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The global tree restoration potential


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The restoration of trees remains among the most effective strategies for climate change mitigation. We mapped the global potential tree coverage to show that 4.4 billion hectares of canopy cover could exist under the current climate. Excluding existing trees and agricultural and urban areas, we found that there is room for an extra 0.9 billion hectares of canopy cover, which could store 205 gigatonnes of carbon in areas that would naturally support woodlands and forests. This highlights global tree restoration as our most effective climate change solution to date. However, climate change will alter this potential tree coverage. We estimate that if we cannot deviate from the current trajectory, the global potential canopy cover may shrink by ~223 million hectares by 2050, with the vast majority of losses occurring in the tropics. Our results highlight the opportunity of climate change mitigation through global tree restoration but also the urgent need for action.
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The global tree restoration potential
Jean-Francois Bastin
*, Yelena Finegold
, Claude Garcia
, Danilo Mollicone
Marcelo Rezende
, Devin Routh
, Constantin M. Zohner
, Thomas W. Crowther
The restoration of trees remains among the most effective strategies for climate change
mitigation. We mapped the global potential tree coverage to show that 4.4 billion hectares
of canopy cover could exist under the current climate. Excluding existing trees and
agricultural and urban areas, we found that there is room for an extra 0.9 billion hectares
of canopy cover, which could store 205 gigatonnes of carbon in areas that would naturally
support woodlands and forests. This highlights global tree restoration as our most effective
climate change solution to date. However, climate change will alter this potential tree
coverage. We estimate that if we cannot deviate from the current trajectory, the global
potential canopy cover may shrink by ~223 million hectares by 2050, with the vast majority
of losses occurring in the tropics. Our results highlight the opportunity of climate change
mitigation through global tree restoration but also the urgent need for action.
Photosynthetic carbon capture by trees is
likely tobe among our most effective strat-
egies to limit the rise of CO
tions across the globe (13). Consequently,
a number of international initiatives [such
as the Bonn Challenge, the related AFR100, and
the New York Declaration on Forests (4,5)] have
established ambitious targets to promote forest
conservation, afforestation, and restoration at a
global scale. The latest special report (1) by the
Intergovernmental Panel on Climate Change
(IPCC) suggests that an increase of 1 billion ha
of forest will be necessary to limit global warm-
ing to 1.5°C by 2050. However, it remains unclear
whether these restoration goals are achievable
might be possible under current or future cli-
mate conditions or where these trees could exist.
Previous efforts to estimate global tree cover
potential have scaled existing vegetation esti-
mates to the biome or ecoregion levels to provide
coarse approximations of global forest degra-
dation (6,7). However, quantitatively evaluating
which environments could support trees requires
that we build models using direct measurements
of tree cover (independent of satellite-derived
models) from protected areas, where vegetation
cover has been relatively unaffected by human
activity. With enough observations that span
the entire range of environmental conditions,
from the lowest to the highest possible tree cover,
we can interpolate these natural tree coveres-
timates across the globe to generate a predictive
understanding of the potential tree cover in the
absence of human activity.
To explore the determinants of potential tree
cover, we used 78,774 direct photo-interpretation
measurements (data file S1) (8)oftreecover
across all protected regions of the world (fig. S1)
(9,10). Using global environmental layers (table
S1) (11), we examined how climate, edaphic, and
topographic variables drive the variation in nat-
ural tree cover across the globe. The focus on
protected areas is intended to approximate nat-
ural tree cover. Of course, these regions are not
entirely free of human activity (11), presenting
slightly lower tree cover than expected in some
regions or higher tree cover than expected in
other regions because of low fire frequency, but
these ecosystems represent areas with minimal
human influence on the overall tree cover. We
then used a random forest machine-learning ap-
proach (12) to examine the dominant environ-
mental drivers of tree cover and generated a
predictive model (Fig. 1) that enables us to inter-
polate potential tree cover across terrestrial eco-
systems. The resulting mapEarthstreecarrying
capacitydefines the tree cover per pixel that
could potentially exist under any set of environ-
mental conditions, with minimal human activity
(Fig. 2A). This work is directly underpinned by
our systematic dataset of direct tree cover mea-
surements (entirely independent of climate and
modeled remote sensing estimates) (13)acrossthe
globe (fig. S1) (10).
Across the worlds protected areas (fig. S2),
tree cover ranged between peaks of 0% in dry
desert and 100% in dense equatorial forest, with
fewer values falling between these two extremes
(figs. S2 and S3). We paired these tree cover mea-
data (table S1) (11). Our resulting random forest
model had high predictive power [coefficient of
determination (R
) = 0.86; intercept = 2.05%
tree cover; slope = 1.06] (Fig. 1); rigorous k-fold
cross-validation (fig. S4A) (11) revealed that our
model could explain ~71% of the variation in tree
cover without bias (R
= 0.71; intercept = 0.34%
tree cover; slope = 0.99) (fig. S3, B and C). Our
k-fold cross-validation approach also allows us
to generate a spatially explicit understanding
of model uncertainty (figs. S5 and S6) (11). Across
all pixels, the mean standard deviation around
the modeled estimate is ~9% in tree cover (28%
ofthemeantreecover)(figs.S5andS6)(11). As
such, these models accurately reflected the dis-
tribution of tree cover across the full range of
protected areas. We then interpolated this ran-
dom forest model across all terrestrial ecosystems
using all 10 soil and climate variables to project
potential tree cover across the globe under exist-
ing environmental conditions.
The resulting map reveals Earths tree carry-
ing capacity at a spatial resolution of 30 arc sec
(Fig. 2A). The model accurately predicts the pres-
ence of forest in all existing forested land on the
planet (fig. S7A) but also reveals the extent of tree
cover that could naturally exist in regions beyond
existing forested lands. The most recent Food and
Agriculture Organization of the United Nations
(FAO) definition of forestcorresponds to a land
of at least 0.5 ha covered by at least 10% tree
Bastin et al., Science 365,7679 (2019) 5 July 2019 1of4
Crowther Lab, Department of Environmental Systems
Science, Institute of Integrative Biology, ETH-Zürich, Zürich,
Food and Agriculture Organization of the
United Nations, Rome, Italy.
Department of Environmental
Systems Science, Institute of Integrative Biology, ETH-Zürich,
Zürich, Switzerland.
Centre de Coopération Internationale
en la Recherche Agronomique pour le Développement
(CIRAD), UR Forest and Societies, Montpellier, France.
*Corresponding author. Email:
Fig. 1. Predicted vs. observed tree cover. (Aand B) The predicted tree cover (xaxes) compared
with the observed tree cover (yaxes). (A) Results as a density plot, with the 1:1 line in dotted
black and the regression line in continuous black (intercept = 2% forest cover; slope = 1.06;
= 0.86), which shows that the model is un-biased. (B) Results as boxplots, to illustrate the quality
of the prediction in all tree cover classes.
on July 7, 2019 from
cover and without agricultural activity or human
settlements (14). Using this definition, our map
reveals that about two-thirds of terrestrial land,
8.7 billion ha, could support forest (table S2).
That value is 3.2 billion ha more than the current
forested area (fig. S7A) (11,15). We estimate that
1.4 billion ha of this potential forest land is lo-
cated in croplands (>99%) and urban areas (<1%),
as delineated by the European Space Agencys
global land cover model (fig. S7B and table S2)
(16), and 1.5 billion ha with croplands as de-
lineated by Fritz et al. (fig. S7C and table S2) (17).
Therefore, ~1.7 billion to 1.8 billion ha of po-
tential forest land (defined as > 10% tr ee co ver)
exists in areas that were previously degraded,
dominated by sparse vegetation, grasslands, and
degraded bare soils.
To avoid the pitfalls of categorical forest defi-
nitions, we also evaluated the tree canopy cover
in a truly continuous scale (fig. S8). We refer to
canopy coveras the area of the land that is
covered by tree crown vertically projected to the
ground (for example, 50% of tree cover over 1 ha
corresponds to 0.5 ha of canopy cover) (fig. S8).
By accounting for all levels of tree cover (from
0 to 100%), this approach balances the relative
contribution of different forest types (such as
woodlands, open forest, and dense forest) and of
wooded lands outside forests (such as savannas)
across the globe.
In total, 4.4 billion ha of canopy cover can be
supported on land under existing climate con-
ditions (pixel uncertainty = 28%; global uncer-
tainty <1%) (table S2) (11). This value is 1.6 billion
ha more than the 2.8 billion ha existing on land
today (10,15). Of course, much of the land that
could potentially support trees across the globe is
currently used for human development and agri-
culture, which are necessary for supporting an
ever-growing human population. On the basis
of both the European Space Agencysgloballand
cover model (16) and on Fritz and colleagues
cropland layer (17), we estimate that 0.9 billion
hectares are found outside cropland and urban
regions (Fig. 2, B and C, and table S2) (11) and
may represent regions for potential restoration.
More than 50% of the tree restoration potential
can be found in only six countries (in million
hectares: Russia, +151; United States, +103; Canada,
+78.4; Australia, +58; Brazil, +49.7; and China,
+40.2) (data file S2), stressing the important re-
sponsibility of some of the worldsleadingeco-
nomies. By comparing our country-level results
to the commitments of 48 countries in the Bonn
Challenge (4), we can provide a scientific eval-
uation of the country-level restoration targets.
Approximately 10% of countries have committed
to restoring an area of land that considerably ex-
ceeds the total area that is available for restora-
tion (data file S2). By contrast, over 43% of the
countries have committed to restore an area that
is less than 50% of the area available for resto-
ration. These results reinforce the need for better
country-level forest accounting, which is critical
for developing effective management and resto-
ration strategies. Of course, it remains unclear
what proportion of this land is public or privately
owned, and so we cannot identify how much
land is truly available for restoration. However,
at a global scale, our model suggests that the
global forest restoration target proposed by the
IPCC (1) of 1 billion ha (defined as >10% tree
cover) is undoubtedly achievable under the cur-
rent climate. By scaling these forest area calcu-
lations by biome-level mean estimates of carbon
storage (18,19), we estimate that vegetation in
the potential restoration areas could store an
Bastin et al., Science 365,7679 (2019) 5 July 2019 2of4
Fig. 2. The current global tree restoration potential. (A) The global potential tree cover
representing an area of 4.4 billion ha of canopy cover distributed across the world. (Band C) The
global potential tree cover available for restoration. Shown is the global potential tree cover (A), from
which we subtracted existing tree cover (15) and removed agricultural and urban areas according to
(B) Globcover (16) and (C) Fritz et al.(17). This global tree restoration potential [(B) and (C)]
represents an area of 0.9 billion ha of canopy cover (table S2).
on July 7, 2019 from
additional 205 gigatonnes of carbon (GtC) if they
were restored to the status of existing forests
(table S2).
Our model accurately depicts the regions
environmental conditions. However, changing
climate conditions may alter the area of land
that could support forest growth over the rest
of the century, a point that needs to be consid-
ered when developing long-term restoration
projects. We tested this possibility by rerunning
our potential tree cover model under future cli-
mate conditions, projected under three Earth
System Models (10) and two Representative Con-
centration Pathways (RCP) scenarios (RCP 4.5
and 8.5) (1). Under both scenarios, the global
tree carrying capacity is lower than the present
day potential because of reductions in the po-
tential area of tropics. This is in stark contrast
to most current model predictions, which ex-
pect global tree cover to increase under climate
change (20). Although warming is likely to in-
crease tree cover in cold regions with low tree
cover (for example, in northern boreal regions
such as Siberia) or with existing open forests
(such as in tropical drylands) (Fig. 3), our model
highlights the high probability of consistent de-
clines of tropical rainforests with high tree cover.
Because the average tree cover in the expand-
ing boreal region (30 to 40%) is lower than that
in declining tropical regions (90 to 100%), our
global evaluation suggests that the potential glob-
al canopy cover will decrease under future cli-
mate scenarios, even if there is a larger total forest
area with >10% tree cover. Therefore, despite
potential increases in canopy cover in boreal
(~130 Mha), desertic (~30 Mha), montane
(~30 Mha), and temperate (~30 Mha) regions, the
potential loss of forest habitat in tropical regions
(~450 Mha) leads to a global loss of 223 Mha
of potential canopy cover by 2050, correspond-
ing to 46 GtC (Fig. 3B and table S3). Such risks
of loss do not account for future changes in
land use, such as pasture and cattle raising (7),
which might also contribute to the urgency of
the situation.
These models of future changes in tree cover
potential reveal insights into how the structure
of vegetation might change over time. Of course,
these models are characterized by high un-
certainty because, unlike the present-day in-
terpolations, we rely on extrapolation of our
machine-learning models outside of the existing
range of global climate conditions. These extrap-
olations cannot be considered to be future pro-
jections of potential forest extent because they do
not incorporate any of the ecological, hydrolog-
ical, and biogeochemical feedbacks that would
be associated with changes in forest cover. For
example, it is possible that elevated CO
trations under future climate scenarios might
enhance the growth of those existing trees, al-
though recent evidence suggests that increased
growth rate does not necessarily translate to in-
crease of carbon storage (21). However, our ap-
proach has a strong predictive power to describe
the potential tree cover in the absence of humans
under any given set of future climate scenarios.
The global photointerpretation dataset offers
the capacity to characterize the potential tree
cover under any given set of environmental con-
ditions. The resulting openly accessible map can
serve as a benchmark map to assess restoration
opportunities (such as tree planting and natural
assisted regeneration) around the globe, with a
tree cover of reference that respects the natu-
ral ecosystem type (for example, from wooded
savannah to dense forest). However, restoration
initiatives must not lead to the loss of existing
natural ecosystems, such as native grasslands,
that can support huge amounts of natural bio-
diversity and carbon. Using existing global land-
cover layers (1517), our maps reveal that there
is likely to be space for at least an additional
0.9 billion ha of canopy cover. If these restored
woodlands and forests were allowed to mature
to a similar state of existing ecosystems in pro-
tected areas, they could store 205 GtC. Of course,
the carbon capture associated with global res-
toration could not be instantaneous because it
would take several decades for forests to reach
maturity. Nevertheless, under the assumption
that most of this additional carbon was sourced
from the atmosphere, reaching this maximum
restoration potential would reduce a consid-
erable proportion of the global anthropogenic
carbon burden (~300 GtC) to date (1). This places
ecosystem restoration as the most effective solu-
tion at our disposal to mitigate climate change.
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Bastin et al., Science 365,7679 (2019) 5 July 2019 3of4
Fig. 3. Risk assessment of future changes in potential tree cover. (A) Illustration of expected losses in potential tree cover by 2050, under the
business as usualclimate change scenario (RCP 8.5), from the average of three Earth system models commonly used in ecology (cesm1cam5,
cesm1bgc, and mohchadgem2es). (B) Quantitative numbers of potential gain and loss are illustrated by bins of 5° along a latitudinal gradient.
on July 7, 2019 from
15. M. C. Hansen et al., Science 342, 850853 (2013).
16. O. Arino et al., Global Land Cover Map for 2009 (GlobCover
2009) (European Space Agency, Université catholique de
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We warmly thank all the members of the Crowther lab team,
not listed as coauthors of the study, for their incredible support.
We also are very grateful to the Google Earth Outreach team for
allowing us the storage expansion for ou r laboratory. Fu ndin g:
This work was supported by grants to T.W.C. from DOB Ecology,
Plant-for-the-Planet, and the German Federal Ministry for Economic
Cooperation and Development. The data collection was partially
supported by the International Climate Initiative of the Federal
Ministry for the Environment, Nature Conservation, Building and
Nuclear Safety of Germany. Author contributions: J.-F.B. conceived
the study. J.-F.B. and D.R. performed the analyses. J.-F.B., Y.F.,
C.G., D.M., M.R., D.R., C.M.Z., and T.W.C. wrote the manuscript.
Competing interests: The authors declare that there are no
competing interests. Data and materials availability: All data are
available in the manuscript or the supplementary materials. The
global tree cover potential map, corresponding to Fig. 2A, isaccessible
online for visualization at https://bastinjf_climate.users.earthengine.
app/view/potential-tree-cover, the Earth engine script to produce the
map is accessible online at
ee5cf5186b5ad0f659cc7a43054f072c, and all related layers are
accessible online at or upon request to the
corresponding author.
Materials and Methods
Figs. S1 to S12
Tables S1 to S3
References (2229)
Data Files S1 and S2
21 February 2019; accepted 21 May 2019
Bastin et al., Science 365,7679 (2019) 5 July 2019 4of4
on July 7, 2019 from
The global tree restoration potential
Zohner and Thomas W. Crowther
Jean-Francois Bastin, Yelena Finegold, Claude Garcia, Danilo Mollicone, Marcelo Rezende, Devin Routh, Constantin M.
DOI: 10.1126/science.aax0848
(6448), 76-79.365Science
, this issue p. 76; see also p. 24Science
cut the atmospheric carbon pool by about 25%.
than 500 billion trees and more than 200 gigatonnes of additional carbon at maturity. Such a change has the potential to
billion hectares of continuous forest. This would represent a greater than 25% increase in forested area, including more
cover could exist outside of existing forests and agricultural and urban land. Ecosystems could support an additional 0.9
the globe (see the Perspective by Chazdon and Brancalion). Their spatially explicit maps show how much additional tree
used direct measurements of forest cover to generate a model of forest restoration potential acrosset al.change. Bastin
The restoration of forested land at a global scale could help capture atmospheric carbon and mitigate climate
The potential for global forest cover
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... Globally afforestation has been considered an important mitigation tool for many years (e.g. Bastin et al., 2019;1.1 ...
... Bateman and Lovett, 2000). Secondly, despite the stated goal of climate change mitigation, afforestation policy is rarely guided by an understanding of the evolution of the carbon storage potential over time of newly planted forest stands when considering projected warming tendencies (Bastin et al. 2019). ...
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... Here we showed that changes in climate and disturbance regimes can have a considerable impact on a landscape's ability to sequester and store carbon. In light of the hopes put into forests and their role in climate change mitigation and adaptation (Bastin et al., 2019, Kaarakka et al., 2021, Chausson et al., 2020, this a concerning finding. While forests can contribute strongly to climate change mitigation, they are not exempt from climate change impacts that can considerably reduce their ability to act as carbon sinks (Anderegg et al., 2020). ...
Forests are one of the most important components of the global carbon cycle. Consequently, forest protection as a nature-based climate solution has garnered increasing interest. Protected areas instated to safeguard biodiversity provide an opportunity to maximize carbon storage in situ, with important co-benefits between conservation and climate change mitigation. However, changing climate and disturbance regimes put this carbon storage function at risk. Here we investigated carbon sequestration and storage in a protected landscape in the German Alps (Berchtesgaden National Park) throughout the 21st century. We simulated the impacts of climate change as well as increasing wind and bark beetle disturbances on cumulative Net Ecosystem Production using a process-based forest landscape model. Considering a wide range of potential changes in wind frequency and speed under a variety of climate change scenarios, we addressed the question under which future conditions the landscape will turn from a carbon sink to a carbon source. While the landscape was a net carbon sink at the end of the simulation in 76 per cent of the simulation runs, increasing disturbances and climate change greatly reduced its carbon sink capacity. Under RCP2.6, the landscape remained a robust carbon sink even under elevated disturbance (probability of turning from sink to source between 0 per cent and 25 per cent). In contrast, carbon release was likely under RCP8.5 even with little change in the disturbance regime (probability: 30 per cent to 95 per cent). Productive areas in lower elevations that currently have the highest carbon density on the landscape were contributing most strongly to a reduction of the carbon sink strength. Our study reveals that the effect of protected areas acting as nature-based climate solutions might be overestimated if the risks from changing climate and disturbance regimes are neglected. We therefore call for a more explicit consideration of future forest dynamics in the discussion of the potential role of forests in climate change mitigation.
... Forests play a crucial and unique role in land carbon uptake and storage, and may have a large climate mitigation potential (Anderegg, Trugman, Badgley, Anderson, et al., 2020;Bastin et al., 2019;Doelman et al., 2020;N. L. Harris et al., 2021;Pan et al., 2011;Reichstein et al., 2013). ...
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Plain Language Summary The occurrence patterns of seasonal extreme drought and wetness events are dramatically shifting with climate warming. However, how will different seasonal extreme climate regimes affect the bioclimatic sensitivity of tree growth remains poorly understood. In this study, we investigated the sensitivity of tree growth to different seasonal climate factors and preceding tree growth conditions during 1951–2013 under different seasonal extreme drought/wetness regimes, using 1,032 tree ring chronologies covering 121 gymnosperm and angiosperm species. We found the magnitude in tree growth reduction caused by seasonal extreme drought events is much larger than that in tree growth stimulation by seasonal extreme wetness events in arid and temperate regions. Tree growth in arid and temperate dry regions is more negatively impacted by extreme drought events in pre‐growing‐seasons (PGSs) than in growing‐seasons. We further found that angiosperms are more sensitive to PGS water availability, while gymnosperms are more sensitive to legacy effects of the preceding tree growth conditions in temperate dry and humid regions. These findings highlight divergent bioclimatic legacy effects on tree growth under different seasonal extreme climate regimes, and provide valuable insights into the future trajectories of forest growth across diverse ecoregions and functional groups in a more extreme climate.
The role of nature restoration in mitigating the impacts of climate change is receiving increasing attention, yet the mitigation potential is often assessed in terms of carbon removal rather than the ability to meet temperature goals, such as those outlined in the Paris Agreement. Here, we estimate the global removal potential from nature restoration constrained by a “responsible development” framework and the contribution this would make to a 1.5°C temperature limit. Our constrained restoration options result in a median of 103 GtC (5%–95% range of −91 to 196 GtC) in cumulative removals between 2020 and 2100. When combined with deep-decarbonization scenarios, our restoration scenario briefly exceeds 1.5°C before declining to between 1.25°C and 1.5°C by 2100 (median, 50% probability). We conclude that additional carbon sequestration via nature restoration is unlikely to be done quickly enough to notably reduce the global peak temperatures expected in the next few decades. Land restoration is an important option for tackling climate change but cannot compensate for delays in reducing fossil fuel emissions.
Referring to the manifold studies and the long-term experiences of the restoration of near-natural ecosystems and traditional land-use types, respectively, examples from all over the world are outlined. Additionally to rewilding as a progressive approach to nature conservation, letting nature take care of itself and enabling natural processes, particularly the restoration of heathland, agricultural grassland, savannas, agroforestry systems, silvopastoral systems, coppice forests, lakes, peatland, coastal mangroves, terraced and irrigation land-use systems is addressed. The unique features of these ecosystems and land-use systems, respectively, which are or could be embedded in traditional and multifunctional cultural landscapes encompass high biodiversity, agrobiodiversity, and agrodiversity, respectively, as well as the provision of manifold ecosystem and landscape services.
Contemporary synthetic biology-based biotechnologies are generating tools and strategies for reprogramming genomes for specific purposes, including improvement and/or creation of microbial processes for tackling climate change. While such activities typically work well at a laboratory or bioreactor scale, the challenge of their extensive delivery to multiple spatio-temporal dimensions has hardly been tackled thus far. This state of affairs creates a research niche for what could be called Environmental Galenics (EG), i.e. the science and technology of releasing designed biological agents into deteriorated ecosystems for the sake of their safe and effective recovery. Such endeavour asks not just for an optimal performance of the biological activity at stake, but also the material form and formulation of the agents, their propagation and their interplay with the physico-chemical scenario where they are expected to perform. EG also encompasses adopting available physical carriers of microorganisms and channels of horizontal gene transfer as potential paths for spreading beneficial activities through environmental microbiomes. While some of these propositions may sound unsettling to anti-genetically modified organisms sensitivities, they may also fall under the tag of TINA (there is no alternative) technologies in the cases where a mere reduction of emissions will not help the revitalization of irreversibly lost ecosystems. This article is part of the theme issue ‘Ecological complexity and the biosphere: the next 30 years’.
Technical Report
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Cambodia's Protected Areas provide critical ecosystem services and are key to climate change mitigation and adaptation. Despite rapid economic growth in recent years, Cambodia remains a biodiversity hotspot in the region, providing critical ecosystem services. Cambodia has one of the highest ratios, globally, of territory in Protected Areas (PAS). The PAS contain rich biodiversity and ecosystems that have been largely lost in neighboring countries. These PAS also provide critical ecosystem services to Cambodia's economy in terms of water flows regulation, sedimentation control, non-timber forest products, and ecotourism revenues. This report aims to provide support to the Royal Government of Cambodia (RGC) in identifying new economic opportunities to develop livelihoods through the Cambodia Sustainable Landscape and Ecotourism Project (CSLEP). The recommendations are intended to be practical and implementable during the lifetime of the project. The development objective of the CSLEP is to improve PAS management, promote ecotourism opportunities, and promote non-timber forest products (NTFPs) in the Cardamom Mountains Tonle Sap area. This report focuses on opportunities for economic development in Community Protected Areas (CPAs) and Community Forestry (CF), and more generally, for people living in buffer areas around PAS in the CMC. Following a chapter providing the context in Cambodia and an overview of the landscape dynamics and livelihoods within it, the report outlines planning needs for conservation-friendly development and presents opportunities for Conservation-friendly economic activities (CFEA). Based on the assessment of the barriers to establishing an enabling environment for private sector engagement, options for job creation are discussed, followed by recommendations for developing value chains and enabling conditions for private sector participation.
Savannas cover a wide climatic gradient across large portions of the Earth’s land surface and are an important component of the terrestrial biosphere. Savannas have been undergoing changes that alter the composition and structure of their vegetation such as the encroachment of woody vegetation and increasing land-use intensity. Monitoring the spatial and temporal dynamics of savanna ecosystem structure (e.g., partitioning woody and herbaceous vegetation) and function (e.g., aboveground biomass) is of high importance. Major challenges include misclassification of savannas as forests at the mesic end of their range, disentangling the contribution of woody and herbaceous vegetation to aboveground biomass, and quantifying and mapping fuel loads. Here, we review current (2010–present) research in the application of satellite remote sensing in savannas at regional and global scales. We identify emerging opportunities in satellite remote sensing that can help overcome existing challenges. We provide recommendations on how these opportunities can be leveraged, specifically (1) the development of a conceptual framework that leads to a consistent definition of savannas in remote sensing; (2) improving mapping of savannas to include ecologically relevant information such as soil properties and fire activity; (3) exploiting high-resolution imagery provided by nanosatellites to better understand the role of landscape structure in ecosystem functioning; and (4) using novel approaches from artificial intelligence and machine learning in combination with multisource satellite observations, e.g., multi-/hyperspectral, synthetic aperture radar (SAR), and light detection and ranging (lidar), and data on plant traits to infer potentially new relationships between biotic and abiotic components of savannas that can be either proven or disproven with targeted field experiments.
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It is generally accepted that animal heartbeat and lifespan are often inversely correlated, however, the relationship between productivity and longevity has not yet been described for trees growing under industrial and pre-industrial climates. Using 1768 annually resolved and absolutely dated ring width measurement series from living and dead conifers that grew in undisturbed, high-elevation sites in the Spanish Pyrenees and the Russian Altai over the past 2000 years, we test the hypothesis of grow fast-die young. We find maximum tree ages are significantly correlated with slow juvenile growth rates. We conclude, the interdependence between higher stem productivity, faster tree turnover, and shorter carbon residence time, reduces the capacity of forest ecosystems to store carbon under a climate warming-induced stimulation of tree growth at policy-relevant timescales.
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Land change is a cause and consequence of global environmental change1,2. Changes in land use and land cover considerably alter the Earth's energy balance and biogeochemical cycles, which contributes to climate change and-in turn-affects land surface properties and the provision of ecosystem services1-4. However, quantification of global land change is lacking. Here we analyse 35 years' worth of satellite data and provide a comprehensive record of global land-change dynamics during the period 1982-2016. We show that-contrary to the prevailing view that forest area has declined globally5-tree cover has increased by 2.24 million km2 (+7.1% relative to the 1982 level). This overall net gain is the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16 million km2 (-3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover. The mapped land changes and the driver attributions reflect a human-dominated Earth system. The dataset we developed may be used to improve the modelling of land-use changes, biogeochemical cycles and vegetation-climate interactions to advance our understanding of global environmental change1-4,6.
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In an era of massive biodiversity loss, the greatest conservation success story has been the growth of protected land globally. Protected areas are the primary defense against biodiversity loss, but extensive human activity within their boundaries can undermine this. Using the most comprehensive global map of human pressure, we show that 6 million square kilometers (32.8%) of protected land is under intense human pressure. For protected areas designated before the Convention on Biological Diversity was ratified in 1992, 55% have since experienced human pressure increases. These increases were lowest in large, strict protected areas, showing that they are potentially effective, at least in some nations. Transparent reporting on human pressure within protected areas is now critical, as are global targets aimed at efforts required to halt biodiversity loss.
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Carbon stocks in vegetation have a key role in the climate system. However, the magnitude, patterns and uncertainties of carbon stocks and the effect of land use on the stocks remain poorly quantified. Here we show, using state-of-the-art datasets, that vegetation currently stores around 450 petagrams of carbon. In the hypothetical absence of land use, potential vegetation would store around 916 petagrams of carbon, under current climate conditions. This difference highlights the massive effect of land use on biomass stocks. Deforestation and other land-cover changes are responsible for 53-58% of the difference between current and potential biomass stocks. Land management effects (the biomass stock changes induced by land use within the same land cover) contribute 42-47%, but have been underestimated in the literature. Therefore, avoiding deforestation is necessary but not sufficient for mitigation of climate change. Our results imply that trade-offs exist between conserving carbon stocks on managed land and raising the contribution of biomass to raw material and energy supply for the mitigation of climate change. Efforts to raise biomass stocks are currently verifiable only in temperate forests, where their potential is limited. By contrast, large uncertainties hinder verification in the tropical forest, where the largest potential is located, pointing to challenges for the upcoming stocktaking exercises under the Paris agreement.
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Better stewardship of land is needed to achieve the Paris Climate Agreement goal of holding warming to below 2 °C; however, confusion persists about the specific set of land stewardship options available and their mitigation potential. To address this, we identify and quantify "natural climate solutions" (NCS): 20 conservation, restoration , and improved land management actions that increase carbon storage and/or avoid greenhouse gas emissions across global forests, wetlands, grasslands, and agricultural lands. We find that the maximum potential of NCS-when constrained by food security, fiber security, and biodiversity conservation-is 23.8 petagrams of CO 2 equivalent (PgCO 2 e) y −1 (95% CI 20.3-37.4). This is ≥30% higher than prior estimates, which did not include the full range of options and safeguards considered here. About half of this maximum (11.3 PgCO 2 e y −1) represents cost-effective climate mitigation, assuming the social cost of CO 2 pollution is ≥100 USD MgCO 2 e −1 by 2030. Natural climate solutions can provide 37% of cost-effective CO 2 mit-igation needed through 2030 for a >66% chance of holding warming to below 2 °C. One-third of this cost-effective NCS mitigation can be delivered at or below 10 USD MgCO 2 −1. Most NCS actions-if effectively implemented-also offer water filtration, flood buffer-ing, soil health, biodiversity habitat, and enhanced climate resilience. Work remains to better constrain uncertainty of NCS mitigation estimates. Nevertheless, existing knowledge reported here provides a robust basis for immediate global action to improve ecosystem stewardship as a major solution to climate change. climate mitigation | forests | agriculture | wetlands | ecosystems
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We created a new dataset of spatially interpolated monthly climate data for global land areas at a very high spatial resolution (approximately 1 km 2). We included monthly temperature (minimum, maximum and average), precipitation, solar radiation, vapour pressure and wind speed, aggregated across a target temporal range of 1970–2000, using data from between 9000 and 60 000 weather stations. Weather station data were interpolated using thin-plate splines with covariates including elevation, distance to the coast and three satellite-derived covariates: maximum and minimum land surface temperature as well as cloud cover, obtained with the MODIS satellite platform. Interpolation was done for 23 regions of varying size depending on station density. Satellite data improved prediction accuracy for temperature variables 5–15% (0.07–0.17 ∘ C), particularly for areas with a low station density, although prediction error remained high in such regions for all climate variables. Contributions of satellite covariates were mostly negligible for the other variables, although their importance varied by region. In contrast to the common approach to use a single model formulation for the entire world, we constructed the final product by selecting the best performing model for each region and variable. Global cross-validation correlations were ≥ 0.99 for temperature and humidity, 0.86 for precipitation and 0.76 for wind speed. The fact that most of our climate surface estimates were only marginally improved by use of satellite covariates highlights the importance having a dense, high-quality network of climate station data.
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Dryland biomes cover two-fifths of Earth’s land surface, but their forest area is poorly known. Here, we report an estimate of global forest extent in dryland biomes, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at (i) very high spatial resolution and (ii) very high temporal resolution, which are available through the Google Earth platform. We show that in 2015, 1327 million hectares of drylands had more than 10% tree-cover, and 1079 million hectares comprised forest. Our estimate is 40 to 47% higher than previous estimates, corresponding to 467 million hectares of forest that have never been reported before. This increases current estimates of global forest cover by at least 9%.
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This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total).
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The GlobCover initiative of ESA developed and demonstrated a service for the generation of global land cover maps, based on Envisat MERIS Fine Resolution (300 m) mode data. ESA and Université catholique de Louvain demonstrated the possibility to use the GlobCover system operationally by delivering GlobCover 2009, the 2009 global land cover map, within a year of the last satellite acquisition. For maximum user benefit the thematic legend of GlobCover is compatible with the UN Land Cover Classification System (LCCS). The system is based on an automatic pre-processing and classification chain. Finally, the global land cover map was validated by an international group of land cover experts and the validation reports are also available to the user community.
Plans to triple the area of plantations will not meet 1.5 °C climate goals. New natural forests can, argue Simon L. Lewis, Charlotte E. Wheeler and colleagues.