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Effects of afforestation on water yield: a global synthesis
with implications for policy
KATHLEEN A. FARLEY
*
w, ESTEBAN G. JOBBA
´GYwzand ROBERT B. JACKSON
*
w
*
Center on Global Change, Duke University, Durham, NC 27708, USA, wDepartment of Biology and Nicholas School of the
Environment and Earth Sciences, Duke University, Durham, NC 27708, USA, zGrupo de Estudios Ambientales – IMASL,
Universidad Nacional de San Luis & CONICET, San Luis 5700, Argentina
Abstract
Carbon sequestration programs, including afforestation and reforestation, are gaining
attention globally and will alter many ecosystem processes, including water yield. Some
previous analyses have addressed deforestation and water yield, while the effects of
afforestation on water yield have been considered for some regions. However, to our
knowledge no systematic global analysis of the effects of afforestation on water yield
has been undertaken. To assess and predict these effects globally, we analyzed 26
catchment data sets with 504 observations, including annual runoff and low flow. We
examined changes in the context of several variables, including original vegetation type,
plantation species, plantation age, and mean annual precipitation (MAP). All of these
variables should be useful for understanding and modeling the effects of afforestation
on water yield. We found that annual runoff was reduced on average by 44% ( 3%) and
31% ( 2%) when grasslands and shrublands were afforested, respectively. Eucalypts
had a larger impact than other tree species in afforested grasslands (P50.002), reducing
runoff (90) by 75% ( 10%), compared with a 40% ( 3%) average decrease with pines.
Runoff losses increased significantly with plantation age for at least 20 years after
planting, whether expressed as absolute changes (mm) or as a proportion of predicted
runoff (%) (Po0.001). For grasslands, absolute reductions in annual runoff were greatest
at wetter sites, but proportional reductions were significantly larger in drier sites
(Po0.01 and Po0.001, respectively). Afforestation effects on low flow were similar to
those on total annual flow, but proportional reductions were even larger for low flow
(Po0.001). These results clearly demonstrate that reductions in runoff can be expected
following afforestation of grasslands and shrublands and may be most severe in drier
regions. Our results suggest that, in a region where natural runoff is less than 10% of
MAP, afforestation should result in a complete loss of runoff; where natural runoff is
30% of precipitation, it will likely be cut by half or more when trees are planted. The
possibility that afforestation could cause or intensify water shortages in many locations
is a tradeoff that should be explicitly addressed in carbon sequestration programs.
Keywords: afforestation, land-use change, plantation, runoff, water yield
Received 21 December 2004; accepted 15 March 2005
Introduction
The conversion of natural grasslands to plantations has
occurred over extensive areas of the southern hemi-
sphere and will likely continue with new policy and
market incentives to reduce atmospheric CO
2
concen-
trations. Through the clean development mechanism
(CDM), the Kyoto Protocol allows for developed
countries to offset part of their CO
2
emissions by
establishing carbon-sequestering projects, including
reforestation and afforestation. Afforestation has been
suggested as a way to simultaneously sequester carbon,
increase wood and paper supplies, and diversify rural
incomes (Vertessy, 2001). Not surprisingly, the focus of
much of the research on this land-use change has been
Correspondence: Kathleen A. Farley, Duke University, Box 91000,
Durham, NC 27708, USA, tel. 11 831 241 1236;
fax 11 831 333 1736, e-mail: farley@duke.edu
Global Change Biology (2005) 11, 1565–1576, doi: 10.1111/j.1365-2486.2005.01011.x
r2005 Blackwell Publishing Ltd 1565
on sequestering and storing carbon in the biomass and
soils of afforested areas. However, converting grass-
lands or shrublands to plantations will likely affect
many other ecosystem processes, including water yield
from rivers and streams (e.g. Duncan, 1995; Dye, 1996;
Bashkin & Binkley, 1998; Paul et al., 2002; Jobba
´gy &
Jackson, 2003, 2004; Farley et al., 2004).
Water yield is altered through changes in transpira-
tion, interception, and evaporation, all of which tend to
increase when grasslands or shrublands are replaced
with trees. Transpiration rates are influenced by
changes in rooting characteristics, leaf area, stomatal
response, plant surface albedo, and turbulence (Brooks
et al., 1997; Hoffmann & Jackson, 2000; Jackson et al.,
2001; Vertessy, 2001). Although transpiration is tradi-
tionally considered the more important component of
forest evapotranspiration (ET), interception and subse-
quent evaporation from the canopy can also increase
substantially, particularly with conifers (Pearce & Rowe,
1979; Cannell, 1999). Evaporation of intercepted pre-
cipitation is generally low in grasslands, but can
account for 10–20% of rainfall for broadleaf trees and
20–40% for conifers (Le Maitre et al., 1999). The sum of
the changes in evaporation and transpiration in planta-
tion catchments leads to an increase in ET (Holmes &
Sinclair, 1986); for example, ET from a catchment
planted with eucalyptus could be 40–250 mm higher
than from a grassland catchment (Zhang et al., 1999).
Despite recognition of higher ET rates in plantations,
the likelihood that this will reduce water yield has not
always been acknowledged (Vertessy & Bessard, 1999),
particularly within the context of afforestation pro-
grams for carbon sequestration.
Studies of the effect of vegetation change on water
yield have focused primarily on the removal of woody
vegetation (e.g. Bosch & Hewlett, 1982; although see
Scott et al., 2000). Using results from deforestation
studies to predict the effects of afforestation may be
problematic because they are not necessarily opposite
and reversible processes (Robinson et al., 1991). The
changes in runoff induced by deforestation and
afforestation likely differ in magnitude, timing, and
relationship to site characteristics. Deforestation studies
are distinguished by factors such as soil disturbance
and deposition of slash and litter, which can affect
streamflow patterns (Vertessy, 1999). The duration of
most deforestation and afforestation studies is also
vastly different, and the short time period of the former
increases the chance that the effect of rainfall variability
will be difficult to separate from the catchment response
(Vertessy, 1999). In addition, the timing of changes in
runoff may differ significantly, with abrupt changes
associated with deforestation and more gradual
changes with plantation age following afforestation.
Although the effects of plantation age and rotation
length are important for predicting the consequences of
afforestation on water yield, these effects are lacking in
most studies (Best et al., 2003). A better understanding
of the age–runoff relationship after afforestation will
allow managers to make predictions using more
realistic rotation scenarios – in which a proportion of
the landscape is in early growth stages, and full aging is
prevented by harvesting. In addition, the effect of
afforestation on low flow is an important component of
this framework. Changes in low flow may be even more
important than changes in annual flow, as the dry
season is when reduced water supply will have the
most severe effects for users, particularly in arid and
semiarid regions (Smith & Scott, 1992; Scott & Smith,
1997; Sharda et al., 1998; Robinson et al., 2003).
In this paper, we quantified the change in streamflow
associated with afforestation globally. Our specific
objectives were to: (1) assess the direction, range, and
extent of changes in total annual streamflow and low
flow associated with afforestation, (2) examine the
interactions with original vegetation type, tree species
planted, plantation age, and climate, and (3) provide a
predictive framework for modeling the effects of
afforestation on water yield for carbon sequestration
scenarios. To accomplish these objectives, we analyzed
26 catchment data sets containing 504 annual observa-
tions to assess the effects of afforestation on water yield.
These catchment studies included sites that were
converted from grassland, pasture, or shrubland to
pines, eucalypts, or other species (primarily spruce).
Methods
Data synthesis
We compiled catchment data sets from peer-reviewed
journals as well as reports from governmental and
nongovernmental research institutes, representing
many parts of the southern hemisphere, as well as
India, the UK, and Germany in the northern hemi-
sphere (Appendix A). We examined data from affor-
ested regions with a previous land cover of grassland or
shrubland where runoff was measured following
planting, and included all the data sets we found with
these characteristics. Most of the data were from paired
catchment studies, in which streamflow from grassland
or shrubland catchments was compared with that of
nearby afforested catchments.
We examined the data set for several variables. Most
studies reported changes in runoff for several years
after afforestation, with some beginning at age 0 and
others beginning later in the rotation. The number of
years of runoff data varied with each study, with some
1566 KATHLEEN A. FARLEY et al.
r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
studies covering less than a decade and others as much
as four decades (Appendix A). For afforested catch-
ments that were harvested after the full rotation length,
we included only the data up to the time of harvesting.
In cases where data were available from more than one
source for the same catchment, we used multiple
sources if the information did not overlap (such as
covering different time periods or reporting different
types of flow data, such as annual vs. low flow). Where
they reported the same data for the same time period,
we chose those that covered the longest time period
and, in some cases, used the additional data sets for
supplementary information, such as area planted or
calibration period. In no cases were duplicate data from
a single catchment used in the analyses. Our database
consisted of runoff data for each year reported for a
given catchment; for example, where a study included
data for plantation ages 1–8, we used each of the 8 years
as a data point in our analyses.
The percent of the catchment afforested varied among
data sets (Appendix A). In more than three-fourths of
the cases, half or more of the catchment was planted,
although in three cases it was only 20–40%, and in
several cases it was not reported. We based our analyses
on the original data sets, uncorrected for the proportion
of the catchment afforested, which means that our
estimates are conservative, as we are likely under-
estimating the magnitude of the effects. An alternative
used by some researchers is to scale the catchment
results by the percentage afforested. To satisfy those
researchers, we performed a parallel analysis, scaling
all the data to a minimum area planted (75%). For this
analysis, all catchments in which less than 75% of the
area was planted had the data scaled linearly up to 75%
– because it is not typical practice in forestry to plant
100% of a catchment (Scott & Smith, 1997). The data
from the catchments for which we lacked information
on the area planted were included without scaling. The
figures and discussion are based on the unscaled data,
but we have included an overview of the analyses using
the scaled data in the results section.
The studies included in the data set used one of two
general approaches to calculate the change in runoff
following afforestation. In 60% of the data sets, the
change in runoff was reported as predicted runoff minus
observedrunoff.Theapproachtakenineachofthese
studies to calculate predicted runoff was based on a
calibration of runoff between the control and planted
catchments before afforestation. Predicted runoff for a
given year was calculated based on runoff from the
control catchment in that year and the relationship
between the control and planted catchments derived from
the calibration period. In the remaining 40% of data
sets, the change in runoff was calculated as runoff in the
control catchment minus runoff in the planted catchment.
Weusedthedataastheauthorspresentedthem.
In the results, we refer to changes in runoff as
absolute changes (mm) and proportional changes (% of
predicted or control runoff). Because changes in runoff
vary from year to year with variations in rainfall,
expressing changes as a proportion of expected flow is
useful as a way to remove this climatic variability (Scott
& Smith, 1997). Not all data sets provided both absolute
and proportional runoff values, so some of the data
points included in one analysis are absent in the other.
In addition to the change in annual runoff, a number
of studies also reported change in low or base flow.
Low flow was typically defined in the studies as the
flow rate during the driest 3–4 months of the year, or as
dry weather summer flow (Smith & Scott, 1992; Scott &
Smith, 1997; Sharda et al., 1998; Robinson et al., 2003). In
some cases, it was defined more precisely by using an
exceedance level (the flow exceeded for a certain
percent of the year, generally ranging from 75% to
95%) as a threshold (Fahey & Watson, 1991; Scott &
Smith, 1997; Robinson et al., 2003).
Statistical analyses
The effect of original (pre-afforestation) vegetation type,
plantation species, plantation age, and mean annual
precipitation (MAP) on the change in runoff were
tested using one-way ANOVAs followed by Tukey’s HSD
post hoc tests; where conditions of normality and
homogeneity of variance were not met, nonparametric
Kruskal–Wallis tests were used as noted. In each case,
the dependent variable was either the proportional
change in runoff (%) or the absolute change in runoff
(mm) following afforestation. The factors evaluated
included original vegetation type (grassland or shrub-
land), plantation species (pines, eucalypts, or other
species), plantation age class (using 5-year intervals), or
MAP (o1000, 1000–1250, 1250–1500, 41500 mm). For
the analysis of the relationship between change in
runoff and plantation age, linear, logarithmic, and
quadratic regressions were compared and the curve
with the best fit, based on adjusted least-squares
regression, was selected. Because we knew, a priori,
that there should be no change in runoff at age zero, we
used regressions through the origin (Zar, 1999). This
alters the definition of the r
2
from the more typical r
2
of
a regression that is not forced through the origin.
Results
Runoff decreased consistently and substantially with
afforestation across the entire data set (Fig. 1, Po0.001).
More than one-fifth of the catchments experienced
EFFECTS OF AFFORESTATION ON WATER YIELD 1567
r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
reductions of 75% or more during at least 1 year and
13% of the catchments experienced 100% runoff
reductions for at least 1 year (Fig. 1a, c). Both the
original vegetation type at a site and plantation species
significantly influenced proportional changes in
streamflow (Table 1, Po0.001 and Po0.05, respec-
tively). When averaged across ages, annual runoff
reductions were greater in grasslands (44 3%) than
shrublands (31 2%) (Table 1, Po0.001). Eucalypts had
a greater impact than pines in sites that were originally
grasslands, with runoff reductions of 75% ( 10%) and
40% ( 3%), respectively (Table 1, Po0.001).
Plantation age strongly affected runoff, whether
expressed as absolute or as proportional changes (Table
2; Fig. 1, Po0.001 in both cases). Runoff reductions in
afforested grasslands and shrublands were similar in
the first 5 years after tree establishment (16% and
15%, respectively), but diverged as the plantations
aged (Table 2). Afforested grasslands reached a 50%
reduction in runoff by the tenth year, compared with
35% in afforested shrublands at the same age (Table 2).
In proportional terms, maximum reductions were
reached 5 years earlier and were substantially larger
when grasslands were afforested (67% compared with
43% in shrublands, Table 2).
Decreases in streamflow were sustained through 30
years in grasslands and, in absolute terms, showed no
sign of recovery with plantation age (Fig. 1b). In
proportional terms, there appeared to be some recovery
for afforested grasslands after 20 years (Fig. 1a), but
most of this is attributed to a single catchment where a
defoliation outbreak coincided with several years of
above-average rainfall, after which runoff losses again
became more severe (Scott et al., 2000). In contrast,
shrublands showed a distinct recovery in runoff after
approximately 35 years of afforestation, both in
proportional and absolute amounts (Fig. 1c, d). Because
eucalyptus rotations are shorter than 35 years, none of
the eucalyptus sites in the database extended to the age
at which this recovery occurred. However, the data
from the grassland sites demonstrated a more complete
loss of runoff with eucalypts, with many reaching 100%
reductions in streamflow within 10 years (Fig. 1a),
suggesting that the trend toward recovery may only
apply to shrublands planted with pine.
Afforestation reduced runoff across a broad range of
climates (Fig. 2). Reductions in runoff were significantly
related to MAP for afforested grasslands in both
proportional and absolute terms. For grasslands, the
wettest sites (MAP41500 mm yr
1
) had the largest
absolute reductions (287 44 mm) but the smallest
proportional reductions (27 4%). In contrast, propor-
tional losses were far greater at the driest grassland site
(62 10%) (Fig. 2), suggesting that the effects of
afforestation on water yield will be more severe in drier
regions. For shrublands, proportional and absolute
reductions were largest at the driest sites
(MAP 51000–1250 mm yr
1
, data not shown), but they
also were significantly older than the wettest sites, so age
may be a confounding factor for the shrubland analysis.
Across the data set, proportional losses in low flow
with afforestation were closely correlated with, but even
larger than, proportional losses in annual flow (Fig. 3,
Po0.001). These data suggest that dry-season losses are
Table 1 Mean change in runoff ( SE) following afforestation, by original vegetation type and by planted vegetation type,
averaged across plantations 30 years old
Afforested
from
Afforested to Change in
runoff (%)
Catchment
n
Change in
runoff (mm)
Catchment
n
MAP (mm) Drunoff (mm)/
MAP (mm) (%)
Grassland Any species 44 ( 3)
**
13 170 ( 13)
ns
11 1241 ( 16) 15 ( 0.9)
Shrubland 31 ( 2)
**
8162 ( 8)
ns
8 1262 ( 10) 14 ( 0.6)
Grassland or
shrubland
Pines 35 ( 2)
ns
14 165 ( 8)
ns
14 1236 ( 10) 14 ( 0.5)
Eucalypts 50 ( 5)
ns
4173 ( 20)
ns
4 1336 ( 23) 14 ( 1.7)
Other species 39 ( 7)
ns
3 1415 ( 33)
Grassland only Pines 40 ( 3)
*
9167 ( 13)
ns
9 1260 ( 18) 14 ( 0.9)
Eucalypts 75 ( 10)
*
1202 ( 38)
ns
1 1166 ( 0) 19 ( 3.2)
Other species 39 ( 7)
*
3 1415 ( 33)
Shrubland only Pines 30 ( 2)
ns
5163 ( 9)
ns
5 1226 ( 9) 15 ( 0.6)
Eucalypts 38 ( 5)
ns
3159 ( 23)
ns
3 1414 ( 24) 12 ( 1.9)
In order to make differences between grasslands and shrublands and among plantation species comparable, all plantations 30
years old were included. Drunoff/MAP 5change in runoff (mm)/mean annual precipitation (mm)100. Catchment n5the
number of catchments represented in each category. Significance symbols refer only to comparisons of mean change in runoff among
the groups within a category (i.e. grassland vs. shrubland pooled across all tree species; pines vs. eucalypts vs. other species pooled
across grasslands and shrublands; and pines vs. eucalypts vs. other species compared within either grasslands or shrublands).
**
Po0.001,
*
Po0.05, ns, not significant. Significance was determined using Kruskal–Wallis tests.
1568 KATHLEEN A. FARLEY et al.
r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
predicted to be even more severe than total annual
losses for afforestation scenarios, possibly leading to
shifts from perennial to intermittent flow regimes in dry-
region streams. In proportional terms, low flow declined
with plantation age through approximately 25 years and
then began to recover somewhat (Fig. 4a, b). However,
Plantation age (yrs) Plantation age (yrs)
Plantation age (yrs) Plantation age (yrs)
3020100
Change in runoff (%)
Change in runoff (%)
20
0
−20
−40
−60
−80
−100
Plantation type
Other
Eucalyptus
Pine
All species
R2 = 0.75; P<0.001 R2 = 0.71; P<0.001
R2 = 0.82; P<0.001 R2 = 0.74; P<0.001
3020100
Change in runoff (mm)
Change in runoff (mm)
200
0
−200
−400
−600
Plantation type
Other
Eucalyptus
Pine
All species
403020100
40
20
0
−20
−40
−60
−80
−100
Plantation type
Eucalyptus
Pine
All species
403020100
400
200
0
−200
−400
−600
Plantation type
Eucalyptus
Pine
All species
(a)
(b) (d)
(c)
Fig. 1 (a–d) Proportional and absolute changes in runoff with plantation age, by original vegetation type. The complete data set was
used for curve-fitting, but to improve resolution of the figure grassland curves are only displayed to 30 years. Eight points 440 years are
not displayed, clustered around 30% and 500 mm (a, b; see Table 2). Regressions were through the origin. Regression equations: (a)
Y505.636X10.112X
2
, (b) Y5017.516X10.115X
2
, (c) Y504.398X10.108X
2
, (d) Y5022.044X10.520X
2
.
Table 2 Mean change in runoff ( SE) following afforestation as a function of plantation age, by previous vegetation type
Age (years) Grassland Shrubland
Drunoff (%) nDrunoff (mm) nDrunoff (%) nDrunoff (mm) n
1–5 16 53545 17 34 15 3
ab
36 81 20
a
36
6–10 50 636152 18 37 35 4
c
40 158 17
ab
40
11–15 67 530216 18 29 39 4
c
30 214 16
b
30
16–20 58 529247 28 27 43 4
c
23 230 13
b
23
21–25 42 612304 62 10 35 4
bc
20 168 22
ab
20
26–30 54 44456 48 4 32 4
abc
20 193 20
b
20
31–35 38 6
c
17 203 26
b
17
36–40 12 8
a
880 56
a
8
41–45 36 73669 103 3
46–50 27 25526 31 5
Po0.001
*
0.001
*
0.001 0.001
Significance was determined using one-way ANOVAs followed by Tukey’s HSD post hoc tests, where conditions of normality and
homogeneity of variance were met; within each of those columns, means followed by different letters are significantly different from
each other at P0.05.
*
Kruskal–Wallis tests were used.
n5the number of runoff measurements in each age interval (taken from all catchments in which that plantation age range was
represented).
EFFECTS OF AFFORESTATION ON WATER YIELD 1569
r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
the recovery may be species specific, as the loss of low
flow appears to be more complete for eucalyptus and
other species than for pines (Fig. 4a). The pattern of
decline and recovery may also occur with the absolute
change in low flow (Fig. 4b), although the effect in the
first 10–15 years following afforestation was highly
variable, ranging from an increase of 10 mm to a
decrease of almost 250 mm.
Scaling the data to 75% cover affected the magnitude
of the changes in streamflow somewhat, but did not alter
the patterns with plantation age, climate, or vegetation
type. The change in magnitude was most notable when
looking at single year runoff reductions; when data were
scaled, one-third (rather than one-fifth) of the catch-
ments experienced reductions of 75% or more during at
least 1 year. The effect of scaling was fairly uniform
across vegetation types, as average reductions were
approximately 5 percentage points higher with scaling
(e.g. 45% rather than 40%) for grasslands or shrublands
and for eucalyptus or pine. The relationship between
plantation age and runoff reductions was not altered
substantially by scaling, particularly for young planta-
tions; in the first 5 years after afforestation, runoff
reductions were only 1 percentage point higher. For
afforested grasslands, scaling had little effect on max-
imum reductions, but maximum runoff reductions in
afforested shrublands reached 50% after scaling (com-
pared with 43% without scaling). The pattern of runoff
reductions across climatic zones also remained largely
unchanged with scaling, and it had a minor effect on the
magnitude of runoff reductions; scaling had no effect on
either absolute or proportional runoff reductions for the
wettest sites, but increased the average runoff reductions
in the driest sites from 62% to 66%.
Discussion
Our analysis clearly demonstrates that afforestation of
grasslands and shrublands will typically result in a loss
of one-third to three-quarters of streamflow on average.
Runoff reductions are attained very rapidly after
−350
−300
−250
−200
−150
−100
−50
0
<1000 1000–1250 1250–1500 >1500
Mean annual precipitation (mm)
Change in runoff (mm)
−80
−60
−40
−20
0
Change in runoff (%)
mm**
%***
Fig. 2 Mean change in runoff ( SE) following afforestation as a
function of mean annual precipitation for sites that were originally
grasslands. The low precipitation sites were comprised of slightly
but not significantly younger stands than the wettest sites.
*** Po0.001, ** Po0.01.
Change in total annual runoff (%)
200−20−40−60−80
Change in low flow (%)
20
0
−20
−40
−60
−80
−100
R2 = 0.82; P<0.001
Fig. 3 Relationship between the change in low flow and the
change in total annual flow. Regression equation: Y56.1611
0.990X.
Plantation age (yrs)
Plantation age (yrs)
403020100
Change in low flow (%)
20
0
−20
−40
−60
−80
−100
R2 = 0.76; P<0.001
Pine
Eucalyptus
Other
Plantation type
403020100
Change in low flow (mm)
50
0
−50
−100
−150
−200
−250
R2 = 0.42; P<0.001
Plantation type
Pine
Eucalyptus
(a)
(b)
Fig. 4 (a, b) Change in low flow (% and mm) with plantation
age. Open symbols denote sites that were originally grasslands,
closed symbols were originally shrublands. Regressions were
through the origin. Regression equations: (a) Y505.694X1
0.142X
2
, (b) Y504.799X10.135X
2
.
1570 KATHLEEN A. FARLEY et al.
r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
afforestation, with losses of more than 10% of stream-
flow occurring in the first 2–3 years after tree establish-
ment for most catchments. This indicates that the lag
time between planting and runoff response is usually
short, although the full effect on runoff may not occur
for one or more decades.
Mean annual rainfall is one of the most important
determinants of annual runoff and can have a strong
influence on change in runoff after vegetation change
(Vertessy, 2001; Zhang et al., 2001). In agreement with
previous analyses (Bosch & Hewlett, 1982), our data
show that vegetation change has the largest absolute
impacts on runoff in high-rainfall areas. However, it also
reveals the opposite trend for proportional changes,
which may be a better measure of the effects on water
supplies and are largest in dry areas (Fig. 2). The reason
for the more extreme reductions in drier regions may
simply be that there is less water in those systems; for a
given proportional increase in ET, the effect on runoff
will be larger in drier regions because the fraction of
precipitation that reaches streams is already low.
Rooting depth may also be a factor, as it is expected to
play a particularly important role in increasing ET in
dry climates (Zhang et al., 2001; Schenk & Jackson, 2002).
As this source of increased water use is likely to persist
over the length of a rotation, it could result in larger
proportional runoff reductions overall in dry regions.
While runoff reductions occurred across many sites
and species, afforestation had a greater effect on runoff in
grasslands than in shrublands. The reason for higher
runoff reductions in afforested grasslands compared with
shrublands may be inherently higher runoff with
herbaceous cover. Calder (1986) noted that transpiration
losses from scrub vegetation in India tend to be relatively
high, with such vegetation using twice as much soil
water and drying the soil to twice the depth of annual
crops. Contributing to this effect is the difference in the
depth and distribution of roots among vegetation types,
whichisalteredbytheshiftfromgrassesorshrubsto
trees (Jackson et al., 2000). Shrubs have greater similarity
to trees, in terms of total root biomass and maximum
rooting depth, than to grasses (Jackson et al., 1996); for
this reason, the change in access to water and the change
in transpiration rates are not likely to differ as much
between shrubs and trees as they do between grasslands
and trees. In addition, shrubs may be characterized by a
longer active transpiration period than seasonally dor-
mant grasses, contributing to total annual transpiration
that is higher than that of grasses and more similar to that
of trees. As a result, runoff reductions may be less severe
when shrublands are afforested relative to grasslands.
These differences between pre-afforestation vegeta-
tion types carried over to the age–runoff relationship of
afforested grasslands vs. shrublands. When grasslands
were afforested, runoff reductions occurred earlier,
were larger, and were sustained for a longer period of
time than in shrublands. This may result from
differences in the underlying causes of the change in
ET that leads to lower runoff. The two primary causes
of the increase in ET following afforestation are the
greater capacity for water loss associated with higher
leaf area indexes (LAIs) of the higher stature vegetation
(Calder, 1986) and better access to water sources,
through accessing of deep water or drawing on stored
soil water (Calder et al., 1993; Zhang et al., 2001; Engel et
al., 2005). When grasslands are afforested, deep water
access likely plays an important role, as there should be
a large change in rooting depth (Jackson et al., 1996).
This idea is supported by the fact that ET increases
more than runoff decreases in grassland sites. In the
few studies in our data set (all originally grasslands)
where changes in ET were measured in addition to
change in runoff, a fairly strong relationship was
revealed (Fig. 5, R
2
50.45; Po0.001). The relationship
was not 1 : 1, however, as ET increased more than runoff
decreased. While it is unclear whether this occurs in all
plantation types or how long this pattern could be
maintained, it suggests the use of deep water to
subsidize the increase in ET in afforested grasslands.
In contrast, when shrublands are afforested, the change
in rooting depth is not as large, so that the dominant
mechanism behind increasing ET at those sites may be
the increased capacity for water loss by the trees
relative to shrubs. This mechanism is also likely to be
more a feature of younger plantations – occurring as
the LAI increases and declining as the tree canopy ages
– so that with time the water use of the plantation may
approach the control and runoff could begin to recover.
Change in ET (mm)
5004003002001000
Change in runoff (mm)
0
−100
−200
−300
−400
R2 = 0.45, P=0.002
Fig. 5 Change in runoff as a function of change in evapotran-
spiration (ET). All sites in this data set, which included plantation
ages ranging from 0 to 20 years, were originally grasslands.
EFFECTS OF AFFORESTATION ON WATER YIELD 1571
r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
In addition to differences between afforested grass-
lands and shrublands, there were significant differences
between pines and eucalypts in cases where the original
vegetation was grassland. Eucalypts caused larger
proportional changes in annual runoff than pines did
and also appeared to cause more severe and complete
losses of low flow within the first 10–15 years after
afforestation. Differences in the growth patterns between
pines and eucalypts likely play a role in producing these
differences. Decreases in runoff following afforestation
are positively related to the growth rate of the planted
stands (Bosch & Hewlett, 1982), with evidence suggest-
ing that the rate of increase in ET is more rapid under
eucalypts because of their rapid early growth and
canopy closure (Dye, 1996). This rapid increase in ET
should correspond to larger reductions in runoff under
eucalyptus in the early part of the rotation. Although
growth will begin to slow as the stands age, eucalyptus
rotations tend to be relatively short compared with pine,
so that overall average water use per rotation is higher
(Bosch & von Gadow, 1990), resulting in greater overall
runoff reductions. While there is likely to be some
variation in species effects by region, generalizations
regarding the effects of different plantation species on
runoff should be useful for planning afforestation
projects and the tree species that will be used in them.
Important interactions may also exist between planta-
tion species and climate, with different plantation types
having more severe effects on runoff under different
precipitation regimes. In our data set, both eucalypts and
pines had their greatest relative impact in lower rainfall
regions. However, the two types of plantations differed
markedly in terms of absolute reductions. Eucalypts
averaged across all ages up to 30 years in the data set
produced the smallest runoff reductions (90 14 mm) in
high rainfall zones (MAP41500 mm); for pines, the
largest runoff reductions (189 40 mm) occurred in
higher rainfall regions. This pattern may be explained
bytherelativeimportanceofincreasesinwetcanopy
evaporation vs. transpiration for different species and in
different climatic zones. Interception storage and evapora-
tion from the canopy are thought to be greater for needle-
leaved than for broad-leaved trees (Zinke, 1967; Cannell,
1999); the dense canopies of conifers allow for higher
canopy storage of rainfall and can lead to large intercep-
tion losses (typically ranging from 15% to 24%, and in
somecasesreachingasmuchas60%;LeMaitreet al.,
1999). For eucalypts, which tend to establish deep roots at
a young age (Dye, 1996), higher transpiration is likely the
more important component of increasing ET following
afforestation (Vertessy, 2001). In addition to differing
among tree species, evaporation and transpiration also
play different roles under different climate regimes. In
higher rainfall zones, evaporation of intercepted rainfall is
themoreimportantcomponentofincreasingET(Holmes
& Wronski, 1981; Duncan, 1995), while in drier regions the
ability of the vegetation to reach and exploit deep soil
water stores to maintain transpiration is an important
determinant of changes in water yield (Pearce & Rowe,
1979). Therefore, in drier regions, where transpiration is
the more important contributor to absolute increases
in ET following afforestation (Scott & Lesch, 1997),
eucalypts are likely to cause more severe runoff reduc-
tions. In wetter regions, where interception plays a more
important role, pines may cause more severe runoff
reductions. These differences can have important implica-
tions for decisions about where plantations are established
and which tree species are used.
Implications for policy
Our analysis shows that general relationships between
plantation age and runoff responses exist. Streamflow
response to afforestation can be expected to be very
rapid (within 5 years of planting), maximum runoff
reductions can be expected between 15 and 20 years
after planting, and runoff reductions will likely be
larger and more sustained when grasslands are
afforested than when shrublands are. These differences
among the areas in which afforestation is considered a
potential land use are important in planning where
plantations should be located, as well as which species
should be used. In addition, a better understanding of
the timing of the most extreme reductions in runoff
may help water managers in their planning. For
example, given that the effect of afforestation on low
flow is somewhat larger than on total flow, this may be
an important variable to incorporate as a guide for
afforestation zoning (Scott & Smith, 1997).
Our results also indicate that some past perceptions
about where afforestation projects should best be
located in order to minimize effects on runoff may be
misleading. Specifically, the assumption that changes in
runoff will be less severe in low rainfall areas does not
hold true when proportional runoff reductions are
considered. While it has been suggested that some of
the negative hydrologic impacts of afforestation could
be minimized by establishing plantations in lower
rainfall zones (Vertessy, 2001), our data indicate that
this prescription would be unlikely to ameliorate runoff
reductions and may actually result in more severe local
impacts. This information may be critical for zoning of
afforestation projects, in particular in semiarid regions.
The ability to predict the likely effects of afforestation
in specific locations with limited information will be the
biggest challenge to zoning and planning for these
projects. Catchment data are collected over decades
and are unavailable for many regions of the world.
1572 KATHLEEN A. FARLEY et al.
r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
However, some indicators, such as the change in runoff
as a percent of MAP at a site, may provide a gauge of
the probable severity of the loss of runoff. The average
ratio tended to be around 14–15% of MAP for most
cases in our synthesis (Table 1), and was surprisingly
conservative, regardless of whether the sites were
originally grasslands or shrublands (15% and 14%,
respectively) and whether they were planted to pine or
eucalyptus (14% for both) (this value also coincides well
with the difference in ET between forest and grassland
as a percent of MAP in the curves described in Holmes
& Sinclair, 1986). From this we can conclude that, on
average, trees are able to use approximately 15% more
precipitation than grasses or shrubs. This suggests that,
in a region where natural runoff is in the range of 10% of
MAP, afforestation can be expected to result in a
complete loss of runoff; where natural runoff is 30% of
precipitation, it could be reduced by half or more when
trees are planted. The percent of precipitation used by
trees may be higher than 15% in some regions (e.g.
grasslands planted to eucalyptus; see Table 1), but this
value can serve as a useful indicator for land managers
and policy makers in guiding the location of plantations
with respect to the demand for water resources.
Conclusion
The environmental ‘co-effects’ of afforestation programs
have received much less attention than the carbon
sequestration potential. However, one of the so-called
‘crunch issues’ that have been debated in determining
how to implement land-use change and forestry projects
within the CDM is their potential impact on local
livelihoods and environments (Pedroni, 2003). Our
synthesis clearly indicates that a reduction in runoff
can be expected with afforestation of grasslands and
shrublands, which will have ecological and socioeco-
nomic ramifications. In some locations, such as parts of
Australia where lower runoff can ameliorate salinity
and groundwater upwelling, this will be a positive
change. In many other regions, reduced runoff will
cause or intensify water shortages, a tradeoff that
should be explicitly recognized before land conversion.
Acknowledgements
Funding for this work was provided by the Center on Global
Change at Duke University, NSF, and the Biological and
Environmental Research (BER) Program, US Department of
Energy, through the Southcentral Regional Center of NIGEC. We
would like to thank two anonymous reviewers whose thought-
ful comments were very helpful in improving this manuscript.
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Appendix A
See Table A1 for catchment data sets used in the
synthesis.
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r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
Table A1 Datasets used in the synthesis
Source Name of site(s) Location Latitude/
longitude
MAP
(mm)
Original vegetation Plant species Plantation age
(years)
Percent
planted
Data
type
Notes
Borg et al.
(1988)
Padbury Reservoir Southwest Australia N/A 880 Crops and pastures Pinus radiata,
Eucalyptus
globulus
3–8 70 P–O
Bosch (1979) Cathedral Peak II Winterton, Natal Drakensberg,
South Africa
291000S/291150E 1400 Grassland P. patula 1–26 52 Supp
Calder &
Newson (1979)
Wye and Severn
rivers, Plynlimon
Wales, UK N/A 2350 Pasture Picea sitchensis
(80%)
43–50 100 C–P Planting from
1937 to 1964;
1937 used to
calculate
plantation age
Dons (1986) Tarawera North Island, New Zealand 1500 Scrub and native
bush
Pine Average for
1–18
28 C–P MAP
estimated from
graph
Dons (1987) Purukohukohu North Island, New Zealand 381260S/1761130E 1550 Pasture P. radiata Average for
8–11
N/A C–P
Duncan (1995) C14 Moutere Gravel hill country,
Nelson, New Zealand
N/A 1020 Pasture P. radiata 1–21 N/A C–P
Fahey &
Jackson (1997)
Glendhu Waipori River, Otago, New
Zealand
451500S 1350 Tussock grassland P. radiata 9–12 67 C–P
Fahey &
Watson (1991)
Glendhu Waipori River, Otago, New
Zealand
451500S 1355 Tussock grassland P. radiata 1–8 67 C-P Catchment
was contour-
ripped to
60 cm depth
prior to
planting
Mwendera
(1994)
Luchelemu River Malawi 111450S/331500E 1300 Montane grass and
scrub
Pine and
eucalyptus
Mean 93 C-P Low flow only
Na
¨nni (1970) Cathedral Peak II Winterton, Natal Drakensberg,
South Africa
281000S/291150E 1660 Grassland P. patula 1–16 75 Supp Planting of CP
II began in
1951, but not
finished until
1961
Cathedral Peak III 1545 Grassland P. patula 1–8 81
Robinson
(1998)
Coalburn Northwest England N/A 1350 Grassland and bog Sitka spruce 24 N/A C–P
Robinson et al.
(1991)
FM/N Chiemseemoors, Germany 471480N/121260E 1440 Bog formerly used
for agriculture
Norway
spruce
4–25 N/A P–O
FM/S
Samraj et al.
(1988)
Glenmorgan,
Ootacamund
Nilgiri Plateau, South India 111280N/761370E 1535 Grassland and
woodland
E. globulus 1–10 59 P–O
Scott & Lesch
(1997)
Mokobulaan A Lydenburg, Mpumalanga,
South Africa
271170S/301340E 1135 Grassland E. grandis 1–17 100 Supp
Mokobulaan B 1170 Grassland P. patula 1–21 100
(Continued)
EFFECTS OF AFFORESTATION ON WATER YIELD 1575
r2005 Blackwell Publishing Ltd, Global Change Biology,11, 1565–1576
Table A1 (Con td.)
Source Name of site(s) Location Latitude/
longitude
MAP
(mm)
Original vegetation Plant species Plantation age
(years)
Percent
planted
Data
type
Notes
Scott et al.
(2000)
Westfalia D Tzaneen, Mpumalanga, South
Africa
231430S/301040E 1250 Scrub E. grandis 1–15 83 P–O Scrub forest
cleared before
planting
Mokobulaan A Lydenburg, Mpumalanga,
South Africa
271170S/301340E 1170 Grassland E. grandis 1–22 97
Mokobulaan B Winterton, Natal Drakensberg,
South Africa
281000S/291150E 1180 Grassland P. patula 1–20 95 Controlled
burn before
planting
Cathedral Peak II Jonkershoek, Western Cape,
South Africa
331570S/181150E 1400 Grassland P. patula 1–29 75
Cathedral Peak III 1515 Grassland P. patula 1–22 86
Bosboukloof 1125 Fynbos shrubland P. radiata 5–38 57
Biesievlei 1300 1–35 98
Tierkloof 1320
Lambrechtsbos B 1145 1–40 36
Lambrechtsbos A 1125 1–32 82
1–18 89
Sharda et al.
(1998)
Glenmorgan,
Ootacamund
Nilgiri Plateau, South India 111280N/761370E 1535 Grassland and
woodland
E. globulus 1–10 59 P–O Second
rotation
Smith (1987) Taieri River (Jura
Creek)
East Otago, South Island, New
Zealand
N/A 1000 Pasture P. radiata,P.
nigra
N/A N/A C–P Catchments
cleared of
native grasses
and shrubs,
planted with
pasture or pine
Smith (1992) Moutere Hills Nelson, New Zealand 411220S/1731040E 1050 Pasture (ryegrass) P. radiata 5–9 20 P–O
Smith & Scott
(1992)
Westfalia D Tzaneen, Mpumalanga, South
Africa
221430S/301040E 1600 Scrub E. grandis 1–8 83 P–O Low flow data
Mokobulaan A Lydenburg, Mpumalanga,
South Africa
241170S/301340E 1150 Grassland E. grandis 1–12 100
Mokobulaan B 1150 Grassland P. patula 1–11 95
Van Wyk
(1987)
Bosboukloof Jonkershoek, Western Cape,
South Africa
331570S/181150E 1300 Fynbos P. radiata 57 Supp
Biesievlei 1425 98
Tierkloof 1800 36
Lambrechtsbos B 1475 82
Lambrechtsbos A 1415 89
Data type refers to the way in which the data were used in the synthesis: data were either reported and used as predicted–observed runoff (P–O) or as control catchment–planted
catchment runoff (C–P); some data sets were only used for supplementary information (e.g. planted area, year of plantation, etc.) (Supp).
Plantation age refers to the range of plantation ages reported for a given catchment.
MAP, mean annual precipitation; N/A, not available.
1576 KATHLEEN A. FARLEY et al.
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