_Jibrin and Abdulhamed BEST published journal 2016

Jibrin et al., (2016)
Biological and Environmental Sciences Journal for the Tropics 13(1) June, 2016 ISSN 0794 – 9057
ECOLOGICAL VULNERABILITY ASSESSMENT OF KPASHIMI FOREST
RESERVE AND SURROUNDING PARKLAND AREA IN NIGER STATE,
NIGERIA
Jibrin A.1
*, Abdulhamed A. I.1
and Abdulkadir A. 2
1
Department of Geography, Ahmadu Bello University, Zaria, NIGERIA
2
Department of Geography, Federal University of Technology, Minna, NIGERIA
*Correspondence: Jibrin, A. Tel: +234-803-697-8420. E-mail: abdullahi717@hotmail.com
ABSTRACT
The weight of scientific evidence indicates that forest ecosystems are highly vulnerable to climate
change. However, there is little understanding on the implications of climate change for woodland
ecological functioning in the developing countries such as Nigeria. The aim of the study was to
examine the ecological vulnerability of Kpashimi forest reserve to climate change. The study employed
the IPCC Vulnerability Index (IPCC-VI) based on the exposure, sensitivity and adaptive capacity levels
of the ecosystem. Data were obtained through ecological Survey (ES) and Participatory Rural
Appraisal (PRA) with active participation of the nine forest dependent communities surrounding
Kpashimi forest reserve. The results were obtained using composite index; generated by aggregating
the indicators. The findings revealed that Kpashimi forest reserve and the surrounding parkland is
vulnerable to climate change impacts due to higher index values of exposure (0.387) and sensitivity
(0.397) above the adaptive capacity index value (0.356). It also shows that the overall IPCC-VI
yielded 0.012 values which indicates moderately vulnerable situation of the forest reserve ecosystem
to the adverse effect of climate change. By implication, the forest reserve is highly sensitive and more
exposed to climate change impacts than its capacity to adapt to the impact. Consequently, ecological
threshold may soon be exceeded and ecological resilience undermined. The study thus recommends
diversification and extension of protected areas for the conservation of ecosystems that are most
vulnerable to climate change. It also recommends reformation of existing vegetation management
activities so as to maximize climate change mitigation and adaptation opportunities.
Keywords: forest ecosystem, vulnerability, exposure, sensitivity, adaptive capacity,
INTRODUCTION
There is overwhelming scientific consensus that climate
change is currently having ecological, social and
economic impacts at local, national, regional and global
scales. Over the coming decades, the impact on
ecosystems is likely to become more severe
(Intergovernmental Panel on Climate Change-IPCC,
2007a). Like many other developing countries, Nigeria’s
forest and savannah ecosystems are highly vulnerable
to the impacts of climate change and climate variability
(Odjugo, 2005; Adefolalu et al., 2007; and Ayuba et al.,
2007). While details are still lacking, it is expected that
the effects of any significant change in climate would
shift the boundaries of major ecological zones of the
country as well as have tremendous impact on the
wildlife they support (Federal Republic of Nigeria -FRN
2003). These conditions together with the country’s
ecological diversity and enormous environmental
problems (United Nations Environment Programme –
UNEP, 2008) make the requirement for mitigation and
adaptation quite considerable. Yet, according to FRN
(2003), the potentials to support adaptation and
mitigation measures is yet to be fully realized due to
low level of information on the actual ecological
vulnerability of ecosystems in Nigeria.
Forest ecosystems provide many provisioning,
supportive, regulating and cultural services that are
indispensable for human subsistence and development
(Millenium Ecosystem Assessment- MEA, 2005). Their
ability to continue to provide these services and other
functions is mostly determined by climatic conditions
and human interference. Consequently, the growth,
survival, regeneration and productivity of the forest
ecosystems are climate dependent (Brovkin, 2002).
According to FRN (2003), climate change will affect
forestry through higher temperatures, elevated Co2
concentration, precipitation changes, increased weeds,
pests and disease pressure, and increased vulnerability
of organic carbon pools. To deal with current and future
limitations posed by these changes on forest
ecosystems, assessments of ecosystem vulnerability are
crucial for identifying adaptation needs and for avoiding
the worst possible consequences of climate change, for
both human and natural systems. They are also needed
for detecting locations and ecosystems, in which
investments in adaptation and ecosystem management
can produce the biggest returns.
Ecological vulnerability assessment is a risk
assessment process that evaluates the likelihood that
adverse ecological effects may occur or have occurred
as a result of exposure to one or more stressors
(Environmental Protection Agency –EPA, 1992).
B E S T JO U R N A L
BEST JOURNAL 13(1): 182 - 191
Date received: 12/04/2016
Date accepted: 5/06/2016
Printed in Nigeria
182

An ecological risk assessment commonly evaluates the
potential adverse effects that human activities have on
the plants and animals that make up ecosystems, and
has developed, in recent years as an alternative
assessment paradigm (EPA, 1992; Suter, 1993). Some
investigators conceptualized ecological vulnerability as a
function of exposure, sensitivity, and adaptive capacity
(Eakin and Luers, 2006; Gallop´ın, 2006). The definition
is valuable as it embraces its own characters for
ecosystem that is, experiencing internal or external
system disturbance (MaCarthy et al., 2001), the ability
of a system to adjust its behavior and characteristics in
order to enhance its capacity versus external stress
(Brook, 2003), and the establishing principle of
ecological vulnerability index system (David, Andrew
and Lindsay, 2012). The assessment of ecological
vulnerability is progressively important as it enables one
to ascertain the potential problem and to stimulate eco-
environment protection (Ying et al., 2007).
There are many attempts to define
vulnerability in relation to climate change. Vulnerability
is defined as ‘the propensity of human and ecological
systems to suffer harm and their ability to respond to
stresses imposed as a result of climate change effects’
(Adger et al., 2007). The IPCC (2007b) defines
vulnerability to climate change as a function of three
elements: exposure, sensitivity, and adaptive capacity
(Adger, 2006; Reed et al., 2013). Exposure refers to the
extent to which a community is exposed to climate-
related events; sensitivity refers to the extent to which
the community is affected by the exposure; and
adaptive capacity is the ability of the community to
withstand or recover from the effects of the exposure.
The combination of these three elements determines
the extent to which an individual or group, a physical or
social system is vulnerable to climate change and has
been used extensively in assessing climate change
vulnerability (Cinner et al., 2012; Shah et al., 2013).
Resilience is closely linked with the concept of
vulnerability. Resilience is the ability to return to a
steady state following a perturbation (Tilman and
Downing, 1994; Tilman, 1996). While Gunderson (2000)
defined ecological resilience as the amount of
disturbance that an ecosystem could withstand without
changing self-organized processes and structures.
IPCC (2007a) Fourth Assessment Report gave
the most acceptable definition of climate change, which
states that “climate change is a change in the state of
the climate that can be identified (eg. by using
statistical tests) by changes in the mean and/or the
variability of its properties, and that persists for an
extended period typically decades or longer”. The
climate of Nigeria has shown considerable temporal and
spatial shifts in its variability and change since the late
1960s and early 1970s through a careful study of
meteorological data (FRN, 2003; Nigerian
Meteorological Agency, 2012). Specifically, Odjugo,
(2005); Adefolalu et al., (2007); and Ayuba et al., 2007)
have shown that Nigeria is already being plagued with
diverse ecological problems, which have been directly
linked to the on-going climate change. These studies
focused more on climatic impacts. Most available data
on climate change are mainly global whereas the
effects are more at local levels. Jibrin (2009; 2013; and
2014; Jibrin et al., 2013) studied deforestation and
forest degradation in the Kpashimi forest reserve.
However, reliable information is lacking on the
ecological vulnerability of the forest reserve; while it is
exposed to climate change stressors. The aim of the
study is to examine the ecological vulnerability of
Kpashimi forest reserve to climate change. The
objectives of the study were to: determine the degree
of exposure, sensitivity and adaptive capacity of
Kpashimi forest reserve and surrounding parkland area
in Niger state.
MATERIALS AND METHODS
Study area
Kpashimi Forest Reserve is located between latitude 8o
40′ to 8o
52′ North and longitude 6o
39′ to 6o
49′ East
covering approximately 213.101 kilometres square
(Figure 1). The study area is characterized by
alternating wet and dry season climate coded as ‘Aw’ by
Koppen’s classification. The mean annual rainfall is
about 1,400 mm with mean annual temperature of
about 28o
C (Ojo, 1977). The geology of the study area
is made up of cretaceous sedimentary rocks underlain
by the Precambrian basement complex rocks
(FORMECU, 1994). The topography is gently
undulating. Soils in the study area based on the CCTA
(Commission de Cooperation Technique en Afrique)
classification system belong to ferruginous tropical soils.
In some depressional areas, and valley bottom positions
hydromorphic soils are found; while those around the
inselbergs and other residual hills, and at the bed of
rivers, are weakly developed (Areola, 1978; Jaiyeoba
and Essoka, 2006). The study area lies within the
southern Guinea savannah; classified as woodland
savannah vegetation with the understory dominated by
annual grasses (Keay, 1953; Jaiyeoba and Essoka,
2006).
183

Figure 1: Relief and Drainage system of Kpashimi forest reserve.
Methods
Ecological Survey (ES) and Participatory Rural Appraisal
(PRA) techniques were adopted for the study with
active participation of the nine forest dependent
communities surrounding Kpashimi forest reserve.
Forest dependent people are defined by DFID (2000) as
those that use forest as a source of water, fuel wood,
shelter and a broad suite of non-timber forest products
(medicinal plants, culinary herbs, fodder, rattans, gums,
resins, latex and oils). Structured questionnaire was
used. Using the formula of Yamane (1967), the study
area with an estimated population of about 30,000,
yielded the sample size of 395. Each of the nine
communities was considered as a cluster and an equal
number of 44 copies of a questionnaire was
administered randomly in the communities comprising
of Nassarawa, Fapo, Gulu, Lafian Kpada, Makeri, Kunko,
Lafian zago, Zago, and Mayaki. Analysis of survey data
used a 5-point likert scale statistical technique, with
categories as follows: (5 = very high, 4 = high, 3 =
moderate, 2 = low and 1 = very low.
The IPCC-IV vulnerability assessment
framework was employed in this study based on three
components of exposure, sensitivity, and adaptive
capacity. Each of these components of vulnerability
consists of a series of indicative conditions. The data for
the indicators was normalized to bring consistency
using the formula eq. (1) or eq. (2). For each
component a value was obtained by combining the data
for the indicators under it using the formula eq. (3).
184

Biological and Environmental Sciences Journal for the Tropics 13(1), June, 2016 ISSN 0794 – 9057
…………………………………………………………………….……………………………….. eq.(1)
…………………………………………………………………………………………… eq.(2)
…………………………………………………………………………………………………………eq.(3)
Where:
Xij= normalized score for observed values of positively
related indicators
Yij= normalized score for observed values of negatively
related indicators
Min= minimum indicator value
Max= maximum indicator value
VI= Component Vulnerability index
K= indicators
The aggregate final vulnerability index for the study
area was calculated using the formula (eq. 4). Scaling is
done from -1 to +1 indicating low to high vulnerability.
………
………………………eq.(4)
Where:
IPCC-VI= IPCC Vulnerability Index
Eindex = Exposure index
ACindex = Adaptive Capacity index
Sindex = Sensitivity index
RESULTS AND DISCUSSION
The indicator framework for vulnerability assessment
employed in this study is presented in Table 1. The
table indicates the values for each of the measured
indicators, the respective component values and the
aggregate IPCC-VI value.
Exposure: The exposure component encompasses two
broad elements – aspects of the system of interest that
are likely to be affected by climate change and the
changes in the climate itself. The types and magnitude
of exposure to climate change impacts was measured
using a total of 16 indicators (see table 1). Figure 2
indicates that increasing temperature, erratic rainfall
pattern uncertainty in the onset and end of rainy
season are the major indicator variables that make the
area more vulnerable to climate change. The recent
scenario analysis for temperature and rainfall for the
study area by FRN (2003) indicates that there will be a
decrease in rainfall for the region in the first four
months of the year (January – April) with increase in
temperature conditions of between 3o
to 5o
for the rest
of the 21st century. Therefore, reduction in plant cover
and productivity may be an obvious response of the
forest reserve to any drying trends. If climate factor
such as temperature and precipitation change in a
region beyond the tolerance of a species phenotypic
plasticity the distribution changes of the species may be
inevitable (Lynch and Lande, 1993). There is already
strong evidence that plant species are shifting their
ranges in altitude and latitude as a response to
changing regional climates (Parmesan and Yohe, 2003).
The effect of temperature changes is likely to be larger
and more important than any other factor (Kehlenbeck
and Schrader, 2007). In turn, changes in vegetation
composition may have significant effects on the local
heat balance while extreme temperatures can be
harmful when beyond the physiological limits of plant.
185

Table 1: The Vulnerability indicator assessment results
Note: F.R.= Functional Relationship ; + = Positive functional relationship; - = Negative functional relationship
Component S.
No
Indicator F.R. Indicator
Index
Component
Index
EXPOSURE
1 Delay in rainy season onset + 0.418
0.387
2 Decreasing amount of annual rainfall + 0.181
3 Erratic rainfall pattern + 0.842
4 Heavy and long periods of rainfall + 0.172
5 Early rains followed by dry weeks + 0.574
6 Uncertainty in the onset and end of rainy season + 0.712
7 Increasing length of dry season + 0.301
8 Increasing incidence of drought + 0.010
9 Increasing temperature + 0.971
10 Increasing thunderstorm and strong winds + 0.220
11 Overflowing of stream and river in the rainy season + 0.435
12 Increasing cases of flooding incidence + 0.441
13 Increasing rate of soil erosion + 0.327
14 Decrease in soil moisture + 0.052
15 Unpredictability of rainfall + 0.522
16 Occurrence of Heat waves + 0.018
ADAPTIVE
CAPACITY
1 Restriction on logging and lumbering - 0.741
0.356
2 Agroforestry practices - 0.681
3 Afforestation - 0.302
4 Reforestation - 0.675
5 Watershed management - 0.19
6 Selective tree cutting - 0.391
7 Planting trees for shade - 0.503
8 Use of energy saving stove - 0.024
9 Use of local drip irrigation - 0.69
10 Avoidance of bush burning - 0.241
11 Increasing fallow period - 0.331
12 Incentives for conservation - 0.017
13 Erosion control measures - 0.102
14 Use of resistant varieties of plant species. - 0.097
SENSITIVITY
1 Reduced vegetation cover by living plants + 1.000
0.397
2 Reduced ground cover by litter and plant residues + 0.311
3 Decline in species diversity + 0.418
4 Decline in plant life form composition + 0.271
5 Increase in undesirable plant species (weeds) + 0.190
6 Reduced tree density + 0.851
7 Reduced plant vigor and biomass production + 0.256
8 Increase in invasive species/loss of native species + 0.134
9 Reduced forage production. + 0.657
10 Increase in relative area of bush and shrubs + 0.226
11 Increased plant mortality + 0.118
12 Reduced natural regrowth + 0.632
13 Pest and disease infestation + 0.210
14 Soil compaction + 0.083
15 Change of color of leaves + 0.616
16 The grasses dries up faster + 0.473
17 Drying up of streams and rivers + 0.309
IPCC-Vulnerability Index 0.012
186

0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Indicatorindexvalue
Exposure Indicator serial number
Fig. 2: Magnitude of Indicator values for Exposure component
Adaptive capacity: Adaptive capacity denotes the
capacity to cope up with the changes and adapt to
changing conditions. A total of 14 indicators (see table
1) were used to determine the coping or adaptive
capacity of the Kpashimi forest reserve and surrounding
parkland to threatening climate change impacts. Figure
3 reveals that restriction on logging and lumbering, use
of local drip irrigation and agroforestry practices have
the stronger shock absorbers to resist perturbations
that may result from climate change impacts. The low
level of incentives for conservation as indicated in the
fig. 3 would significantly increase the vulnerability of
the ecosystem. In ecological resilience, resilience is
conceptualized as the capacity to absorb shocks while
continuing to function (Adger, 2000; Peterson, 2000).
When change occurs, resilience provides the
components for renewal and reorganization (Gunderson
and Holling, 2002; Berkes et al., 2002). This implies
that the less resilient the system, the lower the capacity
to adapt to and adjust to changes. When a system
improves its resilience, its vulnerability decreases. When
it loses resilience it becomes more vulnerable. The
narrative stems from ecology, where the loss of a
functional component or group in an ecosystem will
severely affect the capacity of the system to reorganize
after a disturbance. Consequently, certain species,
communities, and ecosystems may not be particularly
resilient to the increases in stress or changes in habitat,
and they may be subjected to severe declines in
abundance or may be lost entirely from the landscape.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
1 2 3 4 5 6 7 8 9 10 11 12 13 14
IndicatorIndexvalue
Adaptive Capacity Indicator serial number
Fig. 3: Magnitude of Indicator values for Adaptive capacity component
Sensitivity: Sensitivity reflects the degree of response to
a given shift in climate. The sensitivity of the Kpashimi
forest reserve and surrounding parkland to the amount
of exposure to climate change impacts was measured
using 17 indicators (see table 1). Figure 4 shows that
reduced vegetation cover by living plants, reduced tree
density, and reduced forage production are the most
obvious feedback responses due to climate change
impact. Studies of natural, managed, and disturbed or
impacted ecosystems have shown that ecosystems
under stress appear to keep more of their functional
performance than their species composition (Holling et
al., 1995), as processes are buffered by species
redundancy. Thus, species composition appears more
sensitive than ecosystem processes since it responds
more quickly and recovers more slowly (Angermeir and
Karr, 1994).
187

Changes in species composition may also significantly
alter ecosystem performances (Naeem et al., 1994), like
the resilience of ecosystems to several sources of
disturbance. Forest ecosystems are highly sensitive to
changes in precipitation (Hilbert et al., 2001; Hughen et
al., 2004). There is evidence of change in the onset and
cessation of the rainy season, as well as the intensity
and duration of rainfall events in all parts of Nigeria
(Nigerian Environmental Study/Action Team -NEST,
2003). These changes can affect the physiological and
migratory pattern of some species. According to
Malcolm et al. (2006), changes in the precipitation
pattern affect the structure and function of forest
ecosystems and ecological interactions among species.
0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
IndicatorIndexvalue
Sensitivity Indicator serial number
Fig. 4: Magnitude of Indicator values for Sensitivity component
The results of the major component calculations are
presented collectively in figure 5 illustrating a
vulnerability triangle, which plots the contributing factor
scores for exposure, adaptive capacity and sensitivity. It
shows that Kpashimi forest reserve and surrounding
parkland is vulnerable to climate change impacts due to
higher values of exposure (0.387) and sensitivity
(0.397) above the adaptive capacity value (0.356) (see
table 1). This shows that the study area is considerably
sensitive and exposed to climate variability, extremes,
and their consequences while the adaptive capacity at
which it can cope with or adjust to climate change
impacts is low
.
0.387
0.356
0.397
0.330
0.340
0.350
0.360
0.370
0.380
0.390
0.400
EXPOSURE
ADAPTIVE
CAPACITY
SENSITIVITY
Fig.5: Vulnerability triangle diagram of the contributing factors of the IPCC-VI for Kpashimi forest
reserve and surrounding parkland area
It is noteworthy that the overall IPCC-Vulnerability
Index (ranges between -1 to +1) is 0.012 (see table 1)
which denotes moderately vulnerable condition. The
IPCC-VI becoming positive means the ecosystem is
more exposed to climate extremes and variability than
its capacity to adapt or overcome those adverse
situations. In fact, but for the protected area status of
the forest reserve, the ecosystem would be highly
vulnerable to climate change impacts.
188

Although organisms and the ecosystems can adapt
autonomously, the ability of the ecosystem to
autonomously respond to climate change is inherently
limited. Therefore, in addition to autonomous
adaptation, there must also be planned adaptation and
adoption of adaptation strategies.
CONCLUSION/RECOMMENDATIONS
The findings from this study revealed that over the last
few years, there has been more climatic variability due
to uncertain precipitation pattern and increasing
temperature. Consequently, the ecosystem of Kpashimi
forest reserve and surrounding parkland area is
moderately vulnerable to the impact of climate change.
This is because the exposure and sensitivity levels are
very high whereas the adaptive capacity level is low.
Consequently, ecological threshold may soon be
exceeded and ecological resilience undermined. The
findings from this study provide baseline information for
future studies on climate change impact on the
ecosystem of the study area. The analysis presented
above provide a broad indication of current level of
vulnerability of the Kpashimi forest reserve and
surrounding parkland area; due to climate stressors.
Drawing on the above analysis, the following measures
are recommended:
i. Diversification and extension of protected
areas for the conservation of ecosystems that
are most vulnerable to climate change and sea
level rise;
ii. Maintaining ecological structure and processes
at all levels and reducing existing pressure on
natural ecosystems;
iii. Monitoring to evaluate species and ecosystems
stability from climate change perspective.
iv. Reformation of existing vegetation
management activities so as to maximize
climate change mitigation and adaptation
opportunities.
v. Further, priority must be placed on assessing
future climate conditions which impact the
most vulnerable species so that current and
future management actions can be most
effectively targeted.
REFERENCES
Adefolalu D.O.A. (2007). Climate change and economic
sustainability in Nigeria. Paper presented at
the International conference on climate
change, Nnamdi Azikiwe University, Awka 12-
14 June 2007.
Adger W. N. (2000). Social and Ecological Resilience:
Are They Related? Progress in Human
Geography 24, 347-364
Adger, W. N. (2006). Vulnerability. Global
Environmental Change 16, 268-81
Adger, W.N., Agrawala, S., Mirza, M.M.Q., Conde, C.,
O’Brien, K., Pulhin, J., Pulwarty, R., Smit, B.,
Takahashi, K. (2007) Assessment of
Adaptation Practices, Options, Constraints
and Capacity. In: Parry, M.L., Canziani, O. F.,
Palutikof, J. P., van der Linden, P. J.,
Hanson, C. E. (eds), Climate Change 2007:
Impacts, Adaptation and Vulnerability.
Contribution of Working Group II to the
Fourth Assessment Report of the
Intergovernmental Panel on Climate Change.
Cambridge University Press, Cambridge, UK,
717-743
Angermeir, P.L., and Karr, J.R. (1994). Biological
integrity versus biological diversity as policy
directives: protecting biotic resources. In:
Bioscience 44: 690-697
Areola, O. (1978). Soil and vegetation resources of
Nigeria. In Oguntoyinbo et al. (Eds.), A
geography of Nigerian development.
Heinemann Education Books Nigeria Limited.
Ayuba, H.K., Maryah, U.M., Gwary, D.M. (2007).
Climate change impact on plant species
composition in six semi-arid rangelands of
Northern Nigeria. Nigerian Geographical
Journal 5(1): 35-42.
Berkes, F., Colding, J., Folke, C. (2002) Navigating
Social-Ecological Systems: Building Resilience
for Complexity and Change. Cambridge
University Press, Cambridge.
Brook, N. (2003). Vulnerability, risk and adaptation: a
conceptual framework. Working Paper 38,
Tyndall Centre for Climate Change Research,
University of East Anglia, Norwich, UK.
Brovkin, V. (2002). Climate-vegetation interaction.
Journal of Physics. 12:57-72.
Cinner, J., McClanahan, T., Graham, N., Daw, T., Maina,
J., Stead, S.(2012). Vulnerability of coastal
communities to key impacts of climate
change on coral reef fisheries. Global
Environmental Change , 22, 12–20.
David, J.A., Andrew, J.D. and Lindsay, C.S. (2012.)
Using principal component analysis for
information-rich socio-ecological vulnerability
mapping in Southern Africa. Applied
Geography, vol. 35, no. 1-2, pp. 515–524.
Department for International Development -DFID
(2000). Numbers of Forest Dependent
People: A Feasibility Study DFID's Forestry
Research Programme.
Eakin, H. and Luers, A. L. (2006.) Assessing the
vulnerability of social environmental systems.
Annual Review of Environment and
Resources, vol. 31, pp. 365–394.
Environmental Protection Agency, U.S. (1992).
Framework for ecological risk assessment.
Washington, DC: Risk Assessment Forum,
U.S. Environmental Protection Agency.
EPA/630/R- 92/001
Federal Republic of Nigeria-FRN (2003). Nigeria’s first
national communication under the United
Nations Framework Convention on Climate
Change. The Ministry of Environment of the
Federal Republic of Nigeria.
189

Forest Management Evaluation and Co-ordinating Unit -
FORMECU (1994). World Bank/Government
of Nigeria Forestry III project Vol. VI
Environmental Assessment, Forest
Management Component, kpashimi Forest
Reserve, Final Draft.
Gallop´ın, G. C. (2006.). Linkages between
vulnerability, resilience, and adaptive
capacity. Global Environmental Change, vol.
16, no. 3, pp. 293–303.
Gunderson, L. H., Holling, C. S. (2002). Panarchy:
Understanding Transformations in Human
and Natural Systems. Island Press,
Washington, DC, USA
Gunderson, L.H. (2000). Ecological Resilience in Theory
and Application. Annual Review of Ecology
and Systematics 31: 425-439.
Hilbert, D.W., Ostendorf, B. & Hopkins, M.S. (2001).
Sensitivity of tropical forests to climate
change in the humid tropics of north
Queensland. Austral Ecology, 26, 590- 603.
Holling, C.S., Schindler, D.W, Walker, B.H., and
Roughgarden, J. (1995). Biodiversity in the
functioning of ecosystems: an ecological
primer and synthesis. In: C.A. Perrings, K.G.
Maler, C. Folke, C.S. Holling and B.O.
Jansson (eds.): Biodiversity loss: ecological
and economic issues. Cambridge University
Press, Cambridge, England, 44-83.
Hughen, P.E., Eglinton,T.I., Xu, L.& Makou, M. (2004).
Abrupt Tropical vegetation response to rapid
climate changes. Science 304, 1955-1959.
Intergovernmental Panel on Climate –IPCC (2007a).
Climate change 2007. The fourth assessment
report (AR4). Synthesis report for
policymakers http: //
www.ipcc.ch/pdf/assessment
report/ar4/syr/ar4_ syr_spm.pdf. (Access
10th August, 2009).
Intergovernmental Panel on Climate -IPCC. (2007b).
Climate change 2007: Impacts, adaptation
and vulnerability. In M. L. Parry, O. F.
Canziani, J. P. Palutikof, P. J. van der Linden
& C. E. Hanson (Eds.), Contribution of
Working Group II to the Fourth Assessment
Report of the Intergovernmental Panel on
Climate Change (p. 976). Cambridge, UK:
Cambridge University Press.
Jaiyeoba, I. A., and Essoka, P. E. (2006). Soils and
Vegetation. The Middle Niger River Basin: A
field course hand book. Department of
Geography, Ahmadu Bello University, Zaria.
Jibrin, A., Isyaku U., Garba S. and Aminu Z. (2013).
Importance of Indigenous Knowledge in
Biodiversity Conservation: A Case Study of
Communities Surrounding Kpashimi Forest
Reserve, Niger State, Nigeria. Journal Of
Environmental Science, Toxicology And Food
Technology (IOSR-JESTFT), International
Organisation of Scientific Research,
Ghaziabad. Volume 5, Issue 6, Pp 10-
17Doi: 10.9790/2402-0561017
Jibrin, A. (2013). A Study of Variation in Physiognomic
Characteristics of Guinea Savanna
Vegetation, In: Environment and Natural
Resources Research Canadian Center of
Science and Education, Toronto 3(2), 52–60.
doi:10.5539/enrr.v3n2p52
Jibrin, A. (2014). Assessment Of Vegetation Cover
Dynamics In The Kpashimi Forest Reserve,
Niger State, Nigeria. Zaria Geographer,
Department of Geography, Ahmadu Bello
University, Zaria. Volume 21 (1) Pp 119- 131
Jibrin, A. (2009). An Assessment of the Pattern of and
Changes in the Vegetation Cover of Kpashimi
Forest Reserve, Niger State. An unpublished
M.Sc. Research thesis, Department of
Geography, Ahmadu Bello University, Zaria.
Keay, R.W. J. (1953). An outline of Nigerian Vegetation.
2nd ed. Lagos: Government Printed.
Kehlenbeck, H. and Schrader, G., (2007). Climate
Change, Happy future for plant pests? Ln:
Secretariat of the convention on Biological
Diversity, 2007. Emerging Issues for
Biodiversity Conservation in a Changing
Climate. CBD Technical Series No. 29,
Montreal, Canada.
Lynch, M. and Lande, R. (1993). Evolution and
extinction in response to environmental
change. In Huey, Raymond B.; Kareiva, Peter
M.; Kingsolver, Joel G. Biotic Interactions and
Global Change. Sunderland, Mass: Sinauer
Associates. pp. 234—50.
MaCarthy, J.J., Canziani, O.F., Leary, N.A., Dokken,
D.J. and White, K.S. (2001). Climate Change
2001: Impact, Adaptation, and Vulnerability,
Cambridge University Press, Cambridge. UK.
Malcolm, J.R., Liu, C, R.P. Hansen, L., and Hannah, L.
(2006). Global warming and extinction of
endemic species from biodiversity hotspots.
Conservation Biology, 20(2), 538-548.
Millenium Ecosystem Assessment- MEA (2005).
Ecosystems and human well-being:
Synthesis. Washington D.C., Island press.
Naeem, S., Thompson, L.J., Lawler, S.L., Lawton, J.H.,
and Woodfin, R.M. (1994). Declining
biodiversity can alter the performance of
ecosystems. In: Nature 368: 734-737
190

Nigerian Environmental Study/Action Team-NEST.
(2003). Climate Change in Nigeria. A
Communication Guide for Reporters and
Educators. Ibadan: NEST pp. 5-16.
Nigerian Meteorological Agency. (2012). Introduction.
2012 Nigeria Climate Review (pp. 6-7).
Nigerian Meteorological Agency (NIMET),
Abuja.
Odjugo, P.A.O., (2005). An analysis of rainfall pattern in
Nigeria. Global Journal of Environmental
Science, 4(2): 139-145.
Ojo, O. (1977). The climates of West Africa. London:
Heinemann.
Parmesan, C. and Yohe, G. (2003). A globally coherent
fingerprint of climate change impacts across
natural systems Nature, 421 (6918): 37-42.
Peterson, G. (2000). Political Ecology and Ecological
Resilience: An Integration of Human and
Ecological Dynamics. Ecological Economics
35(3), 323–336
Reed, M. S., Podesta, G., Fazey, I., Geeson, N., Hessel,
R., Hubacek, K. (2013). Combining analytical
frameworks to assess livelihood vulnerability
to climate change and analyse adaptation
options. Ecological Economics , 94, 66-77.
Shah, K. U., Dulal, H. B., Johnson, C., & Baptiste, A.
(2013). Understanding livelihood vulnerability
to climate change: Applying the livelihood
vulnerability index in Trinidad and Tobago.
Geoforum , 47, 125–137.
Suter, G.W. (1993): Ecological Risk Assessment. Lewis
Publishers, Boca Raton, Fl.
Tilman, D. & Downing, J.A. (1994). Biodiversity and
Stability in Grasslands. Nature 367: 363 365.
Tilman, D. (1996). Biodiversity: Population versus
Ecosystem Stability. Ecology 77: 350-363
United Nations Environment Programme –UNEP (2008).
Africa: Atlas of our changing environment.
United Nations Environment Programme.
ProgressPress Inc. p. 374.
Yamane, T. (1967). Statistics: An Introductory Analysis,
2nd Ed., New York: Harper and Row.
Ying, X., Zeng, G.M., Chen, G.Q., Tang, L. Wang, K.
L. and Huang, D. Y. (2007). Combining AHP
with GIS in synthetic evaluation of eco-
environment quality—a case study of Hunan
Province, China, Ecological Modelling, vol.
209, no. 2–4, pp. 97–109.
191

_Jibrin and Abdulhamed BEST published journal 2016

Recomendados

Recomendados

Más contenido relacionado

La actualidad más candente

La actualidad más candente (20)

Destacado

Destacado (15)

Similar a _Jibrin and Abdulhamed BEST published journal 2016

Similar a _Jibrin and Abdulhamed BEST published journal 2016 (20)

_Jibrin and Abdulhamed BEST published journal 2016