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Climate and potential habitat suitability for cultivation and in situ conservation of the black plum (Vitex doniana Sweet) in Benin, West Africa

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  • Laboratoire de Biomathématiques et d'Estimations Forestières (LABEF/FSA/UAC)

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Sustainable management actions are needed for several indigenous agro forestry plant species like the black plum (Vitex doniana Sweet) because they are facing increasing pressures due to the rapid human growth and threats such as climate change. By combining species distribution modelling using the Maximum Entropy Algorithm (MaxEnt) and representation gap analysis, this study accessed the impacts of current and future (2050) climates on the potential distribution of Vitex doniana in Benin with insight on the protected areas network (PAN). The model showed a high goodness-of-fit (AUC = 0.92 ± 0.02) and a very good predictive power (TSS = 0.72 ± 0.01). Our findings indicated annual mean rainfall, annual mean diurnal range of temperature and mean temperature of the driest quarter as the most important predictors driving the distribution of V. doniana. Under current climate, about 85 % of Benin area is potentially suitable for its cultivation. This potential suitable area is projected to increase by 3 to 12 % under future climatic conditions. A large proportion (76.28 %) of the national PAN was reported as potentially suitable for the conservation of the species under current climate with increase projections of 14 to 23 % under future climate. The study showed that V. doniana can be cultivated in several areas of Benin and that the PAN is potentially suitable for its conservation. These findings highlighted some of the opportunities of integrating V. doniana in the formal production systems of Benin and also its potentialities in ecosystems restoration under the changing climate.
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RESEARCH PAPER OPEN ACCESS
Climate and potential habitat suitability for cultivation and in
situ conservation of the black plum (
Vitex doniana
Sweet) in
Benin, West Africa
Achille Hounkpèvi*1,2, Félicien Tosso3,4, Dossou Sèblodo Judes Charlemagne
Gbèmavo1, Edouard Konan Kouassi5, Daouda Koné2, Romain Glèlè Kakaï1
1 Laboratoire de Biomathématiques et d’Estimations Forestières (LABEF), Faculté des Sciences
Agronomiques, Université d’Abomey-Calavi, Abomey-Calavi, Bénin
2 Graduate Research Program Climate change and Biodiversity, WASCAL, UFR Biosciences,
University Félix Houphouët-Boigny, Campus of Bingerville, Abidjan, Côte d’Ivoire
3 University of Liège, Gembloux Agro-Bio Tech., Terra & Biose, Forest Resources Management,
Tropical Forestry, Passage des Déportés, Gembloux, Belgium
4 Laboratoire d’Ecologie Appliquée (LEA), Faculté des Sciences Agronomiques, Université
d’Abomey-Calavi, Abomey-Calavi, Bénin
5 Laboratoire de Botanique, UFR Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte
d’Ivoire
Article published on April 22, 2016
Key words: Climatic envelope, MaxEnt, Species distribution modelling, Representation gap analysis, Vitex
doniana.
Abstract
Sustainable management actions are needed for several indigenous agro forestry plant species like the black plum (Vitex
doniana Sweet) because they are facing increasing pressures due to the rapid human growth and threats such as climate
change. By combining species distribution modelling using the Maximum Entropy Algorithm (Max Ent) and representation gap
analysis, this study accessed the impacts of current and future (2050) climates on the potential distribution of Vitex doniana in
Benin with insight on the protected areas network (PAN). The model showed a high goodness-of-fit (AUC = 0.92 ± 0.02) and a
very good predictive power (TSS = 0.72 ± 0.01). Our findings indicated annual mean rainfall, annual mean diurnal range of
temperature and mean temperature of the driest quarter as the most important predictors driving the distribution of V.
doniana. Under current climate, about 85 % of Benin area is potentially suitable for its cultivation. This potential suitable area
is projected to increase by 3 to 12 % under future climatic conditions. A large proportion (76.28 %) of the national PAN was
reported as potentially suitable for the conservation of the species under current climate with increase projections of 14 to 23 %
under future climate. The study showed that V. doniana can be cultivated in several areas of Benin and that the PAN is
potentially suitable for its conservation. These findings highlighted some of the opportunities of integrating V. doniana in the
formal production systems of Benin and also its potentialities in ecosystems restoration under the changing climate.
* Corresponding Author: Achille Hounkpèvi * hounkpeviachille@gmail.com
International Journal of Agronomy and Agricultural Research (IJAAR)
ISSN: 2223-7054 (Print) 2225-3610 (Online)
http://www.innspub.net
Vol. 8, No. 4, p. 67-80, 2016
International Journal of Agronomy and Agricultural Research (IJAAR)
ISSN: 2223-7054 (Print) 2225-3610 (Online)
http://www.innspub.net
Vol. 5, No. 1, p. 14-22, 2014
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Introduction
Indigenous agro forestry species, formerly considered
as less useful and underutilized products are
becoming nowadays important resources for many
food security policies mainly in developing countries
(Garrity, 2004, Oladélé, 2011). These species provide
several goods to local communities enhancing then
their capacity to face food shortage (Atato et al., 2011)
and to alleviate poverty (Akinnifesi et al., 2008,
Oladélé, 2011). Moreover, they provide several
ecosystem services and contribute to biodiversity
conservation (Vodouhè et al., 2011). Unfortunately,
most of these agroforestry species are overexploited
and threatened in their natural biotopes (Maundu et
al., 2006). In fact, habitat and population of these
species are facing increasing pressures due to the
rapid human population growth (Maundu et al.,
2006, Nacoulma et al., 2011, Haarmeyer et al., 2013,
Mensah et al., 2014) and this combined with climate
change add several uncertainties to their fitness and
survival (IPCC, 2007, FAO, 2012). This situation has
enhanced the need of developing sustainable
management, domestication and conservation
strategies for those species with a focus on climate
change.
Climate change, one of the biggest challenges for this
century, occurs mainly as alterations over time in
weather parameters such as temperature,
precipitation and wind, and changes in temperature
are the most considered facts (de Chazal and
Rounsevell, 2009). The implications of these change
are significant for the long-term stability of natural
ecosystems and for the many benefits and services
that humans take from them (Lucier et al., 2009).
Several impacts have been reported on biological
systems, with species extinction being the most
extreme and irreversible negative impact (Bellard et
al., 2012). In Africa for instance, more than 5,000
species might lose their natural habitat before 2080
(McClean et al., 2005). To avoid or reduce the
amplitude of those effects, biodiversity components
must produce adaptive responses which can be of
several time-dependent types (Parmesan, 2006,
Bellard et al., 2012). Whatever the adaptation
mechanism used, species responses to climate change
have been observed along three non-exclusive axes:
time (e.g. phenology), space (e.g. range) and self (e.g.
physiology), with the first two axes being the most
easily observable (Parmesan, 2006). In the spatial
point of view, through seed dispersal, plant species
track appropriate conditions and follow them by
shifting their geographical range in order to stay in
quasi-equilibrium with the climatic conditions they
are adapted to (Bellard et al., 2012). Evidences of
such geographical range shifting have been given by
several modelling studies and experimental trials on
species tolerance. These studies revealed significant
changes in the distribution of some species and
ecosystems, principally due to increasing temperature
and alteration of precipitation regimes (Walther et
al., 2002, Campbell et al., 2009).
In this context of a changing climate, assessing spatial
dynamics of suitable habitat of useful species is an
important steps towards their domestication and
integration into formal agricultural production
systems especially in developing countries where
rural population are still dependent on such resources
(Oladélé, 2011). Furthermore, this assessment is
relevant for in situ conservation planning strategies
taking into account the existing extensive protected
areas network. Despite the increasing literature on
climate change impacts on plant species distribution
and effectiveness of protected areas network in
conserving suitable habitat of native plant species
(Fandohan et al., 2013), little is known on how
climate could affect habitat suitability for cultivation
and conservation of several useful indigenous
agroforestry species such as the black plum.
The black plum (Vitex doniana Sweet) is one of these
very important indigenous agroforestry species
valued by local communities in many parts of Africa
and for which sustainable management and
domestication programs are required (Maundu et al.,
2009, Achigan-Dako et al., 2011, Mapongmetsem et
al., 2012). Beside its potential role in soil fertility
improvement by litter production (Mapongmetsem et
al., 2005), several parts of the species are used for
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food, medicine and other purposes (Dadjo et al.,
2012). It is known that its leaves are used as fodder
for livestock and the young leaves as leafy vegetables
in sauces preparation. The blackish pulp of its ripened
fruits is edible and used in preparation of some sweet
drinks. The wood is suitable for construction and fire
(Arbonnier, 2004, Ky, 2008, Orwa et al., 2009, Dadjo
et al., 2012). The mature leaves, the bark and the
roots have phytotherapeutic properties and are used
to heal several diseases (Iwueke et al., 2006, Kilani,
2006, Padmalatha et al., 2009). Given its socio-
economic importance, its integration into the formal
production systems could foster domestication
strategies and reduce anthropogenic pressures on its
natural populations. In addition, knowledge on its
conservation by protected areas is relevant for
designing strategies for plant genetic resources
management. It is therefore crucial to assess impacts
of climate on the species habitat in order to identify
suitable areas for its cultivation and conservation.
Thus, through species distribution modelling using
the Maximum Entropy Algorithm “MaxEnt” (Phillips
et al., 2006) and representation gap analysis, this
study aimed at assessing impacts of current and
future (2050) climates on V. doniana’s habitat
suitability for its cultivation and in situ conservation
in Benin. Specifically, it addressed the following
research questions: i) what are the bioclimatic
variables controlling V. doniana’s potential
distribution? ii) How will the species’ habitat
suitability change with climate? iii) How far the
national protected areas network might conserve the
species’ suitable habitat under current and future
climates?
Material and methods
Target species and study area
The black plum (Vitex doniana Sweet) is a deciduous
plant species occurring in tropical Africa from
Senegal to Somalia and to South Africa, also in
Comoros and Seychelles (Arbonnier, 2004, Ky,
2008). It was formerly classified in the Verbenaceae
family but based upon several phylogenetic studies, it
has been transferred to the Lamiaceae family
(Cantino et al., 1992, Harley et al., 2004). It colonises
various habitats from forests to savannahs, often in
wet localities and along rivers, and on termite
mounds, up to 2000 m altitude. It occurs in regions
with a mean annual rainfall between 750-2000 mm
and temperature ranging from 10 to 30°C (Arbonnier,
2004, Ky, 2008, Orwa et al., 2009). It has been
mentioned as naturally occurring in all the three
climatic zones of Benin (Assogbadjo et al., 2012).
Fig. 1. Climatic zones and protected areas network of
Benin.
The study was carried out in Benin republic (114,763
km2), located between 6°10’ and 12°50’ N and 1° and
3°40’ E in West Africa (Fig. 1). The country’s climatic
profile shows two contrasting climatic zones (Guinean
vs. Sudanian) and a transitional zone (Sudano-
Guinean). The Guinean zone (between 6°25’ and
7°30’ N) is characterised by a subequatorial climate
with four seasons (two rainy and two dry). The
rainfall of about 1200 mm per year is bimodal mostly
from March to July and September to November. The
temperature varies between 25 and 29 °C, and the
relative humidity varies between 69 % and 97 %. The
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Sudanian zone (9°45’ - 12°25’ N) has a tropical dry
climate with two equal length seasons (rainy and dry).
The mean annual rainfall in this zone is often less
than 1000 mm and occurs mainly from May to
September. The relative humidity varies from 18% to
99% and temperature from 24 to 31°C. The Sudano-
Guinean (from 7°30’ to 9°45’ N) is a transitional zone
with two rainy seasons merging in a unimodal regime.
The annual rainfall fluctuate between 900 and 1110
mm, the temperature is between 25 and 29°C and
relative humidity from 31 % to 98 % (Fandohan et al.,
2011, Gnanglè et al., 2011, Assogbadjo et al., 2012).
About 24 % of the country (approximately 27,310.47
km2) is legally protected by the national protected
areas network constituted of two parks (Pendjari in
the North-western part and W in the extreme
Northern part of the country, Fig. 1) and several
classified forests (IUCN and UNEP-WCMC, 2015).
Data collection
A total of 227 occurrence points (longitude and latitude)
were obtained from fieldwork in Benin and from the
Global Biodiversity Information Facility portal (GBIF,
2015) for the West African region (Fig. 2).
Fig. 2. Occurrence of V. doniana in West Africa
(Data source: GBIF and fieldwork).
Bioclimatic data for current (1950-2000) and
projections for 2050 were extracted from World Clim
(available at www.worldclim.org/bioclim), Version 1.4
database (Hijmans et al., 2005) at 2.5-minute grid
resolution (approximately 4.62 x 4.62 km2 in West
Africa). This database includes 19 bioclimatic
variables (Bio1 to Bio19) which are derived from
average minimum and maximum temperature and
rainfall data (Hijmans et al., 2005).
According to the future climate (2050), projections
from two models of the Coupled Model
Intercomparison Project phase 5 (CMIP5) were
preferred because of their commonness use and
satisfactory features for simulating the global climate
response to increasing greenhouse gas concentration
(Fandohan et al., 2015, McSweeney et al., 2015).
These models were the Met Office climate model
(HadGEM2-ES) and the Model for Interdisciplinary
Research on Climate Change (MIROC5). They were
considered under two of the four Representative
Concentration Pathway (RCP) developed by the
Intergovernmental Panel on Climate Change (IPCC)
in its Fifth Assessment Report: RCP 4.5 and RCP 8.5.
These RCP were preferred because they projected the
most divergent trends for the West African region
compared to the others (IPCC, 2013). With this
divergent trend (low vs. high emissions scenario), the
range of emissions uncertainty is well captured
(Harris et al., 2014). For instance, temperature is
projected to rise above industrial level by at least
1.4°C under RC 4.5 in West Africa by mid-21st
century, with atmospheric CO2 reaching 500 ppm and
by 2°C with atmospheric CO2 over 550 ppm under the
more drastic RCP 8.5 (IPCC, 2013).
The Protected Area Network (PAN) map of Benin was
obtained from the World Database on Protected
Areas (IUCN and UNEP-WCMC, 2015) and used to
assess the in situ conservation of the species in the
country under current and future climates.
Data analysis
The Maximum Entropy species distribution model
algorithm (MaxEnt, version 3.3.3k” Princeton
University, Princeton, New Jersey, USA) was used for
the habitat suitability modelling. This modelling tool
requiring presence-only data is one of the best-
performing algorithm among those using climate
modelling approaches (Phillips et al., 2006) and is
relatively robust for small sample sizes (Pearson et
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al., 2007). It is a machine learning method that
estimates species’ distribution across a study area by
calculating the probability distribution of maximum
entropy subject to the constraint that the expected
value of each feature under this estimated
distribution should match its empirical average
(Phillips et al., 2006). Although there are several
conceptual ambiguities and uncertainties about
bioclimatic envelope modelling (Schwartz, 2012),
MaxEnt remains an important modelling tool in
assessing potential impacts of climate change on
species distribution (Elith et al., 2011a).
During the modelling process, presence data were
cleaned up by removing duplicate records in grids in
order to reduce sampling bias which may result from
the over sampling of some sites in the study area
(Elith et al., 2006). Only the less-correlated (r < 0.85)
bioclimatic variables were selected with the
environmental niche modelling tools (ENMTs) and
used for the modelling (Elith et al., 2011b). During
these bioclimatic variables selection process, priority
was given to those reflecting water availability since
plants distribution in the study area is known to be
under the influence of mainly soil moisture, total
rainfall, air humidity and the length of the dry season
(Adomou et al., 2006). MaxEnt’s internal Jackknife
test was performed to assess the contribution of the
selected variables in the distribution of the species
(Pearson et al., 2007).
Twenty five percent (25%) of the occurrence points
was used for model testing and 75% for model
calibration in five replicates. The five replicates were
averaged through cross-validation. Two criteria were
used to evaluate the performance i.e. goodness-of-fit
and predictive power of the model: (i) the area under
the receiver operating characteristic curve (AUC) and
the true skill statistic (TSS) (Allouche et al., 2006,
Elith et al., 2006, Pearson et al., 2007). The AUC is
the probability that a randomly chosen presence point
of the species will be ranked as more suitable than a
randomly chosen absence point (Elith et al., 2006). A
model is considered as having a good fit when its AUC
is close to one (AUC ≥ 0.75) (Elith et al., 2006). The
TSS is the capacity of the model to accurately detect
true presences (sensitivity) and true absences
(specificity). A model with TSS 0 indicates a
random prediction, while a model with a TSS close to
1 (TSS > 0.5) has a good predictive power (Allouche et
al., 2006).
To capture the correct range of each bioclimatic
factor, we performed the modelling process using
occurrence and climatic data for the whole West
Africa. The outputs of MaxEnt were then clipped on
Benin, to mark out the study area. The potential
habitat suitability across the study area was assessed
based on the logistic probability distributions
generated by Ma x Ent using the 10 percentile
training presence logistic threshold. Thus, areas with
occurrence probability above the threshold value were
considered as suitable for the species and areas with
occurrence probability below the threshold value were
taken as unsuitable habitats (Scheldeman and van
Zonneveld, 2010, Fandohan et al., 2015).
Suitable/unsuitable habitats of the species under
current and future climates were mapped in ArcGIS
10.3 (ESRI, 2014).
Representation gap analysis was used to assess how
far the national protected areas network conserve the
species (Fandohan et al., 2013, Tantipisanuh et al.,
2016). For that, PAN of Benin was overlain on the
present and future habitat suitability maps and
proportions of suitable and unsuitable areas within
the PAN were estimated in ArcGIS 10.3 (ESRI, 2014).
Results
Bioclimatic variables importance and model
performance
Five of the 19 bioclimatic variables were selected as
less-correlated (r < 0.85) and used for the species
potential habitat modelling. Annual mean rainfall,
annual mean diurnal range of temperature and mean
temperature of the driest quarter were the most
important predictors driving the species’ distribution
(Table 1). These variables have significant effect on
the gain when used in isolation or removed from the
modelling process (Fig. 3). Annual mean rainfall was
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the most uniquely informative predictor because its
presence/absence in the model considerably affects
the gain; its contribution and permutation
importance were around 50 % (Table 1). The five
bioclimatic variables used for the modelling showed
significant variation (Wilcoxon signed-rank test, p-
value < 0.05) between current climate and future
projections with the most important changes reported
in the Sudanian and Sudano-Guinean zones (Table 2).
Annual mean rainfall, annual mean temperature and
mean temperature of the driest quarter were
projected to increase in all zones whatever the
climatic scenario. Meanwhile, precipitation of the
driest month is projected to significantly decrease in
the Guinean zone and to remain stable in the other
zones.
Table 1. Variables contribution and permutation
importance (%).
Varia-
bles
Definition
Contri-
bution
(%)
bio12
Annual mean rainfall
48.7
bio2
Annual mean diurnal
range of temperature
28.6
bio9
Mean temperature of
the driest quarter
15
bio1
Annual mean
temperature
5.4
bio14
Precipitation of the
driest month
2.3
Fig. 3. Jackknife of regularized training gain for V.
doniana.
Table 2. Current and future projections of selected bioclimatic variables in Benin (mean ± standard deviation).
Climatic
zones
Climate
Bio12
Bio2
Bio9
Bio1
Bio14
Guinean
Current
1136.92a ± 59.56
82.95a ± 15.54
279.91a ± 1.96
273.82a ± 2.34
9.49a ± 3.84
He4.5
1137.54a ± 59.24
79.11b ± 13.78
300.29b ± 3.00
293.11b ± 3.46
7.42b ± 2.49
He8.5
1135.98b± 61.53
78.92b ± 13.80
306.60b ± 3.58
299.10b ± 3.63
6.41b ± 2.35
Mi4.5
1231.52b ± 65.83
82.50b ± 14.89
297.10b ± 2.42
288.93b ± 2.46
7.08b ± 2.90
Mi8.5
1214.40b ± 61.77
79.94b ± 13.49
298.92b ± 3.06
290.82b ± 2.11
7.15b ± 2.91
Sudano-
Guinean
Current
1096.08a ± 51.52
121.36a ± 7.05
270.82a ± 4.22
269.80a ± 3.58
3.21a ± 1.24
He4.5
1149.18b ± 70.28
114.45b ± 8.57
295.06b ± 4.29
292.35b ± 3.65
3.23b ± 1.26
He8.5
1152.14b ± 75.71
113.31b ± 7.68
301.94b ± 3.99
299.01b ± 3.41
3.17b ± 1.17
Mi4.5
1201.67b ± 63.17
120.40b ± 7.45
290.18b ± 4.14
286.30b ± 2.79
2.28b ± 1.01
Mi8.5
1233.80b ± 73.76
115.69b ± 8.62
292.94b ± 2.78
289.03b ± 2.22
2.19b ± 0.96
Sudanian
Current
1054.32a ± 94.99
131.05a ± 1.97
268.49a ± 8.27
273.04a ± 6.64
0.20a ± 0.40
He4.5
1167.59b ± 78.19
128.66b ± 1.94
294.00b ± 6.95
295.52b ± 7.06
0.20a ± 0.40
He8.5
1190.36b ± 80.81
125.14b ± 1.78
301.27b ± 7.18
303.63b ± 7.26
0.20a ± 0.40
Mi4.5
1173.18b ± 98.35
131.53b ± 2.10
287.37b ± 9.20
291.70b ± 6.70
0.20a ± 0.40
Mi8.5
1206.60b ± 110.07
131.02a ± 2.44
294.92b ± 7.61
297.30b ± 6.89
0.20a ± 0.40
Values were extracted from Worldclim database
Version 1.4 at 2.5-minute grid resolution
(approximately 4.62 x 4.62 km2 in West Africa) based
on the occurrence points of V. doniana in Benin. In
each climatic zone, significant differences between
current and each future scenario are shown by letters
following mean values (Wilcoxon signed-rank test, p-
value < 0.05). He4.5 & He8.5: HadGEM2-ES under
respectively RCP 4.5 and 8.5. Mi4.5 & Mi8.5:
MIROC5 under respectively RCP 4.5 and 8.5. Bio12 =
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Annual mean rainfall (mm); Bio2 = Annual mean
diurnal range of temperature (10 x °C); Bio9 = Mean
temperature of the driest quarter (10 x °C); Bio1 =
Annual mean temperature (10 x °C); Bio14 =
Precipitation of the driest month (mm).
The model had a very goodness-of-fit (cross-validated
average AUC = 0.92 ± 0.02) and a very good
predictive power (TSS = 0.72 ± 0.01). The 10th
percentile training presence logistic threshold for the
habitat suitability discrimination was 0.22. Areas
with occurrence probability above this threshold were
then considered as suitable for the species, the
remaining been considered as unsuitable areas.
Fig. 4. Response curves of V. doniana to bioclimatic
predictors in the habitat suitability modelling.
Responses of V. doniana to the selected bioclimatic
predictors
Vitex doniana preferred areas with the annual mean
rainfall between 800 and 1200 mm (Fig. 4a).
Occurrence probability of the species was at its
highest level for annual mean diurnal range of
temperature around 6°C and decreased progressively
when the range increased up to 12°C. Areas with
diurnal range of temperature between 12.5 and 15°C
were also suitable for the species (Fig. 4b). Globally,
habitat suitability of the species increased with the
mean temperature of the driest quarter (Fig. 4c), but
it decreased with the annual mean temperature (Fig.
4d). Similarly, increases in the precipitation of the
driest month reduced the habitat suitability of V.
doniana (Fig. 4e).
Logistic output is the occurrence probability of V.
doniana. a- Annual mean rainfall (bio12, mm); b-
Annual mean diurnal range of temperature (bi o2,°C x
10); c- Mean temperature of driest quarter (bi o9,°C x
10); d- Annual mean temperature (bio1, °C x 10); e-
Precipitation of driest month (bio14, mm).
Suitable areas for cultivation of V. doniana in Benin
Under current climatic conditions, about 85 % (≈
98,005 km2) of Benin’s area was potentially suitable
for the cultivation of V. doniana (Table 3). This
suitable habitat consisted of two blocks: a southern
block and a northern block. The first block covered
the Guinean zone and the lower part of the Sudano-
Guinean zone; the second block included the upper
part of the Sudano-Guinean zone and the Sudanian
zone except its extreme northern part which is not
actually suitable for the species (Fig. 5a). The habitat
suitability was projected to increase by 3 to 12 %
(about 3,512 to 14,278 km2) under future climatic
conditions for the year 2050 (Table 3; Fig. 5b, c, d &
e). For instance, the extreme northern part of the
country will become suitable for the cultivation of the
species under all the considered future climatic
projections. For the RCP 4.5 projections, the increase
of the suitable habitat will be two times more
important for MIROC5 than for HadGEM2-ES.
Meanwhile, when considering RCP 8.5, the most
important increase of the suitable area will be noted
under Had GEM2-ES (Table 3).
Conservation of V. doniana by protected areas
network under current and future climate
Under current climate, about 76 % (≈ 20,832 km2) of
the national PAN was suitable for the conservation of
V. doniana (Table 3). Regarding the two national
parks, the major part of the W national park was not
currently suitable for the conservation of the species
(Fig. 5a). Future climate will slightly ameliorate the in
situ conservation of the species by the national PAN.
Indeed, the proportion of the conserved suitable
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habitat will increase under the future climatic
projections with HadGEM2-ES showing the greatest
variation (thus, +20.71 and +23.27 % for RCP 4.5 and
RCP 8.5 respectively). The most important change
will likely occur in the W National Park in the
Sudanian zone (Fig. 5).
Table 3. Dynamic of suitable areas for cultivation and conservation of V. doniana
Climate
Cultivation
Conservation by PAN
Area (Km2)
Area
(%)
Variation
(%)
Area (Km2)
Area
(%)
Current
98,005.21
85.40
-
20,832.46
76.28
RCP 4.5
HadGEM2-ES
103,522.26
90.21
+4.81
26,487.87
96.99
MIROC5
108,502.07
94.54
+9.15
25,603.57
93.75
RCP 8.5
HadGEM2-ES
112,283.42
97.84
+12.44
27,187.08
99.55
MIROC5
101,517.94
88.46
+3.06
24,760.40
90.66
Fig. 5. Potential suitability maps for cultivation and
conservation of V. doniana under current and future
climate in Benin.
a. Current climatic conditions; b. Future projection
according to HadGEM2-ES under RCP 4.5; c. Future
projections HadGEM2-ES under RCP 8.5; d. Future
projections with MIROC5 under RCP 4.5 and e.
Future projections according to MIROC5 under RCP
8.5.
Discussion
Species potential distribution is driven by biotic and
abiotic factors with climate playing a determinant role
(Walther, 2003, Adomou et al., 2006, Sommer et al.,
2010). There are evidences that change in climate will
affect distribution of several species (IPCC, 2007,
Busby et al., 2010). Species distribution modelling
(SDM) are widely used to determine habitat
suitability patterns at large spatial scales and to
produce spatially explicit and comprehensive maps
that are particularly useful for identifying areas where
conservation efforts are most needed or effective.
Generally, these SDM techniques taking into account
information on habitat requirements derived from
known occurrence sites are widely used to predict
potential habitat of species under current or possible
future conditions. Even if these models can not
indicate the realised niche, they provide relevant
habitat suitability information for a given species and
can guide sustainable management plans (Phillips et
al., 2006, Sommer et al., 2010, Schwartz, 2012). This
information on the derived distribution map are
useful in identifying suitable areas for cultivation and
assessing conservation status of target species by
protected areas network (Schwartz, 2012, Fandohan
et al., 2013, Tantipisanuh et al., 2016).
Here, Maximum entropy algorithm (Ma x Ent), one of
the most used SDM techniques, was used to assess
habitat suitability for cultivation and in situ
conservation of V. doniana by PAN under current and
future (2050) climatic conditions. The future climatic
conditions considered were the projections of the Met
Office climate model (Had GEM2-ES) and the Model
for Interdisciplinary Research on Climate Change
(MIROC5) under RCP 4.5 and RCP 8.5. These
climatic models projected significant changes in the
Int. J. Agri. Agri. R.
Hounkpèvi et al.
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75
study area (Table 2). by mid-21st century (Hijmans et
al., 2005, IPCC, 2013).
Findings indicated annual mean rainfall, annual
mean diurnal range of temperature and mean
temperature of the driest quarter as the most
important predictors driving the distribution of V.
doniana (Table 1). Among these predictors, mean
annual rainfall showed the greatest contribution
confirming the importance of water availability in
plants distribution (Adomou et al., 2006). The
ecological optimum of the species regarding this
climatic predictor is from 800 to 1200 mm (Fig. 4a),
and it is effectively within the range of 750-2000 mm
indicated by the literature (Arbonnier, 2004, Ky,
2008, Orwa et al., 2009). Regarding temperature
factor, it is mainly annual mean diurnal range of
temperature and mean temperature of the driest
quarter that mostly controlled the species distribution
(Table 1).
Following our findings, approximately 85% of Benin’s
area is potentially suitable for the cultivation of V.
doniana and about 76% of the national PAN is
suitable for its conservation. Significant increases
were projected under future climatic (2050) scenarios
with several currently unsuitable areas becoming
suitable under all the climatic models mainly in the
Sudanian and Sudano-Guinean zones. This increase
in habitat suitability can be explained by the
significant changes projected for the bioclimatic
parameters in 2050 (Table 2). Indeed, according to
the climatic models used in this study, the extreme
northern part of the country (annual mean rainfall
mostly below 700 mm) are projected to become
wetter with annual rainfall reaching 900 mm
(Hijmans et al., 2005). These changes in the rainfall
will likely make the areas suitable for V. doniana
since its ecological optimum is between 750 and 2000
mm/year (Arbonnier, 2004, Ky, 2008, Orwa et al.,
2009). The high plasticity of the species in habitat
selection also support our findings (Arbonnier, 2004,
Ky, 2008, Orwa et al., 2009).
Although models in both RCP showed similar
increasing trend of the habitat suitability for
cultivation and conservation of the species, some
particularities were noted. For instance, the most
important variations were noted under the projection
of the drastic scenario i.e. RCP 8.5 (Table 3). This
climatic scenario is more likely than the second
because even though important mitigation actions are
being undertaken, the Earth’s climate system will still
be facing the ‘committed warming’ (Harris et al.,
2014). However, because of the important
uncertainties regarding the climatic models (Harris et
al., 2014), one should be cautious regarding these
projections.
Even though habitat suitability for cultivation and
conservation of V. doniana are projected to have
significant increases in the country, its productivity
under future climate might be affected either
positively or negatively. In fact, the species may have
undergone several physiological adaptations in
response to past climates, but under the current rapid
climate change, the expansion of the species in new
areas will likely require important energy-dependant
adjustments in morphological, physiological or
behavioural traits of the species and this could have
negative impacts on its productivity (Challinor et al.,
2006). Long term studies are then required on the
physiology, phenology and productivity of the species
through its climatic range in order to build a
consistent database for the sustainable management
of the species under the changing climate.
Conclusion and implications of the study
Findings of this study suggested that Vitex doniana, a
key agroforestry species for local communities in
tropical Africa can be cultivated in a wide range of
areas in Benin. Moreover, the national protected
areas network offered a large extent of favourable
areas for its in situ conservation. With the apparently
positive impact of future climate on its habitat
suitability, V. doniana can be considered as a good
candidate for ecological restoration of degraded
ecosystems with regard to challenges like climate
change.
Int. J. Agri. Agri. R.
Hounkpèvi et al.
Page
76
Conflict of interest
No conflicts of interest to declare.
Acknowledgements
Authors thank the German Government, particularly
the Federal Ministry of Education and Research
(BMBF) for their financial support to AH through a
PhD scholarship and a research budget allowance.
They also grateful to Enoch Bessah for language
editing.
Abbreviations
AUC: Area under the receiver operating characteristic
curve
CMIP5: Coupled Model Intercomparison Project
phase 5
ENMTs: Environmental niche modelling tools
GBIF: Global Biodiversity Information Facility
HadGEM2-ES: Met Office climate model
IPCC: Intergovernmental Panel on Climate Change
MaxEnt: Maximum Entropy
MIROC5: Model for Interdisciplinary Research on
Climate Change
PAN: Protected Area Network
RCP: Representative Concentration Pathway
SDM: Species distribution modelling
TSS: True skill statistic
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... R.Br. ex G.Don (Dotchamou et al., 2016), and Vitex donania Sweet (Hounkpèvi et al., 2016). On the other hand, despite this growing literature, some threatened species do not benefit from effective conservation strategies. ...
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Afzelia africana Sm – a multipurpose leguminous tree species – is threatened in West Africa – a climate change hotspot region. Yet, although the impacts of land use on this species dynamics have been widely reported, there is a little literature on the impacts of climate change on its spatial distribution. This study aimed to predict the impacts of climate change on the geographic distribution of A. africana in Burkina Faso. A total of 4,066 records of A. africana was compiled from personal fieldwork and vegetation database. Current and future bioclimatic variables were obtained from WorldClim website. For future climatic projections, six global climate models (GCMs) were selected under two emission scenarios (RCP 4.5 & RCP 8.5) and two horizons (2050 & 2070). Presence data and bioclimatic variables were processed in ArcGIS software and used in the algorithm MaxEnt (maximum of entropy) to predict the species distribution. Findings showed that maximum temperature of warmest month and mean temperature of coldest quarter mostly affect the habitat suitability of A. africana. About 25.54% of Burkina Faso land surface was currently suitable for A. africana conservation. Under future climatic projections, all the climate models predict climate-driven habitat loss of the species with a southward range shift. Across the two emission scenarios, the spatial extent of suitable habitats was predicted to decline from 9.43 to 23.99% and from 12.29 to 25% by the horizons 2050 and 2070, respectively. Habitat loss and range shifts predicted in this study underline the high vulnerability of A. africana to future climate change. Reforestation actions and the protection of predicted suitable habitats are recommended to sustain the species conservation.
... Sensitivity and specificity of the model was assessed using area under curve (AUC). When, the AUC value of a model is (AUC ≥ 0.75), such models are said to accurately predict the spatial and temporal occurrence of species ( Idohou et al., 2016 ;Hounkpèvi et al., 2016 ). The capacity of the models to predict true presence and true absence was further validated with true skill statistic (TSS) ( Elith et al., 2006 ;Pearson et al., 2007 ). ...
... The logistic probability distributions generated by MaxEnt using the 10th percentile training presence logistic threshold were used to assess the potential habitat suitability of the species in Nigeria. Suitability of occurrence was based on areas above the threshold, whereas areas below the threshold were considered not suitable ( Hounkpèvi et al., 2016 ;Scheldeman and van Zonneveld, 2010 ). Map production for habitat suitability and unsuitability was done in ArcGIS 10.3 ( ESRI, 2014 ). ...
... Modelling species distribution have been used extensively to ascertain suitable habitat and large scales cultivation, to produce maps that will be useful for identifying areas where conservation efforts can be successful. Previous works ( Hounkpèvi et al., 2016 ;Sommer et al., 2010 ;Walther, 2003 ) had reported the potential role of biotic and abiotic factors for species distribution modelling and habitat suitability patterns. IPCC (2007) gave evidences that change in climatic conditions will significantly influences the distribution of several species. ...
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Garcinia kola is an indigenous multipurpose tree species, with significant cultural value and medical benefits, commonly found in the tropical rain forest zone of West and Central Africa. The species has been reported to be over-used and are now classified as vulnerable species close to commercial extinction. Hence, requires immediate conservation action. This study assessed the impact of climate on habitat for cultivation of G. kola in Nigeria. Ecological niche modelling approach was used to estimate the current geographical range and predicts the future distribution of G. kola in Nigeria, using the nineteen (19) bioclimatic environment layers at a 30 arc seconds resolution. Two climate models were used (HadGEM2-ES and CNRM-CM5) with two Representative Concentration Pathways (RCP), RCP 4.5 and RCP 8.5 scenarios as predictor variables for projections of the potential geographical range of this species for 2050 horizon. Results revealed that about 397,094 km² area, corresponding to 43.6 % of Nigeria land surface, are currently suitable for cultivating G. kola. The future projections showed a significant decrease in area suitable for propagating G. kola under the RCP scenarios used in the two climate models. HadGEM2-ES predicts 27.2 and 26.1 % loss of suitable habitats under RCP 4.5 and 8.5, respectively, by 2050 while CNRM-CM5 projects 26.7 and 35.8 % decrease for the corresponding RCPs. Furthermore, the HadGEM2-ES predicts that 149,365 and 159,384 km² corresponding to 16.4 % and 17.5 % of total land area will be suitable for cultivation of G. kola in Nigeria under RCP 4.5 and 8.5, respectively. The model results showed that climate change would have significant influence on the future suitable habitat of G. kola in Nigeria and the species is more subservient in moist, humid area and some part of derived savanna zone in Nigeria. The results underscore the significant influences of climate change on the ecology of G. kola. Based on these results, immediate action should be initiated to conserve this valued species and secure their inherent agro-ecosystems services
... To date, priority setting for the domestication of indigenous fruit trees in the region has been done mostly on three fronts: (i) climate change and habitat suitability, e.g., [124,160,400,413]; ...
... For instance, black plum (Vitex doniana) is a highly valued multipurpose tree in Benin. Currently, the species can potentially be cultivated in about 85% of the country, but this area is expected to increase by 3-12% under future climatic conditions [413]. In contrast, nearly 51% of Burkina Faso is presently suitable for the cultivation of V. paradoxa, and that the area may decline by 13% by 2070 [124]. ...
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This paper follows the transition from ethnobotany to a deeper scientific understanding of the food and medicinal properties of African agroforestry tree products as inputs into the start of domestication activities. It progresses on to the integration of these indigenous trees as new crops within diversified farming systems for multiple social, economic and environmental benefits. From its advent in the 1990s, the domestication of indigenous food and non-food tree species has become a global programme with a strong African focus. This review of progress in the third decade is restricted to progress in Africa, where multi-disciplinary research on over 59 species has been reported in 759 research papers in 318 science publications by scientists from over 833 research teams in 70 countries around the world (532 in Africa). The review spans 23 research topics presenting the recent research literature for tree species of high priority across the continent, as well as that in each of the four main ecological regions: the humid zone of West and Central Africa; the Sahel and North Africa; the East African highlands and drylands; and the woody savannas of Southern Africa. The main areas of growth have been the nutritional/medicinal value of non-timber forest products; the evaluation of the state of natural resources and their importance to local people; and the characterization of useful traits. However, the testing of putative cultivars; the implementation of participatory principles; the protection of traditional knowledge and intellectual property rights; and the selection of elite trees and ideotypes remain under-researched. To the probable detriment of the upscaling and impact in tropical agriculture, there has been, at the international level, a move away from decentralized, community-based tree domestication towards a laboratory-based, centralized approach. However, the rapid uptake of research by university departments and national agricultural research centres in Africa indicates a recognition of the importance of the indigenous crops for both the livelihoods of rural communities and the revitalization and enhanced outputs from agriculture in Africa, especially in West Africa. Thus, on a continental scale, there has been an uptake of research with policy relevance for the integration of indigenous trees in agroecosystems and their importance for the attainment of the UN Sustainable Development Goals. To progress this in the fourth decade, there will need to be a dedicated Centre in Africa to test and develop cultivars of indigenous crops. Finally, this review underpins a holistic approach to mitigating climate change, as well as other big global issues such as hunger, poverty and loss of wildlife habitat by reaping the benefits, or ‘profits’, from investment in the five forms of Capital, described as ‘land maxing’. However, policy and decision makers are not yet recognizing the potential for holistic and transformational adoption of these new indigenous food crop opportunities for African agriculture. Is ‘political will’ the missing sixth capital for sustainable development?
... The reduction of nearly 57.1% (scenario RCP 2.4), 57.2% (scenario RCP 4.5) and 60.2% (scenario RCP 8.5%) in the predictive power of the observed model when the variables studied are permuted justify their determining roles in the prediction of the spatio-temporal dynamics of the sorghum growing areas. Indeed, these variables act in direct symbiosis on the plants and constitute the major climatic parameters in plant ecology and are determinant for the prediction of the spatio-temporal dynamics of species production areas (Dossou et al., 2016;Hounkpêvi et al., 2016;Fandohan et al., 2015;Soufiyanou et al., 2019). The current climatic conditions (scenario RCP 2.5) indicate that the production areas in the East and West of the Sudanian region are and will remain completely suitable for the cultivation of Sorghum bicolor by 2050. ...
... In the same line, future increases in temperature would significantly reduce suitable habitats of baobab tree by 41 to 100% in Ethiopia (Birthane et al., 2020). In the contrary, future climate conditions are likely to increase the potential suitable area of V. doniana by 3 to 12% in Benin (Hounkpèvi et al., 2016). Likewise, Fandohan et al. (2013) revealed that increase in rainfall is likely to convert some currently highly suitable zones of Tamarindus indica (semi-arid and sub-humid dry) into poorly suitable areas at horizon 2050, in Benin. ...
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This study assessed the vulnerability of five indigenous agroforestry trees to climate change: Adansonia. digitata, Vitellaria paradoxa, Parkia biglobosa, Tamarindus indica, and Vitex doniana, using the vulnerability of rural communities that rely on these species as a proxy. An integrated assessment approach, encompassing exposure, sensitivity, and adaptive capacity was adopted. Individual questionnaires were administered to 340 farmers, across seven Local Government Areas (LGA): Bosso, Rafi, Lavun, Lapai, Mashegu, Kontagora, and Borgu in Niger State. Data were collected on farmers’ perceptions about species vulnerability to climate change. The vulnerability index was computed based on nineteen indicators. Trend analysis of rainfall and temperature dataset over 40 years, indicated on one side no trend of annual rainfall, but a significant increase of annual temperature on the other side, supported by high intra-annual variability. Although observed variabilities in the climate were confined within the known tolerance limits of these species, reduction in productivity was the most reported impact (58.21% of the respondents). A change in species’ distribution, progressive extirpation, premature fructification, and tree mortality were also mentioned among the impacts of climate change. V. doniana was perceived to be the most vulnerable by 68.75% of the respondents followed by A. digitata, while V. paradoxa and T. indica seemed not to be vulnerable to climate change according to 48.65% and 27.00% of the respondents, respectively. There was a spatial variability of species vulnerability. The study concluded that the cultural importance of the species influences the extent to which the species are perceived to be vulnerable to climate change. This conclusion draws more attention toward the promotion of sustainable use and conservation of indigenous tree species to reduce their vulnerability to future climate conditions.
... Hypsipyla robusta will face upon 2055, a severe regression of its areas of distribution. Hounkpèvi et al. (2016) found that climate changes will make ...
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Khaya senegalensis Desr & Juss and Garcinia kola Heckel are two medicinal forest trees species that provide as well lots of meaningful Non Timber Forest Products as Forest Timber Products. Those two species are undergoing many threats including climate change and forest pest attack. In order to provide forest resources managers and planted forest promoters with forest pest prevention means, forest species restoration and conservation strategies, this study was aimed at assessing the vulnerability of Khaya senegalensis to climate change and to the invasion of Hypsipyla robusta Moore in Benin over time and space; and analyzing how far climate changes can help to restore and conserve Garcinia kola, an extinct species in the wild in Benin. To this end, MaxEnt approach for Ecological Niche Modelling was used to compute suitable areas for target species under current, and future climates (RCP 4.5 and RCP 8.5 of AfriClim Ensemble mean,). Biodiversity presence data were gathered on the database of the Global Biodiversity Information Facility (GBIF). Gap analysis and Spatio-temporal Analysis were performed using Geographic Information System Tools. In the case of K. senegalensis, projections at horizon 2055 from AfriClim Ensemble mean showed that it can occur in the future with some areas left out and some gained. The loss was assessed at 15-16% of Benin superficies while the gain was 2-3% of the country’s total area. As for Hypsipyla robusta, climate change will provide only habitat loss of about 66% of the country’s total area. So, some plantation sites being currently exposed to biological attack from the pest could no more exist in the future, giving hope for Khaya senegalensis’ high quality wood production. Meanwhile, there will be an ecological imbalance due to the drastic potential habitat loss for the insect. It is worth that future investigations focus on the economics of attacks in plantations. As for Garcinia kola, results revealed that climate change proved to have only positive consequences on its distribution. Considering the High Confidence Projection Areas (HCPA), the percentage of municipalities predicted suitable for the species is far above the percentage of Protected Areas Network (PAN) predicted as such (7.44% versus 0.93%). RCP4.5 and RCP8.5 of AfriClim Ensemble mean indicated respectively 3.00% and 6.27% of PAN as positive climate change impact zones, predicted respectively 13.60% and 17.60% of the total municipalities’ areas as such. Therefore, it is worth relying not only on PAN but also and mainly on urban forestry and reforestation to restore and conserve the species. Further studies focusing on the introduction of Garcinia kola in urban areas, and its use for reforestation are compulsory. Key Words: Khaya senegalensis, Hypsipyla robusta, Garcinia kola, Ecological niche Modelling, Forest pest outbreak, Climate change.
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Quercus infectoria and Quercus libani are two important species distributed across most of the Kurdistan Region of Iraq's mountain ranges (KRI). They have significant ecological, medicinal, and socioeconomic values. Recent studies have documented how plant distributions have been impacted by climate change. This study's goal is to establish the existing distributions of both species, measure the consequences of prospective environmental conditions on their distributions, predict possible habitat distributions, map the overlapped habitat ranges for the species in the KRI, and identify the key factors influencing their distributions. For these aims, distribution data points of the species, different environmental factors, including the existing climate, three emission predictions for the 2050s, 2070s, and 2090s of two general circulation models (GCMs), a machine learning approach, and geospatial techniques were used. Modeling revealed that the total magnitude of the habitat increase for the species would be less than the overall magnitude of the habitat contraction. The yearly mean temperature, yearly precipitation, and minimum temperature during the coldest period mostly alter the target species' geographic dispersion. Across the three emission scenarios of the both models, Q. infectoria habitat would contract by 2760.9–2856.9 km² (5.36–5.55%), 2856.9–3357.2 km² (5.55–6.52%) and 2822.1–3400.2 km² (5.48–6.60%), whereas it would expand by 1153.3–1638.9 km² (2.24–3.18%), 761.0–1556.8 km² (1.48–3.02%), and 721.5–1547.1 km² (1.40–3.00%) for the 2050s, 2070s, and 2090s, respectively. A similar pattern was also noted for Q. libani. The two species' habitat ranges in KRI would be considerably reduced due to climate change. The species' estimated area would extend mostly to the east and southeast of the KRI at high altitudes. The mountain areas, notably those where the species overlap by 1767.2–1807.5 km² (3.43–3.51%) for the two GCMs, must be the primary objective of conservation efforts. This research presents new baseline data for future research on mountain forest ecosystems and the techniques of biodiversity conservation to reduce climate change's effects in Iraq.
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