Tipping points in tropical tree cover: linking theory to data

It has recently been found that the frequency distribution of remotely sensed tree cover in the tropics has three distinct modes, which seem to correspond to forest, savanna, and treeless states. This pattern has been suggested to imply that these states represent alternative attractors, and that the response of these systems to climate change would be characterized by critical transitions and hysteresis. Here, we show how this inference is contingent upon mechanisms at play. We present a simple dynamical model that can generate three alternative tree cover states (forest, savanna, and a treeless state), based on known mechanisms, and use this model to simulate patterns of tree cover under different scenarios. We use these synthetic data to show that the hysteresis inferred from remotely sensed tree cover patterns will be inflated by spatial heterogeneity of environmental conditions. On the other hand, we show that the hysteresis inferred from satellite data may actually underestimate real hysteresis in response to climate change if there exists a positive feedback between regional tree cover and precipitation. Our results also indicate that such positive feedback between vegetation and climate should cause direct shifts between forest and a treeless state (rather than through an intermediate savanna state) to become more likely. Finally, we show how directionality of historical change in conditions may bias the observed relationship between tree cover and environmental conditions.     

Sixteen hundred years of increasing tree cover prior to modern deforestation in Southern Amazon and Central Brazilian savannas

Tropical ecosystems are under increasing pressure from land‐use change and deforestation. Changes in tropical forest cover are expected to affect carbon and water cycling with important implications for climatic stability at global scales. A major roadblock for predicting how tropical deforestation affects climate is the lack of baseline conditions (i.e., prior to human disturbance) of forest–savanna dynamics. To address this limitation, we developed a long‐term analysis of forest and savanna distribution across the Amazon–Cerrado transition of central Brazil. We used soil organic carbon isotope ratios as a proxy for changes in woody vegetation cover over time in response to fluctuations in precipitation inferred from speleothem oxygen and strontium stable isotope records. Based on stable isotope signatures and radiocarbon activity of organic matter in soil profiles, we quantified the magnitude and direction of changes in forest and savanna ecosystem cover. Using changes in tree cover measured in 83 different locations for forests and savannas, we developed interpolation maps to assess the coherence of regional changes in vegetation. Our analysis reveals a broad pattern of woody vegetation expansion into savannas and densification within forests and savannas for at least the past ~1,600 years. The rates of vegetation change varied significantly among sampling locations possibly due to variation in local environmental factors that constrain primary productivity. The few instances in which tree cover declined (7.7% of all sampled profiles) were associated with savannas under dry conditions. Our results suggest a regional increase in moisture and expansion of woody vegetation prior to modern deforestation, which could help inform conservation and management efforts for climate change mitigation. We discuss the possible mechanisms driving forest expansion and densification of savannas directly (i.e., increasing precipitation) and indirectly (e.g., decreasing disturbance) and suggest future research directions that have the potential to improve climate and ecosystem models.     

Colombian dry moist forest transitions in the Llanos Orientales—A comparison of model and pollen-based biome reconstructions

Colombian vegetation, at the ecological level of the biome, is reconstructed at six sites using pollen data assigned a priori to plant functional types and biomes. The chosen sites incorporate four savanna sites (Laguna Sardinas, Laguna Angel, El Piñal and Laguna Carimagua), a site on the transition between savanna and Amazon rainforest (Loma Linda) and a site within the Amazon rainforest (Pantano de Monica). The areal extent of tropical moist forest, tropical dry forest and steppe have been subject to significant change: differential responses of the vegetation to climatic shifts are related to changes in plant available moisture, duration of dry season and edaphic controls on the vegetation. The record from El Piñal shows that the present-day savanna vegetation, dominated by steppe (Poaceae) with little occurrence of woody savanna taxa (e.g. Curatella, Byrsonima), was present since the last glacial period of the northern hemisphere. Unfortunately, El Piñal is located on an edaphic savanna and is not particularly responsive to registering change. Most records cover the early Holocene; one site records the El Abra stadial (Younger Dryas equivalent), when forest expansion reflects more humid climatic conditions and higher plant available moisture. During the early and middle Holocene, the maximum expansion of steppe and tropical dry forest occurred, indicating that dry climatic conditions continued to around 4000 ¹⁴C BP. The following period, from shortly before 4000 ¹⁴C BP, is characterised by an increase in forest and gallery forests, reflecting a wetter period probably with a shorter annual dry season. Anthropogenic influence on the vegetation is recorded by all the records over the last millennial, particularly characterised by a reduction in forest cover and high amplitude changes in vegetation.Biome transitions from one type to another, and the environmental controls on this shift, are investigated by applying a vegetation model (BIOME-3). The model uses climatic data from six meteorological stations that, encompass a range of environments within lowland Colombia, which are similar to the pollen data. The signals of vegetation change can be translated to the main environmental controls of temperature and moisture to indicate the degree of change needed in these parameters to record the vegetation change depicted by the pollen data. Moisture balance is the dominant control on driving vegetation change whether under seasonal or annual control. The combined reconstruction from pollen data and model output of biome-scale vegetation dynamics for lowland Colombia allows an understanding of the environmental controls to be developed.     

Valuation and sustainable use of tropical rainforest

Studies of the extraction of non-timber forest products have shown that the standing rainforest may be more valuable than alternatives involving deforestation

Although this article is about placing a value on rainforest, it begins by stressing the importance and value of rainforest for its environmental function, particularly for the control of world climate patterns. It is then shown how rainforest peoples depend on the plants around them and in some study areas were found to have a use for every tree on the one-hectare plots. It is therefore not surprising that the rainforest can contain many non-timber forest products (NTFPs) of commercial potential, some of which such as rubber latex and Brazil nuts have been in the market economy for many years. A summary is given of various attempts to place a value on rainforest for its NTFPs. Each of the three studies showed that the extraction of these products could be more valuable than alternative land uses involving deforestation. Various rainforest countries such as Brazil, Guatemala, and Indonesia have set up extractive reserves where local people are allowed to extract NTFPs but not to clear cut the forest. Extractive reserves have slowed down deforestation in some areas, but only provide a meagre subsistence existence for their inhabitants, so while they are useful, they are not a panacea that will solve all the conservation problems of tropical rainforest.     

Early warning signals of simulated Amazon rainforest dieback

We test proposed generic tipping point early warning signals in a complex climate model (HadCM3) which simulates future dieback of the Amazon rainforest. The equation governing tree cover in the model suggests that zero and non-zero stable states of tree cover co-exist, and a transcritical bifurcation is approached as productivity declines. Forest dieback is a non-linear change in the non-zero tree cover state, as productivity declines, which should exhibit critical slowing down. We use an ensemble of versions of HadCM3 to test for the corresponding early warning signals. However, on approaching simulated Amazon dieback, expected early warning signals of critical slowing down are not seen in tree cover, vegetation carbon or net primary productivity. The lack of a convincing trend in autocorrelation appears to be a result of the system being forced rapidly and non-linearly. There is a robust rise in variance with time, but this can be explained by increases in inter-annual temperature and precipitation variability that force the forest. This failure of generic early warning indicators led us to seek more system-specific, observable indicators of changing forest stability in the model. The sensitivity of net ecosystem productivity to temperature anomalies (a negative correlation) generally increases as dieback approaches, which is attributable to a non-linear sensitivity of ecosystem respiration to temperature. As a result, the sensitivity of atmospheric CO₂ anomalies to temperature anomalies (a positive correlation) increases as dieback approaches. This stability indicator has the benefit of being readily observable in the real world.     

Assessing the impact of deforestation and climate change on the range size and environmental niche of bird species in the Atlantic forests,Brazil

Aim Habitat loss and climate change are two major drivers of biological diversity. Here we quantify how deforestation has already changed, and how future climate scenarios may change, environmental conditions within the highly disturbed Atlantic forests of Brazil. We also examine how environmental conditions have been altered within the range of selected bird species. Location Atlantic forests of south‐eastern Brazil. Methods The historical distribution of 21 bird species was estimated using Maxent . After superimposing the present‐day forest cover, we examined the environmental niches hypothesized to be occupied by these birds pre‐ and post‐deforestation using environmental niche factor analysis (ENFA). ENFA was also used to compare conditions in the entire Atlantic forest ecosystem pre‐ and post‐deforestation. The relative influence of land use and climate change on environmental conditions was examined using analysis of similarity and principal components analysis. Results Deforestation in the region has resulted in a decrease in suitable habitat of between 78% and 93% for the Atlantic forest birds included here. Further, Atlantic forest birds today experience generally wetter and less seasonal forest environments than they did historically. Models of future environmental conditions within forest remnants suggest generally warmer conditions and lower annual variation in rainfall due to greater precipitation in the driest quarter of the year. We found that deforestation resulted in a greater divergence of environmental conditions within Atlantic forests than that predicted by climate change. Main conclusions The changes in environmental conditions that have occurred with large‐scale deforestation suggest that selective regimes may have shifted and, as a consequence, spatial patterns of intra‐specific variation in morphology, behaviour and genes have probably been altered. Although the observed shifts in available environmental conditions resulting from deforestation are greater than those predicted by climate change, the latter will result in novel environments that exceed temperatures in any present‐day climates and may lead to biotic attrition unless organisms can adapt to these warmer conditions. Conserving intra‐specific diversity over the long term will require considering both how changes in the recent past have influenced contemporary populations and the impact of future environmental change.     

The ghosts of forests past and future: deforestation and botanical sampling in the Brazilian Amazon

The remarkable biodiversity of the Brazilian Amazon is poorly documented and threatened by deforestation. When undocumented areas become deforested, in addition to losing the fauna and flora, we lose the opportunity to know which unique species had occupied a habitat. Here we quantify such knowledge loss by calculating how much of the Brazilian Amazon has been deforested and will likely be deforested until 2050 without having its tree flora sufficiently documented. To this end, we analysed 399 147 digital specimens of nearly 6000 tree species in relation to official deforestation statistics and future deforestation scenarios. We find that by 2017, 30% of all the localities where tree specimens had been collected were mostly deforested. Some 300 000 km² (12%; 485 25 × 25 km grid cells) of the Brazilian Amazon had been deforested by 2017, without having a single tree specimen recorded. An additional 250 000–900 000 km² of severely under-collected rainforest will likely become deforested by 2050. If future tree sampling is to cover this area, sampling effort has to increase two- to six-fold. Nearly 255 000 km² or 7% of rainforest in the Brazilian Amazon is easily accessible but does yet but remain under-collected. Our study highlights how progressing deforestation increases the risk of losing undocumented species of a hyper-diverse tree flora.     

Surrogate species protection in Bolivia under climate and land cover change scenarios

The Amazon rainforest covers more than 60% of Bolivia’s lowlands, providing habitat for many endemic and threatened species. Bolivia has the highest rates of deforestation of the Amazon biome, which degrades and fragments species habitat. Anthropogenic habitat changes could be exacerbated by climate change, and therefore, developing relevant strategies for biodiversity protection under global change scenarios is a necessary step in conservation planning.In this research we used multi-species umbrella concept to evaluate the degree of habitat impacts due to climate and land cover change in Bolivia. We used species distribution modeling to map three focal species (Jaguar, Lowland Tapir and Lesser Anteater) and assessed current protected area network effectiveness under future climate and land cover change scenarios for 2050.The studied focal species will lose between 70% and 83% of their ranges under future climate and land-cover change scenarios, decreasing the level of protection to 10% of their original ranges. Existing protected area network should be reconsidered to maintain current and future biodiversity habitats.     

Abrupt shifts in African savanna tree cover along a climatic gradient

Aim To describe patterns of tree cover in savannas over a climatic gradient and a range of spatial scales and test if there are identifiable climate‐related mean structures, if tree cover always increases with water availability and if there is a continuous trend or a stepwise trend in tree cover. Location Central Tropical Africa. Methods We compared a new analysis of satellite tree cover data with botanical, phytogeographical and environmental data. Results Along the climatic transect, six vegetation structures were distinguished according to their average tree cover, which can co‐occur as mosaics. The resulting abrupt shifts in tree cover were not correlated to any shifts in either environmental variables or in tree species distributions. Main conclusions A strong contrast appears between fine‐scale variability in tree cover and coarse‐scale structural states that are stable over several degrees of latitude. While climate parameters and species pools display a continuous evolution along the climatic gradient, these stable structural states have discontinuous transitions, resulting in regions containing mosaics of alternative stable states. Soils appear to have little effect inside the climatic stable state domains but a strong action on the location of the transitions. This indicates that savannas are patch dynamics systems, prone to feedbacks stabilizing their coarse‐scale structure over wide ranges of environmental conditions.     

Assessing the impacts of past and ongoing deforestation on rainfall patterns in South America

Despite recent advances in modeling forest–rainfall relationships, the current understanding of changes in observed rainfall patterns resulting from historical deforestation remains limited. To address this knowledge gap, we analyzed how 40 years of deforestation has altered rainfall patterns in South America as well as how current Amazonian forest cover sustains rainfall. First, we develop a spatiotemporal neural network model to simulate rainfall as a function of vegetation and climate inputs in South America; second, we assess the rainfall effects of observed deforestation in South America during the periods 1982–2020 and 2000–2020; third, we assess the potential rainfall changes in the Amazon biome under two deforestation scenarios. We find that, on average, cumulative deforestation in South America from 1982 to 2020 has reduced rainfall over the period 2016–2020 by 18% over deforested areas, and by 9% over non-deforested areas across South America. We also find that more recent deforestation, that is, from 2000 to 2020, has reduced rainfall over the period 2016–2020 by 10% over deforested areas and by 5% over non-deforested areas. Deforestation between 1982 and 2020 has led to a doubling in the area experiencing a minimum dry season of 4 months in the Amazon biome. Similarly, in the Cerrado region, there has been a corresponding doubling in the area with a minimum dry season of 7 months. These changes are compared to a hypothetical scenario where no deforestation occurred. Complete conversion of all Amazon forest land outside protected areas would reduce average annual rainfall in the Amazon by 36% and complete deforestation of all forest cover including protected areas would reduce average annual rainfall in the Amazon by 68%. Our findings emphasize the urgent need for effective conservation measures to safeguard both forest ecosystems and sustainable agricultural practices.     

Satellite‐based estimates reveal widespread forest degradation in the Amazon

Anthropogenic and natural forest disturbance cause ecological damage and carbon emissions. Forest disturbance in the Amazon occurs in the form of deforestation (conversion of forest to non‐forest land covers), degradation from the extraction of forest resources, and destruction from natural events. The crucial role of the Amazon rainforest in the hydrologic cycle has even led to the speculation of a disturbance “tipping point” leading to a collapse of the tropical ecosystem. Here we use time series analysis of Landsat data to map deforestation, degradation, and natural disturbance in the Amazon Ecoregion from 1995 to 2017. The map was used to stratify the study area for selection of sample units that were assigned reference labels based on their land cover and disturbance history. An unbiased statistical estimator was applied to the sample of reference observations to obtain estimates of area and uncertainty at biennial time intervals. We show that degradation and natural disturbance, largely during periods of severe drought, have affected as much of the forest area in the Amazon Ecoregion as deforestation from 1995 to 2017. Consequently, an estimated 17% (1,036,800 ± 24,800 km², 95% confidence interval) of the original forest area has been disturbed as of 2017. Our results suggest that the area of disturbed forest in the Amazon is 44%–60% more than previously realized, indicating an unaccounted for source of carbon emissions and pervasive damage to forest ecosystems.     

Tree line shifts in the Swiss Alps: Climate change or land abandonment?

Questions: Did the forest area in the Swiss Alps increase between 1985 and 1997? Does the forest expansion near the tree line represent an invasion into abandoned grasslands (ingrowth) or a true upward shift of the local tree line? What land cover / land use classes did primarily regenerate to forest, and what forest structural types did primarily regenerate? And, what are possible drivers of forest regeneration in the tree line ecotone, climate and/or land use change? Location: Swiss Alps. Methods: Forest expansion was quantified using data from the repeated Swiss land use statistics GEOSTAT. A moving window algorithm was developed to distinguish between forest ingrowth and upward shift. To test a possible climate change influence, the resulting upward shifts were compared to a potential regional tree line. Results: A significant increase of forest cover was found between 1650 m and 2450 m. Above 1650 m, 10% of the new forest areas were identified as true upward shifts whereas 90% represented ingrowth, and we identified both land use and climate change as likely drivers. Most upward shift activities were found to occur within a band of 300 m below the potential regional tree line, indicating land use as the most likely driver. Only 4% of the upward shifts were identified to rise above the potential regional tree line, thus indicating climate change. Conclusions: Land abandonment was the most dominant driver for the establishment of new forest areas, even at the tree line ecotone. However, a small fraction of upwards shift can be attributed to the recent climate warming, a fraction that is likely to increase further if climate continues to warm, and with a longer time‐span between warming and measurement of forest cover.     

Response of Free-Living Nitrogen-Fixing Microorganisms to Land Use Change in the Amazon Rainforest

The Amazon rainforest, the largest equatorial forest in the world, is being cleared for pasture and agricultural use at alarming rates. Tropical deforestation is known to cause alterations in microbial communities at taxonomic and phylogenetic levels, but it is unclear whether microbial functional groups are altered. We asked whether free-living nitrogen-fixing microorganisms (diazotrophs) respond to deforestation in the Amazon rainforest, using analysis of the marker gene nifH. Clone libraries were generated from soil samples collected from a primary forest, a 5-year-old pasture originally converted from primary forest, and a secondary forest established after pasture abandonment. Although diazotroph richness did not significantly change among the three plots, diazotroph community composition was altered with forest-to-pasture conversion, and phylogenetic similarity was higher among pasture communities than among those in forests. There was also 10-fold increase in nifH gene abundance following conversion from primary forest to pasture. Three environmental factors were associated with the observed changes: soil acidity, total N concentration, and C/N ratio. Our results suggest a partial restoration to initial levels of abundance and community structure of diazotrophs following pasture abandonment, with primary and secondary forests sharing similar communities. We postulate that the response of diazotrophs to land use change is a direct consequence of changes in plant communities, particularly the higher N demand of pasture plant communities for supporting aboveground plant growth.     

Environmental change and the carbon balance of Amazonian forests

Extreme climatic events and land‐use change are known to influence strongly the current carbon cycle of Amazonia, and have the potential to cause significant global climate impacts. This review intends to evaluate the effects of both climate and anthropogenic perturbations on the carbon balance of the Brazilian Amazon and to understand how they interact with each other. By analysing the outputs of the Intergovernmental Panel for Climate Change (IPCC) Assessment Report 4 (AR4) model ensemble, we demonstrate that Amazonian temperatures and water stress are both likely to increase over the 21st Century. Curbing deforestation in the Brazilian Amazon by 62% in 2010 relative to the 1990s mean decreased the Brazilian Amazon's deforestation contribution to global land use carbon emissions from 17% in the 1990s and early 2000s to 9% by 2010. Carbon sources in Amazonia are likely to be dominated by climatic impacts allied with forest fires (48.3% relative contribution) during extreme droughts. The current net carbon sink (net biome productivity, NBP) of +0.16 (ranging from +0.11 to +0.21) Pg C year^?1 in the Brazilian Amazon, equivalent to 13.3% of global carbon emissions from land‐use change for 2008, can be negated or reversed during drought years [NBP = ?0.06 (?0.31 to +0.01) Pg C year^?1]. Therefore, reducing forest fires, in addition to reducing deforestation, would be an important measure for minimizing future emissions. Conversely, doubling the current area of secondary forests and avoiding additional removal of primary forests would help the Amazonian gross forest sink to offset approximately 42% of global land‐use change emissions. We conclude that a few strategic environmental policy measures are likely to strengthen the Amazonian net carbon sink with global implications. Moreover, these actions could increase the resilience of the net carbon sink to future increases in drought frequency.     

Land‐use change outweighs projected effects of changing rainfall on tree cover in sub‐Saharan Africa

Global change will likely affect savanna and forest structure and distributions, with implications for diversity within both biomes. Few studies have examined the impacts of both expected precipitation and land use changes on vegetation structure in the future, despite their likely severity. Here, we modeled tree cover in sub‐Saharan Africa, as a proxy for vegetation structure and land cover change, using climatic, edaphic, and anthropic data (R² = 0.97). Projected tree cover for the year 2070, simulated using scenarios that include climate and land use projections, generally decreased, both in forest and savanna, although the directionality of changes varied locally. The main driver of tree cover changes was land use change; the effects of precipitation change were minor by comparison. Interestingly, carbon emissions mitigation via increasing biofuels production resulted in decreases in tree cover, more severe than scenarios with more intense precipitation change, especially within savannas. Evaluation of tree cover change against protected area extent at the WWF Ecoregion scale suggested areas of high biodiversity and ecosystem services concern. Those forests most vulnerable to large decreases in tree cover were also highly protected, potentially buffering the effects of global change. Meanwhile, savannas, especially where they immediately bordered forests (e.g. West and Central Africa), were characterized by a dearth of protected areas, making them highly vulnerable. Savanna must become an explicit policy priority in the face of climate and land use change if conservation and livelihoods are to remain viable into the next century.     

Tracking unstable states: ecosystem dynamics in a changing world

Ecological systems can show complex and sometimes abrupt responses to environmental change, with important implications for their resilience. Theories of alternate stable states have been used to predict regime shifts of ecosystems as equilibrium responses to sufficiently slow environmental change. The actual rate of environmental change is a key factor affecting the response, yet we are still lacking a non-equilibrium theory that explicitly considers the influence of this rate of environmental change. We present a metacommunity model of predator–prey interactions displaying multiple stable states, and we impose an explicit rate of environmental change in habitat quality (carrying capacity) and connectivity (dispersal rate). We study how regime shifts depend on the rate of environmental change and compare the outcome with a stability analysis in the corresponding constant environment. Our results reveal that in a changing environment, the community can track states that are unstable in the constant environment. This tracking can lead to regime shifts, including local extinctions, that are not predicted by alternative stable state theory. In our metacommunity, tracking unstable states also controls the maintenance of spatial heterogeneity and spatial synchrony. Tracking unstable states can also lead to regime shifts that may be reversible or irreversible. Our study extends current regime shift theories to integrate rate-dependent responses to environmental change. It reveals the key role of unstable states for predicting transient dynamics and long-term resilience of ecological systems to climate change.     

Climate change, human land use and future fires in the Amazon

There is increasing consensus that the global climate will continue to warm over the next century. The biodiversity-rich Amazon forest is a region of growing concern because many global climate model (GCM) scenarios of climate change forecast reduced precipitation and, in some cases, coupled vegetation models predict dieback of the forest. To date, fires have generally been spatially co-located with road networks and associated human land use because almost all fires in this region are anthropogenic in origin. Climate change, if severe enough, could alter this situation, potentially changing the fire regime to one of increased fire frequency and severity for vast portions of the Amazon forest. High moisture contents and dense canopies have historically made Amazonian forests extremely resistant to fire spread. Climate will affect the fire situation in the Amazon directly, through changes in temperature and precipitation, and indirectly, through climate-forced changes in vegetation composition and structure. The frequency of drought will be a prime determinant of both how often forest fires occur and how extensive they become. Fire risk management needs to take into account landscape configuration, land cover types and forest disturbance history as well as climate and weather. Maintaining large blocks of unsettled forest is critical for managing landscape level fire in the Amazon. The Amazon has resisted previous climate changes and should adapt to future climates as well if landscapes can be managed to maintain natural fire regimes in the majority of forest remnants.     

Declining Amazon biomass due to deforestation and subsequent degradation losses exceeding gains

In the Amazon, deforestation and climate change lead to increased vulnerability to forest degradation, threatening its existing carbon stocks and its capacity as a carbon sink. We use satellite L-Band Vegetation Optical Depth (L-VOD) data that provide an integrated (top-down) estimate of biomass carbon to track changes over 2011–2019. Because the spatial resolution of L-VOD is coarse (0.25°), it allows limited attribution of the observed changes. We therefore combined high-resolution annual maps of forest cover and disturbances with biomass maps to model carbon losses (bottom-up) from deforestation and degradation, and gains from regrowing secondary forests. We show an increase of deforestation and associated degradation losses since 2012 which greatly outweigh secondary forest gains. Degradation accounted for 40% of gross losses. After an increase in 2011, old-growth forests show a net loss of above-ground carbon between 2012 and 2019. The sum of component carbon fluxes in our model is consistent with the total biomass change from L-VOD of 1.3 Pg C over 2012-2019. Across nine Amazon countries, we found that while Brazil contains the majority of biomass stocks (64%), its losses from disturbances were disproportionately high (79% of gross losses). Our multi-source analysis provides a pessimistic assessment of the Amazon carbon balance and highlights the urgent need to stop the recent rise of deforestation and degradation, particularly in the Brazilian Amazon.     

Amazon's vulnerability to climate change heightened by deforestation and man‐made dispersal barriers

Species migrations in response to climate change have already been observed in many taxonomic groups worldwide. However, it remains uncertain if species will be able to keep pace with future climate change. Keeping pace will be especially challenging for tropical lowland rainforests due to their high velocities of climate change combined with high rates of deforestation, which may eliminate potential climate analogs and/or increase the effective distances between analogs by blocking species movements. Here, we calculate the distances between current and future climate analogs under various climate change and deforestation scenarios. Under even the most sanguine of climate change models (IPSL_CM4, A1b emissions scenario), we find that the median distance between areas in the Amazon rainforest and their closest future (2050) climate analog as predicted based on just temperature changes alone is nearly 300 km. If we include precipitation, the median distance increases by over 50% to >475 km. Since deforestation is generally concentrated in the hottest and driest portions of the Amazon, we predict that the habitat loss will have little direct impact on distances between climate analogs. If, however, deforested areas also act as a barrier to species movements, nearly 30% or 55% of the Amazon will effectively have no climate analogs anywhere in tropical South America under projections of reduced or Business‐As‐Usual deforestation, respectively. These ‘disappearing climates’ will be concentrated primarily in the southeastern Amazon. Consequently, we predict that several Amazonian ecoregions will have no areas with future climate analogs, greatly increasing the vulnerability of any populations or species specialized on these conditions. These results highlight the importance of including multiple climatic factors and human land‐use in predicting the effects of climate change, as well as the daunting challenges that Amazonian diversity faces in the near future.     

Simulating the response of land-cover changes to road paving and governance along a major Amazon highway: the Santarém–Cuiabá corridor

The spatial distribution of human activities in forest frontier regions is strongly influenced by transportation infrastructure. With the planned paving of 6000 km of highway in the Amazon Basin, agricultural frontier expansion will follow, triggering potentially large changes in the location and rate of deforestation. We developed a land‐cover change simulation model that is responsive to road paving and policy intervention scenarios for the BR‐163 highway in central Amazonia. This corridor links the cities of Cuiabá, in central Brazil, and Santarém, on the southern margin of the Amazon River. It connects important soybean production regions and burgeoning population centers in Mato Grosso State with the international port of Santarém, but 1000 km of this road are still not paved. It is within this context that the Brazilian government has prioritized the paving of this road to turn it into a major soybean exportation facility. The model assesses the impacts of this road paving within four scenarios: two population scenarios (high and moderate growth) and two policy intervention scenarios. In the ‘business‐as‐usual’ policy scenario, the responses of deforestation and land abandonment to road paving are estimated based on historical rates of Amazon regions that had a major road paved. In the ‘governance’ scenario, several plausible improvements in the enforcement of environmental regulations, support for sustainable land‐use systems, and local institutional capacity are invoked to modify the historical rates. Model inputs include data collected during expeditions and through participatory mapping exercises conducted with agents from four major frontier types along the road. The model has two components. A scenario‐generating submodel is coupled to a landscape dynamics simulator, ‘DINAMICA’, which spatially allocates the land‐cover transitions using a GIS database. The model was run for 30 years, divided into annual time steps. It predicted more than twice as much deforestation along the corridor in business‐as‐usual vs. governance scenarios. The model demonstrates how field data gathered along a 1000 km corridor can be used to develop plausible scenarios of future land‐cover change trajectories that are relevant to both global change science and the decision‐making process of governments and civil society in an important rainforest region.