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.     

Land Use and Land Cover Change Dynamics across the Brazilian Amazon: Insights from Extensive Time-Series Analysis of Remote Sensing Data

Throughout the Amazon region, the age of forests regenerating on previously deforested land is determined, in part, by the periods of active land use prior to abandonment and the frequency of reclearance of regrowth, both of which can be quantified by comparing time-series of Landsat sensor data. Using these time-series of near annual data from 1973–2011 for an area north of Manaus (in Amazonas state), from 1984–2010 for south of Santarém (Pará state) and 1984–2011 near Machadinho d’Oeste (Rondônia state), the changes in the area of primary forest, non-forest and secondary forest were documented from which the age of regenerating forests, periods of active land use and the frequency of forest reclearance were derived. At Manaus, and at the end of the time-series, over 50% of regenerating forests were older than 16 years, whilst at Santarém and Machadinho d’Oeste, 57% and 41% of forests respectively were aged 6–15 years, with the remainder being mostly younger forests. These differences were attributed to the time since deforestation commenced but also the greater frequencies of reclearance of forests at the latter two sites with short periods of use in the intervening periods. The majority of clearance for agriculture was also found outside of protected areas. The study suggested that a) the history of clearance and land use should be taken into account when protecting deforested land for the purpose of restoring both tree species diversity and biomass through natural regeneration and b) a greater proportion of the forested landscape should be placed under protection, including areas of regrowth.     

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.     

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.     

Annual Carbon Emissions from Deforestation in the Amazon Basin between 2000 and 2010

Reducing emissions from deforestation and forest degradation (REDD+) is considered one of the most cost-effective strategies for mitigating climate change. However, historical deforestation and emission rates―critical inputs for setting reference emission levels for REDD+―are poorly understood. Here we use multi-source, time-series satellite data to quantify carbon emissions from deforestation in the Amazon basin on a year-to-year basis between 2000 and 2010. We first derive annual deforestation indicators by using the Moderate Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) product. MODIS indicators are calibrated by using a large sample of Landsat data to generate accurate deforestation rates, which are subsequently combined with a spatially explicit biomass dataset to calculate committed annual carbon emissions. Across the study area, the average deforestation and associated carbon emissions were estimated to be 1.59 ± 0.25 M ha•yr⁻¹ and 0.18 ± 0.07 Pg C•yr⁻¹ respectively, with substantially different trends and inter-annual variability in different regions. Deforestation in the Brazilian Amazon increased between 2001 and 2004 and declined substantially afterwards, whereas deforestation in the Bolivian Amazon, the Colombian Amazon, and the Peruvian Amazon increased over the study period. The average carbon density of lost forests after 2005 was 130 Mg C•ha⁻¹, ~11% lower than the average carbon density of remaining forests in year 2010 (144 Mg C•ha⁻¹). Moreover, the average carbon density of cleared forests increased at a rate of 7 Mg C•ha⁻¹•yr⁻¹ from 2005 to 2010, suggesting that deforestation has been progressively encroaching into high-biomass lands in the Amazon basin. Spatially explicit, annual deforestation and emission estimates like the ones derived in this study are useful for setting baselines for REDD+ and other emission mitigation programs, and for evaluating the performance of such efforts.     

Influence of Deforestation,Logging, and Fire on Malaria in the Brazilian Amazon

Malaria is a significant public health threat in the Brazilian Amazon. Previous research has shown that deforestation creates breeding sites for the main malaria vector in Brazil, Anopheles darlingi, but the influence of selective logging, forest fires, and road construction on malaria risk has not been assessed. To understand these impacts, we constructed a negative binomial model of malaria counts at the municipality level controlling for human population and social and environmental risk factors. Both paved and unpaved roadways and fire zones in a municipality increased malaria risk. Within the timber production states where 90% of deforestation has occurred, compared with areas without selective logging, municipalities where 0–7% of the remaining forests were selectively logged had the highest malaria risk (1.72, 95% CI 1.18–2.51), and areas with higher rates of selective logging had the lowest risk (0.39, 95% CI 0.23–0.67). We show that roads, forest fires, and selective logging are previously unrecognized risk factors for malaria in the Brazilian Amazon and highlight the need for regulation and monitoring of sub-canopy forest disturbance.     

Avian ecological succession in the Amazon: A long‐term case study following experimental deforestation

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Discerning Fragmentation Dynamics of Tropical Forest and Wetland during Reforestation,Urban Sprawl,and Policy Shifts

Despite the overall trend of worldwide deforestation over recent decades, reforestation has also been found and is expected in developing countries undergoing fast urbanization and agriculture abandonment. The consequences of reforestation on landscape patterns are seldom addressed in the literature, despite their importance in evaluating biodiversity and ecosystem functions. By analyzing long-term land cover changes in Puerto Rico, a rapidly reforested (6 to 42% during 1940–2000) and urbanized tropical island, we detected significantly different patterns of fragmentation and underlying mechanisms among forests, urban areas, and wetlands. Forest fragmentation is often associated with deforestation. However, we also found significant fragmentation during reforestation. Urban sprawl and suburb development have a dominant impact on forest fragmentation. Reforestation mostly occurs along forest edges, while significant deforestation occurs in forest interiors. The deforestation process has a much stronger impact on forest fragmentation than the reforestation process due to their different spatial configurations. In contrast, despite the strong interference of coastal urbanization, wetland aggregation has occurred due to the effective implementation of laws/regulations for wetland protection. The peak forest fragmentation shifted toward rural areas, indicating progressively more fragmentation in forest interiors. This shift is synchronous with the accelerated urban sprawl as indicated by the accelerated shift of the peak fragmentation index of urban cover toward rural areas, i.e., 1.37% yr⁻¹ in 1977–1991 versus 2.17% yr⁻¹ in 1991–2000. Based on the expected global urbanization and the regional forest transition from deforested to reforested, the fragmented forests and aggregated wetlands in this study highlight possible forest fragmentation processes during reforestation in an assessment of biodiversity and functions and suggest effective laws/regulations in land planning to reduce future fragmentation.     

Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point

Some model experiments predict a large-scale substitution of Amazon forest by savannah-like vegetation by the end of the twenty-first century. Expanding global demands for biofuels and grains, positive feedbacks in the Amazon forest fire regime and drought may drive a faster process of forest degradation that could lead to a near-term forest dieback. Rising worldwide demands for biofuel and meat are creating powerful new incentives for agro-industrial expansion into Amazon forest regions. Forest fires, drought and logging increase susceptibility to further burning while deforestation and smoke can inhibit rainfall, exacerbating fire risk. If sea surface temperature anomalies (such as El Niño episodes) and associated Amazon droughts of the last decade continue into the future, approximately 55% of the forests of the Amazon will be cleared, logged, damaged by drought or burned over the next 20 years, emitting 15–26 Pg of carbon to the atmosphere. Several important trends could prevent a near-term dieback. As fire-sensitive investments accumulate in the landscape, property holders use less fire and invest more in fire control. Commodity markets are demanding higher environmental performance from farmers and cattle ranchers. Protected areas have been established in the pathway of expanding agricultural frontiers. Finally, emerging carbon market incentives for reductions in deforestation could support these trends.     

Mapping suitable great ape habitat in and around the Lobéké National Park,South‐East Cameroon

As a result of extensive data collection efforts over the last 20–30 years, there is quite a good understanding of the large‐scale geographic distribution and range limits of African great apes. However, as human activities increasingly fragment great ape spatial distribution, a better understanding of what constitutes suitable great ape habitat is needed to inform conservation and resource extraction management. Chimpanzees (Pan troglodytes troglodytes) and gorillas (Gorilla gorilla gorilla) inhabit the Lobéké National Park and its surrounding forest management units (FMUs) in South‐East Cameroon. Both park and neighboring forestry concessions require reliable evidence on key factors driving great ape distribution for their management plans, yet this information is largely missing and incomplete. This study aimed at mapping great ape habitat suitability in the area and at identifying the most influential predictors among three predictor categories, including landscape predictors (dense forest, swampy forest, distance to water bodies, and topography), human disturbance predictors (hunting, deforestation, distance to roads, and population density), and bioclimatic predictor (annual precipitation). We found that about 63% of highly to moderately suitable chimpanzee habitat occurred within the Lobéké National Park, while only 8.4% of similar habitat conditions occurred within FMUs. For gorillas, highly and moderately suitable habitats occurred within the Lobéké National Park and its surrounding FMUs (82.6% and 65.5%, respectively). Key determinants of suitable chimpanzee habitat were hunting pressure and dense forest, with species occurrence probability optimal at relatively lower hunting rates and at relatively high‐dense forest areas. Key determinants of suitable gorilla habitat were hunting pressure, dense forests, swampy forests, and slope, with species occurrence probability optimal at relatively high‐dense and swampy forest areas and at areas with mild slopes. Our findings show differential response of the two ape species to forestry activities in the study area, thus aligning with previous studies.     

Ecological Niche Modelling Predicts Southward Expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), Vector of Leishmania (Leishmania) amazonensis in South America,under Climate Change

Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector’s climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: “stabilization” and “high increase”. Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela. These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.     

Patterns of Land Cover Change in and Around Madidi National Park, Bolivia

This study examines how human land uses and biophysical factors serve as predictors of land cover change in and around Madidi National Park in Bolivia. The Greater Madidi Landscape ranges over an elevational gradient from < 200 m in the Amazon basin to 6000 m in the high Andes, contains more than ten major ecosystem types, and several protected areas and sustainable use zones. In this study, Landsat Thematic Mapper satellite images collected over the study area at the beginning of the 1990s and then the 2000s were classified according to broad land cover types. Below elevations of 3000 m, the landscape experienced equal rates of deforestation and secondary forest increases of approximately 0.63 percent annually, resulting in no significant net change. Below elevations of 1000 m, however, we found an annual net loss in forest cover of 0.11 percent. Across the landscape, land cover change was most likely to occur near areas previously deforested, near roads and population centers, and at low elevations. We found net deforestation rates to be inversely related to strength of natural resource protection laws in protected areas and other jurisdictions. Results suggest little net change for the landscape as a whole, but that local scale changes may be significant, particularly near roads. Management policies favorable for biodiversity conservation in this landscape should limit the building of new roads and immigration to biologically sensitive areas and continue to support protected areas, which are achieving a positive result for forest conservation.     

Carbon Pools and Emissions from Deforestation in Extra-Tropical Forests of Northern Argentina Between 1900 and 2005

We estimated carbon pools and emissions from deforestation in northern Argentine forests between 1900 and 2005, based on forest inventories, deforestation estimates from satellite images and historical data on forests and agriculture. Carbon fluxes were calculated using a book-keeping model. We ran 1000 simulations for a 105-year period with different combinations of values of carbon stocks (Mg C ha⁻¹), soil carbon in the top 0.2 m, and annual deforestation series. The 1000 combinations of parameters were performed as a sensitivity analysis that for each run, randomly selected the values of each variable within a predefined range of values and probability distributions. Using the simulation outputs, we calculated the accumulated C emissions due to deforestation from 1900 to 2005 and the annual emission as the average of the 1000 simulations, and uncertainties of our estimates as the standard deviation. We found that northern Argentine forests contain an estimated 4.54 Pg C (2.312 Pg C in biomass and 2.233 Pg C in soil). Between 1900 and 2005 approximately 30% of the forests were deforested, yielding carbon emissions of 0.945 (SD = 0.270) Pg C. Estimated average annual carbon emissions between 1996 and 2005, mostly from deforestation of the Chaco dry forests, were 20,875 (SD = 6,156) Gg C y⁻¹ (1 Gg = 10⁻⁶ Pg). These values represent the largest source of carbon from land-cover change in the extra-tropical southern hemisphere, between 0.9 and 2.7% of the global carbon emissions from deforestation, and approximately 10% of carbon emissions from the Brazilian Amazon. Deforestation, which has accelerated during the last decades as a result of modern agriculture expansion, represents a major national source of greenhouse gases and the second emission source, after fossil fuel consumption by fixed sources. We conclude that Argentine forests are an important carbon pool and emission source that need more attention for accurate global estimates, and seasonally dry forest deforestation is a key component of the Argentine carbon cycle. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Quantifying avoided deforestation in Pará: Protected areas,buffer zones and edge effects

Percentage of forests saved due to establishment of protected areas is an important piece of information for government institutions and, therefore, is the goal of this study. However, non random location selection bias makes such information directly unobservable. To overcome this problem, propensity score matching was applied. Unlike in previous studies, impact of buffer zone management was assessed by estimating avoided deforestation in buffer zones and park edges. The study area is the state of Pará. Overall results revealed that park protection saved 0.72% of protected surface from deforestation during 2000–2004 year period (∼2900 km² of forests). The highest percentage of avoided deforestation was recorded in protected areas, situated near deforestation hotspots: central part of Eastern Pará, alongside Trans-Amazonian highway and on the banks of Amazon River. The findings also suggest that buffer zones tend to reduce deforestation where pressure on forests is lower, but substitution effect takes over in areas of high deforestation pressure (since loggers are prevented from deforesting within conservation units, deforestation in surrounding areas increases). Finally, the study does not find evidence of edge effects in the state of Pará.     

Assessing the conservation of Miombo timber species through an integrated index of anthropogenic and climatic threats

AimAngolan Miombo woodlands, rich in timber species of the Leguminosae family, go through one of the highest rates of deforestation in sub‐Saharan Africa. This study presents, on the basis of updated information of the distribution of Leguminosae timber species native to Angola, an integrated index framing the main threats for trees, which aims to support new conservation measures.LocationSub‐Saharan Africa, Republic of Angola.MethodsThe current distribution areas of six Leguminosae timber species (i.e., Afzelia quanzensis, Brachystegia spiciformis, Guibourtia coleosperma, Isoberlinia angolensis, Julbernardia paniculata, and Pterocarpus angolensis) were predicted through ensemble modeling techniques. The level of threat to each species was analyzed, comparing the species potential distribution with a threat index map and with the protected areas. The threat index of anthropogenic and climatic factors encompasses the effects of population density, agriculture, proximity to roads, loss of tree cover, overexploitation, trends in wildfires, and predicted changes in temperature and precipitation.ResultsOur results revealed that about 0.5% of Angola''s area is classified as of “Very high” threat, 23.9% as “High” threat, and 66.5% as “Moderate” threat. Three of the studied species require special conservation efforts, namely B. spiciformis and I. angolensis, which have a large fraction of predicted distribution in areas of high threat, and G. coleosperma since it has a restricted distribution area and is one of the most valuable species in international markets. The priority areas for the conservation of Leguminosae timber species were found in Benguela and Huíla.Main conclusionsThis study provides updated data that should be applied to inform policymakers, contributing to national conservation planning and protection of native flora in Angola. Moreover, it presents a methodological approach for the predictions of species distribution and for the creation of a threat index map that can be applied in other poorly surveyed tropical regions.     

Using Species Distribution Models to Predict Potential Landscape Restoration Effects on Puma Conservation

A mosaic of intact native and human-modified vegetation use can provide important habitat for top predators such as the puma (Puma concolor), avoiding negative effects on other species and ecological processes due to cascade trophic interactions. This study investigates the effects of restoration scenarios on the puma’s habitat suitability in the most developed Brazilian region (São Paulo State). Species Distribution Models incorporating restoration scenarios were developed using the species’ occurrence information to (1) map habitat suitability of pumas in São Paulo State, Southeast, Brazil; (2) test the relative contribution of environmental variables ecologically relevant to the species habitat suitability and (3) project the predicted habitat suitability to future native vegetation restoration scenarios. The Maximum Entropy algorithm was used (Test AUC of 0.84 ± 0.0228) based on seven environmental non-correlated variables and non-autocorrelated presence-only records (n = 342). The percentage of native vegetation (positive influence), elevation (positive influence) and density of roads (negative influence) were considered the most important environmental variables to the model. Model projections to restoration scenarios reflected the high positive relationship between pumas and native vegetation. These projections identified new high suitability areas for pumas (probability of presence >0.5) in highly deforested regions. High suitability areas were increased from 5.3% to 8.5% of the total State extension when the landscapes were restored for ≥ the minimum native vegetation cover rule (20%) established by the Brazilian Forest Code in private lands. This study highlights the importance of a landscape planning approach to improve the conservation outlook for pumas and other species, including not only the establishment and management of protected areas, but also the habitat restoration on private lands. Importantly, the results may inform environmental policies and land use planning in São Paulo State, Brazil.     

Quantifying and Valuing Potential Climate Change Impacts on Coral Reefs in the United States: Comparison of Two Scenarios

The biological and economic values of coral reefs are highly vulnerable to increasing atmospheric and ocean carbon dioxide concentrations. We applied the COMBO simulation model (COral Mortality and Bleaching Output) to three major U.S. locations for shallow water reefs: South Florida, Puerto Rico, and Hawaii. We compared estimates of future coral cover from 2000 to 2100 for a “business as usual” (BAU) greenhouse gas (GHG) emissions scenario with a GHG mitigation policy scenario involving full international participation in reducing GHG emissions. We also calculated the economic value of changes in coral cover using a benefit transfer approach based on published studies of consumers'' recreational values for snorkeling and diving on coral reefs as well as existence values for coral reefs. Our results suggest that a reduced emissions scenario would provide a large benefit to shallow water reefs in Hawaii by delaying or avoiding potential future bleaching events. For Hawaii, reducing emissions is projected to result in an estimated “avoided loss” from 2000 to 2100 of approximately $10.6 billion in recreational use values compared to a BAU scenario. However, reducing emissions is projected to provide only a minor economic benefit in Puerto Rico and South Florida, where sea-surface temperatures are already close to bleaching thresholds and coral cover is projected to drop well below 5% cover under both scenarios by 2050, and below 1% cover under both scenarios by 2100.     

Carrot or Stick? Modelling How Landowner Behavioural Responses Can Cause Incentive-Based Forest Governance to Backfire

Mitigating the negative impacts of declining worldwide forest cover remains a significant socio-ecological challenge, due to the dominant role of human decision-making. Here we use a Markov chain model of land-use dynamics to examine the impact of governance on forest cover in a region. Each land parcel can be either forested or barren (deforested), and landowners decide whether to deforest their parcel according to perceived value (utility). We focus on three governance strategies: yearly incentive for conservation, one-time penalty for deforestation and one-time incentive for reforestation. The incentive and penalty are incorporated into the expected utility of forested land, which decreases the net gain of deforestation. By analyzing the equilibrium and stability of the landscape dynamics, we observe four possible outcomes: a stationary-forested landscape, a stationary-deforested landscape, an unstable landscape fluctuating near the equilibrium, and a cyclic-forested landscape induced by synchronized deforestation. We find that the two incentive-based strategies often result in highly fluctuating forest cover over decadal time scales or longer, and in a few cases, reforestation incentives actually decrease the average forest cover. In contrast, a penalty for deforestation results in the stable persistence of forest cover (generally >30%). The idea that larger conservation incentives will always yield higher and more stable forest cover is not supported in our findings. The decision to deforest is influenced by more than a simple, “rational” cost-benefit analysis: social learning and myopic, stochastic decision-making also have important effects. We conclude that design of incentive programs may need to account for potential counter-productive long-term effects due to behavioural feedbacks.     

Effectiveness of Nature Reserve System for Conserving Tropical Forests: A Statistical Evaluation of Hainan Island,China

Evaluating the effectiveness of existing nature reserve systems for the conservation of tropical forests is an urgent task to save the remaining biodiversity. Here, we tested the effectiveness of the reserve system on Hainan Island by conducting a three-way comparison of changes in forest area in locations within the reserves, adjacent to the reserves, and far outside of the reserves. We used a general linear model to control for the effects of covariates (historical forest area, elevation, slope, and distance to nearest roads), which may also be correlated with the changes in forest area, to better explain the effectiveness of the reserve system. From 2000 to 2010, the forest area inside Hainan’s nature reserve system showed an increase while adjacent unprotected areas and the wider, unprotected landscape both experienced deforestation. However, the simple inside-outside comparisons may overestimate the protective effect of the reserve system. Most nature reserves (>60%) showed increasing fragmentation. And the risk of rapid deforestation remained high at low elevations, where remaining forests tend to be easily logged and converted to commercial plantations. Future conservation efforts should pay more attention to those sites with less challenging environmental conditions.