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Tropical deforestation is responsible for around one tenth of total anthropogenic carbon emissions, and tropical protected areas (PAs) that reduce deforestation can therefore play an important role in mitigating climate change and protecting biodiversity and ecosystem services. While the effectiveness of PAs in reducing deforestation has been estimated, the impact on global carbon emissions remains unquantified. Here we show that tropical PAs overall reduced deforestation carbon emissions by 4.88 Pg, or around 29%, between 2000 and 2012, when compared to expected rates of deforestation controlling for spatial variation in deforestation pressure. The largest contribution was from the tropical Americas (368.8 GgC y

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha–1) at spatial scales ranging from 5 to 250 m (0.025–6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20–400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Understanding the mechanism of photosynthetic seasonality in Amazonian evergreen forests is critical for its formulation in global climate and carbon cycle models. However, the control of the unexpected photosynthetic seasonality is highly uncertain.[br/] Here we use eddy-covariance data across a network of Amazonian research sites and a novel evapotranspiration (E) and two-leaf-photosynthesis-coupled model to investigate links between photosynthetic seasonality and climate factors on monthly scales. It reproduces the GPP seasonality (R-2=0.45-0.69) with a root-mean-square error (RMSE) of 0.67-1.25gCm(-2)d(-1) and a Bias of -0.03-1.04gCm(-2)d(-1) for four evergreen forest sites.[br/] We find that the proportion of diffuse and direct sunlight governs the photosynthetic seasonality via their interaction with sunlit and shaded leaves, supported by a proof that canopy light use efficiency (LUE) has a strong linear relationship with the fraction of diffuse sunlight for Amazonian evergreen forests. In the transition from dry season to rainy season, incident total radiation (Q) decreased while LUE and diffuse fraction increased, which produced the large seasonal increase (similar to 34%) in GPP of evergreen forests.[br/] We conclude that diffuse radiation is an important environmental driver of the photosynthetic seasonality in tropical Amazon forests yet depending on light utilization by sunlit and shaded leaves. Besides, the GPP model simulates the precipitation-dominated GPP seasonality (R-2=0.40-0.69) at pasture and savanna sites. These findings present an improved physiological method to relate light components with GPP in tropical Amazon. Plain Language Summary Understanding the mechanism of photosynthetic seasonality in Amazonian evergreen forests is critical for its formulation in global climate and carbon cycle models. However, the control of the unexpected photosynthetic seasonality is highly uncertain. Here we use eddy-covariance data across a network of Amazonian research sites and a novel evapotranspiration (E) and two-leaf-photosynthesis-coupled model to investigate links between photosynthetic seasonality and climate factors on monthly scales. It reproduces the GPP seasonality (R2= 0.45-0.69) for four evergreen forest sites. We find that the proportion of diffuse and direct sunlight governs the photosynthetic seasonality via their interaction with sunlit and shaded leaves, supported by a proof that canopy light-use efficiency (LUE) has a strong linear relationship with the fraction of diffuse sunlight for Amazonian evergreen forests. We conclude that diffuse radiation is an important environmental driver of the photosynthetic seasonality in tropical Amazon forests yet depending on light utilization by sunlit and shaded leaves. Besides, the GPP model simulates the precipitation-dominated GPP seasonality (R2= 0.40 similar to 0.69) at pasture and savanna sites. These findings present an improved physiological method to relate light components with GPP in Amazon.

Three years of monthly growth increment data identified large interannual differences in growth rate across six contrasting species in a broadleaved, temperate forest with minimum management intervention (Wytham Woods, UK). Growth rates varied by species and canopy position, and were higher in canopy species. Growth rate in 2010 was up to 40% lower than in 2011 and 2012. This can best be explained as an effect of low temperature, which delayed the start of spring and the growing season. This had a greater impact on the growth of sub-canopy trees than that of canopy species. In temperate systems, late spring and summer is an important component of the whole growing season carbon balance because of long day length. In 2010 there were also periods of lower-than-average rainfall, which may additionally have constrained growth during the growing season. Fluctuations and seasonal changes in both temperature and rainfall are projected to continue, so we may expect to see increasing differences in growth and growth rates. A small effect of location relative to the nearest edge was also detected, with higher growth rates only found >50 m from the forest edge. The findings have implications for forest structure and productivity under climate change, and may thus inform current and future forest management.

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25ha), all stems 1cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 degrees S-61 degrees N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 degrees C), changes in precipitation (up to +/- 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8g Nm(-2)yr(-1) and 3.1g Sm(-2)yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.

Global climate change is already impacting species and ecosystems across the planet. Trees, although long-lived, are sensitive to changes in climate, including climate extremes. Shifts in tree species' distributions will influence biodiversity and ecosystem function at scales ranging from local to landscape; dry and hot regions will be especially vulnerable. The Australian continent has been especially susceptible to climate change with extreme heat waves, droughts, and flooding in recent years, and this climate trajectory is expected to continue. We sought to understand how climate change may impact Australian ecosystems by modeling distributional changes in eucalypt species, which dominate or codominate most forested ecosystems across Australia. We modeled a representative sample of Eucalyptus and Corymbia species (n = 108, or 14% of all species) using newly available Representative Concentration Pathway (RCP) scenarios developed for the 5th Assessment Report of the IPCC, and bioclimatic and substrate predictor variables. We compared current, 2025, 2055, and 2085 distributions. Overall, Eucalyptus and Corymbia species in the central desert and open woodland regions will be the most affected, losing 20% of their climate space under the mid-range climate scenario and twice that under the extreme scenario. The least affected species, in eastern Australia, are likely to lose 10% of their climate space under the mid-range climate scenario and twice that under the extreme scenario. Range shifts will be lateral as well as polewards, and these east-west transitions will be more significant, reflecting the strong influence of precipitation rather than temperature changes in subtropical and midlatitudes. These net losses, and the direction of shifts and contractions in range, suggest that many species in the eastern and southern seaboards will be pushed toward the continental limit and that large tracts of currently treed landscapes, especially in the continental interior, will change dramatically in terms of species composition and ecosystem structure.

Many studies have predicted the potential impacts of climate change on species’ distributions at large spatial scales, yet the role of more local-scale effects remains poorly explored. Addressing more localised impacts requires that new integrated modelling approaches are developed to address fine-scale processes including species’ dispersal and local connectivity. Here we integrate four models (a continental scale bioclimatic envelope model, a regional scale bioclimate and land use suitability model, a dispersal model, and a connectivity model) in a scale-dependent hierarchical framework. The approach has been used to analyse the fine scale impacts of climate change on species’ distributions within two contrasting case study regions located in East Anglia (UK) and Almeria (Spain). Eight and six species respectively were used to test our approach under three climate change scenarios. Despite the uncertainties inherent in the modelling approach, our analyses suggest two general conclusions: (i) climate change involves the development of transient conditions and fragmentation within the core of species distributions; (ii) climate change would favour the opening of gaps within the current vegetation zones, rather than a simple zonal shift of them. Dynamic and integrated conservation policies are required, that take account of the current and potential future spatial arrangement of species and their habitats, to assist species to respond to future environmental change.

©2015. The Authors. Atmospheric aerosol scatters solar radiation increasing the fraction of diffuse radiation and the efficiency of photosynthesis. We quantify the impacts of biomass burning aerosol (BBA) on diffuse radiation and plant photosynthesis across Amazonia during 1998-2007. Evaluation against observed aerosol optical depth allows us to provide lower and upper BBA emissions estimates. BBA increases Amazon basin annual mean diffuse radiation by 3.4-6.8% and net primary production (NPP) by 1.4-2.8%, with quoted ranges driven by uncertainty in BBA emissions. The enhancement of Amazon basin NPP by 78-156 Tg C a-1 is equivalent to 33-65% of the annual regional carbon emissions from biomass burning. This NPP increase occurs during the dry season and acts to counteract some of the observed effect of drought on tropical production. We estimate that 30-60 Tg C a-1 of this NPP enhancement is within woody tissue, accounting for 8-16% of the observed carbon sink across mature Amazonian forests.

declined at a rate of 0.3% yr � 1 , and the wet season decline was 0.1% yr � 1 . In the west of the region a 1% increase in CRDRP is indicated. Changes in forest composition and productivity may be linked to changes in CRDRP in that decreases in cloud cover in sunny regions or dry seasons may cause a decline in productivity, whereas declines in cloud cover in cloudy regions, or during cloudy seasons, may cause an increase in productivity.

Fire in high-elevation forest ecosystems can have severe impacts on forest structure, function and biodiversity. Using a 105-year data set, we found increasing elevation extent of fires in the Sierra Nevada, and pose five hypotheses to explain this pattern. Beyond the recognized pattern of increasing fire frequency in the Sierra Nevada since the late 20th century, we find that the upper elevation extent of those fires has also been increasing. Factors such as fire season climate and fuel build up are recognized potential drivers of changes in fire regimes. Patterns of warming climate and increasing stand density are consistent with both the direction and magnitude of increasing elevation of wildfire. Reduction in high elevation wildfire suppression and increasing ignition frequencies may also contribute to the observed pattern. Historical biases in fire reporting are recognized, but not likely to explain the observed patterns. The four plausible mechanistic hypotheses (changes in fire management, climate, fuels, ignitions) are not mutually exclusive, and likely have synergistic interactions that may explain the observed changes. Irrespective of mechanism, the observed pattern of increasing occurrence of fire in these subalpine forests may have significant impacts on their resilience to changing climatic conditions.

Despite a global political commitment to reduce biodiversity loss by 2010 through the 2002 Convention on Biological Diversity, declines are accelerating and threats are increasing ( 1 ). Major threats to biodiversity are habitat loss, invasion by exotic species and pathogens, and climate change, all principally driven by human activities. Although fossil fuel (FF) extraction has traditionally been seen as a temporary and spatially limited perturbation to ecosystems ( 2 ), even local or limited biodiversity loss can have large cascade effects on ecosystem function and productivity...