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LETTER doi:10.1038/nature13717
A global strategy for road building
William F. Laurance
1
, Gopalasamy Reuben Clements
1,2
, Sean Sloan
1
, Christine S. O’Connell
3
, Nathan D. Mueller
4
, Miriam Goosem
1
,
Oscar Venter
1
, David P. Edwards
5
, Ben Phalan
6
, Andrew Balmford
6
, Rodney Van Der Ree
7
& Irene Burgues Arrea
8
The number and extent of roads will expand dramatically this century
1
.
Globally, at least 25 million kilometres of new roads are anticipated
by 2050; a 60% increase in the totallength of roads over that in 2010.
Nine-tenths of all road construction is expected to occur in develop-
ing nations
1
, including many regions that sustain exceptional biodi-
versity and vital ecosystem services. Roads penetrating into wilderness
or frontier areas are a major proximate driver of habitat loss and frag-
mentation, wildfires, overhunting and otherenvironmental degrada-
tion, oftenwith irreversible impacts on ecosystems
2–5
. Unfortunately,
much road proliferation is chaotic or poorly planned
3,4,6
, and the rate
of expansion is so great that it oftenoverwhelms the capacity of envi-
ronmental planners and managers
2–7
.Herewepresentaglobalscheme
for prioritizing road building. This large-scale zoning plan seeks to
limit the environmental costs of road expansion while maximizing
its benefits for human development, by helping to increase agricul-
tural production, which is an urgent priority given that global food
demand could double by mid-century
8,9
. Our analysisidentifies areas
with high environmental values where future road building should
be avoided if possible, areas where strategic road improvements could
promote agricultural development with relatively modest environ-
mental costs, and ‘conflict areas’ whereroad building could have size-
able benefits for agriculture but with serious environmental damage.
Our plan provides a template for proactively zoning and prioritizing
roads during the most explosive era of road expansion in human history.
A multitude of factors is promoting rapid road expansion globally,
includinga quest for valuable resources such astimber, minerals, oiland
arable land, and initiatives to increase regional trade, transportation and
energy infrastructure
4,7
. Yet, while new roads can promote social and
economic development
10,11
, they also can open a Pandora’s box of envi-
ronmental problems
2–7
. This is especially the case in pristine or frontier
regions, wherenew roads often dramaticallyincrease land colonization,
habitat disruption, and overexploitation of wildlife and natural resources
2–6
.
It is broadly understood that the best strategy for maintaining the integ-
rity of wilderness areas is by ‘avoiding the first cut’—keeping them road-
free
4
—because deforestation is highly contagious spatially
12
and because
new roads tend to spawn networks of secondary and tertiary roads that
greatly increase the extent of environmental damage
4
. Unfortunately,
new roads are now penetrating into many of the world’s last surviving
wildernesses, including the Amazon
2,5,6,10
, New Guinea
13
, Siberia
14
and
the Congo Basin
3,11,15
.
However, some roads generate substantial social and economic ben-
efits with only modest environmental costs. Particularly in developing
nations, vast expanses of land havebeen settled buthave low agricultural
productivity because of poor access to fertilizers and modern farming
technologies
11,16
. In such contexts, new roads—or road improvements
such as paving—could increase access to agricultural supplies and markets,
facilitating production increases and lowering post-harvest crop losses
13,17
.
As such accessible areas tend to sustain more prosperous rural livelihoods,
they may also act as ‘magnets’, attracting colonistsaway from environ-
mentally vulnerable frontier areas, such as the margins of forests
17,18
.In
this way, improving transportation in suitable areas could help to con-
centrate and improve agricultural production, raising farm yields
11,13
while
potentially promoting land sparing for nature conservation
19
.
Despite the pivotal role that roads have in human land-use, efforts
to plan and zone roads are extremely inadequate. First, although roads
increasingly dominate muchof Earth’s land surface (Fig. 1),many roads
are unmapped, especially in developing nations; in the Brazilian Amazon,
for example, the total length of unofficial or illegal roads is nearly triple
that of official roads
20
. Second,environmental-impact assessmentsoften
place the burden of proof on road opponents
21,22
, who rarely have suf-
ficient information on rare species, biological resources and ecosystem
services
23
needed to determine the actual environmental costs of roads.
Third, many road assessments are limited in scope
4,22
, focusing only on
the direct effects of road building while ignoring its critical indirect effects,
such as promoting deforestation, fires, poaching and land speculation.
Finally, because there is no strategic, proactive system for zoning roads
globally, road projects must be assessed with little information on their
broader context (see the 2013 report on high-risk road development by
the ConservationStrategy Fund; http://conservation-strategy.org/sites/
default/files/field-file/CSFPolicyBrief_14_english_1.pdf). This increases
the burden on road planners and evaluators,who are being swamped by
the unprecedented pace of contemporary road expansion
2–7,11,15,20
.
For these reasons, we devised a ‘global roadmap’ to identify areas in
which roadsor road improvementsare likely to have major costs or ben-
efits. The map has two components: an environmental-values layer that
estimates the natural importance of ecosystems, and a road-benefits layer
that estimates the potential for increased agricultural production, in part
via new or improved roads. Combining these two layers allows us to
identify areas where roads or road upgrades could have large potential
benefits, areas where road building should be avoided wherever possible,
and conflict areas where their potential costs and benefits are both sizeable.
We created the environmental-values layer (Fig. 2a) by integrating
global data sets on three classes of parameters: biodiversity (number of
threatened terrestrial-vertebrate species, estimated number of plant spe-
cies per ecoregion); key wilderness habitats (G200 terrestrial ecoregions,
important bird areas and endemic bir d areas, biodiversity hotspots, fron-
tier forests, high-biodiversity wilderness areas); and carbon storageand
climate-regulation services ofthe local ecosystem (seeMethods and Sup-
plementary Figs 1–11). Values for each class were equally weighted, rescaled
(range: 0–1) and then averaged to produce the environmental-values
layer. Regions that scored highly on this layer include wet and humid
tropical and subtropical forests, Mediterranean ecosystems, wildlife-rich
savanna woodlands in South America and Africa, many islands, certain
mountain ranges, and some higher-latitude forests, among others.
The road-benefits layer(Fig. 2b) identifies areas where new roads or
road improvements could potentially help to improve agricultural pro-
duction.Like the environmental-values layer, it is a relative index(range:
0–1). In general terms, areas that score highly on this layer have been
largely converted to agriculture (and thus have little native vegetation
remaining), arerelatively low-yielding despite having soils and climates
1
Centre for Tropical Environmental and Sustainability Science, and College of Marine and Environmental Sciences, James Cook University, Cairns, Queensland 4878, Australia.
2
Kenyir Research Institute,
Universiti Malaya Terengganu, 21030 Kuala Terengganu, Malaysia.
3
Institute on the Environment, and Department of Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, Minnesota
55108, USA.
4
Center for the Environment, Harvard University, Cambridge, Massachusetts 02138, USA.
5
Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK.
6
Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK.
7
Australian Research Centre for Urban Ecology, and School of Botany, University of Melbourne, Melbourne, Victoria 3010,
Australia.
8
Conservation Strategy Fund, 663-2300 Curridabat, San Jose
´, Costa Rica.
11 SEPTEMBER 2014 | VOL 513 | NATURE | 229
Macmillan Publishers Limited. All rights reserved
©2014
broadly suitable for agriculture, are not so distant from urban markets
that crop-transportation costs would be prohibitive even with new or
improvedroads, and are expected to see large future increases in agricul-
tural production to meet projected food or export demands (see Methods
and Supplementary Figs 12–16 for details of how these data sets were
integrated). All continents have regions that score highly, including parts
of south Asia, east and southeast Asia, West and East Africa, central Eur-
asia, west-central North America, Central America and Mexico, and the
Atlantic region of South America.
We classified each of the environmental-values (Fig. 2a) and road-
benefits (Fig. 2b) layers into deciles and then cross-tabulated them to
generate 100 unique colour combinations (see Supplementary Infor-
mation for details). In this scheme, green-shaded areas are where road
building would have relatively high environmental costs and only modest
potential benefits for agriculture. Red-shaded areas are the opposite, with
high potential to increase agricultural production and lower scores on the
environmental-values axis. Black and dark-shaded areas are ‘conflict
zones’ with high values on both axes, whereas white and light-shaded
areas are lower priorities for both environment and agriculture.
On top of this scheme we overlaid polygons for 177,857 protected areas
(Supplementary Fig. 17) globally, using available data from the World
Database on Protected Areas (http://www.wdpa.org). Protected areas
Figure 1
|
The distribution of major roads globally. Roads are indicated
in black; white areas lack mapped roads. The quality of road maps varies
greatly among nations, with many smaller and unofficial roads remaining
unmapped. We generated this map using data from the integrated gROADS
database (http://sedac.ciesin.columbia.edu/data/set/groads-global-roads-
open-access-v1; accessed 7 June 2014); Center for International Earth Science
Information Network - CIESIN - Columbia University, and Information
Technology Outreach Services - ITOS - University of Georgia. 2013. Global
Roads Open Access Data Set, Version 1 (gROADSv1). Palisades, NY: NASA
Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/
10.7927/H4VD6WCT.
a
High : 1
Low : 0
b
High : 1
Low : 0
Figure 2
|
The environmental-values and road-benefits layers. a,b, The
environmental-values layer (a) integrates data on terrestrial biodiversity, key
habitats, wilderness, and environmental services. The road-benefits layer
(b) shows areas broadly suitable for agricultural intensification, where new
roads or road improvements could potentially promote increased production.
See Supplementary Information for data sources.
RESEARCH LETTER
230 | NATURE | VOL 513 | 11 SEPTEMBER 2014
Macmillan Publishers Limited. All rights reserved
©2014
were zoned fully green because we judged that they should be free of
new roads wherever possible, given that roads can facilitate illegal acti-
vities such as poaching, encroachment, and vehicle-related road-kill of
wildlife
2–4
that are contrary to the goals of protected-area management
24,25
.
The resulting global roadmap (Fig. 3)attempts to portray key relative
risks and rewards of road building for each 1-km
2
pixel on Earth’s land
surface. In broad terms, our map illustrates the enormous potential for
environmental loss and degradation as a result of contemporary road
expansion (Table 1 and Supplementary Fig. 18). Roads are currently pro-
liferating or planned in manyareas categorized as having high environ-
mental values but only modest agricultural potential, such as the Amazon
Basin, parts of the Asia-Pacific region, and higher-latitude forests in the
Northern Hemisphere.
The roadmap also reveals extensive conflict areas (Fig. 3), where environ-
mentaland agricultural values are both high, particularly inSub-Saharan
Africa,Madagascar, Central America, the Mediterranean, southeast and
south-central Asia, the Andes, and theAtlantic regionof South America.
Conflict zones often occur in regions withrapid population growth,high
speciesendemism, or both.In total, 1.97 billionhectares (15.3%of global
land area) fall into conflict areas (Table 1). Land-use pressures in such
regions are mounting rapidly; it has been estimated that, unless current
agricultural yields markedly improve, approximately 1 billion hectares
of additional farming and grazing land will be needed by 2050 to meet
projected food demands
9
, with extensive additional lands converted for
production of biofuels
26
.
However, our road-planning scheme also suggests that many areas
could be targeted for agricultural production increases with relatively
modest environmental costs.Such areas include expanses of the Indian
subcontinent, centralEurasia, the Irano-Anatolian region, and African
Sahel, amongothers (Fig. 3). In total, 1.46billion hectares of land(11.4%
of global land area) is zoned red (Table 1), suggesting that there is con-
siderable potential on every continent to increase agricultural produc-
tion, by raising yields on existing farming and grazing land.
Although improved roads or other transportation can facilitate agricul-
tural yield increases
11,13,17,18
, additional measures—such as investments in
improved farming methods, fertilizers and, where appropriate, irrigation—
will also be essential. A particular challenge will be devising strategies
to help developing nations with exceptional environmental values, such
as Madagascar and Indonesia (Fig. 2a), to meet pressing economic and
food-production needs while limiting the environmental costs of rapid
road development. For such nations, international payments forecosys-
tem services, ecotourism, and sustainable harvesting of native production
forests could potentially help to balance economic and environmental
priorities
27
. A further priority when planning road and agricultural invest-
ments is to considerhow factors such as inter-annual weather variability
or projected future climate change could impact on crop yields
28
.
The global roadmap we created underscores the potential benefits and
need for strategic road planning, but actual road planning will be under-
taken at smaller national or regional scales. For this, we created more
detailed maps that show finer-scale features (for example, Extended Data
Fig. 1). These maps and their components are freely available (http://
global-roadmap.org) andcan be combined with additional data, such as
more detailed information on topography, soils, existing croplands and
local road networks, to facilitate road planning.
Integrating local information is important because the drivers and
environmental impacts of road construction will vary in different con-
texts. For example, in arable, largely road-freeareas of East Africa (Fig. 4a),
new roads driven by a burgeoning mining boom
11,29
could provoke major
land-use changes andhabitat loss. Yetexpanding roads from timber and
miningoperations could also have large impacts in Siberia (Fig.4b), even
No data
Environmental values
Agricultural potential
Figure 3
|
A global roadmap. Shown are priority road-free areas (green
shades), priority agricultural areas (red shades), conflict areas (dark shades),
and lower-priority areas(light shades). Values of the environmental-values and
road-benefits layers are each divided into deciles, yielding 100 unique colour
combinations. See Supplementary Information for details and data sources.
Table 1
|
Percentages of seven geographical regions that fall into four broad categories on the global roadmap
Zone Africa Asia Australia Europe North and Central America South America Oceania Global
Conserve 29.03 45.69 34.21 26.44 47.39 66.28 95.29 42.96
Agriculture 7.93 12.44 3.63 32.92 11.35 6.83 0.23 11.40
Conflict 24.75 14.87 7.01 9.10 8.70 15.74 0.58 15.34
Low-tension 38.30 27.00 55.15 31.54 32.55 11.14 3.89 30.30
Total area 29,805 44,174 7,693 9,670 23,395 17,662 412 132,811
Data on the total areas of each region are given in km
2
x10
3
. ‘Conserve’ zones are where road building would have relatively high environmental costs (above-median environmental values; Fig. 2a) and modest
potential agricultural benefits (below-median road-benefits values; Fig. 2b). ‘Agriculture’ zones have the opposite attributes (above-median road-benefits values and below-median environmental values).
‘Conflict’ zones have both above-median environmental values and above-median road-benefits values, whereas ‘low-tension’ zones are lower priorities for both environment and agriculture (with below-median
environmental and road-benefits values). See Supplementary Fig. 18 for a map of these zones.
LETTER RESEARCH
11 SEPTEMBER 2014 | VOL 513 | NATURE | 231
Macmillan Publishers Limited. All rights reserved
©2014
though agricultural potential is limited, by promoting forest fires and
clearing
14
. In general, we expect road impacts to be lowest in unproduc-
tive, arid regions, moderate in carbon-rich ecosystems such as higher-
latitude forests, and most damaging in species- and carbon-rich ecosystems
such as tropical forests, particularly where few roads currently exist.
We see our global road-mapping scheme as a working model—an
important first step towards strategic road planning to reduce environ-
mental damage—that can be downscaled and tailored for particularcir-
cumstances. We believe such proactive planning should be a central
element of any discussion about road expansion and associated land-
use zoning
13,30
. Given that the total length of new roads anticipated by
mid-century
1
would encircle the Earth more than 600 times, there is
little time to lose.
Online Content Methods, along with any additional Extended Data display items
and SourceData, are available in theonline version of the paper;references unique
to these sections appear only in the online paper.
Received 19 May; accepted 28 July 2014.
Published online 27 August 2014.
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Supplementary Information is available in the online version of the paper.
Acknowledgements We thank T. Brooks, S. Butchart, J. Geldmann, S. Goosem,
C. Mendenhall,N. Pares, S. Pimm, U. Srinivasan,N. Velho, and two anonymous referees
for comments and feedback. The Australian Research Council provided support.
Author Contributions W.F.L. and A.B. initially conceived the study, and W.F.L.
coordinated its design, analysis, and manuscript preparation. G.R.C. and S.S.
conducted the spatial analyses; C.S.O., N.D.M., O.V., G.R.C., S.S. and B.P. generated or
collated key datasets; and M.G., D.P.E., R.V.D.R. and I.B.A. provided ideas and critical
feedback.
Author Information Reprints and permissions information is available at
www.nature.com/reprints. The authors declare no competing financial interests.
Readers are welcome to comment on theonline version of the paper. Correspondence
and requests for materials should be addressed to W.F.L. (bill.laurance@jcu.edu.au).
ab
Figure 4
|
Mapped roads overlaid onto the roads-benefits layer. a,b,In
eastern Africa (a) and Siberia (b), roads are rapidly expanding into relatively
road-free areas, but for different reasons. Narrow black lines indicate mapped
roads. In both regions, areas with darker-red colours have greater agricultural
potential than those with lighter colours. See Supplementary Information for
data sources.
RESEARCH LETTER
232 | NATURE | VOL 513 | 11 SEPTEMBER 2014
Macmillan Publishers Limited. All rights reserved
©2014
METHODS
We used ArcGIS 10.1 and IDRISI Selva to integrate spatial data relevant to our
global roadmap. Analyses were conducted using Goode’s homolosine equal-area
projection and a 1-km
2
pixel size, yielding ,132.8 million pixels for Earth’s ter-
restrial surface (excluding Antarctica). Larger freshwater bodies (.50 km
2
) were
removed before analysisbut land areas under ice or permafrost were not excluded.
A small fraction (2.21%)of all pixels lacked data (mostly in Greenland) and so were
excluded from the analysis.
We created the environmental-values layer (Fig. 2a) by integrating global data
sets on biodiversity (numberof threatened terrestrial-vertebrate species,estimated
number of plant species per ecoregion); key wilderness habitats (G200 terrestrial
ecoregions, important bird areas and endemic bird areas, biodiversity hotspots,
frontier forests, high-biodiversity wilderness areas); andcarbon storage and climate-
regulation services of the local ecosystem (Supplementary Figs 1–11). Areas that scored
highly on the road-benefits layer (Fig. 2b) were defined by having: a high propor-
tion of land already under farming or grazing; soils and climates that are broadly
suitable for agriculture; large agricultural yield gaps; large projected increases i nf uture
agricultural production; and the potential to access urban markets with improved
transportation (Supplementary Figs 12–16). The globaldata sets that comprise the
environmental-values and road-benefits layers, and the methods by which they
were integrated, are described in detail in the Supplementary Information.
LETTER RESEARCH
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©2014
Extended Data Figure 1
|
Roadmaps for northern South America and
Sub-Saharan Africa. Magnified images such as these could be integrated
with local-scale data to facilitate actual road planning. Values of the
environmental-values and road-benefits layers are each divided into deciles,
yielding 100 unique colour combinations. See Supplementary Information for
data sources.
RESEARCH LETTER
Macmillan Publishers Limited. All rights reserved
©2014
CORRECTIONS & AMENDMENTS
CORRIGENDUM
doi:10.1038/nature13876
Corrigendum: A global strategy for
road building
William F. Laurance, Gopalasamy Reuben Clements,
Sean Sloan, Christine S. O’Connell, Nathan D. Mueller,
Miriam Goosem, Oscar Venter, David P. Edwards, Ben Phalan,
Andrew Balmford, Rodney Van Der Ree & Irene Burgues Arrea
Nature 513, 229–232 (2014); doi:10.1038/nature13717
In this Letter, as a result of an inadvertent spreadsheet error, four values
presented in Table 1 were slightly inflated. These relate to the propor-
tions of Earth’s total land surface located within the ‘conserve’, ‘agri-
culture’, ‘conflict’ and ‘low-tension’ zones. The correct percentage values
for these four zones under the ‘global’ heading are 42.96, 11.40, 15.34
and 30.30, respectively. Two of these values (the global percentages for
conflict and agriculture zones) were also mentioned in the main text.
We apologise for these errors, which have now been corrected in the
online versions of the Letter, and do not affect the interpretation of our
analyses.
262|NATURE|VOL514|9OCTOBER2014
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©2014
... The construction of the economic benefit layer aims to comprehensively evaluate the impact of railway transportation construction on economic benefits, with the objective of identifying regions with higher economic potential for the construction or improvement of railway transportation systems. Specifically, considering the impact of rail transportation on economic development, based on the IEA report 10 and the location theory 11 , in terms of economic benefits, three indicators including freight volume 10 , passenger volume 10 , and intensity of economic activities 12 , encompassing 11 sub-indicators layers such as crops, biofuel crops, coal, conventional oil, unconventional oil, gas resources, metallic minerals, non-metallic minerals, nighttime light, accessibility and global population density data 3,13 . The preliminary distribution of these sub-indicators is illustrated in Fig. 1. ...
... Drawing on the research findings of Laurance et al. 3 and the requirements of Sustainable Development Goals (SDGs) 14 , we have constructed an environmental conservation layer by integrating global datasets across seven first-level indicators: ecological importance, lakes and wetlands, protected areas, topography, natural disasters, climate, and carbon reserves. Moreover, the global distribution of values for sub-indicators of these first-level indicators is depicted in Fig. 3. Similarly, these sub-indicators were subsequently standardized and aggregated to generate the environmental conservation layer as illustrated in Fig. 4, which encompasses the entire globe except Antarctica and small island nations in the oceans. ...
... Consequently, applying our research findings to specific areas necessitates consideration of local social, political, and cultural factors. Further detailed investigations and discussions should be based on our research results 3 . ...
Article
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Drawing from the United Nations Sustainable Development Goals (SDGs), this study offers a framework for optimizing rail transit routes, balancing economic benefits with environmental preservation. Using the Bivariate Choropleth-Multi-Criteria Decision Analysis (BC-MCDA) model, we categorize global regions into economic benefit, environmental conservation, high-conflict, and low-conflict zones. Specifically, 7.42% are identified as economic benefit zones, suitable for rail transit expansion with minimal environmental impact. Meanwhile, 16.14% are environmental conservation zones, requiring preservation and 76% are low-conflict zones, where maintaining existing land use is advised. Only 0.62% are high-conflict zones, demanding careful planning. Addressing how to utilize land more effectively and sustainably in transportation development to foster economic growth while avoiding harm to biodiversity and ecosystems, this study provides actionable insights. It advances sustainable transportation planning by integrating environmental and economic considerations, offering practical guidance for aligning infrastructure projects with global sustainability goals.
... However, in natural environments, the lower abundance of the species in degraded landscapes may also be exacerbated by higher levels of illegal extraction. Degraded landscapes have become prime targets for illegal extractors (Tabarelli et al. 2004), as they have lower vegetation density (Crouzeilles et al. 2016), are predominantly outside protected areas (Gonçalves-Souza et al. 2021), have accessible trails (Benítez-López et al. 2017), and are often near access infrastructures such as roads and highways (Laurance et al. 2014;Trombulak & Frissell 2000). ...
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Content Habitat loss and fragmentation are two processes resulting from land-use changes that significantly affect biodiversity worldwide. These two processes alongside illegal hunting are the main causes of the reduction in fauna diversity, richness, and biomass, which together characterize defaunation. Large animal species are the most affected by this process, compromising ecosystem services such as seed dispersal. Objectives We evaluated the isolated and combined effects of habitat loss, fragmentation and the nonrandom defaunation of large seed dispersers on the population expansions of the tropical palm Euterpe edulis. Methods We modeled the spatial dynamics of the species via RangeShiftR in landscapes with different degrees of habitat percentage and fragmentation, simulating two distinct scenarios: nondefaunated, with a complete assembly of avian seed dispersers, and defaunated, with an impoverished assembly of large avian frugivores. Then, we developed linear regression models using the total abundance and density at the end of a 100-year simulation as response variable, and we selected the best model based on the Akaike information criterion. Results Habitat loss, fragmentation, and defaunation negatively affect the abundance and density of E. edulis. Furthermore, the interaction effect between defaunation and habitat percentage was significant, indicating that in nondefaunated scenarios, the abundance and density of E. edulis increase substantially. Additionally, habitat loss has a greater negative effect on population expansion than fragmentation, which has a lower predictive power. Conclusion These results help address the effects of habitat loss, fragmentation and defaunation on the population expansion of E. edulis. Our models contribute to the strategic planning of actions aimed at the conservation of E. edulis, highlighting habitat loss as a central point in allocating efforts for the protection of this species, as well as the importance of considering fauna data in estimates of the population expansion capacity of plant species.
... Given that a significant proportion of the GRIP data is derived from official government sources, unofficial and local roads might be under-represented 22 . Unofficial or informal roads could constitute an increasing portion of the road networks, particularly in relatively untouched areas, like the Congo Basin and the Amazon, these were built illegally to exploit natural resources or for plantations 21,60,61 . Therefore, to improve future evaluations of the socio-environmental effects of road networks requires the development of more accurate and comprehensive spatial road network datasets 21,22 . ...
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Sprawling road networks cutting through forested areas continue to be a potent catalyst of deforestation in tropical regions. Yet, pantropical assessments limited by the lack of high-resolution global maps of tropical forest loss induced by road networks. Here, we harnessed the road dataset from the Global Roads Inventory Project and the forest loss dataset from Global Forest Change, to produce global tropical high-resolution maps of road impact index spanning 2001 to 2020. We find that the forest area within a 1-km distance from roads accounts for about one-sixth, but its proportion of forest loss is nearly one-third, the road impact index is 2.45 times higher than those beyond the zone. The road impact index of all countries shows a decreasing trend with the distance from roads and increasing from 2001 to 2020. Our findings emphasize the urgent need for globalized efforts to protect the intact forests and rehabilitate degraded forests along roadside.
... Fences and walls are one of the oldest tools used by people to manage other people and wildlife, e.g. by marking territorial boundaries, separating livestock from wild animals, or monitoring the movement of people through border controls. There is no reliable measure of extent of the global fence network, however it is estimated to be at least 10 times that of the global road network (Jakes et al. 2018), which is currently more than 64 million km (Dulac 2013), and expected to reach 90 million km by 2050 (Laurance et al. 2014). Despite the enormous extent of the fence network, fences are rarely subjected to environmental impact assessments, and the ecological impacts of fencing are severely underestimated and understudied (Jakes et al. 2018, McInturff et al. 2020, Buton et al. 2024. ...
... In addition to the above-mentioned network problems, wilderness environments also feature poor road conditions [128]; due to the sparse population, many roads in the wilderness are not well built, are usually composed of bare soil, or there may even be no roads that can allow people to walk. At this time, if there is a rainstorm and other bad weather, then the soil roads will become very muddy, which is extremely unfavorable to human use. ...
... Acoording to Laurance (2014), roads and trails to previously unreachable wooded areas are made possible by fragmentation. This facilitates illicit activities like poaching, mining, and logging, all of which worsen forest degradation and encourage deforestation. ...
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The study analyzed effects of land fragmentation on deforestation among small scale farmers in Ife East Local Government Area of Osun State, Nigeria. The data were sourced mainly from primary sources using structured questionnaire. A multi-stage random sampling technique was used to select 100 small scale farmers from the study area. Data for the study were analyzed using both descriptive statistics and Ordinary Least Square regression. The result of the analysis revealed that on the average, the respondents felled up to 16 trees in the past 3 years. The results further showed that the respondents cleared an average forest area of about 2 hectares in the past 3 years for farming. Result of regression analysis revealed that farm size (1.994), number of plots farmed (3.221), hectares of forest land cleared (2.029) and plot size (0.522) were significant and positively influenced deforestation in the study area. Results also revealed that most (53.0%) of the respondents identified poverty (mean = 2.35) as the major negative effect of deforestation on small scale farmers. It was recommended that Government and Non-Governmental Organizations should implement programmes that would help in reduction of poverty, which is the main push behind deforestation amongst others.
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Ghana recently legalized mining in forest reserves but the impacts of this policy shift on forest cover, biodiversity and carbon stocks are not well documented. We analysed forest cover dynamics between 2018 and 2023 in the Oda River Forest Reserve and inventoried data from 12 plots in non-mined and mined (low, moderate and heavily) sites for its consequences on biodiversity and carbon stocks. Forest cover declined by 5.9%, shrinking from 16,959.89 ha in 2018 to 15,952.82 ha in 2023, while illegal mining expanded astronomically by 1,917.6%, increasing from 52.78 ha to 1,059.85 ha, with the most rapid expansion occurring between 2022 and 2023. The study revealed significant reductions in plant species richness and diversity across trees, shrubs, and climbers in mined areas, with heavily mined zones exhibiting a complete absence of vegetation. The Shannon diversity index and structural attributes such as tree height and diameter also significantly declined, reflecting the widespread ecological disruption caused by mining activities. Non-mined areas demonstrated higher biodiversity (S = 13.33, H = 2.41), greater structural complexity, and maintained the highest carbon stocks (689.11 Mg C ha − 1 ), emphasizing their role in mitigating climate change. In contrast, heavily mined areas exhibited complete carbon loss, resulting in substantial potential CO 2 emissions (2,522.15 tCO 2 e). Our results demonstrate the urgent need for effective land management policies, enforcement of mining regulations, and restoration efforts, including reforestation with native species. Addressing mining in forest reserves is critical to preserving biodiversity, mitigating climate change, and ensuring the resilience of forest ecosystems.
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Fencing is one of the most widely utilized tools for reducing human‐wildlife conflict in agricultural landscapes. However, the increasing global footprint of fencing exceeds millions of kilometers and has unintended consequences for wildlife, including habitat fragmentation, movement restriction, entanglement, and mortality. Here, we present a novel and quantitative approach to prioritize fence removal within historic migratory pathways of white‐bearded wildebeest (Connochaetes taurinus) across Kenya's Greater Masai Mara Ecosystem. Our approach first assesses historic and contemporary landscape connectivity of wildebeest between seasonal ranges by incorporating two sets of GPS tracking data and fine‐scale fencing data. We then predict connectivity gains from simulated fence removal and evaluate the impact of different corridor widths and locations on connectivity and removal costs derived from locally implemented interventions. Within the study system, we found that modest levels of fence removal resulted in substantial connectivity gains (39%–54% improvement in connectivity for 15–140 km of fence line removed). By identifying the most suitable corridor site, we show that strategically placed narrow corridors outperform larger, more expensive interventions. Our results demonstrate how and where targeted fence removal can enhance connectivity for wildlife. Our framework can aid in identifying suitable and cost‐effective corridor restoration sites to guide decision‐makers on the removal of fences and other linear barriers. Our approach is transferable to other landscapes where the removal or modification of fences or similar barriers is a feasible mitigation strategy to restore habitat and migratory connectivity.
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The number and extent of roads will expand dramatically this century. Globally, at least 25 million kilometres of new roads are anticipated by 2050; a 60% increase in the total length of roads over that in 2010. Nine-tenths of all road construction is expected to occur in developing nations, including many regions that sustain exceptional biodiversity and vital ecosystem services. Roads penetrating into wilderness or frontier areas are a major proximate driver of habitat loss and fragmentation, wildfires, overhunting and other environmental degradation, often with irreversible impacts on ecosystems. Unfortunately, much road proliferation is chaotic or poorly planned, and the rate of expansion is so great that it often overwhelms the capacity of environmental planners and managers. Here we present a global scheme for prioritizing road building. This large-scale zoning plan seeks to limit the environmental costs of road expansion while maximizing its benefits for human development, by helping to increase agricultural production, which is an urgent priority given that global food demand could double by mid-century. Our analysis identifies areas with high environmental values where future road building should be avoided if possible, areas where strategic road improvements could promote agricultural development with relatively modest environmental costs, and 'conflict areas' where road building could have sizeable benefits for agriculture but with serious environmental damage. Our plan provides a template for proactively zoning and prioritizing roads during the most explosive era of road expansion in human history.
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Road construction is now common through wilderness and protected areas in tropical and subtropical countries with adverse consequences for their high native biodiversity. Here, we summarize the scope of the problem and advance specific compromise solutions that reconcile development with conservation.
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Feeding a growing global population in a changing climate presents a significant challenge to society. The projected yields of crops under a range of agricultural and climatic scenarios are needed to assess food security prospects. Previous meta-analyses have summarized climate change impacts and adaptive potential as a function of temperature, but have not examined uncertainty, the timing of impacts, or the quantitative effectiveness of adaptation. Here we develop a new data set of more than 1,700 published simulations to evaluate yield impacts of climate change and adaptation. Without adaptation, losses in aggregate production are expected for wheat, rice and maize in both temperate and tropical regions by 2 °C of local warming. Crop-level adaptations increase simulated yields by an average of 7–15%, with adaptations more effective for wheat and rice than maize. Yield losses are greater in magnitude for the second half of the century than for the first. Consensus on yield decreases in the second half of the century is stronger in tropical than temperate regions, yet even moderate warming may reduce temperate crop yields in many locations. Although less is known about interannual variability than mean yields, the available data indicate that increases in yield variability are likely.
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Increasing agricultural productivity to 'close yield gaps' creates both perils and possibilities for biodiversity conservation. Yield increases often have negative impacts on species within farmland, but at the same time could potentially make it more feasible to minimize further cropland expansion into natural habitats. We combine global data on yield gaps, projected future production of maize, rice and wheat, the distributions of birds and their estimated sensitivity to changes in crop yields to map where it might be most beneficial for bird conservation to close yield gaps as part of a land-sparing strategy, and where doing so might be most damaging. Closing yield gaps to attainable levels to meet projected demand in 2050 could potentially help spare an area equivalent to that of the Indian subcontinent. Increasing yields this much on existing farmland would inevitably reduce its biodiversity, and therefore we advocate efforts both to constrain further increases in global food demand, and to identify the least harmful ways of increasing yields. The land-sparing potential of closing yield gaps will not be realized without specific mechanisms to link yield increases to habitat protection (and restoration), and therefore we suggest that conservationists, farmers, crop scientists and policy-makers collaborate to explore promising mechanisms.
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Africa is on the verge of a mining boom. We review the environmental threats from African mining development, including habitat alteration, infrastructure expansion, human migration, bushmeat hunting, corruption, and weak governance. We illustrate these threats in Central Africa, which contains the vast Congo rainforest, and show that more than a quarter of 4,151 recorded mineral occurrences are concentrated in three regions of biological endemism—the Cameroon-Gabon Lowlands, Eastern DRC Lowlands, and Albertine Rift Mountains—and that most of these sites are currently unprotected. Threats are not uniform spatially, and much of the Congo Basin is devoid of mineral occurrences and may be spared from direct mining impacts. Some of the environmental impacts of African mining development could potentially be offset: mining set-asides could protect some wildlife habitats, whereas improving transportation networks could increase crop yields and spare land for conservation. Research and policy measures are needed to (1) understand the synergies between mining and other development activities, (2) improve environmental impact assessments, (3) devise mitigation and offsetting mechanisms, and (4) identify market choke points where lobbying can improve environmental practice. Without careful management, rapid mining expansion and its associated secondary effects will have severe impacts on African environments and biodiversity.
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A noteworthy feature of international environmental discourse since the late-1980s has been the shift toward anticipatory policies. Precaution is the leading policy approach that has emerged to guide environmental decision-makers confronted with inadequate information. The "precautionary principle" has found expression in Australia in the 1992 Intergovernmental Agreement on the Environment, various Commonwealth environmental management strategies and a number of pieces of Commonwealth and State legislation. It also has been accepted tentatively by the courts as a factor which should be taken into account in appropriate circumstances. However, existing Australian environmental management approaches fail to advance precaution in a substantive manner. Most hope for the advancement of precaution has rested on its potential to be a mandatory consideration by ministerial authorities when exercising planning powers. However, courts have cast doubt on the legal status of the principle because of the typically weak formulations of it in legislation and policy documents. In this article, a method is suggested by which the principle could be integrated systematically in environmental planning so that it could be given effect in environmental management practice. The writer proposes that environmental impact assessment (EIA) Australia's foremost environmental protection regime should be modified to give effect to the precautionary principle. A three-step method by which this could be achieved is presented. First, the EIA trigger of environmental 'significance' must be broadened; second, uncertainties must be assessed; and third, environmental uncertainty must have greater influence in decision-making.