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Comment on “High-resolution global maps of 21st-century forest cover change”



Hansen et al. (Reports, 15 November 2013, p. 850) published a high-resolution global forest map with detailed information on local forest loss and gain. We show that their product does not distinguish tropical forests from plantations and even herbaceous crops, which leads to a substantial underestimate of forest loss and compromises its value for local policy decisions.
Comment on High-resolution global
maps of 21st-century forest
cover change
Robert Tropek,
*Ondřej Sedláček,
Jan Beck,
Petr Keil,
Zuzana Musilová,
Irena Šímová,
David Storch
Hansen et al. (Reports, 15 November 2013, p. 850) published a high-resolution global
forest map with detailed information on local forest loss and gain. We show that their
product does not distinguish tropical forests from plantations and even herbaceous
crops, which leads to a substantial underestimate of forest loss and compromises its
value for local policy decisions.
The high-resolution global map of forest cov-
er loss and gain in Hansen et al.(1)isa
fascinating and much-needed tool for both
research and conservation planning. The
authors claim that [t]he information con-
tent of the presented data sets...provides a trans-
parent, sound, and consistent basis on which to
quantify critical environmental issues, includ-
ing...(iv) the status of remaining natural forests
of the world and threats to biodiversity(v) the
effectiveness of existing protected-area networks
(vi) the economic drivers of natural forest con-
version to more intensive land uses.After study-
ing the supplementary data application (http://
global-forest) in detail, we express serious con-
for these purposes.
The main problem lies in Hansen et al.sdef-
inition of forest as all vegetation taller than 5m
in height[supplementary materials for (1)]. Such
a structural definition includes types of planta-
tions that have already replaced substantial parts
of tropical (and also extratropical) forests. Mono-
cultures of oil palm, rubber, or Eucalyptus are
recognized as some of the biggest threats to
tropical biodiversity (24), and their expansion
into forest systems continues at an alarming rate
[see (5) for details]. Although these plantations
are technically forestsin the definition above,
they do not provide the benefits of forest vege-
tation as enumerated by the authorsi.e., eco-
system services, including biodiversity richness,
climate regulation, carbon storage, and water
supplies(69). Classifying plantations as forests
confuses an endangered habitat with its greatest
threats and thus underestimates real forest loss.
To evaluate Hansen et al.sforestmap,we
compiled sites for which we had detailed infor-
mation (e.g., from our previous fieldwork). We
compared these validation sites to the forest map
and identified three ways in which the product
failed to accurately assess forest cover gain and
loss (see Table 1 and Fig. 1 for specific cases):
1) Areas deforested and converted into planta-
tions before 2000 are classified as forests (cases
1 to 19, Table 1, and Fig. 1, A to E), which leads to
an overestimation of total forested area. Further-
more, plantation management such as cutting
old growth plantation and replanting with new
crops is interpreted as forest gain/loss.
2) Areas deforested around 2000 and re-
identified as forest gain,although their conser-
vation value has been largely lost in such cases
(case 20, Table 1).
3) Contrary to the given definition of forest,
vegetation lower than 5 m (e.g., pineapple, soy-
beans, or tea plantations) is often classified as
forest. Including these types of vegetation as
forestfurther biases estimates of forest cover
gain and loss (cases 21 to 24, Table 1, and Fig. 1, F
to H).
errors in every examined tropical region suggests
that these represent systematic misinterpretations
with substantial consequences for inferences
based on the product. Following our personal
knowledge of several tropical regions and a sur-
vey of Hansen et al.s map application, we ten-
tatively estimate that the forest loss may be
underestimated by tens of percents in the trop-
ics. Similar issues may also occur outside the
tropics, where species-poor wood plantations
are widespread (5,10).
We warn that classification of high-resolution
satellite data based on a single and simplistic
algorithm can provide only limited insight into
real forest dynamics at local scales. This forest
map may provide preliminary identification of
ongoing changes [e.g., (11)], but without locally
specific calibration and evaluation and/or accom-
panying maps of pixel-specific classification un-
certainty, it will mislead conservation policy-makers
and managers, with potentially serious conse-
quences for biodiversity and socioeconomic is-
sues. The fact that the product comes with an
easy-to-use online application further enhances
the potential for uncritical use by nonspecialists
and various interest groups.
Although the global loss of tree cover reported
by Hansen et al.(1) represents a serious en-
vironmental issue, the replacement of natural
forests by plantations (often with comparable
tree cover) is a more important environmental
and biodiversity problem at the local scale. Plan-
tations are often characterized by considerably
lower diversity than extensively used open coun-
tryside, including nonintensive pastures and small
fields (2,12). In this respect, the results of Hansen
et al. are misleading and can potentially lead to
abuse by local policy-makers who could consider
an increase of tree cover a conservation success,
even if this change is accompanied by decreases
in biological diversity. The stated conservation
relevance and utility of the approach of Hansen
et al. is thus seriously compromised and calls for
a critical reevaluation.
1. M. C. Hansen et al., Science 342, 850853 (2013).
2. J. Barlow et al., Proc. Natl. Acad. Sci. U.S.A. 104, 1855518560
3. L. P. Koh, D. S. Wilcove, Conserv. Lett. 1,6064 (2008).
4. D. S. Wilcove, X. Giam, D. P. Edwards, B. Fisher, L. P. Koh,
Trends Ecol. Evol. 28, 531540 (2013).
5. E. G. Brockerhoff, H. Jactel, J. A. Parrotta, C. P. Quine, J. Sayer,
Biodivers. Conserv. 17, 925951 (2008).
6. R. Guo, R. M. Gifford, Glob. Change Biol. 8, 345360 (2002).
7. E. B. Fitzherbert et al., Trends Ecol. Evol. 23, 538545
8. L. Gibson et al., Nature 478, 378381 (2011).
9. A. D. Ziegler et al., Glob. Change Biol. 18, 30873099
10. F. T. Maestre, J. Cortina, For. Ecol. Manage. 198, 303317
11. R. Koenig, Science 320, 14391441 (2008).
12. H. M. Pereira, G. C. Daily, Ecology 87, 18771885 (2006).
We thank K. Mertes for English proofreading and valuable
comments on the manuscript. This work was partly supported
by the Czech Science Foundation (14-36098G).
20 November 2013; accepted 4 April 2014
Department of Environmental Science (Biogeography),
University of Basel, St. Johanns-Vorstadt 10, CH-4056 Basel,
Institute of Entomology, Biology Centre,
Academy of Sciences of the Czech Republic, Branisovska 31,
CZ-370 05 Ceske Budejovice, Czech Republic.
of Ecology, Faculty of Science, Charles University in Prague,
Vinicna 7, CZ-128 44 Praha 2, Czech Republic.
of Ecology and Evolutionary Biology, Yale University, 165
Prospect Street, New Haven, CT 06520, USA.
Center for
Theoretical Study, Charles University in Prague and Academy
of Sciences of the Czech Republic, Jilska 1, CZ-110 00 Praha
1, Czech Republic.
Zoological Institute, University of Basel,
Vesalgasse 1, CH-4051 Basel, Switzerland.
*Corresponding author. E-mail:
SCIENCE 30 MAY 2014 VOL 344 ISSUE 6187 981-d
Table 1. Examples of serious misclassifications by Hansen et al.(1). Geographic coordinates allow easy checking of current vegetation in the
supplementary online map application ( Hundreds of additional examples of similar
errors can easily be found in the application map by simply following plantation maintenance roads. Often, even details such as individual oil palms or
soybean rows are clearly visible.
Case no. Figure Country Region Latitude Longitude Hansen et al.Actual
1 1A Philippines Davao, Mindanao 7°26'1.29''N 125°38'6.26''E Stable forest Banana
2 1B Ecuador Quevedo, Los Rios 1°0'46.76''S 79°29'59.33''W Forest with
large regrowth
Oil palm
3 1C Costa Rica Damas, Puntarenas 9°31'59.50''N 84°14'16.20''W Forest with
large regrowth
Oil palm
4 1D Malaysia Sepang, Kuala Lumpur
International Airport
2°43'55.97''N 101°40'49.64''E Forest with
large regrowth
Oil palm
5 1E Cameroon Mundemba, Southwest 4°57'1.16''N 8°52'18.66''E Forest with large
clearings and regrowth
Oil palm
6 Cameroon Bafut-Ngemba, Forest Reserve
Northwest Province
5°54'11.90''N 10°11'43.61''E Stable forest Eucalyptus
7 Cameroon Penda Mboko,
Southwest Province
4°16'14.68''N 9°26'12.66''E Stable forest Rubber
8 Malaysia (Borneo) Left bank of
Kinabatangan River, Sabah
5°32'40''N 118°166''E Forest with clearings
and regrowth
Oil palm
9 Philippines South of Tagum,
Davao del Norte
7°21'28.04''N 125°47'52.59''E Stable forest Coconut
10 Papua New Guinea Gusap, Morobe 6°4'53.08''S 146°0'12.95''E Large forest regrowth Oil palm
11 Indonesia Bogor, West Java 6°30'47.64''S 106°43'35.64''E Large forest regrowth Oil palm
12 Indonesia North Konawe,
Southeast Sulawesi
3°12'40.73''S 122°7'30.66''E Large forest regrowth Oil palm
13 Venezuela Ciudad Guayana,
Bolívar State
8°35'33.84''N 62°35'54.19''W Forest with large
clearings and regrowth
Pine tree
14 Peru Santa Lucía,
San Martín
8°19'40.71''S 76°29'50.67''W Forest with
large regrowth
Oil palm
15 Benin Saketé, Plateau
6°48'36.02''N 2°30'10.52''E Forest with
clearings and regrowth
Oil palm
16 Côte dIvoire Ebobo,
5°15'43.42''N 3°1'46.12''W Forest with
clearings and regrowth
Oil palm
17 Nigeria Benin City,
Edo State
6°9'39.23''N 5°41'0.33''E Forest with
large regrowth
Oil palm
18 Liberia Kakata, Margibi 6°32'6.47''N 10°22'57.34''W Forest with
clearings and regrowth
Rubber tree
19 Guinea - Conacry Samaya/Kemaya, Dubréka 10°2'28.65''N 13°48'44.74''W Large forest regrowth Oil palm
20 Cameroon Northern border of Campo
Maan National Park,
South Province
2°40'47.17''N 10°13'8.11''E Large forest regrowth Newly established
rubber trees instead
of freshly cut forest
21 1F Madagascar Ambatoharanana, Sava 14°32'30.80''S 49°35'44.26''E Large forest regrowths Various field crops
22 1G Brazil Tailândia, Pará 2°39'50.20''S 48°53'17.43''W Forest with
large regrowth
23 1H Philippines Tupi, South Cotabato 6°18'31.14''N 124°58'17.75''E Stable forest Pineapple
24 Cameroon Ndawara Belo Ranch,
Northwest Province
6°4'41.37''N 10°22'46.00''E Forest with
large regrowth
Te a
981-d 30 MAY 2014 VOL 344 ISSUE 6187 SCIENCE
Fig. 1. Selected examples of Hansen et al.s(1) failures in classifying of tree plantations (A to E) and herbal crops (F to H) as forest. All the maps are
screenshots from Hansen et al.s supplementary online map application ( taken in November
2013 and modified to highlight details by adding the yellow squares.The colors in the right halves of each panel indicate stable forest (green), forest loss (red), forest
gain (blue), and forest loss and gain (magenta). See Table 1 for more details, including coordinates, and for several additional examples.
SCIENCE 30 MAY 2014 VOL 344 ISSUE 6187 981-d
... An effective and precise forest monitoring system is essential to address forest loss and deforestation rates in the world. Early detection of forest loss is a key tool to reduce emissions from deforestation, preserve habitats, and reduce the alarming acceleration of climate change (Hansen et al. 2013(Hansen et al. , 2014Tropek et al. 2014). However, creating a reliable tool for forest monitoring is not an easy task, as complex remote sensing algorithms are still making progress in screening forests regularly (some examples of the different algorithms and techniques, are reported: Bajocco et al. (2012); Dutrieux et al. (2015); Guo et al. (2022); Hansen and DeFries (2024); Ørka et al. (2022); Panta et al. (2008); Potapov et al. (2015); Song et al. (2014Song et al. ( , 2015. ...
... Besides forest overestimation in densely forested areas, there is a relevant problem concerning GFCD, which we mentioned before and discuss here in more detail, namely, the fact that palm oil plantations and other crops are detected as forest (see also Tropek et al. 2014). In the present study, we do not consider palm oil plantations as forests, as many papers point to the disruption that this monoculture is causing in tropical forests, endangering species and biodiversity (Meijaard et al. 2020). ...
... The other relevant drawback of GFCD is that of miss-classifying lakes, rivers, palm oil and other plantations as forest. Despite the definition of forest given in GFCD, even vegetation lower than 5 m (e.g., pineapple, soybeans, or tea plantations) is often classified as forest (Tropek et al. 2014). Erroneous consideration of plantations represents a serious problem as they do not have the carbon value of forests and often contribute to endanger species and biodiversity (Brockerhoff et al. 2017). ...
Full-text available
Accurate forest assessment is essential to detect and tackle deforestation, especially in emerging economies. In Colombia, three different geo-spatial data sources are available for forest monitoring: the European Space Agency (ESA), the Institute for Hydrology, Meteorology and Environmental Studies (IDEAM), and the Global Forest Change Data (GFCD) from the University of Maryland. These information sources have distinct characteristics, purposes, and coverage, and their peculiarities can lead to marked differences in the results when they are used to produce forest cover maps. In this study, we determine the optimal forest threshold for GFCD and assess the accuracy of the three data sources in mapping forests, on the basis of a stratified sample of sites, with Colombian ecoregions used as strata. At each site, the classification into forest or non-forest, according to one of the sources, is compared with reference data collected through Google Earth imagery and landscape photographs. Accuracy measures are produced at both the ecoregion and national level. IDEAM and GFCD prove to be quite accurate in most cases, and each of them turns out to be the best forest map in about half of the ecoregions. GFCD’s optimal threshold is found to be equal to 90% in almost all those ecoregions for which it represents the best performing data set.
... Therefore, an effective way of understanding fire effects on forest landscapes is to assess its dynamics through changes in structure and ecosystem functions (Forman 1995;Turner and Gardner 2015). Particularly, land cover change (LCC) analysis can reveal the transformation of spatial patterns and trajectories of land cover over time (i.e., structure change), and is the most efficient way to quantitatively assess, manage and understand spatiotemporal dynamics of landscape (Ellis and Ramankutty 2008;Tropek et al. 2013;Turner and Gardner 2015;Song et al. 2018;Radwan et al. 2021). Ecosystem functions usually refer to the combination of processes and structures of an ecosystem, which can be represented as the potential capacity to deliver ecosystem services (Costanza and Daly 1992;Müller et al. 2010). ...
... This trend could be explained by the nature of the historical fires that occurred more than 60 years ago; these fires were often out of control and burned more forest area than expected by the settlers whose goal was to open up the land for agricultural and cattle grazing (Quintanilla 2005). Our observed pattern of agricultural loss and second-growth forest gain contrasts with most studies conducted in other parts of the world, where agricultural land generally tends to expand continually into areas covered by forests (Tropek et al. 2013;Song et al. 2018). The loss of agricultural cover in areas surrounding Coyhaique City is of particular interest; Coyhaique is experiencing a constant urban expansion (Hernández-Moreno and Reyes-Paecke 2018) which has begun to show changes in land cover principally from agricultural cover to housing (i.e., land ownership subdivision for peri-urban housing), a pattern also observed for other cities in southern Chile (e.g., Gálvez et al. 2021). ...
... Despite the disturbances caused by historical fires, our study shows that this forest landscape could be considered mostly intact or with low anthropization, which is in agreement with global studies (Potapov et al. 2017;Jacobson et al. 2019). This is an important observation in the context of current trends in global change and the accelerated rates of land use and land cover change both locally in Chile Locher-Krause et al. 2017;Miranda et al. 2017;Otavo and Echeverría 2017;Altamirano et al. 2020) and global (Tropek et al. 2013;Venter et al. 2016;Allan et al. 2017;Song et al. 2018;Potapov et al. 2020). This suggests that for isolated landscapes such as Patagonia, it is still possible to maintain IFL proportions even in times of global change. ...
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Context Western Chilean Patagonia is an isolated temperate region with an important proportion of intact forest landscapes (IFL) that was subjected to large-scale fires over 60 years ago. However, there is no empirical evaluation of the land cover dynamics to establish the forest loss and recovery, and the effect on the landscape structure and function, and remnant IFL following the fires. Objectives The present study addressed the following questions: (1) What have been the main trends of the land cover dynamics between 1984 and 2018 following earlier fires, and how have these trends shaped the spatial patterns and potential carbon stock of forests in western Patagonia? (2) What proportion of forest landscape remains intact following fires in this region? Methods We selected the Coyhaique Province (1,231,910 ha) in western Chilean Patagonia as the study area. Land cover maps for three dates (1984, 2000, 2018) were used to evaluate landscape dynamics after fires. A map of persistence and change occurrence was made to estimate the IFL area over the 1984–2018 period. Landscape metrics were used to assess landscape structure change, and potential carbon stock was estimated based on a literature review. Results Following fires, the main land cover changes between 1984 and 2018 were loss of ~ 32,600 ha of old-growth forest and a recovery of ~ 69,000 ha of second-growth forest. The increase in second-growth forest area mainly resulted from loss of agricultural cover (~ 41% of the area). Despite these changes, ~ 61% of the area could potentially remain as IFL after fires. Over the 1984–2018 period, a slight increase in fragmentation of old-growth forest, and a decline in second-growth forest were observed. Coyhaique Province experienced a slight increase (3.6%) in overall potential carbon stock, likely as a result of second-growth forest recovery. Conclusions Our study provides the first evidence of the western Patagonia landscape state after more than six decades since the large-scale fires. The results provide baseline information on landscape structure and function that could help to make conservation and forest management decisions on specific territory areas.
... Forest detection, in particular, raises additional challenges. Different definitions of 'forest'-for instance, using minimum vegetation height or land use criteria-can be challenging to measure (Tropek et al., 2014). More subtle changes in forest structure, such as selective logging or fire-induced degradation, are particularly hard to detect without very high spatial and temporal resolution imagery (Gao et al., 2020). ...
... The dataset has a coarser resolution of approximately five kilometers. Importantly, both datasets capture tree cover rather than forest cover (Tropek et al., 2014), and may be used in combination with secondary data (e.g., Potapov et al., 2017) to measure deforestation specifically. Moreover, these datasets do not capture the important distinction between rotational forestry (i.e., repeated cutting and replanting of trees) and forest clearing for agricultural conversion. ...
... Previous studies indicate that potential uncertainties exist in some regions (such as Canada, China and Brazil) in the GFW tree cover data [61][62][63][64] . Here, we used tree cover maps from individual countries or regions including Canada 65 , the United States 66 , eastern Europe 67 , northern Europe 68 , China 69 and tropical moist forests 70 (Supplementary Table 2 and Supplementary Fig. 19), which were calibrated or validated using national forest cover statistics or field inventory data 71 (Supplementary Fig. 20), as a means to provide an alternative data source for tree cover gain and loss 72 . ...
Full-text available
The direct biophysical effects of fine-scale tree cover changes on temperature are not well understood. Here, we show how land surface temperature responds to subgrid gross tree cover changes. We find that in many forests, the biophysical cooling induced by enhanced evapotranspiration due to tree cover gain is greater in magnitude than the warming from tree cover loss. Therefore, the goal of no biophysical warming effects from tree cover changes could be achieved by regaining a fraction of previously lost tree cover areas. This percentage differs between different forest biomes, ranging from 75% in tropical to 83% in temperate forests. Neglecting this asymmetric temperature effect of fine-scale tree cover change ignores the fact that biophysical feedbacks continue to cause surface temperature changes even under net-zero tree cover changes. Thus, it is necessary to account for gross, rather than net, tree cover changes when quantifying the biophysical effects of forests.
... Linking frontier type and woodland protection classes with regional conservation assets can fur- There are several reasons to be cautious about our results, although we believe none affect our conclusions. First, tree cover loss data can underestimate tree cover when trees are at low densities (Tropek et al., 2014) and some forest loss may indicate tree harvesting and not deforestation, although tree plantations are uncommon in most tropical dry woodland regions (Fagan, 2020;Fagan et al., 2022). Second, we are analysing woodland loss processes against static datasets of PAs and conservation assets. ...
Full-text available
Tropical and subtropical dry woodlands are rich in biodiversity and carbon. Yet, many of these woodlands are under high deforestation pressure and remain weakly protected. Here, we assessed how deforestation dynamics relate to areas of woodland protection and to conservation priorities across the world's tropical dry woodlands. Specifically, we characterized different types of deforestation frontier from 2000 to 2020 and compared them to protected areas (PAs), Indigenous Peoples' lands and conservation areas for biodiversity, carbon and water. We found that global conservation priorities were always overrepresented in tropical dry woodlands compared to the rest of the globe (between 4% and 96% more than expected, depending on the type of conservation priority). Moreover, about 41% of all dry woodlands were characterized as deforestation frontiers, and these frontiers have been falling disproportionately in areas with important regional (i.e. tropical dry woodland) conservation assets. While deforestation frontiers were identified within all tropical dry woodland classes of woodland protection, they were lower than the average within protected areas coinciding with Indigenous Peoples' lands (23%), and within other PAs (28%). However, within PAs, deforestation frontiers have also been disproportionately affecting regional conservation assets. Many emerging deforestation frontiers were identified outside but close to PAs, highlighting a growing threat that the conserved areas of dry woodland will become isolated. Understanding how deforestation frontiers coincide with major types of current woodland protection can help target context-specific conservation policies and interventions to tropical dry woodland conservation assets (e.g. PAs in which deforestation is rampant require stronger enforcement, inactive deforestation frontiers could benefit from restoration). Our analyses also identify recurring patterns that can be used to test the transferability of governance approaches and promote learning across social-ecological contexts.
... Global forest maps (Hansen et al. 2013) fail to distinguish between tropical forests and plantations of Cashew, or, for that matter, of banana, oil palm or pineapple plantations. The net result is an underestimate of real forest loss (Tropek et al. 2014). Cashew plantations are economically profitable (Monteiro et al. 2017) and are considered as beneficial afforestation leading to less soil erosion, enhanced soil fertility, a cooler microclimate and rehabilitation of degraded lands (CILSS 2016). ...
Full-text available
The Sahel is thinly covered by trees, but nevertheless forms an important habitat for millions of tree-dwelling birds. We describe tree availability and tree selection of 14 insectivorous Afro-Palearctic migrants and 18 Afro-tropical residents (10 insectivores, 3 frugivores and 5 nectarivores) inhabiting the Sahel from the Atlantic to the Red Sea. Of the 304 woody species identified across the region during systematic fieldwork in stratified plots, we noted height and canopy surface of 760,000 individual woody plants. Birds present in trees and shrubs were recorded separately per individual woody plant. 99.5% of the birds were concentrated in only 41 woody species. For 20 out of 32 bird species, Winter Thorn Faidherbia albida was the tree species most often used. Two other important tree species were Umbrella Thorn Acacia tortilis and Desert Date Balanites aegyptiaca. Representing only 11% of the total woody canopy cover, these three species attracted 89% of Western Bonelli’s Warblers Phylloscopus bonelli and 77% of Subalpine Warblers Curruca iberiae + subalpina + cantillans. High selectivity for particular woody species was typical for migrants and residents, irrespective of their diet. Bird species feeding in shrubs used a larger variety of woody species than bird species feeding in tall trees. The highest bird densities (80–160 birds/ha canopy) were found in three shrubs with a limited distribution in the southern Sahara and northern Sahel: the berry-bearing Toothbrush Tree Salvadora persica, the small thorny shrub Sodad Capparis decidua and the small tree Maerua crassifolia. Other bird-rich woody species were without exception thorny (Balanites aegyptiaca, various species of acacia and ziziphus). In contrast, the five woody species most commonly distributed across the region (Cashew Anacardium occidentale, African Birch Anogeissus leiocarpus, Com - bretum glutinosum, Guiera senegalensis and Shea Tree Vitellaria paradoxa), representing 27% of the woody cover in the study sites, were rarely visited by foraging birds. In this sub-Saharan region, it is not total woody cover per se that matters to birds, but the presence of specific woody species. This finding has important implications: remote sensing studies showing global increase or decline of woody vegetation without identifying individual species have little value in explaining trends in arboreal bird populations. Local people have a large impact on the species composition of the woody vegetation in the Sahel, with positive and negative consequences for migrants wintering in this region. Faidherbia albida, the most important tree for birds in the sub-Saharan dry belt, is highly valued by local people and has the distinction of leafing in winter and being attractive to arthropods. On the other hand, migratory and African bird species have been negatively affected by the rapidly expanding cashew plantations since the early 1980s.
Two factors have elevated recent academic and policy interest in tropical deforestation: first, the realization that it is a major contributor to climate change; and second, a revolution in satellite-based measurement that has revealed that it is proceeding at a rapid rate. We begin by reviewing the methodological advances that have enabled measurement of forest loss at a fine spatial resolution across the globe. We then develop a simple benchmark model of deforestation based on classic models of natural resource extraction. Extending this approach to incorporate features that characterize deforestation in developing countries—pressure for land use change, significant local and global externalities, weak property rights, and political economy constraints—provides us with a framework for reviewing the fast-growing empirical literature on the economics of deforestation in the tropics. This combination of theory and empirics provides insights not only into the economic drivers and impacts of tropical deforestation but also into policies that may affect its progression. We conclude by identifying areas where more work is needed in this important body of research.
Agrarian expansion and intensification in the tropical agricultural‐forest frontiers (TAFF) are continuously encroaching on forests, yet the magnitudes and processes of agricultural‐forest advances and retreats remain lacking investigation systematically and quantitatively. With over three‐decade (1987–2018) of land‐cover products, here, we revealed the spatiotemporal dynamic processes of agricultural advance and forest retreat and then quantified forest loss (FL) due to cropland and plantation expansion (PE) in Mainland Southeast Asia (MSEA). First, the agricultural expansion and FL peaked in the late 1990s to early 2000s and decelerated afterward in MSEA. Meanwhile, the continuous decline in deforestation rates was accompanied by a decline in the patches of forest fragments, while cropland and plantations first decreased and then increased. Second, 85% of cropland expansion (CE) occurred in forest frontiers of Myanmar (37%) and Thailand (32%) in particular, compared with 72% of PE in plantation‐forest frontiers, for example, 24% in Thailand and 22% in Cambodia. Third, 51% and 37% of the forests that declined were converted into cropland and plantations, respectively, with obvious national variations. In the least developed countries, such as Myanmar and Cambodia, CE dominated (65%), while the proportion of PE in Thailand and Vietnam was up to 56%. Finally, over 10% of the advances and retreats (re‐)occurred in various protected areas, with the expansion ratio of cropland and plantations nearly 1:2, particularly the Cambodia‐Thailand border. We thus appeal for more effective efforts from governments, the scientific community, and international initiatives (e.g., the UN‐REDD and Sustainable Development Goals) to further study and solve the issues of forest retreat and agricultural advance across the entire TAFF. Our new findings and insights about agricultural‐forest advances and retreats in their frontiers can enrich existing pan‐regional research of forest conversion or FL and agricultural expansion and provide an encouraging basis for action to reduce environmental degradation in tropical forests, including protected areas.
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Monitoring is essential to ensure that environmental goals are being achieved, including those of sustainable agriculture. Growing interest in environmental monitoring provides an opportunity to improve monitoring practices. Approaches that directly monitor land cover change and biodiversity annually by coupling the wall-to-wall coverage from remote sensing and the site-specific community composition from environmental DNA (eDNA) can provide timely, relevant results for parties interested in the success of sustainable agricultural practices. To ensure that the measured impacts are due to the environmental projects and not exogenous factors, sites where projects have been implemented should be benchmarked against counterfactuals (no project) and control (natural habitat) sites. Results can then be used to calculate diverse sets of indicators customized to monitor different projects. Here, we report on our experience developing and applying one such approach to assess the impact of shaded cocoa projects implemented by the Instituto de Manejo e Certificação Florestal e Agrícola (IMAFLORA) near São Félix do Xingu, in Pará, Brazil. We used the Continuous Degradation Detection (CODED) and LandTrendr algorithms to create a remote sensing-based assessment of forest disturbance and regeneration, estimate carbon sequestration, and changes in essential habitats. We coupled these remote sensing methods with eDNA analyses using arthropod-targeted primers by collecting soil samples from intervention and counterfactual pasture field sites and a control secondary forest. We used a custom set of indicators from the pilot application of a coupled monitoring framework called TerraBio. Our results suggest that, due to IMAFLORA’s shaded cocoa projects, over 400 acres were restored in the intervention area and the community composition of arthropods in shaded cocoa is closer to second-growth forests than that of pastures. In reviewing the coupled approach, we found multiple aspects worked well, and we conclude by presenting multiple lessons learned.
Full-text available
Forests in Flux Forests worldwide are in a state of flux, with accelerating losses in some regions and gains in others. Hansen et al. (p. 850 ) examined global Landsat data at a 30-meter spatial resolution to characterize forest extent, loss, and gain from 2000 to 2012. Globally, 2.3 million square kilometers of forest were lost during the 12-year study period and 0.8 million square kilometers of new forest were gained. The tropics exhibited both the greatest losses and the greatest gains (through regrowth and plantation), with losses outstripping gains.
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Losses of natural and semi-natural forests, mostly to agriculture, are a signiW-cant concern for biodiversity. Against this trend, the area of intensively managed plantation forests increases, and there is much debate about the implications for biodiversity. We pro-vide a comprehensive review of the function of plantation forests as habitat compared with other land cover, examine the eVects on biodiversity at the landscape scale, and synthesise context-speciWc eVects of plantation forestry on biodiversity. Natural forests are usually more suitable as habitat for a wider range of native forest species than plantation forests but there is abundant evidence that plantation forests can provide valuable habitat, even for some threatened and endangered species, and may contribute to the conservation of biodi-versity by various mechanisms. In landscapes where forest is the natural land cover, planta-tion forests may represent a low-contrast matrix, and aVorestation of agricultural land can assist conservation by providing complementary forest habitat, buVering edge eVects, and An 'oxymoron' is a Wgure of speech using an intended combination of two apparently contradictory terms.
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In the semiarid areas of the Mediterranean basin, restoration activities during the XXth century have mainly relied on extensive plantations of Pinus halepensis, which now cover thousands of hectares. Here we review studies that have evaluated the effects of these plantations on soils, vegetation, faunal communities, and forest fires. The effects of P. halepensis plantations on soil properties are highly dependent on the planting technique employed. Plantations frequently show enhanced runoff and soil losses when compared to natural shrublands, as well as limited improvement in most physio-chemical properties, which rarely reach the values shown by natural shrublands even 40 years after planting. The increase in tree cover resulting from the introduction of P. halepensis is commonly accompanied by an increase in water use, which may have relevant hydrological consequences at the catchment scale. Most studies performed so far have shown an overall negative effect of P. halepensis plantations on spontaneous vegetation. In these plantations, vegetation is dominated by early-successional species, and the establishment of late-successional sprouting shrubs—even after several decades—has been rarely reported. The effects of P. halepensis plantations on faunal communities may vary depending on the animal group considered. Available studies suggest that P. halepensis plantations can reduce bird biodiversity and promote pest outbreaks. Our review contributes to the debate on the suitability of mono-specific extensive P. halepensis plantations, and suggests that afforestation programmes should be revised.
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Oil palm is one of the world's most rapidly increasing crops. We assess its contribution to tropical deforestation and review its biodiversity value. Oil palm has replaced large areas of forest in Southeast Asia, but land-cover change statistics alone do not allow an assessment of where it has driven forest clearance and where it has simply followed it. Oil palm plantations support much fewer species than do forests and often also fewer than other tree crops. Further negative impacts include habitat fragmentation and pollution, including greenhouse gas emissions. With rising demand for vegetable oils and biofuels, and strong overlap between areas suitable for oil palm and those of most importance for biodiversity, substantial biodiversity losses will only be averted if future oil palm expansion is managed to avoid deforestation.
In 2004, Navjot Sodhi and colleagues warned that logging and agricultural conversion of Southeast Asia's forests were leading to a biodiversity disaster. We evaluate this prediction against subsequent research and conclude that most of the fauna of the region can persist in logged forests. Conversely, conversion of primary or logged forests to plantation crops, such as oil palm, causes tremendous biodiversity loss. This loss is exacerbated by increased fire frequency. Therefore, we conclude that preventing agricultural conversion of logged forests is essential to conserving the biodiversity of this region. Our analysis also suggests that, because Southeast Asian forests are tightly tied to global commodity markets, conservation payments commensurate with combined returns from logging and subsequent agricultural production may be required to secure long-term forest protection.
The effects of land use change on soil carbon stocks are of concern in the context of international policy agendas on greenhouse gas emissions mitigation. This paper reviews the literature for the influence of land use changes on soil C stocks and reports the results of a meta analysis of these data from 74 publications. The meta analysis indicates that soil C stocks decline after land use changes from pasture to plantation (−10%), native forest to plantation (−13%), native forest to crop (−42%), and pasture to crop (−59%). Soil C stocks increase after land use changes from native forest to pasture (+ 8%), crop to pasture (+ 19%), crop to plantation (+ 18%), and crop to secondary forest (+ 53%). Wherever one of the land use changes decreased soil C, the reverse process usually increased soil carbon and vice versa. As the quantity of available data is not large and the methodologies used are diverse, the conclusions drawn must be regarded as working hypotheses from which to design future targeted investigations that broaden the database. Within some land use changes there were, however, sufficient examples to explore the role of other factors contributing to the above conclusions. One outcome of the meta analysis, especially worthy of further investigation in the context of carbon sink strategies for greenhouse gas mitigation, is that broadleaf tree plantations placed onto prior native forest or pastures did not affect soil C stocks whereas pine plantations reduced soil C stocks by 12–15%.
Policy makers across the tropics propose that carbon finance could provide incentives for forest frontier communities to transition away from swidden agriculture (slash-and-burn or shifting cultivation) to other systems that potentially reduce emissions and/or increase carbon sequestration. However, there is little certainty regarding the carbon outcomes of many key land-use transitions at the center of current policy debates. Our meta-analysis of over 250 studies reporting above- and below-ground carbon estimates for different land-use types indicates great uncertainty in the net total ecosystem carbon changes that can be expected from many transitions, including the replacement of various types of swidden agriculture with oil palm, rubber, or some other types of agroforestry systems. These transitions are underway throughout Southeast Asia, and are at the heart of REDD+ debates. Exceptions of unambiguous carbon outcomes are the abandonment of any type of agriculture to allow forest regeneration (a certain positive carbon outcome) and expansion of agriculture into mature forest (a certain negative carbon outcome). With respect to swiddening, our meta-analysis supports a reassessment of policies that encourage land-cover conversion away from these [especially long-fallow] systems to other more cash-crop-oriented systems producing ambiguous carbon stock changes – including oil palm and rubber. In some instances, lengthening fallow periods of an existing swidden system may produce substantial carbon benefits, as would conversion from intensely cultivated lands to high-biomass plantations and some other types of agroforestry. More field studies are needed to provide better data of above- and below-ground carbon stocks before informed recommendations or policy decisions can be made regarding which land-use regimes optimize or increase carbon sequestration. As some transitions may negatively impact other ecosystem services, food security, and local livelihoods, the entire carbon and noncarbon benefit stream should also be taken into account before prescribing transitions with ambiguous carbon benefits.
Oil palm is one of the world's most rapidly expanding equatorial crops. The two largest oil palm-producing countries—Indonesia and Malaysia—are located in Southeast Asia, a region with numerous endemic, forest-dwelling species. Oil palm producers have asserted that forests are not being cleared to grow oil palm. Our analysis of land-cover data compiled by the United Nations Food and Agriculture Organization suggests that during the period 1990–2005, 55%–59% of oil palm expansion in Malaysia, and at least 56% of that in Indonesia occurred at the expense of forests. Using data on bird and butterfly diversity in Malaysia's forests and croplands, we argue that conversion of either primary or secondary (logged) forests to oil palm may result in significant biodiversity losses, whereas conversion of pre-existing cropland (rubber) to oil palm results in fewer losses. To safeguard the biodiversity in oil palm-producing countries, more fine-scale and spatially explicit data on land-use change need to be collected and analyzed to determine the extent and nature of any further conversion of forests to oil palm; secondary forests should be protected against conversion to oil palm; and any future expansion of oil palm agriculture should be restricted to pre-existing cropland or degraded habitats.
Human-driven land-use changes increasingly threaten biodiversity, particularly in tropical forests where both species diversity and human pressures on natural environments are high. The rapid conversion of tropical forests for agriculture, timber production and other uses has generated vast, human-dominated landscapes with potentially dire consequences for tropical biodiversity. Today, few truly undisturbed tropical forests exist, whereas those degraded by repeated logging and fires, as well as secondary and plantation forests, are rapidly expanding. Here we provide a global assessment of the impact of disturbance and land conversion on biodiversity in tropical forests using a meta-analysis of 138 studies. We analysed 2,220 pairwise comparisons of biodiversity values in primary forests (with little or no human disturbance) and disturbed forests. We found that biodiversity values were substantially lower in degraded forests, but that this varied considerably by geographic region, taxonomic group, ecological metric and disturbance type. Even after partly accounting for confounding colonization and succession effects due to the composition of surrounding habitats, isolation and time since disturbance, we find that most forms of forest degradation have an overwhelmingly detrimental effect on tropical biodiversity. Our results clearly indicate that when it comes to maintaining tropical biodiversity, there is no substitute for primary forests.