipality scale assessment to our knowledge of actor-specific contributions to deforestation and forest degradation for the BLA during the slowdown period from 2004 to 2011. Similar to previous studies, we combine Brazilian government agricultural census and remote sensing data, but we do so at the scale of individual census tracts (CTs). Thus, our analysis draws on survey data from 13,303 CTs, comprising 3.5 million km² (69.9% of the BLA), instead of only 771 municipalities for the same area. Specifically, we quantify the absolute contribution of different actor types to total deforestation between 2004 and 2011, as well as their contribution to avoided deforestation relative to the mean deforestation rate observed during the official Brazilian government baseline period of 1996–2005; changes in the absolute and relative contribution of different actors to deforestation during the slowdown period; and actor-specific differences in levels of forest fragmentation and degradation. Actors are defined on the basis of differences in the size of dominant properties within each CT. CTs that lack census information on property size distributions because of their geographic isolation and low population density are classified as remote areas. We interpret these findings in the context of the ongoing decline in deforestation rates across the BLA and the challenges of further reducing deforestation while also promoting sustainable social and economic development.     

Satellite-based deforestation alerts with training and incentives for patrolling facilitate community monitoring in the Peruvian Amazon

Despite substantial investments in high-frequency, remote-sensed forest monitoring in the Amazon, early deforestation alerts generated by these systems rarely reach the most directly affected populations in time to deter deforestation. We study a community monitoring program that facilitated transfer of early deforestation alerts from the Global Forest Watch network to indigenous communities in the Peruvian Amazon and trained and incentivized community members to patrol forests in response to those alerts. The program was randomly assigned to 39 of 76 communities. The results from our analysis suggest that the program reduced tree cover loss, but the estimated effects from the experiment are imprecise: We estimate a reduction of 8.4 ha per community in the first year (95% CI [−19.4, 2.6]) and 3.3 ha in the second year (95% CI: [−13.6, 7.0]) of monitoring. The estimated reductions were largest in communities facing the largest threats. Data from monitoring records and community surveys provide evidence about how the program may affect forest outcomes. Community members perceived that the program’s monitors were new authorities with influence over forest management and that the monitors’ incentivized patrols were substitutes for traditional, unincentivized citizen patrols that suffer from free riding and inhibit timely community detection of and responses to deforestation. Should our findings be replicated elsewhere, they imply that externally facilitated community-based monitoring protocols that combine remote-sensed early deforestation alerts with training and incentives for monitors could contribute to sustainable forest management.

Accelerating deforestation of the Amazon rainforest represents a grave threat to local ecosystems with global consequences for the climate crisis and preservation of biodiversity (1, 2). Over the past 40 y, governments and international nongovernmental organizations have invested in the use of satellite monitoring systems for the detection and measurement of deforestation (3). National governments in Brazil, Peru, and Colombia have adopted alert systems that generate remote-sensed deforestation data that measure tree cover loss (4). While remote sensing technologies now provide frequent, high-resolution deforestation alerts (5), there is not evidence that instituting these alerts reduces subsequent deforestation globally or in Latin America (6). One possible reason for the limited efficacy of early alerts is that local governments and communities often lack access to the resultant data to respond to and prevent further deforestation (7).Several related challenges limit the efficacy of tropical forest protection policies in the Amazon. First, most national policies privilege centralized (state) prevention of deforestation or enforcement of antideforestation laws over community prevention efforts. However, state enforcement in remote regions of the Amazon is resource-intensive, and limited state capacity arguably curtails such enforcement. In turn, these failures of state enforcement leave populations living on the deforestation frontier—typically indigenous communities—responsible for confronting or deterring deforestation. Second, national investments in early deforestation alerts remain inaccessible to front-line communities (7). Thus, while community participation is central to the management of common pool resources (CPRs) (8–10), communities frequently lack information on where in vast communal forests deforestation has occurred until it is well under way and difficult to halt.Responding to these challenges, we examine the effects of a community monitoring program that combined the sharing of satellite-detected early deforestation alerts with training and incentives for patrolling community forests. The monitoring program, based in the Peruvian Amazon, addresses these shortcomings in existing policies by: 1) making remote-sensed early deforestation alerts accessible to forest communities; and 2) strengthening communities’ capacity for monitoring with training and incentives. Monitoring is well-documented as an institution that can facilitate sustainable governance of CPRs (11–13). The integration of remote-sensed alerts alongside training and incentives aims to increase the efficiency of monitoring by providing information on the location of tree cover loss in large communal territories.The program trained three monitors selected by each participating community to conduct monitoring of community forests using a smartphone mapping application (SI Appendix, Fig. S6). The monitors received monthly deforestation alerts from Peru’s national Geobosques platform for monitoring deforestation, which relies on estimates of tree cover loss from Landsat-based Global Forest Watch (GFW) data. Monitors were remunerated for conducting monthly patrols to investigate deforestation in community forests. With the information collected by monitors, communities made autonomous decisions on how to respond to potential threats, either through direct intervention or by alerting state authorities.We conduct a preregistered randomized controlled trial (RCT) in 76 communities in collaboration with local indigenous federations and Rainforest Foundation US, the nongovernmental organization (NGO) that designed and implemented the monitoring program. These communities depend on the natural resources afforded by the rivers and forests for their livelihoods and sustenance. Large-scale deforestation and degradation from timber extraction (14), slash-and-burn agriculture by invading settlers from the Peruvian highlands (15), and, increasingly, cultivation of low-altitude coca variants (16, 17) threaten the long-term survival of these communities.Our research design and data collection make two contributions. First, the experimental research design allows us to estimate the causal effects of the monitoring program on community resource governance and rates of tree cover loss. This study is part of a larger Evidence in Governance and Politics Metaketa initiative of six coordinated field experiments that test how external support for community monitoring affects the overuse or degradation of resources. The harmonized community monitoring treatments (SI Appendix, section SI1) facilitate a meta-analysis that is used to probe the external validity of our findings. The present paper contextualizes the findings from the experiment in Peru and elaborates study-specific policy implications. To date, there have been very few experimental studies of forest conservation (18), and the studies in this project represent early experimental studies of community monitoring on CPR governance.Second, we compile high-frequency data on monitoring and tree cover loss, an original household survey, and semistructured interviews. Using these data, we examine how the introduction of monitoring interacts with existing community dynamics by bridging existing large-N studies that rely upon remote-sensed data (9) and smaller-N case studies of indigenous communities’ forest-governance practices (19, 20).We find imprecisely estimated reductions in tree cover loss in the treatment communities. Over the first year of the program, tree cover loss decreased by 8.4 ha (95% CI: [−19.4,2.6]). These reductions are concentrated in the communities most vulnerable to deforestation: We find no evidence of tree cover loss in the half of communities predicted to be at low risk for deforestation based on past trends. However, we identify a reduction of 22.0 ha (95% CI: [−46.3,2.3]) in tree cover loss in the higher-risk half of communities. In the second year, the effects of monitoring were substantially attenuated: Tree cover loss decreased only 3.3 ha (95% CI: [−13.6,7.0]). We further show that monitoring practices became routinized over time in treatment communities, and monitors’ learning about where deforestation and degradation occurred led to more efficient detection of deforestation. Examining community governance, counter to our predictions, but consistent with recent findings elsewhere in Peru (21), we find that the treatment lowered community members’ willingness to participate in or contribute to collective action on forest issues. Instead, the monitoring program effectively moved the task of patrolling the forests—a public good—to the domain of trained, remunerated monitors, who function as bureaucrats. Effective “bureaucratization” of forest-patrol tasks formerly subject to collective action failures is consistent with suggestive evidence of reduced tree cover loss.     

Greenhouse gas emissions from alternative futures of deforestation and agricultural management in the southern Amazon

The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006–2050) impacts on carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO₂-equivalents (CO₂-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24–49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2–0.4 Pg CO₂-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.     

Deforestation and Malaria on the Amazon Frontier: Larval Clustering of Anopheles darlingi (Diptera: Culicidae) Determines Focal Distribution of Malaria

We performed bimonthly mosquito larval collections during 1 year, in an agricultural settlement in the Brazilian Amazon, as well as an analysis of malaria incidence in neighboring houses. Water collections located at forest fringes were more commonly positive for Anopheles darlingi larvae and Kulldorff spatial analysis pinpointed significant larval clusters at sites directly beneath forest fringes, which were called larval “hotspots.” Remote sensing identified 43 “potential” hotspots. Sampling of these areas revealed an 85.7% positivity rate for A. darlingi larvae. Malaria was correlated with shorter distances to potential hotpots and settlers living within 400 m of potential hotspots had a 2.60 higher risk of malaria. Recently arrived settlers, usually located closer to the tip of the triangularly shaped deforestation imprints of side roads, may be more exposed to malaria due to their proximity to the forest fringe. As deforestation progresses, transmission decreases. However, forest remnants inside deforested areas conferred an increased risk of malaria. We propose a model for explaining frontier malaria in the Amazon: because of adaptation of A. darlingi to the forest fringe ecotone, humans are exposed to an increased transmission risk when in proximity to these areas, especially when small dams are created on naturally running water collections.     

Protecting the Amazon with protected areas

This article addresses climate-tipping points in the Amazon Basin resulting from deforestation. It applies a regional climate model to assess whether the system of protected areas in Brazil is able to avoid such tipping points, with massive conversion to semiarid vegetation, particularly along the south and southeastern margins of the basin. The regional climate model produces spatially distributed annual rainfall under a variety of external forcing conditions, assuming that all land outside protected areas is deforested. It translates these results into dry season impacts on resident ecosystems and shows that Amazonian dry ecosystems in the southern and southeastern basin do not desiccate appreciably and that extensive areas experience an increase in precipitation. Nor do the moist forests dry out to an excessive amount. Evidently, Brazilian environmental policy has created a sustainable core of protected areas in the Amazon that buffers against potential climate-tipping points and protects the drier ecosystems of the basin. Thus, all efforts should be made to manage them effectively.     

Governance regime and location influence avoided deforestation success of protected areas in the Brazilian Amazon

Protected areas in tropical countries are managed under different governance regimes, the relative effectiveness of which in avoiding deforestation has been the subject of recent debates. Participants in these debates answer appeals for more strict protection with the argument that sustainable use areas and indigenous lands can balance deforestation pressures by leveraging local support to create and enforce protective regulations. Which protection strategy is more effective can also depend on (i) the level of deforestation pressures to which an area is exposed and (ii) the intensity of government enforcement. We examine this relationship empirically, using data from 292 protected areas in the Brazilian Amazon. We show that, for any given level of deforestation pressure, strictly protected areas consistently avoided more deforestation than sustainable use areas. Indigenous lands were particularly effective at avoiding deforestation in locations with high deforestation pressure. Findings were stable across two time periods featuring major shifts in the intensity of government enforcement. We also observed shifting trends in the location of protected areas, documenting that between 2000 and 2005 strictly protected areas were more likely to be established in high-pressure locations than in sustainable use areas and indigenous lands. Our findings confirm that all protection regimes helped reduce deforestation in the Brazilian Amazon.Terrestrial protected areas, an integral component of biodiversity conservation policy, have also become a centerpiece of global efforts to reduce carbon emissions from tropical deforestation (1). In the past decade, governments across the tropical biome have continued to expand their protected area networks (2), and international donors have pledged billions of dollars for forest-based climate change mitigation (3, 4). Situated at the overlap between multiple global and local interests (5, 6), protected areas are managed under a wide range of governance regimes to achieve better ecological and social outcomes. Although all these regimes establish some form of spatially explicit restrictions on land use and resource extraction, such restrictions can vary substantially (7).A common distinction between governance regimes is that between strictly protected areas that discourage consumptive resource use or even physical access and sustainable use areas that allow for controlled resource extraction, land use change, and in many instances human settlements (8). Indigenous lands, established primarily to safeguard the rights and livelihoods of indigenous people, are put forward as a third type of protected areas with considerable potential to contribute to climate change mitigation (9). Recent prospects of international carbon payments tied to avoided deforestation have reignited the interest of donors and governments to understand the extent to which each of these governance arrangements are effective in helping conserve tropical forest carbon (10, 11).Keen theoretical debates surround the extent to which controlled resource use in protected areas can reduce deforestation. Proponents of strict conservation have long argued that ruling out resource extraction coupled with enforcement by protected area guards is more likely to be effective at achieving conservation than more inclusionary approaches (12–15). Other contributors highlight that such enforcement has often proved insufficient to inhibit extraction in tropical parks (16–18) and that forest-dependent communities, including indigenous people, can have stronger incentives than disinterested or understaffed government agencies to protect their livelihood base against externally driven deforestation pressures (19–21). From this latter perspective, allowing controlled resource use in protected areas can help leverage local support for creating and enforcing regulations against such pressures (22, 23). Supporting indigenous communities in their efforts to demarcate and manage their territories promises similar synergies (24).Although these lines of argument differ, authors commonly identify two contextual factors as influencing the advantages of one protection regime over the other: (i) the willingness and capacity of government agencies to enforce conservation regulations and (ii) the intensity of deforestation pressures to which a given area is exposed. Whether and how the relative effectiveness of protection regimes varies along these contextual dimensions, however, remains poorly understood. High-pressure locations, for example, may prove particularly challenging for strict protected areas that lack local constituencies (25), but could facilitate external enforcement because of greater accessibility and lower travel costs (26). Indigenous actors have been characterized as both weak (27) and strong (9, 23, 28) in avoiding deforestation in high-pressure areas. Similarly, strengthening government enforcement and other regulatory policies could improve the performance of strictly protected areas. However, positive effects could be offset if enforcement displaced deforestation into less accessible parks (29) or increased subsistence deforestation in sustainable use areas and indigenous lands.Empirical evidence also continues to be inconclusive. Recent studies find evidence that sustainable use areas and indigenous lands tend to be situated in locations with higher deforestation pressure compared with strictly protected areas (8, 30–32), giving the former a greater potential to avoid deforestation (Fig. 1). In line with this observation, three studies have found that sustainable use areas and indigenous lands, in the aggregate, have avoided more deforestation and forest fires than strictly protected areas in the Brazilian Amazon and globally (8, 31, 32). Another study from Brazil suggests that strictly protected areas, in the aggregate, blocked deforestation pressures more successfully than did sustainable use areas, whereas indigenous lands were even more effective (36). Taken together, these studies seem to suggest that sustainable use areas and indigenous lands are more successful by virtue of location, whereas strictly protected areas and indigenous lands are more successful by virtue of successfully enforced regulations. However, more systematic empirical examination is necessary to understand the joint functional relationships between avoided deforestation, governance regimes, deforestation pressures, and government enforcement in tropical protected areas.Open in a separate windowFig. 1.Relationship between deforestation pressure (deforestation rate in the absence of protection) and impact of four imaginary protected areas: “A” has high deforestation rates, but is estimated to have avoided deforestation compared with what would have been expected in the absence of protection. “B” has deforestation rates identical to those of “A,” but due to its location in a low-pressure area is estimated to have increased deforestation (see note below). “C,” although perfectly untouched by deforestation, is estimated to have a lower absolute impact than “A.” Located in an area of extremely low deforestation pressure, “D” is “passively protected” (10) and will thus never be able to claim avoided deforestation, regardless of its observed deforestation rates. Note: Global protected area assessments have identified countries whose protected areas exhibit higher rates of land use change than the counterfactual of no protection (33). Although this phenomenon is poorly understood, which may point to methodological weaknesses, protected areas can have undesired negative effects, e.g., if resource users engage in environmentally degrading activities as a form of protest against protection (34, 35).We examined whether and how the effectiveness of 292 strictly protected areas, sustainable use areas, and indigenous lands in the Brazilian Amazon covaried with differences in deforestation pressure and federal government enforcement. Covering an area of more than 5 million km², the Brazilian Amazon exhibits significant spatial differences in terms of agricultural potential, transport infrastructure, and market access; as a result, deforestation pressures vary widely across the region. In addition, Brazil’s federal enforcement efforts underwent a major shift in recent history: Having made international headlines for a historical high in Amazon deforestation rates between 2000 and 2005, Brazil achieved radical reductions in deforestation rates in the second half of the past decade (37). Although part of these reductions were attributed to price declines of agricultural commodities, recent analyses also show that regulatory government policies—including a drastic increase in enforcement activities, embargoes on soy and beef markets in selected municipalities, and the expansion and strengthening of protected area networks—all contributed significantly to the observed reductions (36, 38, 39). By examining the relationships between avoided deforestation, protection type, and deforestation pressure in both the first and the second half of the past decade, our analysis sheds analytical and empirical light on how governance regime, location, and government enforcement jointly influence conservation outcomes in protected areas.     

Follow-up of participants in the Canadian Association of Gastroenterology Scholars’ Program, 2006 to 2012

The Canadian Association of Gastroenterology (CAG) Scholars’ Program (previously known as the Bright Lights Course) is designed to encourage trainees to consider a subspecialty career in gastroenterology. A formal analysis of the Scholars’ Program performed in 2007 revealed that 82% of participants invited to the program pursued or were planning to pursue a career in gastroenterology. The positive results are consistent with the CAG’s strategic plan of developing “the next generation of gastroenterology clinical practitioners, researchers, educators, and leaders” and to “attract, train, and retain the best and the brightest to gastroenterology”. The present study was a follow-up analysis of participants in the Scholars’ Program between 2006 and 2012. Although 93.1% of participants had an interest in gastroenterology before attending the Scholars’ Program, the majority (68.7%) reported a greater interest in gastroenterology after the program. Similar to the study from 2007, the present study again illustrates the importance and success of the Scholars’ Program in generating interest and retaining candidates in gastroenterology.     

Changes in Disability Levels Among Older Adults Experiencing Adverse Events in Postacute Rehabilitation Care: A Prospective Observational Study

This study aimed to assess the relationship between adverse events (AEs) and changes in the levels of disability from admission to discharge during inpatient rehabilitation programs.A prospective cohort study was conducted among a cohort of inpatients (216 older adults) admitted to a rehabilitation unit. The occurrences of any AE were reported. The level of disability regarding mobility activities was estimated using the disability qualifiers from the International Classification of Functioning, Disability, and Health. Changes in the levels of disability between admission and discharge were assessed. Baseline-measured covariates were also selected.Regarding all 4 disability levels (“no limitation,” “mild,” “moderate,” “severe,” and “complete disability”), a total of 159 participants experienced an improvement at discharge (126 participants progressed 1 level, whereas 33 improved 2 disability levels), 56 made no change, and no participants experienced a decline.The occurrence of fall-related events and the diagnostic group (musculoskeletal system) are specific predictive factors of change in the level of disability. The odds of undergoing a change in any disability level between admission and discharge decreases by 68% (1–0.32) when patients experience fall-related events (odds ratio [OR] = 0.32, 95% confidence interval [CI] = 0.11–0.97, P = 0.041) and increases for individuals with musculoskeletal conditions (OR = 3.91, 95% CI = 1.34–11.38, P = 0.012).Our findings suggest that increased efforts to prevent the occurrence of these AEs, together with early interventions suited to the diagnosis of the affected system, may have a positive influence on the improvement of disability. Further studies should evaluate disability over time after discharge to obtain a better sense of how transient or permanent the associated disability may be.     

Exploring the likelihood and mechanism of a climate-change-induced dieback of the Amazon rainforest

We examine the evidence for the possibility that 21st-century climate change may cause a large-scale “dieback” or degradation of Amazonian rainforest. We employ a new framework for evaluating the rainfall regime of tropical forests and from this deduce precipitation-based boundaries for current forest viability. We then examine climate simulations by 19 global climate models (GCMs) in this context and find that most tend to underestimate current rainfall. GCMs also vary greatly in their projections of future climate change in Amazonia. We attempt to take into account the differences between GCM-simulated and observed rainfall regimes in the 20th century. Our analysis suggests that dry-season water stress is likely to increase in E. Amazonia over the 21st century, but the region tends toward a climate more appropriate to seasonal forest than to savanna. These seasonal forests may be resilient to seasonal drought but are likely to face intensified water stress caused by higher temperatures and to be vulnerable to fires, which are at present naturally rare in much of Amazonia. The spread of fire ignition associated with advancing deforestation, logging, and fragmentation may act as nucleation points that trigger the transition of these seasonal forests into fire-dominated, low biomass forests. Conversely, deliberate limitation of deforestation and fire may be an effective intervention to maintain Amazonian forest resilience in the face of imposed 21st-century climate change. Such intervention may be enough to navigate E. Amazonia away from a possible “tipping point,” beyond which extensive rainforest would become unsustainable.     

Covid-fatigued? A longitudinal study of Norwegian older adults’ psychosocial well-being before and during early and later stages of the COVID-19 pandemic

As the pandemic continues, many older adults are facing prolonged isolation and stress while having less access to traditional ways of coping. There is widespread concern that the situation is increasingly taking its toll on older adults’ psychological and social well-being. We use linear mixed models to examine psychosocial impacts and predictors thereof among older Norwegians in early and later stages of the pandemic. Longitudinal data were collected online in the Norwegian Counties Public Health Survey right before the pandemic and in June and November–December 2020 in two counties (baseline n = 4,104; age 65–92). Outcomes include loneliness (single item, UCLA3), psychological ill-being (worried, anxious, depressed), and psychological well-being (satisfied, engaged, happy). From before to three months into the pandemic men’s psychosocial well-being remained stable, whereas women’s slightly declined. Five months later we observe broad and substantial declines in psychosocial well-being. These impacts disproportionately affect women (all outcomes) and single and older individuals (loneliness only) and are not moderated by educational level, urbanicity, or whether self or partner are reported “at risk” due to health problems. Pre-pandemic low social support and high psychological distress predict relatively improved psychosocial well-being. Older Norwegians seemed to manage the pandemic’s early stage without clear psychosocial impacts. However, we observe notably compromised well-being during the second wave of COVID-19 in late 2020. Lessons learned about the nature and distribution of the psychosocial impacts of prolonged health-threats and social distancing provide valuable knowledge for intervention design during this and future pandemics.     

Global cost estimates of reducing carbon emissions through avoided deforestation

Tropical deforestation is estimated to cause about one-quarter of anthropogenic carbon emissions, loss of biodiversity, and other environmental services. United Nations Framework Convention for Climate Change talks are now considering mechanisms for avoiding deforestation (AD), but the economic potential of AD has yet to be addressed. We use three economic models of global land use and management to analyze the potential contribution of AD activities to reduced greenhouse gas emissions. AD activities are found to be a competitive, low-cost abatement option. A program providing a 10% reduction in deforestation from 2005 to 2030 could provide 0.3–0.6 Gt (1 Gt = 1 × 10⁵ g) CO₂·yr⁻¹ in emission reductions and would require $0.4 billion to $1.7 billion·yr⁻¹ for 30 years. A 50% reduction in deforestation from 2005 to 2030 could provide 1.5–2.7 Gt CO₂·yr⁻¹ in emission reductions and would require $17.2 billion to $28.0 billion·yr⁻¹. Finally, some caveats to the analysis that could increase costs of AD programs are described.     

Probabilistic framework for assessing the ice sheet contribution to sea level change

Previous sea level rise (SLR) assessments have excluded the potential for dynamic ice loss over much of Greenland and Antarctica, and recently proposed “upper bounds” on Antarctica’s 21st-century SLR contribution are derived principally from regions where present-day mass loss is concentrated (basin 15, or B15, drained largely by Pine Island, Thwaites, and Smith glaciers). Here, we present a probabilistic framework for assessing the ice sheet contribution to sea level change that explicitly accounts for mass balance uncertainty over an entire ice sheet. Applying this framework to Antarctica, we find that ongoing mass imbalances in non-B15 basins give an SLR contribution by 2100 that: (i) is comparable to projected changes in B15 discharge and Antarctica’s surface mass balance, and (ii) varies widely depending on the subset of basins and observational dataset used in projections. Increases in discharge uncertainty, or decreases in the exceedance probability used to define an upper bound, increase the fractional contribution of non-B15 basins; even weak spatial correlations in future discharge growth rates markedly enhance this sensitivity. Although these projections rely on poorly constrained statistical parameters, they may be updated with observations and/or models at many spatial scales, facilitating a more comprehensive account of uncertainty that, if implemented, will improve future assessments.     

From the Cover: Mountain runoff vulnerability to increased evapotranspiration with vegetation expansion

Climate change has the potential to reduce surface-water supply by expanding the activity, density, or coverage of upland vegetation, although the likelihood and severity of this effect are poorly known. We quantified the extent to which vegetation and evapotranspiration (ET) are presently cold-limited in California’s upper Kings River basin and used a space-for-time substitution to calculate the sensitivity of riverflow to vegetation expansion. We found that runoff is highly sensitive to vegetation migration; warming projected for 2100 could increase average basin-wide ET by 28% and decrease riverflow by 26%. Kings River basin ET currently peaks at midelevation and declines at higher elevation, creating a cold-limited zone above 2,400 m that is disproportionately important for runoff generation. Climate projections for 2085–2100 indicate as much as 4.1 °C warming in California’s Sierra Nevada, which would expand high rates of ET 700-m upslope if vegetation maintains its current correlation with temperature. Moreover, we observed that the relationship between basin-wide ET and temperature is similar across the entire western slope of California’s Sierra Nevada, implying that the risk of increasing montane ET with warming is widespread.Roughly 4 billion people globally and 20 million people in the state of California rely on mountain runoff for freshwater, and there is growing concern these water resources will prove vulnerable to climate change (1–6). River flow (Q) is a function of precipitation (P) minus evapotranspiration (ET) (P−ET); increased montane ET with warming, either because of the direct effect of temperature on evaporative demand or the indirect effect of warming on vegetation density and distribution, would reduce Q (5, 7–9). However, hydrologic model projections for California’s Sierra Nevada have discounted this possibility, indicating little or no effect of warming on annual ET (10–13). This result appears linked to two model assumptions: (i) models have often assumed the properties of montane vegetation will remain static, and (ii) models have often implicitly assumed that current annual montane ET is almost entirely limited by water availability and that warming will simply hasten the beginning and end of the growing season.Recent evidence calls both of these assumptions into question. Widespread increases in subalpine tree growth, tree-line altitude, and species distribution with elevation have been reported with recent climate trends in California and elsewhere, implying that rapid vegetation shifts are possible (14–16). Time series of Sierra Nevada forest greenness indicate a transition from water limitation at low elevation to cold limitation at high altitude, implying that upper elevation ET is sensitive to warming (17). Nonetheless, the extent to which annual montane ET is currently temperature-limited, as well as the sensitivity of large-scale ET to vegetation redistribution, remain largely unquantified.We used the upper Kings River basin in California’s Sierra Nevada as a case study of the sensitivity of montane runoff to increased ET with warming. The Kings River is one of ∼11 major rivers draining the western slope of the Sierra Nevada. The upper Kings River basin extends from the Pine Flat Reservoir to the Sierra crest and drains 3,998 km², with a mean elevation of 2,332 m and an estimated average precipitation of ∼1,000 mm yr⁻¹. The Kings River is particularly important for hydroelectric generation and as a source of water for agriculture: the Kings River service area was home to ∼750,000 people and generated gross agricultural revenues of ∼US$3 billion in 2003 (13, 18).     

Sensitivity of the Predictive Hypoglycemia Minimizer System to the Algorithm Aggressiveness Factor

Background:

The Predictive Hypoglycemia Minimizer System (“Hypo Minimizer”), consisting of a zone model predictive controller (the “controller”) and a safety supervision module (the “safety module”), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The “aggressiveness factor,” a pivotal variable in the system, governs the speed and magnitude of the controller’s insulin dosing characteristics in response to changes in CGM levels.

Methods:

Twelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results.

Results:

As aggressiveness increased from “conservative” to “medium” to “aggressive,” the controller recommended less insulin (–3.3% vs –14.4% vs –19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values.

Conclusion:

The Hypo Minimizer’s controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics.     

No buzz for bees: Media coverage of pollinator decline

Although widespread declines in insect biomass and diversity are increasing concerns within the scientific community, it remains unclear whether attention to pollinator declines has also increased within information sources serving the general public. Examining patterns of journalistic attention to the pollinator population crisis can also inform efforts to raise awareness about the importance of declines of insect species providing ecosystem services beyond pollination. We used the Global News Index developed by the Cline Center for Advanced Social Research at the University of Illinois at Urbana–Champaign to track news attention to pollinator topics in nearly 25 million news items published by two American national newspapers and four international wire services over the past four decades. We found vanishingly low levels of attention to pollinator population topics relative to coverage of climate change, which we use as a comparison topic. In the most recent subset of ∼10 million stories published from 2007 to 2019, 1.39% (137,086 stories) refer to climate change/global warming while only 0.02% (1,780) refer to pollinator populations in all contexts, and just 0.007% (679) refer to pollinator declines. Substantial increases in news attention were detectable only in US national newspapers. We also find that, while climate change stories appear primarily in newspaper “front sections,” pollinator population stories remain largely marginalized in “science” and “back section” reports. At the same time, news reports about pollinator populations increasingly link the issue to climate change, which might ultimately help raise public awareness to effect needed policy changes.     

Proven Anti-Wetting Properties of Molybdenum Tested for High-Temperature Corrosion-Resistance with Potential Application in the Aluminum Industry

The behavior of Mo in contact with molten Al was modelled by classical molecular dynamics (CMD) simulation of a pure Mo solid in contact with molten Al at 1200 K using the Materials Studio^®. Results showed that no reaction or cross diffusion of atoms occurs at the Mo(s)–Al(l) interface, and that molten Al atoms exhibit an epitaxial alignment with the exposed solid Mo crystal morphology. Furthermore, the two phases {Mo(s) and Al(l)} are predicted to interact with weak van der Waals forces and give interfacial energy of about 203 mJ/m². Surface energy measurements by the sessile drop experiment using the van Oss–Chaudhury–Good (VCG) theory established a Mo(s)–Al(l) interface energy equivalent to 54 mJ/m², which supports the weak van der Waals interaction. The corrosion resistance of a high purity (99.97%) Mo block was then tested in a molten alloy of 5% Mg mixed in Al (Al-5 wt.%Mg) at 1123 K for 96 h, using the ALCAN’s standard “immersion” test, and the results are presented. No Mo was found to be dissolved in the molten Al-Mg alloy. However, a 20% mass loss in the Mo block was due to intergranular corrosion scissoring the Mo block in the ALCAN test, but not as a result of the reaction of pure Mo with the molten Al-Mg alloy. It was observed that the Al-Mg alloy did not stick to the Mo block.     

Ecological feedbacks following deforestation create the potential for a catastrophic ecosystem shift in tropical dry forest

The long-term ecological response to recurrent deforestation associated with shifting cultivation remains poorly investigated, especially in the dry tropics. We present a study of phosphorus (P) dynamics in the southern Yucatán, highlighting the possibility of abrupt shifts in biogeochemical cycling resulting from positive feedbacks between vegetation and its limiting resources. After three cultivation–fallow cycles, available soil P declines by 44%, and one-time P inputs from biomass burning decline by 76% from mature forest levels. Interception of dust-borne P (“canopy trapping”) declines with lower plant biomass and leaf area, limiting deposition in secondary forest. Potential leaching losses are greater in secondary than in mature forest, but the difference is very small compared with the difference in P inputs. The decline in new P from atmospheric deposition creates a long-term negative ecosystem balance for phosphorus. The reduction in soil P availability will feed back to further limit biomass recovery and may induce a shift to sparser vegetation. Degradation induced by hydrological and biogeochemical feedbacks on P cycling under shifting cultivation will affect farmers in the near future. Without financial support to encourage the use of fertilizer, farmers could increase the fallow period, clear new land, or abandon agriculture for off-farm employment. Their response will determine the regional balance between forest loss and forest regrowth, as well as the frequency of use and rate of recovery at a local scale, further feeding back on ecological processes at multiple scales.     

Place cell discharge is extremely variable during individual passes of the rat through the firing field

The idea that the rat hippocampus stores a map of space is based on the existence of “place cells” that show “location-specific” firing. The discharge of place cells is confined with remarkable precision to a cell-specific part of the environment called the cell’s “firing field.” We demonstrate here that firing is not nearly as reliable in the time domain as in the positional domain. Discharge during passes through the firing field was compared with a model with Poisson variance of the location-specific firing determined by the time-averaged positional firing rate distribution. Place cells characteristically fire too little or too much compared with expectations from the random model. This fundamental property of place cells is referred to as “excess firing variance” and has three main implications: (i) Place cell discharge is not only driven by the summation of many small, asynchronous excitatory synaptic inputs. (ii) Place cell discharge may encode a signal in addition to the current head location. (iii) The excess firing variance helps explain why the errors in computing the rat’s position from the simultaneous activity of many place cells are large.