Journal of Atmospheric Science Research | Vol.5, Iss.1 January 2022

Alexander Kokhanovsky, Germany
Fan Ping, China
Svetlana Vasilivna Budnik, Ukraine
S. M. Robaa, Egypt
Daniel Andrade Schuch, Brazil
Nicolay Nikolayevich Zavalishin, Russian Federation
Isidro A. Pérez, Spain
Lucille Joanna Borlaza, France
Che Abd Rahim Bin Mohamed, Malaysia
Mengqian Lu, China
Sheikh Nawaz Ali, India
ShenMing Fu, China
Nathaniel Emeka Urama, Nigeria
Thi Hien To, Vietnam
Prabodha Kumar Pradhan, India
Tianxing Wang, China
Zhengqiang Li, China
Haider Abbas Khwaja, United States
Kuang Yu Chang, United States
Wen Zhou, China
Mohamed El-Amine Slimani, Algeria
Xiaodong Tang, China
Perihan Kurt-Karakus, Turkey
Anning Huang, China
Olusegun Folarin Jonah, United States
Pallav Purohit, Austria
Pardeep Pall, Canada
Service Opare, Canada
Donglian Sun, United States
Jian Peng, United Kingdom
Vladislav Vladimirovich Demyanov, Russian Federation
Chuanfeng Zhao, China
Jingsong Li, China
Suleiman Alsweiss, United States
Ranis Nail Ibragimov, United States
Raj Kamal Singh, United States
Lei Zhong, China
Chenghai Wang, China
Lichuan Wu, Sweden
Naveen Shahi, South Africa
Hassan Hashemi, Iran
David Onojiede Edokpa, Nigeria
Maheswaran Rathinasamy, India
Zhen Li, United Kingdom
Anjani Kumar, India
Netrananda Sahu, India
Aisulu Tursunova, Kazakhstan
Hirdan Katarina de Medeiros Costa, Brazil
Masoud Rostami, Germany
Editor-in-Chief
Dr. Qiang Zhang
Beijing Normal University, China
Dr. José Francisco Oliveira Júnior
Federal University of Alagoas (UFAL), Maceió, Alagoas, Brazil
Dr. Jianhui Bai
Institute of Atmospheric Physics, Chinese Academy of Sciences, China
Editorial Board Members

Dr. Qiang Zhang
Dr. José Francisco Oliveira Júnior
Dr. Jianhui Bai
Editor-in-Chief
Journal of
Atmospheric Science
Research
Volume 3 Issue 3· July 2020 · ISSN 2630-5119 (Online)
Volume 5 Issue 1 • • ISSN 2630-5119 (Onli
January 2022

Volume 5 ｜ Issue 1 ｜ January 2022 ｜ Page1-53
Journal of Atmospheric Science Research
Contents
Articles
1 GIS & Remote Sensing Based Morphometric Parameters and Topographic Changes of the Lower Orashi
River in Niger Delta
Desmond Eteh Edirin Akpofure Solomon Otobo
11 Reasons for Modern Warming: Hypotheses and Facts
Nikolai Nikolaevich Zavalishin
18 A Preliminary Exploration of the Functional Value Assessment of Ecosystem Services in Aral City
Guona Luo Xiancan Li Shuang Liu Muhang Li Shuya Zhang
34 Advanced Method for Forecasting and Warning of Severe Convective Weather and Local-scale Hazards
V. Spiridonov N. Sladić B. Jakimovski M. Ćurić
Review
25 Agroforestry for Climate Change Adaptation, Resilience Enhancement and Vulnerability Attenuation in
Smallholder Farming Systems in Cameroon
Nyong Princely Awazi

1
Journal of Atmospheric Science Research | Volume 05 | Issue 01 | January 2022
https://ojs.bilpublishing.com/index.php/jasr
Copyright © 2021 by the author(s). Published by Bilingual Publishing Co. This is an open access article under the Creative Commons
Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License. (https://creativecommons.org/licenses/by-nc/4.0/).
https://orcid.org/0000-0003-0660-6743
*Corresponding Author:
Desmond Eteh,
Department of Geology, Niger Delta University, Wilberforce Island, Bayelsa State, Nigeria;
Email: desmondeteh@gmail.com
DOI: https://doi.org/10.30564/jasr.v5i1.3873
ARTICLE
GIS & Remote Sensing Based Morphometric Parameters and
Topographic Changes of the Lower Orashi River in Niger Delta
Desmond Eteh*
● Edirin Akpofure Solomon Otobo
Department of Geology, Niger Delta University, Wilberforce Island, Bayelsa State, Nigeria
ARTICLE INFO ABSTRACT
Article history
Received: 25 October 2021
Accepted: 24 November 2021
Published: 13 December 2021
In watershed hydrology, the morphometric features of a river basin are vital
to examine the lower Orashi River basin morphological and hydrological
aspects, as well as its flood potential, based on their morphometric
characteristics using remotely sensed SRTM data that was analyzed with
ArcGIS software. The areal, linear, and relief aspects of the Orashi River
basin were examined as morphometric parameters. The lower Orashi
river basin, according to the findings, has a total size of 625.61 km2
and a
perimeter of 307.98 km, with a 5th order river network based on Strahler
categorization and a dendritic drainage pattern. Because of low drainage
density, the drainage texture is very fine, the relief is low, and the slope is
very low. Bifurcation ratio, circularity ratio, drainage density aspect ratio,
form factor, and stream frequency values indicate that the basin is less
elongated and would produce surface runoff for a longer period, while
topographic changes show that the river is decreasing with depth in the land
area at about the same elevation as a result of sand deposited due to lack of
maintenance by dredging, which implies that the basin is morphometrically
elevated and sensitive to erosion and flooding. To understand geo-
hydrological features and to plan and manage watersheds, morphometric
analysis based on geographic information systems and remote sensing
techniques is beneficial.
Keywords:
Morphometric analysis
Topographic changes
Hydrology
Flood
GIS
1. Introduction
The quantitative assessment and measurement of
a landform's shape, surface, and extent is known as
morphometrics [1]
. In most case, an extensive watershed
development plan begins with a thorough morphometry
understanding of the streams or drainage basins.
Modelling various hydrological processes of a river or
canal basin relies heavily on geomorphological attributes
or qualities of a stream or river basin. Traditionally,
morphometric analysis entails determining the length of
streams, the bifurcation ratio, and the stream density per
unit drainage area, as well as the difference in elevation,
perimeter, and drainage basin area. The drainage basin or
watershed is viewed as a basic tool in the examination of
some parts of the hydrological cycle and can likewise be

2
portrayed as an open framework [2]
. The morphometric
research of the drainage basin and channel network serves
an important role in comprehending the drainage basin
geo-hydrological vital function and expresses the climate,
geology, geomorphology, and structural conditions.
Consequential environmental impacts such as flooding,
erosion, etc. have been detected and monitored using
remote sensing and geographic information system (GIS)
technologies [3]
. This study focuses on the morphometric
evaluation of the Lower Orashi River to comprehend
the drainage basins by assessing their morphometric
values, which incorporate the state of the morphometric
framework including the shape of the basin, the length of
the stream, the area, the stream order, the length of stream
segments, bifurcation ratio, density of drainage, and
frequency. Furthermore, to join the geomorphologic and
hydrological characteristics of the drainage basins.
2. Materials and Methods
2.1 Study Area and Geology
The lower Orsahi River, which flows through
Ahoada West LGA in Rivers State, Nigeria, is subjected
to investigation, and the area is fast becoming one
of the increasing urban centers in Nigeria's South-
South geopolitical region. Communities sounding the
area are Jorkarima 1,2,3,4, Akinima, Mbiama, Ushie,
Akiogbologbo, Okarki, Ikodi, Ogbogoro in Ahoade West
Local Government Area, Rivers State. in addition, the
area is accessible by roads and the river and lies between
longitude 0060
20’0 and 0060
40'0 "East and latitude 040
50’0" and 050
10’10" North in the Niger Delta (Figure 1),
with altitude below sea level on the region 39 m further
inland [4]
. The average rainfall and temperature of the area
are 2,899 mm and 26.7°C [3]
. Several settlements in the
area are close to hydrocarbon flow stations owned by the
SPDC and NAOC, and the area is drained by tributaries
that connect to the lower Orashi River [5]
geologically
described the research area as the south-western flank
of the Niger Delta Region. The Niger Delta Basin was
formed when the South American plate separated from
the African plate and a failed rift (Aulacogen) junction
developed. The rifting in the basin began in the late
Jurassic and ended in the mid-Cretaceous epoch. There
are several thrust faults that arise. The delta has a land
area of more than 105,000 km2 [6]
.
Figure 1. Location of Study Area

3
2.2 Data Source
The United States Geological Survey (USGS) earth
explorer [7]
provided the Shuttle Radar Topography
Mission (SRTM) data, and administrative shape file.
2.3 Data Processing
The utilization of ArcGIS software and Arc hydro
extension tools were to process the Digital Elevation
Model data, by keeping the setting on projected
coordinate system using WGS UTM zone N32, which
depicts to process for spatial variation of elevation values
at every geographic point/location within the area, we first
use the Arc hydro tools to process the Digital Elevation
Model image. It makes it possible to analyse and delineate
drainage basin parameters derived from elevation
information. The Strahler's method of stream ordering was
used to obtain drainage basin morphometric parameters
and stream order characteristics from the digitized data [8]
.
3. Results and Discussion
The Evaluation Parameter for Morphometric according
to Clarke [9]
, is the measurement and mathematical analysis
of the earth's surface configuration, including the shape and
dimensions of its landforms. Measurements of the basin
linear, areal, and relief aspects, as well as slope contribution,
are used in the morphometric analysis [10]
. Presented below.
3.1 Linear Morphometric
This means that the drainage network's channel patterns
follow the stream segments' morphological characteristics,
and the analysis is based on the stream network open
linkages such as Stream Order, Stream Number, Stream
Length, Bifurcation Ratio.
3.1.1 Stream order (U)
Stream order analysis has been established as a measure
of a stream's location in the hierarchy of tributaries [11]
.
The lowest fingertip tributaries are categorized as first
stream order, according to Strahler [8]
. A second stream
order is generated when two first stream orders meet; a
third-stream order is formed when two second stream
orders meet, and so on. The Orash River has up to 5th
order tributaries, according to Table 1, with 1st, 2nd, 3rd,
4th, and 5th streams depicted in Figure 3 and Table 1.
Table 1. Morphometric Characteristics for catchment area
(Linear)
Stream
Order
Stream No
(Nu)
Stream Length
(Lu)
Mean Stream Length
(MLu)
1st Order 5432 810.73 0.15
2nd Order 742 273.82 0.37
3rd Order 232 113.31 0.49
4th Order 87 43.37 0.50
5th Order 28 12.63 0.45
∑Nu= 6521 ∑LU = 1253.86
Figure 2. Flow diagram

4
Figure 3. Stream Order
The total number of streams evaluated in the
assessment of stream number is 6,521, with dendritic
drainage present in the area. Horton [12]
observed that
when a basin has a large number of stream segments of
progressively decreasing orders, the number of segments
tends to form a geometric series, beginning with the
single highest-order segment and rising in proportion to
the constant ratio. When the relationship is plotted on the
logarithmic and arithmetic scales on the Y-axis and X-axis,
it creates a negative linear pattern on the Y-axis (Figure 4).
3.1.2 Stream Length (Lu)
The length of a stream is one of the most important
hydrological properties of a basin since it indicates the
characteristics of surface runoff. Streams with shorter
lengths are more common in locations with steeper slopes
and finer textures. Longer streams typically have smoother
surfaces with lower slopes. The total length of stream
segments is usually greatest in the first stream orders and
gradually reduces as the stream order increases. When
plotted against the corresponding order, the logarithms

5
1
10
100
1000
1st Order 2nd Order 3rd Order 4th Order 5th Order
Stream
Number
in
logarithmic
Stream Order
Figure 4. Stream number against Stream order.
of the number of stream segments of different orders
generally lie on a straight line [12]
. In a first-order stream,
the overall length of stream segments is greatest, and it
decreases as stream order increases. The 1st and 2nd order
streams in the study region are longer than the 3rd, 4th,
and 5th order streams, respectively (Table 1). The stream
length evaluation in Table 1 reveals that stream length
reduced as stream order increased.
Rb = Nu/Nu+1 (1) [13]
Nu = Total no. of stream , u is the segments of order
Nu +1 = No. of segments of the next higher order
Rb=5432/742=7.32
Rb=742/232=3.20
Rb=232/87=2.67
Rb=82/28=2.93
Mean Bifurcation ratio = 16.12/4= 4.03
3.2 Areal Morphometric Parameters
The length of a basin outline, which can be plotted
and approximated using GIS software, is known as
its perimeter. The basin area and characteristics were
determined to be 625.61 km2
and 307.98 km, respectively.
3.2.1 Drainage density (Dd)
Drainage density (Dd) is defined as the length of
streams per unit area divided by the size of drainage
basins by Horton [14]
. It is written as:
Dd = Lu/A (2) [12]
Where, Dd= Drainage Density, Lu=Total stream length
of all orders, A= Area of the basin
A low drainage density implies porous subsurface strata
and is a defining property of coarse drainage, which often
exhibits values less than 5.0. [8]
observed that when basin
relief is low, low drainage density is preferred, and vice versa.
The lower Orashi River basin has a Dd of 2.00 km/km2
,
indicating that the studied region has a porous or permeable
underlying material with moderate drainage and low relief.
3.2.2 Drainage Texture (Tx)
Climate, lithology, vegetation, rainfall, soil type etc.
all influence drainage texture, which is a measure of
relative channel spacing in a fluvial-dissected landscape
[14]
. Drainage density in the studied area is 20.84 km/km2
(Table 2), indicate very fine texture.
Tx = Nu/P (3) [12]
3.2.3 Stream Frequency (Fs)
The total number of stream segments per unit area
within a basin is referred as the stream frequency (Fs)
[12]
. The frequency of streams in the watershed has a
positive connection with drainage density, meaning that
as drainage density rises, stream population rises as well.
Climate, vegetation covering, rock, run off intensity,
rainfall, infiltration topography and soil types, and slope
all influence drainage frequency and density. The Fs of the
basin is 10.44 (Table 2) indicate surface runoff leading to
flooding.
Fs =∑Nu/A (4) [12]
∑Nu = Total No. of stream segments of all order and A
= Area (km2
)
3.2.4 Form Factor (Rf)
This component indicates the magnitude of a basin's
flow in a particular region [14]
. The form factor is always
smaller than 0.754. (This number indicates a completely
circular watershed.) A lower form factor results in a longer
basin, while a higher value results in a circular basin.
Larger peak flows with a shorter duration occur in basin
with high form factors, while in extended watersheds with
low form factors, flatter peak flows with a longer duration

6
occur. The Rf value for the study region is 0.24, which
is more in line with the basin circular form than with its
elongated shape. Where Rf is the Form factor, A is the
area of basin (km2
) and Lb2
is the square of basin length.
Rf = A/Lb2
(5) [14]
A = Area (km2
) and Lb2
= Square of Basin Length
3.2.5 Elongation Ratio (Re)
The ratio of the diameter of a circle of the same size
as the drainage basin to the greatest length of the basin
is known as the elongation ratio (Re) [13]
. The elongation
ratio is found in a wide range of climatic and geologic
types, with values ranging from 0.6 to 1.0. (0.9-0.10), oval
(0.8-0.9), less elongated (0.7-0.8), elongated (0.5-0.7),
and more elongated (0.5-0.7). (0.5-0.7). A circular basin
discharges runoff more efficiently than an elongated basin
[15]
. The value varies from 0.6 to 0.8 for high relief areas,
and values near to 1.0 indicate areas with very little relief
and a circular form [8]
. Table 2 shows that the research
area Re is 0.15, indicate very low sloped, little relief and
Circular shape.
Re = (2A/π)/Lb2
(6) [13]
A= Area (km2
) and Lb = Basin length (km)
3.2.6 Circulatory Ratio (Rc)
The Circulatory Ratio is the relationship between the
area of a basin and the area of a circle having the same
diameter as the basin perimeter [16]
. The Rc value of the
basin is 0.08, indicating an elongated shape, low runoff
flow, and high subsoil permeability. Rc is an integer with
no dimensions. Its low, middle, and high levels correspond
to the tributary basins' youth, maturity, and elderly stages
of life [17]
.
Rc= 4*Pi*A/P2
(7) [9]
Pi = 3.14, A = Area (km2
) and P2
= Square of the
perimeter (km)
3.2.7 Length of Overland Flow (Lg)
This is length of water over the ground before it is
concentrated into the mainstream, affecting the drainage
basin hydrologic and physiographic dynamics [12]
.
Infiltration (exfiltration) and percolation through the soil,
both of which fluctuate in time and area, have a substantial
impact on Lg [18]
. The high Lg value suggests that
precipitation had to travel a considerable distance before
concentrating in stream channels [19]
. In this study, the
length of overland flow is 1.00 km, indicating decreased
distance runoff in the study area.
Lg = 1∕2Dd (8) [12]
3.2.8 Basin Length (Lb)
The longest dimension of a basin to its main drainage
channel is called basin length. When compared to a more
compact basin, the greater the length of the basin, the
lesser the likelihood of flooding. Varied workers have
given different interpretations to basin length (Lb) by
Schumm [13]
and Cannon [20]
. Lb is the longest length in the
basin, measuring 50.84 kilometers from the catchment to
the point of confluence.
3.2.9 Constant Channel Maintenance (C)
The 0.5 km long basin channel (Table 2) illustrates that
structural factors have negligible impact on infiltration
rates, surface runoff, less discharges, and watersheds.
C = 1/D (9) [13]
where D= Drainage Density
3.3 Relief Morphometric Parameters
These deal with the characteristics like as relief, relief
ratio, ruggedness number, and so on. Relief Aspects is a
subfield of geology.
3.3.1 Basin Relief (Bh)
The relief of a basin is determined by subtracting
the height of the basin mouth from the elevation of the
basin's highest point, and then multiplying the result by
100. Strahler [21]
in order to understand the geomorphic
qualities of the basin, as well as the development of
landforms and drainage systems, the flow of surface and
sub-surface water, the permeability of the terrain, and
the erosional properties of the terrain, it is necessary to
first understand the basin geomorphic qualities [8]
. In the
research, the value of Bh is assessed to be 31.00 meter
(Table 2). Because of this, the low relief value of the basin
indicates that infiltration is strong and runoff is little.
H=Z-z (10) [21]
3.3.2 Relief Ratio (Rh)
It's a ratio with no dimensions. Rh ratios above a
certain threshold indicate a steep slope and high relief,
and vice versa. In steeper basins, run-off is often faster,
resulting in more peaked basin discharges and increased
erosive power [22]
. The Rh values is 0.0014 (Table 2),
suggesting very low relief and a very low slope, implying
that it is less susceptible to sudden erosion. Where Rh is
the Relief ratio, H is total relief, Lb is Basin length .
Rh=H/Lb (11) [13]

7
3.3.3 Relative Relief
The relative relief of a basin is calculated by dividing
the difference in height between the highest and lowest
points in the basin (H) by the perimeter of the basin (P)
[23,24]
. As a consequence of relative relief being an essential
morphometric measure employed in the overall evaluation
of the morphological features of terrain in the research
area, the result is 0.007 (Table 2) in the study region [23,24]
.
Relative relief = H/P (12) [24]
3.3.4 Ruggedness Number (Rn)
When the maximum basin relief (Bh) and drainage
density (Dd) of a unit are multiplied together, the result is
called Rn. It is a measure of the irregularity of the surface.
Whenever the size of both variables and the slope are
both big, the roughness number reaches an exceptionally
high level of value [21]
. In the current basin, the roughness
number is 0.14, indicating that it has a very low slope and
is less prone to severe erosion.
Table 2. Morphometric Characteristics of lower Orashi
River Catchment (Areal Aspects and Relief)
S/N NAMES VALUES
1 Area (A) 625.61 km2
2 Perimeter (P) 307.98 km
3 Stream Order 5
4 Mean Stream Length 0.19 km
5 Mean Stream Length Ratio 1.4
6 Mean Bifurcation Ratio 4.03
7 Drainage Density (Dd) 2.00 km/km2
8 Stream Frequency (Fs) 10.44
9 Drainage Texture (T) 20.84 km/km
10 Basin Length (Lb) 50.84 km
11 Circulatory Ratio (Rc 0.08
12 Elongation 0.15
13 Form Factor (Ff) 0.24 km/km
14 Constant channel maintenance(C) 0.5 km
15 Length of overland flow (Lg) 1.0km/km
16 Basin relief (Bh) 31.00 m
17 Relative relief (R) 0.07 km
18 Relief ratio (Rr) 0.0014
19 Ruggedness number (Rn) 0.14
3.4 Topographic Changes
The results of the analysis of the geomorphological
sequence in the profiles established in Figure 5 show
that the terrain has a low elevation in Figure 6a at 6h,
and the river shows that the width of the river decreases
in various topographical changes like the shows Figure
6a, 6b, 6c and 6e due to accretion. Figures 6f, 6g and
6h show that the depth of the river is almost at the same
elevation in the land area due to the deposition of sand
due to lack of maintenance by dredging the river, resulting
in flooding during the season. rains. According to Eteh
and Okechukwu [3]
proper planning and management of
the flood situation is essential to avoid major effects on
flooding during the rainy season in the Niger Delta. It
is therefore important to study the terrain of the area by
investigating the hydrological property and the depth
of the river to monitor the statue of the area, especially
in terms of the drainage system, making decisions for
the construction of structures mainly along the riparian
communities and including roads, agriculture, buildings
construction, Because most of the topography has poor
drainage system due to lack of planning, structures and
roads are built on drainage canals, resulting in flooding
during the rainy season. Therefore, government need to
plan and manage the waterway because is critical as flood
has come to stay. But we must manage our rivers and
protect the safety of our citizens.
Figure 5. Digital Elevation model showing Cross section
profile

8
Figure 6a. Profile 1
Figure 6b. Profile 2
Figure 6c. Profile 2
Figure 6d. Profile 3
Figure 6e. Profile 4

9
4. Conclusions
The property of drainage basins contains the
size, shape, geology are vital indices for predicting
environmental hazards especially Flood and erosion.
These indices are crucial for predicting environmental
threats, particularly erosion and flooding. They reveal
the rate at which rain reaches a major river, as well as
the frequency and severity of flooding. This research
demonstrates how drainage basin configuration has a
major impact on the occurrence of environmental hazards
in a given area. The narrow outlets of Orashi River
elongated basins restrict runoff velocity and cause long-
lasting flood peaks, yet their near circular form promotes
rapid runoff circulation and the drainage system is
dendric type with higher bifurcation ratio and low relief
in lower Orashi River possess a great threat for erosion
and flooding due to the topography has a poor drainage
system resulting from low altitude in river and land area
as a result of sand deposited due to a lack of maintenance
in low Orash River.
Acknowledgments
The authors express their profound gratitude to the
Managing Director of Geosoft Global Consulting for
processing of the data, Mrs. Francis Omonefe and Mr
Erepamo O.
Conflicts of Interest
The authors declare that they have no conflict of
interest.
References
[1] Kulkarni, M. D. 2015. The Basic Concept to Study
Figure 6h. Profile 7
4. Conclusions
The property of drainage basins contains the size, shape, geology are vital indices for
predicting environmental hazards especially Flood and erosion. These indices are crucial for
predicting environmental threats, particularly erosion and flooding. They reveal the rate at
which rain reaches a major river, as well as the frequency and severity of flooding. This
research demonstrates how drainage basin configuration has a major impact on the
occurrence of environmental hazards in a given area. The narrow outlets of Orashi River
elongated basins restrict runoff velocity and cause long-lasting flood peaks, yet their near
circular form promotes rapid runoff circulation and the drainage system is dendric type with
higher bifurcation ratio and low relief in lower Orashi River possess a great threat for erosion
and flooding due to the topography has a poor drainage system resulting from low altitude in
river and land area as a result of sand deposited due to a lack of maintenance in low Orash
River.
Acknowledgments
Figure 6f. Profile 5
Figure 6g. Profile 6
Figure 6h. Profile 7

10
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11
Nikolai Nikolaevich Zavalishin,
Siberian Regional Research Hydrometeorological Institute, Novosibirsk, 630099, Russia;
Email: znn@sibnigmi.ru
1. Introduction
The World Climate Change Conference held in Mos-
cow in 2003 [1]
was mainly devoted to finding the causes
of significant changes in the Earth’s geospheres in recent
decades. Both natural and anthropogenic factors were
considered, but the problem of their interrelation in the
ongoing processes has not been resolved. The discussions
revealed a whole spectrum of opinions on this subject:
only anthropogenic factors affect the climate, only natural
ones, anthropogenic factors prevail, and natural ones pre-
vail.
The problem of modern warming of the lower atmo-
sphere is the main issue of climatology in recent decades.
There are two points of view: either warming is caused by
mainly natural factors, or by anthropogenic.
The IPCC reports take a standpoint of the anthropogen-
ic type of modern warming, for example [2]
.
Not all researchers agree with this: for example, a
well-reasoned and complete review [3]
provides a detailed
criticism of the position of anthropogenic warming. Let’s
add here the works [4-6]
. That is, the problem has not been
resolved and is under discussion.
The article discusses both hypotheses. Based on the
ARTICLE
Reasons for Modern Warming: Hypotheses and Facts
Nikolai Nikolaevich Zavalishin*
Siberian Regional Research Hydrometeorological Institute, Novosibirsk, 630099, Russia
Article history
Received: 10 November 2021
Accepted: 3 December 2021
Published: 10 December 2021
Two hypotheses of modern warming are considered: natural and anthro-
pogenic. The probabilities of each of them are compared. It is proved that
the hypothesis of natural warming is much more likely than the hypothesis
of anthropogenic warming. It is shown that the displacement of the Sun
from the center of mass of the solar system directly affects the temperature
of the surface atmosphere in the synoptic regions of Eurasia. This result
corresponds to the model of E. P. Borysenkov with variations of the solar
constant or, equivalently, with variations of the Bond albedo.
Keywords:
Hypotheses
Natural
Anthropogenic
Temperature
Lower atmosphere
Albedo
Solar displacement

12
published facts, the probabilities of both the natural hy-
pothesis and the anthropogenic one are estimated.
2. Methods and Materials
The NCEP/NCAR Reanalysis datasets for the period
1972-2012 was used in the study. Two parameters were
taken: outgoing longwave radiation (OLR) and the month-
ly average temperature of the near-surface atmosphere.
The calculation of the Sun displacement from the com-
mon center of mass of the Solar system was carried out
according to the algorithm described in the article [7]
.
Standard statistical methods of data processing were
used.
3. Results
Let us put the question this way: which of the two hy-
potheses of modern warming is more probable?
H1: outgoing shortwave radiation (OSR),
H2: outgoing longwave radiation (OLR).
Let’s start our analysis by considering H2 hypothesis.
If the hypothesis is correct, then modern warming is due
to human activity, that is, to an increase in CO2 emissions,
which increase the greenhouse effect, holding back the
flux of outgoing longwave radiation, and due to this, the
temperature of the surface atmosphere is raised. There-
fore, there should be a trend towards a decrease in the
OLR.
Figure 1 shows a graph of changes in the OLR anom-
alies with an assessment of its trend (the average value in
the period 1975-2012 was taken as the norm). The graph
is built according to NCEP/NCAR Reanalysis data on a
2.5x2.5 degree grid, taking into account the latitude of the
grid points. Since there are 144 grid points in each lati-
tudinal band, then each grid point at a distance between
equatorial and polar regions has various areas.
This effect can be taken into account in two ways:
either to introduce correction factors for each latitudinal
band, taking into account its contribution to the OLR, or
to thin out latitudinal bands so that one grid point has an
approximately equal area. The second option was imple-
mented.
It can be seen from the figure that there is no trend for
a decrease in the OLR in both hemispheres. Moreover,
in the Northern Hemisphere, there is a trend towards an
increase in the OLR by almost 2 W/m2
. This fact is con-
firmed by the result of the analysis for the tropical zone,
published in the article [8]
: their trend reached 7 W/m2
.
So, due to the inconsistency with the data, the probabil-
ity of the H2 hypothesis validity is very small.
Consider the H1 hypothesis. The main conclusion of
the Fourth IPCC Report comes down to the statement that
it is impossible to explain modern warming only by natu-
ral causes [9]
. It is pointed out that it is absolutely true that
changes in the incoming solar radiation flux have fluctu-
ations of order 0.1% and are not able to cause changes in
the temperature of the surface atmosphere by 1.0° C.
At the same time, for some unknown reason, changes
in outgoing shortwave radiation greater by an order of
magnitude are ignored [10]
: a decrease in the mean annual
Bond albedo by 0.01 from 1985 to 2000 (Figure 2).
-4
-3
-2
-1
0
1
2
3
1 975 1 985 1 995 2 005
W/m2
Northern Hemisphere
Southern Hemisphere
Figure 1. Interannual changes in the outgoing longwave radiation of the Earth
It can be seen from the figure that there is no trend for a decrease in the OLR in both
hemispheres. Moreover, in the Northern Hemisphere, there is a trend towards an increase in the
OLR by almost 2 W/m2
. This fact is confirmed by the result of the analysis for the tropical zone,
published in the article [8]
: their trend reached 7 W/m2
.
So, due to the inconsistency with the data, the probability of the H2 hypothesis validity is
Figure 1. Interannual changes in the outgoing longwave radiation of the Earth

13
The figure shows that over a 15-year period, the annual
albedo decreased by 0.011 (0.318-0.307). Note that such
a decrease in albedo corresponds to an increase in the
solar radiation flux by 3.4 W/m2
. This value is sufficient
to cause a modern increase in the temperature of the low-
er atmosphere: data from the article [11]
showed that an
abrupt change in albedo by 0.01 will lead to an increase in
the temperature of the surface atmosphere by 1.1° C, with
a delay caused by the thermal inertia of the hydrosphere.
Consequently, the H1 hypothesis explains modern
warming and is therefore more likely than the H2 hypoth-
esis.
The series in Figure 1, 2 were continued in the articles
[12,13]
. In the article [12]
the Bond albedo anomalies are esti-
mated by the reflected light of the Moon, which, accord-
ing to the authors, does not exceed 0.5 W/m2 for the peri-
od 2001-2018. This is 6 times less than estimate of albedo
anomalies for the period 1984-2000, presented in Figure
2. An anological estimate of Bond’s albedo is given by the
authors of [13]
by the CERES method in the interval 2001-
2020, in their opinion, the albedo anomalies fit into 1.5 W/
m2, but in the interval 2001-2014, the albedo anomalies
are kept within 0.5 W/m2 and only after 2014 go beyond
this limit.
Authors [12]
are sure that solar activity, measured by
Wolf numbers, cannot be the cause of changes in Bond’s
albedo. What is the reason then? Let’s consider this issue
in the discussion.
To understand the processes under study, we need to
consider such a parameter as the displacement of the Sun
relative to the center of mass of the Solar System. For the
first time, the offset was introduced in the article [7]
and
calculated by the formula (1):
RM+Σrkmk=0 (1)
Here R is the displacement vector of the Sun, M is the
mass of the Sun, mk is the mass of planets from Mercury
to Pluto, rk is the radius vector of the k-th planet. Figure 3
shows a graph of the displacement of the Sun, calculated
by the formula (1). The displacement was maximum and
equal to |R|=1.4 million km in May 1982 and was practi-
cally zero in 1990.
Figure 3. The displacement of the Sun from the center of
mass of the Solar system in the plane of the ecliptic for
the period 1980-2021.
Figure 2. Mean monthly (grey) and mean annual (black) dynamics of the Bond albedo [10]
.

14
Let us assume that the albedo changes insignificantly
during the year. Then the question is, in which months
of the year will the effect of albedo change be maximal?
Since the perigee of the Earth’s orbit falls on the
beginning of January (the difference in the incoming solar
radiation reaches 7% compared to the apogee) and, given
that 80% of the surface in the Southern Hemisphere is
covered with water, and only 60% of that in the Northern,
while the hydrosphere is the main heat accumulator, then
we can expect that the effect will be maximum in January.
And, taking into account the thermal inertia of the World
Ocean, the neighboring months, December, February and
March, should be added to this period.
Figure 4 from [14]
shows the monthly mean anomalies of
the surface air temperature in the south of Western Siberia
for the periods 1960-1980 and 1981-2002. The figure
shows that after the Earth passes the perigee, the effect of
the thermal inertia of the World Ocean is observed up to
March.
4. Discussion
The question arises as to the reason for the albedo
change shown in Figure 2. Factors such as deforestation
or volcanic eruptions cannot be the primary cause of
warming, because they have time scale differing from that
of modern warming: hundreds of years vs. years.
What about the effect of greenhouse gases on albedo?
Yes, it exists, but the first factor here is not CO2, but wa-
ter vapor, which takes on 2/3 of the greenhouse effect.
Moreover, water vapor plays a double role: it reduces the
inflow of solar radiation and, at the same time, holds the
OLR steady, increasing the near-surface temperature of
the atmosphere. And which process will be more signifi-
cant, and at what time, is not yet very clear.
What can change the albedo?
How does the displacement of the Sun from the center
of mass of the Solar system effect on albedo and, accord-
ingly, on temperature of the surface atmosphere? To an-
swer this question, let us take the data archives on anom-
alies of the mean monthly temperature of the near-surface
atmosphere for the period 1881-1977 [15,16]
and select here
those weather stations that have observational data for a
period of at least 30 years. Further, for each of these 810
stations, we calculate the difference in the anomalies of
the mean monthly air temperatures at the Sun displace-
ment of less than -0.5 million km and more than 0.5 mil-
lion km.
It turned out that the greatest effect in terms of intensity
is observed in the winter season. Because at the beginning
of January, the influx of solar energy is almost 7% high-
er than at the beginning of July due to the perigee of the
Earth’s orbit, which falls on January 2-5. Almost the entire
effect of changes in winter temperature is concentrated in
the middle and high latitudes of Eurasia (above 40° N):
almost 70% of weather stations belong to 1-38 synoptic
regions.
What is the reason for such an uneven distribution of
atmospheric temperature? It is clear that in the middle
Figure 4. Anomalies of mean monthly near-surface air temperatures in the south of Western Siberia (°C),
between periods of 1960-1980 and 1981-2002

15
and high latitudes of Eurasia, the Gulf Stream is the
main factor in the formation of temperature anomalies.
But why then similar changes are not recorded in the
North America? In our opinion, even if the Pacific
Ocean overheats due to the displacement of the Sun, the
mountains in the west of North America will block the
heating of the surface atmosphere.
Consider the following experiment. Let us calculate the
displacement of the Sun from the common center of mass
of the Solar system, caused by the motion of the planets,
and divide all years into 3 groups: in the first group, we
will include those years when the displacement of the Sun
was more than 0.5 million km; in the second – those when
the displacement of the Sun was less than -0.5 million km;
years with a solar displacement of less than 0.5 million
km in modulus will be removed from consideration.
Further, for each synoptic region, we calculate the average
temperature of the surface atmosphere from the data of
meteostations of this region for the first and second groups
of years and find the difference between them.
Figure 5 shows the result for winter months [17]
. There
is a statistically significant (Student’s t-test at 5% level)
difference in mean winter temperatures of the near-surface
troposphere, which depends on significant displacements
of the Sun.
A theoretical question arose, what will be the tempera-
ture field of the surface atmosphere if the solar radiation
flux increases? According to the model of E.P. Borisenkov
(personal communication), with an increase in the solar
constant by 5% in January (which, of course, is unreal-
istic), the temperature will change, mainly in the middle
and high latitudes of Eurasia by 4-10°C, and in in other
regions only up to 2°C, which is in good agreement with
our results. But, an imbalance can be created without
changing the solar constant: it is enough to change the al-
bedo by the same 5% to get the same result. In fact, as we
saw earlier, the albedo changed by 1%.
Taking into account the relationship of the surface tem-
perature of the atmosphere with the displacement of the
Sun, shown in the last figure, we will build a climate fore-
cast of temperature dynamics. The algorithm for calculat-
ing the forecast is as follows. For each year for the period
1901-2008, the average values from 5 rows of January
air temperatures were calculated at the specified weather
stations Omsk, Barabinsk, Novosibirsk, Tomsk, Barnaul.
The resulting series was transformed into the accumulated
sum of anomalies (“norm” is the average for 1901-1985).
The second row on the graph is proportional to the accu-
mulated sums of the ordinates of the Sun’s displacement
(the direction of the ordinate axis is 2 dozen degrees less
than the longitude of the Earth in mid-January). The pro-
cesses under consideration have similar features: synchro-
nous rise of graphs, inflection point in 1990, close local
extremes (see Figure 6).
However, there are differences. The discrepancies,
especially the temperature rise in 2001-2005, can be ex-
Figure 5. Difference DT = T1-T2 (left part) of average winter temperatures of surface air (°С) in natural synoptic re-
gions (right part), depending on the displacement of the Sun. (T1 is the temperature in years when the displacement is
more than 0.5 million km, T2 is the temperature in years when the displacement is less than -0.5 million km)

16
plained for Western Siberia by a delay of several years
in the response from the hydrosphere to the variability
of solar radiation, as well as by the obvious fact that the
displacement of the Sun is not the only parameter deter-
mining the variability of the temperature of the lower at-
mosphere.
The climate forecast in Figure 6 was published in [14]
in 2009. According to the forecast, in the next 2-3 years
there will be, at least, a decrease in the rate of growth of
the surface temperature of the atmosphere in the 29th syn-
optic area and, after the generation of positive heat anom-
alies by the World Ocean, the January temperature in the
area will gradually return to normal values.
Taking into account our results, we can expect a similar
reaction in Eurasia and on Earth as a whole.
5. Conclusions
The interannual OLR anomaly are analyzed based on
the NCEP/NCAR Reanalysis data. It was shown that there
is a nonnegative linear trend of the OLR from 1975 to
2012. This fact contradicts the hypothesis of an anthropo-
genic cause of modern warming.
The paper deals with the natural component of modern
warming. The OSR graph is given, from which it follows
that the Bond albedo decreased by 0.01 over the period
from 1984 to 2000, which corresponds to an increase in
the solar radiation flux by 3.4 W/m2
. This value is enough
to heat the lower atmosphere of the Earth by 1°C.
It is shown that heating occurs unevenly over the
months of the year due to the Earth’s passage through its
orbit perigee on January 2-3 and to the unequal distribu-
tion of the World Ocean between the Earth’s hemispheres:
80% in the Southern Hemisphere and 60% in the North-
ern Hemisphere. Therefore, on the day of the passage of
perigee, the ocean of the Southern Hemisphere receives
7% more heat than the ocean of the Northern Hemisphere
in early July. This results in the overheating of the atmo-
sphere in December-January, and additional overheating
is realized in February-March due to the thermal inertia of
the World Ocean.
Why has albedo changed? The author sees the root
cause in the displacement of the Sun from the common
center of mass of the Solar system, caused by the motion
of the planets. The maximum bias effect was achieved
in May 1982. This hypothesis was tested in the synoptic
regions of Eurasia based on the winter temperatures of the
near-surface atmosphere. Good agreement was obtained
between our experiment and the results of E.P.Borisen-
kov’s model with variations in the solar constant (Bond
albedo anomalies). Based on this fact, a climatic forecast
of changes in the near-surface temperature of the Earth’s
atmosphere was given.
Figure 6. The sum of January surface atmospheric temperature anomalies in the 29th synoptic region (blue line) and the
sum of solar displacement ordinate anomalies (brown line).

17
References
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[10] Goode P.R., Palle E., Yurchyshyn V.B., et al. Sun-
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CCKEM2015.pdf

18
Xiancan Li,
College of Water Conservancy and Architecture Engineering, Tarim University, Alar, Xinjiang, 843300, China;
Email: 1065381600@qq.com
ARTICLE
A Preliminary Exploration of the Functional Value Assessment of
Ecosystem Services in Aral City
Guona Luo Xiancan Li*
Shuang Liu Muhang Li Shuya Zhang
College of Water Conservancy and Architecture Engineering, Tarim University, Alar, Xinjiang, 843300, China
Article history
Received: 11 November 2021
Accepted: 24 December 2021
Published : 5 January 2022
Using the principles and methods of eco-economics as the research object,
Aral City comprehensively expounds the ecological service functions such
as ecosystem regulation of climate, carbon sequestration, soil conservation,
water conservation and purification environment, and evaluates its
economic value.The total value of the estimated 2021 is 1303.65 million
yuan. At the same time, the importance of ecological service functions of
urban ecosystems, from large to small, is to sequester carbon and release
oxygen, purify the environment, maintain soil, conserd water sources,
regulate the climate. The ecosystem service function which needs to be
paid attention to in the concept of ecological construction and restoration of
the next stage of ecological construction in Aral City.
Keywords:
City of Aral
Ecosystem services function
Economic value assessment
1. Introduction
Ecosystem service function refers to the important role
that the ecosystem plays to the outside in the ecological
process of energy flow and material flow. The ecosystem
not only provides food, medicine, and raw materials for
industrial and agricultural production and other products
necessary for human survival, but also maintains the
life support system that humans rely on for survival and
development. It is generally believed that ecosystem
service functions mainly include ecological integrity;
regulation of ecosystem services; provision of ecosystem
services and cultural ecosystem services. This article
mainly focuses on the second category of urban ecosystem
functions, namely, regulation of ecosystem services to
evaluate.
The natural conditions in Alar are severe and
threatened by sandstorms and salinity. In recent years,
the ecological vulnerability has been increasing due to
various influences. As a life support system, the ecosystem
provides services for the survival and development of
human beings. Its service functions play an irreplaceable
role as a natural barrier for maintaining the ecological
balance of the desert and promoting social and economic
development. Therefore, this article will combine the
physical geography and socio-economic conditions of Alar
City, and use the principles and methods of ecological
economics to explain the basis of the ecological functions

19
of the ecosystem, such as climate regulation, carbon
fixation and oxygen release, soil conservation, water
conservation, and environmental purification. Above,
quantitatively evaluate the economic value of the urban
ecosystem service functions of Alar City in 2021, with
a view to providing help for the sustainable ecological
development of Alar City.
2. Research Progress on Ecosystem Service
Functions
At present, the quantitative evaluation of the economic
value of ecosystem services has become the frontier
field of the current research on ecology and resource
economics, environmental economics and ecological
economics. In this field, domestic and foreign scholars
have conducted relatively extensive research. Costanza
et al. [1]
took forest ecosystems as the research object and
estimated the annual economic value of global ecosystem
service functions. The publication of this article made
the research on ecosystem service functions one of the
hotspots of international sustainable development related
research. With the introduction of foreign research
theories and methods into the country, Chinese scholars
have also launched research on ecosystem service
functions, explored related concepts, and used scientific
evaluation methods to conduct research on the value of
ecosystem service functions in different regions.
The research process of the definition of ecosystem
services. In 1997, Costanza et al. proposed: Ecosystem
services refer to the life support products and services that
humans obtain indirectly or directly from the ecosystem;
Daliy [2]
proposed in the same year: Ecosystem services refer
to the formation of ecosystems and ecological processes to
maintain human survival. In 1999, Ouyang Zhiyun and Wang
Rusong in my country proposed the same definition as Daliy;
then in 2005, MA proposed that ecosystem service functions
refer to the benefits that humans obtain from the ecosystem.
So far, scholars have focused on this content. The research
basically reached agreement.
Ecosystem service value evaluation techniques and
methods. Technology is divided into two categories:
alternative market technology and analog market
technology. The methods are divided into the following
categories: conditioned value method (using market
research methods to consult people’s willingness to pay,
and use it to express the economic value of ecological
service functions); expense method (expressed by people's
expenditure on a certain ecological service function);
Market value method (first calculate the quantitative
value of a certain type of ecosystem service, then study its
shadow price [3-4]
, and then calculate the total economic
value); opportunity cost method (from production costs,
use costs and external costs) Composition) and so on.
3. Evaluation Method of Ecosystem Service
Function Value
3.1 Principle of the Method
The estimation of ecosystem service functions is
affected by many factors, and most of the current work is
to estimate the average regional ecosystem service value.
Costzana et al. provided a method for reference: first,
classify the ecosystems in the study area according to
certain standards; second, calculate the unit area capital of
each part of the ecosystem services according to different
measurement methods; finally, Calculate the total capital
and summarize the structure table [5]
. Therefore, the total
value of regional ecosystem services is:
1 1
m n
ij i
i j
X E E S
D
= =
=
formula X The total value of serving the regional
ecosystem, Dij Represents the unit value of the ecosystem
service function of the i-th ecosystem,SiRepresents the
area of the i-th type of ecosystem.
3.2 Estimation of Ecological Service Value
The evaluation of the service value of urban
ecosystems generally includes the evaluation of the value
of ecological service functions such as climate regulation,
carbon fixation and oxygen release, soil conservation,
water conservation, and environmental purification:
Adjust the climate. The city of Alar is located in a
warm temperate zone, and the adjustment of the urban
climate mainly relies on wetlands. The cooling effect in
summer can reduce the use of urban air-conditioning,
so this function can be measured by the alternative cost
method, that is, reducing the electricity consumption of
air-conditioning.
Carbon fixation and oxygen release. Using afforestation
cost method and carbon tax method [6]
, the value of
carbon sequestration in Alar City is evaluated; while the
value of oxygen released by the ecosystem is calculated
by afforestation method and shadow price method of
industrial oxygen production.The calculation formula and
parameters description are shown in (Table 1).
Maintain the soil. Firstly, the difference between the
amount of soil erosion without vegetation cover and the
actual erosion amount of forest land and grassland is used
to estimate the annual reduction of soil erosion of forest
land and grassland; The value of wind and sand disasters
in 4 aspects.

20
Conserve water sources. The average value of the water
balance method, the canopy interception method and the
atmospheric condensation water conveyance method are
used to estimate the water conservation.
Purify the environment. The substitution cost method
is adopted, and the cost of other environmental pollution
control measures is used to replace the value of the
ecological system to purify the environment.
Part of the evaluation methods mainly refer to the
evaluation formula (Table 2) in the Standards for
Evaluation of Forest Ecosystem Service Functions (LY/T
1721-2008) such as Bai Yuan.
Table 2. Ecological value assessment formula
Carbon
fixation
and oxygen
release
G carbon sequestration by vegetation = 1.63R
carbon×A×B years; G soil carbon sequestration=A×F
soil; U carbon=A×(1.63R carbon×B years+F soil)×C
carbon=(G vegetation carbon sequestration + G soil
carbon sequestration) × C carbon
G oxygen = 1.19AB year; U oxygen = 1.19C oxygen AB
year
In the formula, G vegetation carbon fixation, G soil
carbon fixation, and G oxygen are the annual vegetation
carbon fixation, soil annual carbon fixation, and annual
oxygen release (t/a); U carbon and U oxygen are the
annual forest stand fixation. Carbon and its release value
(yuan/a); R carbon is the carbon content in CO2, B year is
the net productivity of the forest stand (t/hm2
∙a), F soil is
the carbon sequestration per unit area of the forest stand
soil (t/hm2
∙a), C carbon is the price of carbon fixation
(yuan/t)
4. Valuation of Ecosystem Service Function in
Alar City
According to the land survey data of Alar City in
2021, its natural ecosystem is divided into five categories:
grassland, woodland, wetland, natural reserve, and water
area. The total grassland area is 27121 hm2
, the forest land
is 157091 hm2
, the wetland is 9000 hm2
.
However, the reserved area is 128120 hm2
and the
water area is 48710 hm2
.
4.1 The Value of Climate Regulation
Based on research at home and abroad, greening can
reduce the temperature in some areas by 3-5 °C, with a
maximum reduction of 20 °C, and about 10 °C in areas
with buildings[7]
.
The temperature adjustment effect of a large tree
evaporating for a day and night is equal to 1046 KJ, which
is equivalent to 10 air conditioners working for 20 hours.
The power consumption of indoor air conditioners is
0.735 kWh/unit, and the electricity bill is 0.39 yuan/kWh,
totaling 57.33 yuan. Taking 80 trees/hm2
in woodland and
using air conditioners for 60 days per year, the economic
value of the climate regulation function of the ecosystem
in Alar City is:
157091 (hm2
) × 80 (plants/hm2
) × 57.33 (yuan) × 60
(day) = 4.32 million yuan
Table 1. Calculation formula and parameter description
Conserve water
W=A×D=A×(h×P); W=(I+Gv)×A=(P×V+P×G)×A; Uhan = W×(C capacity+C net)
In the formula, W is the moisture coefficient, P is the average annual rainfall (10-3 m), I is the plant canopy interception (10-3 m),
V is the plant interception rate (%), and Gv is the condensation water (mm), G is the ratio of condensed water to precipitation (%);
U culvert is the value of annual water conservation (yuan/a), W is the average water conservation, C capacity is the unit storage
cost (yuan/m3
), and C is net water Purification cost (yuan/m3
)
Soil protection
S soil fixation=G soil fixation/ρh; U soil fixation=G soil fixation/ρh×C excavation=A(X2-X1)/ρh×C soil×P forest
In the formula, S soil fixation is the annual reduction of land loss area, U soil fixation is the annual soil fixation value of the forest
stand (yuan/a), G soil fixation is the annual soil fixation amount of vegetation (t/a), and ρ is the soil bulk density of the forest land (t/
m3
), h is the average thickness of cultivated soil (m), C soil is the cost of digging and transporting the earth (yuan/m3
), X1 and X2
are respectively the soil erosion modulus of forest land and non-forest land, and P forest is Normal income per unit area of
forest
land (yuan/hm2
·a)
G nitrogen = ANB year; G phosphorus = APB year; G potassium = AKB year; U fertilizer = G soil consolidation (NC1/R1+PC1/
R2+KC2/R3+ MC3)
In the formula, G nitrogen, G phosphorus, and G potassium are respectively the amount of fixed nitrogen, fixed phosphorus,
and fixed potassium (t/a); U fertilizer is the accumulation value of tree nutrients (yuan/a); B year is broad-leaved forest Net
productivity (t/hm2
·a); N, P, K are the nitrogen content, phosphorus content, and potassium content of forest trees (%); R1, R2, C1
are nitrogen and phosphorus content of diammonium phosphate fertilizer, respectively Quantity (%) and price (yuan/t); R3 and
C2 are the potassium content (%) and price (yuan/t) of potassium sulfate fertilizer respectively; M is the forest stand soil organic
matter content (%)
Sd=24%G soil consolidation; Vd=24%G soil consolidation×P library
In the formula, Sd is to reduce the amount of sedimentation, Vd is the value of reducing the amount of sedimentation, P reservoir
is the storage capacity cost, G soil fixation is the annual reduction of soil erosion of the forest stand

21
4.2 The Value of Carbon Fixation and Oxygen
Release
The city is a concentrated place, and the amount of O2
absorption and CO2 emissions are both large. On the one
hand, human respiration, the burning of energy, and the
reproduction of microorganisms all need to consume a
large amount of O2; on the other hand, the urban industry
burns coal, oil and natural gas, the respiration of animals
and plants, and the decomposition of microorganisms
release a large amount of CO2. Cities mainly rely on the
photosynthesis and respiration of the original ecosystem
to maintain the dynamic balance of carbon and oxygen in
the atmosphere [8]
.
If an adult consumes about 0.55 kg O2 and releases
0.56 kg CO2 every day, an urban resident can achieve a
dynamic balance of O2 and CO2 with average woodland
or grassland above. An average of 20 square meters of
woodland or grass above 100 square meters can get a
dynamic balance of carbon and oxygen.
4.2.1 The Fixed Value of CO2
According to the query, each hectare of woodland
absorbs 1,000 kg of CO2 per day, and it is calculated that
the forest land in Alar City absorbs 157091 tons of CO2
per year; each hectare of grassland absorbs 0.6 kg of CO2
per day, and it is calculated that the grassland of Alar City
absorbs 16 tons of CO2 per year.
According to the afforestation cost method, the total
economic value of the fixed CO2 of the ecosystem of Alar
City is 303.24 million yuan per year, and the carbon tax
method is estimated to be 151.4 million yuan, and the
average value is 45.64 million yuan to represent the value
of the fixed CO2 of the ecosystem of Alar City.
4.2.2 The Release of O2 Generates Value
According to the query, each hectare of forest land
releases 730 kg O2 per day. It is calculated that the forest
land in Alar City releases 114676 tons of O2 per year; each
hectare of grassland releases 0.9 kg O2 per day, and it is
calculated that the grassland in Alar City releases 24 tons
of O2 per year.
The value assessment was made according to the
afforestation cost method and the carbon tax method, and
the average value was 681.96 million yuan to represent
the value of O2 released by the ecosystem of Alar City.
Adding the value of the fixed CO2 of the ecosystem and
the value of the release of O2, the total economic value of
the ecosystem service of Alar City for carbon fixation and
oxygen release is 1,136,600,000 yuan.
4.3 Conserve the Value of Soil
The protection of soil in natural ecosystems mainly
achieves its economic value through four interconnected
ecological processes, including reduction of topsoil loss,
protection of soil fertility, reduction of sedimentation
disasters, and reduction of wind-sand disasters.
4.3.1 Forest Land and Grassland Reduce the
Total Amount of Soil Erosion Every Year
Potential soil erosion. Potential soil erosion refers
to the maximum amount of soil erosion without any
vegetation cover. The amount of soil erosion between
forested and unforested land under different types of soil
is very different. Therefore, a systematic comparison
of the amount of erosion for different soil types should
be carried out to estimate the potential amount of soil
erosion. In this paper, referring to the calculation standard
of Ouyang Zhiyun et al. [9]
, the moderate erosion depth of
soil without forest land is 15-35 (mm/a), and the erosion
modulus [10-12]
is 150-350 m3
/(hm2
∙a), respectively, the low
limit of erosion modulus is 192 t/(hm2
∙a), the high limit is
447.7 t/(hm2
∙a) and the average value is 319.8 t/(hm2
∙a) to
estimate (Table 3).
Annual soil erosion in woodland and grassland
covered areas. The amount of soil erosion under different
Table 3. Annual potential soil erosion of woodland and grassland in Alar City
Erosion modulus woodland grassland Total potential soil
m3
/( hm2
∙a) Area hm2
Potential erosion amount 107
t Area hm2
Potential erosion amount 104
t Erosion amount 107
t
192 157091 1.67 27121 1.34 1.67
447. 7 3.41 2.84 3.41
319. 8 2.54 2.09 2.54

22
vegetations is different.The erosion modulus is 0.15 and
0.16 respectively. It is estimated that the average annual
soil erosion amount of woodland and grassland in Alar
City is 78174 t and 78177 t respectively, totaling 156351 t.
Annual reduction in soil erosion of woodland and
grassland. According to the comparison estimation of
the above-mentioned potential soil erosion amount and
actual soil erosion amount of forest land and grassland,
it can be obtained that the lowest soil loss of forest land
and grassland in Alar City is reduced by 1.67 (107
t), the
highest by 3.41 (107
t), and the lowest by 2.54 (107
t) each
year.
4.3.2 Estimation of Loss of Forest Land and
Grassland due to Reduced Soil Erosion
The consequences of soil erosion mainly include the
reduction of arable land, loss of soil fertility (nutrients),
and sedimentation of rivers and lakes. Woodland and
grassland reduce the loss of soil erosion by conserving the
soil.
Woodland and grassland reduce the area of land loss
and its indirect value every year. Calculate the amount of
land area reduction based on the amount of soil erosion
and the average thickness of the soil tillage layer. The
average thickness of cultivated soil in my country is 0.15
m as the soil layer thickness of woodland and grassland.
If the average annual soil conservation amount of forests
and grassland in Alar City is calculated by 2.54 (107
t) soil
density of 113 g/cm3
, it is possible to maintain soil every
year. The area is 3894501 (hm2
).
The opportunity cost of land is used to estimate the
economic value of forest and grassland reduction. In 2020,
the average income of forestry and animal husbandry
production will be 208,100 yuan and 167,000 yuan,
respectively. Using the opportunity cost of production for
woodland and grassland, the economic value of the annual
reduction of land waste area of forest and grassland is
estimated to be 301,000 yuan.
Reduce the indirect value of soil fertility loss. Soil
erosion takes away a lot of soil nutrients, mainly soil
organic matter, nitrogen, phosphorus and potassium. The
contents of organic matter, total nitrogen, total phosphorus
and total potassium in different soils are quite different.
According to the average value of the organic matter
and total nitrogen, total phosphorus and total potassium
content of main woodland soil and grassland soil, and
the annual reduction of soil erosion of woodland and
grassland, the least reduction of organic matter loss and
nitrogen and phosphorus of woodland and grassland each
year Estimation of the loss of elements such as potassium,
potassium, etc. [13-15]
, with the average price of chemical
fertilizers in my country at 2,341 yuan/t, the economic
value of the loss of the ecosystem due to the reduction of
soil nitrogen, phosphorus and potassium can be estimated
every year, calculated as Alar City The indirect value of
the ecosystem to reduce the loss of soil fertility is about
156,000 yuan.
Reduce the economic value of sedimentation.
According to the law of sediment movement in major
river basins in my country, 24% of the sediment lost by
soil erosion generally accumulates in reservoirs, rivers,
and lakes. This part of the sediment directly caused the
decline in the storage capacity of reservoirs, rivers, and
lakes, and increased to a certain extent. As a result of
droughts and floods, another 33% stayed and 37% entered
the sea. This article only considers 24% of the siltation in
reservoirs, rivers and lakes, that is, the economic value of
reducing 39.14 million tons of sedimentation every year.
The silt lost by soil erosion is deposited in reservoirs,
rivers, and lakes, which reduces the accumulation of
effective surface water. Therefore, the value of the loss
can be calculated based on the cost of water storage.
The annual reduction of sediment from woodland and
grassland in Alar City is equivalent to a storage capacity
of 4112×106 m3
. According to related research, the cost
of a reservoir with a storage capacity of 1 m3
in my
country is 0.218 yuan. Therefore, the economic value
of the annual reduction of sediment deposition in my
country's woodland and grassland is 860,000 yuan. Based
on the above analysis, the total economic value of soil
maintained by the terrestrial ecosystem of Alar City,
dominated by woodland and grassland, is 14.04 million
yuan each year.
4.4 The Value of Water Conservation
Vegetation has a large amount of live ground cover and
a humus layer formed by accumulating a large amount of
litter, which can maintain and conserve a large amount of
water, and can increase the speed of water infiltration into
the soil layer. At the same time, vegetation plays a role in
redistribution of vertical precipitation, thereby changing
the distribution, flow and velocity of precipitation, and
preventing precipitation from producing a large amount of
surface runoff. The land covered by vegetation infiltrates
quickly and takes a long time, so the infiltration volume
is more than that of bare land, and the flow rate is smaller
than that of bare land. Vegetated land receives more
rainwater than bare land, and soil water storage capacity
is naturally greater.
When evaluating the functional value of water
conservation, domestic scholars Yang Liwen, et al. [16]
,
Qin Shan [17]
, and Yu Xinxiao [18]
mostly used the water

23
balance method to estimate water conservation, and the
runoff coefficient (h) was 0.44, 0.35, and 0.4, respectively.
In view of the natural conditions of dry climate, low
rainfall and strong evaporation in the study area, when
evaluating the function value of water conservation,
this paper mainly adopts the average value of the water
balance method and the canopy interception method and
the atmospheric condensation water transfer method to
estimate the water conservation. The runoff coefficient (h)
is 0.3, the interception rate (V) is 28.92%, and the ratio
(G) of the condensed water of the desert ecosystem to the
annual precipitation is 17.5%, which is more in line with
local actual conditions. Through calculation, the value of
total water conserved in the urban ecosystem of Alar City
is 8.62 million yuan.
4.5 The Value of Purifying the Environment
The role of green plants in purifying the atmosphere
has two main aspects. One is to absorb CO2, release O2,
etc., to maintain the balance of the chemical composition
of the atmosphere; the other is to reduce sulfide, nitrogen,
and sulfide in the air through absorption within the plant
resistance range. The content of harmful substances such
as halogens.
4.5.1 The Value of Absorbing SO2
According to the inquiry, the absorption capacity of
SO2 per hectare of forest land is 8165 kg. It is calculated
that the forest land in Alar City absorbs 1282648 tons of
SO2 per year. Based on the cost of SO2 treatment of 3,000
yuan per ton, if there is no SO2 absorption by forest land,
the cost of eliminating SO2 is 38.47 million yuan.
4.5.2 The Value of NOx Absorption
At present, the cost of denitrification treatment of
automobile exhaust is 1.16 million yuan per ton. One
hectare of forest land can absorb 2,380 kg of nitrogen
oxides a year, and it can be calculated that the functional
value of nitrogen oxides absorbed by existing forest land
in Alar City is 101.6 million yuan.
Therefore, the total economic value of ecological
services in Alar City to purify the environment is 140.07
million yuan.
4.6 Total Value of Ecosystem Service Functions
This study combines the physical geography and
socio-economic conditions of Alar City, and uses the
method of ecological economics to initially calculate the
economic value of some ecological service functions of
the ecosystem in Alar City (Table 4). The results show
that the total economic value of the ecosystem service
function of Alar City is 1.3365 million yuan. From this
incomplete estimate, it can be found that the ecological
service function of the ecosystem of Alar City has huge
ecological and economic benefits.
From the above calculation results, it can be seen that
the total value of the ecosystem service function in Alar
City in 2021 is as follows: carbon fixation and oxygen
release, environmental purification, soil conservation,
water conservation, and climate regulation.
5. Conclusions
Comprehensive consideration of the ecosystem
service function of the ecological environment of Alar
City has huge ecological benefits. Its urban environment
is prominent in the ecosystem service functions of soil
protection, climate regulation, and water conservation,
which can reduce soil erosion, inhibit land salinization
and desertification, improve local climate, and alleviate
water shortages. It plays a vital role. From a long-term
perspective, it will not only alleviate the fragile ecological
environment of the study area, but also improve the local
economic benefits.
In the area structure of grassland, wetland, woodland,
natural reserve and water area, although the area of
wetland is the smallest, the value of ecological service
function is second only to grassland. Due to the large area
of natural reserve, its indirect service value is still inferior
to grassland, woodland and wetland. Through research,
it is found that the effective use of ecosystem service
function value is not only related to the distribution area,
but also has an important relationship with the material
quality and value equivalent of the protection of the
ecological environment. This requires full consideration
of the actual nature of the research area in the process of
measuring the ecological value. Environmental conditions
to improve the accuracy of the measurement results.
Table 4. The total value of ecosystem services in Alar City
Function type Regulate the climate
Carbon fixation and
oxygen release
Conserve the soil Conserve water Purify the environment
Total value (ten thousand
yuan)
432 113660 1404 862 14007

24
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25
Nyong Princely Awazi,
Department of Forestry and Wildlife Technology, College of Technology, The University of Bamenda, Cameroon;
Email: awazinyong@uniba.cm; nyongprincely@gmail.com
REVIEW
Agroforestry for Climate Change Adaptation, Resilience Enhancement
and Vulnerability Attenuation in Smallholder Farming Systems in
Cameroon
Nyong Princely Awazi*
Department of Forestry and Wildlife Technology, College of Technology, The University of Bamenda, Cameroon
Article history
Received: 31 December 2021
Accepted: 20 January 2022
Published : 27 January 2022
The adverse impacts of climate variability and change are felt mostly
by smallholder farmers and smallholder farming systems where rain-
fed agriculture is predominant. Continuous dependence on rain-fed
agriculture has led to declining crop productivity and crop failure in
most cases as weather patterns shift which is very problematic for crop
growth. Agroforestry which is one of the climate-smart, environmentally
benign and agroecological practices has been found to mitigate climate
change adversities while fostering adaptation, enhancing resilience and
attenuating vulnerability especially in smallholder farming systems.
However, in Cameroon, limited empirical research has been done to
ascertain the role played by agroforestry in climate change adaptation,
resilience enhancement and vulnerability attenuation. This paper which is
based on an in-depth review of literature was undertaken to uncover what
has been done so far in terms of empirical studies tackling the role played
by agroforestry in climate change adaptation, resilience and vulnerability
attenuation in Cameroon. It was found that most of the empirical studies
have been carried out in one agroecological zone – the western highlands of
Cameroon, showing that smallholder farmers adopt different agroforestry
practices in the face of climate change with the most common being home
gardens with livestock, home gardens without livestock, scattered trees on
croplands, improved fallows, live fences/hedges and windbreaks, coffee-
based agroforestry, cocoa-based agroforestry, apiculture-based agroforestry,
fodder banks, and plantation crop-based agroforestry practices. These
agroforestry practices provide a plethora of ecosystem services categorized
into provisioning, supporting, regulating and cultural which play an
important role towards fostering climate change adaptation, enhancing
resilience and attenuating vulnerability in smallholder farming systems.
From the findings uncovered by this study, it is imperative for more
empirical studies to be carried out in the other four agroecological zones of
Cameroon where there is a paucity of information regarding the role played
by agroforestry towards fostering climate change adaptation, enhancing
resilience and attenuating vulnerability in smallholder farming systems.
Keywords:
Climate change
Agroforestry
Smallholder farmers
Smallholder farming systems
Vulnerability
Adaptation
Resilience
Cameroon

26
1. Introduction
Smallholder farming systems are the most dominant
farming systems in the developing world and they
contribute towards feeding over half of the population in
developing countries [1]
. These farming systems which
are often less than 2 hectares are used for the cultivation
of crops like maize, beans, millet, sorghum, coffee, tea,
cocoa, oil palms, plantains, banana which supply the
nutrient needs of the population [2]
. However, smallholder
farming systems are today severely threatened by
changing weather patterns and recurrent extreme weather
events induced by global warming and climate change [3]
.
The adverse impacts of climate change on smallholder
farming systems are having ripple effects on smallholder
farmers as crop productivity decline and crop failure are
becoming recurrent [1]
. This dire scenario is threatening
food security in the developing world where a majority
of the population relies on smallholder farms for their
daily food needs. Changing weather patterns and recurrent
extreme weather events are pushing smallholder farmers
to resort to and/or intensify climate-smart practices like
agroforestry [4]
. Agroforestry is a land use system that
has been practiced by farmers for centuries and it is well
known to provide several ecosystem services that benefit
farmers and other land users [5-10]
. However, in recent
years, farmers have been intensifying this practice in
order to benefit from its diverse ecosystem services which
helps them to foster climate change adaptation, enhance
resilience and attenuate vulnerability [11-13]
.
In Cameroon, studies have shown that agroforestry
provides different social, economic and environmental
benefits to agroforestry practitioners [5,10,14,15]
. The
diversity of services provided varies with the type of
agroforestry practice which could be home gardens with
livestock, home gardens without livestock, scattered
trees on croplands, improved fallows, live fences/hedges
and windbreaks, plantation crop-based agroforestry,
apiculture-based agroforestry, and fodder banks. These
different agroforestry practices and the ecosystem services
they provide are helping farmers adapt to, increase
resilience and reduce vulnerability to climate change. This
is because the provisioning, regulating, supporting and
cultural services of agroforestry helps farmers to withstand
stresses and shocks induced by climate change, ensures
food security through the supply of food, guards against
violent winds through windbreaks, reduces soil erosion,
improves underground water supply, provides shade,
buffers extreme climatic conditions, and sequestrates
carbon which helps to mitigate climate change.
Although agroforestry has an important role to play
towards reducing climate change vulnerability, enhancing
resilience and fostering adaptation, very limited empirical
research has been done in Cameroon to assess these
vital roles of agroforestry. This study which is based on
a review of literature was therefore undertaken to: (1)
identify common agroforestry practices in smallholder
farming systems in Cameroon faced with climate change;
(2) assess the role of agroforestry towards climate change
adaptation in smallholder farming systems in Cameroon;
(3) examine the role of agroforestry towards the
enhancement of resilience in smallholder farming systems
in Cameroon; (4) evaluate the role played by agroforestry
towards attenuating vulnerability in smallholder farming
systems in Cameroon; and (5) examine barriers to the
practice of agroforestry faced with climate variability and
change.
2. Climate Variability and Change in Cameroon:
Indicators and Impacts on Smallholder Farmers
Climate variability and change is a reality in Cameroon
evidenced by different indicators and adverse impacts
on farmers in particular and agriculture in general [16-25]
.
Cameroon’s diverse climatic, agro-ecological and relief
regions have been experiencing recurrent extreme weather
events in recent decades. Some of the common indicators
of climate variability and change perceived by farmers
have included droughts (especially in the northern parts
of the country), floods (especially in the coastal regions of
the country), pests and diseases, invasive plant and animal
species, high temperatures, extreme sunshine, bushfires
(especially in the northern regions, the western highlands
and the transition zones bordering the forested southern
part of the country), scanty and erratic rainfall, frequent
storms, prolong dry spells, and the extension of arid
lands towards the humid southern part of Cameroon. The
recurrence of these extreme weather events have major
repercussions on smallholder farmers who depend largely
on the existence of favourable climatic conditions for
cultivation. Thus, the major impacts of climate variability
and change on smallholder farmers and farming systems
include: crop failure, drop in crop yields, poor quality of
farm products, pest and disease attacks, destruction of
crops by bushfires, sickness and death of farmers, soil
infertility due to rampant soil erosion and soil degradation,
reduction in arable land, rain-fed agriculture increasing
becoming difficult necessitating irrigation, post-harvest
losses owing to poor climatic conditions and poor storage
facilities, rapid spread of weeds which destroy crops,
frequent blight episodes especially in crops such as tomato
and potato, disease attack of livestock especially small
ruminants such as goats, sheep and rabbits as well as pigs

27
including local fowls and table birds. The indicators of
climate variability and change and impacts on smallholder
farmers in Cameroon are varied. This in essence calls
for swift action towards promoting climate-smart and
environmentally friendly practices like agroforestry
which have stood the test of time. Agroforestry which is
seemingly a new nomenclature for an old practice has
been practiced for centuries by primitive communities
and peasant farmers around the world. However, faced
with climate variability and change, farmers are increasing
intensifying the practice in order to mitigate the adverse
impacts of climate variability and change while enhancing
resilience, reducing vulnerability and improving adaptation.
3. Climate Change and Common Agroforestry
Practices of Smallholder Farmers
Cameroon being a country found in the tropics, is
bound to bear the brunt of current and predicted changes
in climate. This is worsened by the limited adaptive
capacity of the population (especially smallholder farmers)
as well as high dependence on rain-fed agriculture by
farmers. Thus, in the face of climate change adversities,
most smallholder farmers have been modifying their
smallholder farming systems by integrating and/
or intensifying the practice of agroforestry. The most
common agroforestry practices of smallholder farmers in
the face of climate variability and change include: home
gardens with livestock, home gardens without livestock,
scattered trees on croplands, improved fallows, live
fences/hedges and windbreaks, coffee-based agroforestry,
cocoa-based agroforestry, apiculture-based agroforestry,
fodder banks, oil palm-based agroforestry, rubber-based
agroforestry, banana-based agroforestry [26-33]
.
Home gardens with livestock and home gardens
without livestock are practiced around homesteads where
tree/shrub species like plums, mangoes, guavas, bittterleaf,
oranges, avocados, oil palms, coconut, Calliandra,
Leucaena, and others such as cypress and Eucalyptus are
integrated with crops such as plantains, cocoyams, yams,
cassava, maize, beans, vegetables as well as livestock like
pig, goats, sheep and poultry. Scattered trees on croplands
is an agroforestry practices where trees/shrubs are dotted
all over the farm plot of a farmer. These tree/shrub
species are either planted by the farmer or deliberately
maintained during the cultivation of the farm. Most of the
tree/shrub species integrated in these farm plots are either
biofertilizing species, fruit trees, fuelwood trees, trees for
windbreaks, trees to control soil erosion, trees for building
materials etc. Common crops integrated in the system
include food crops like maize, beans, yams, cocoyams,
cassava, sweet potato, potato, vegetables etc. Improved
fallows are also increasingly being intensified by farmers
in the face of climate change. These improved fallows are
mostly made up of biofertilizing species like Tephrosia
spp, Leucaena spp, Sesbania spp, Calliandra calothrysus
etc. Tree-based biofertilising species like Leucaena spp
and Calliandra calothrysus are integrated simultaneously
with crops while shrub-based biofertilizing species like
Tephrosia spp and Sesbania spp harvested and used as
mulch during the cultivation of crops in order to improve
soil fertility. Common crops cultivated using improved
fallows include cocoyams, maize, beans, groundnuts,
yams, cocoyams, cassava, and vegetables. Live fences/
hedges and windbreaks are equally used by farmers to
limit the impacts of climate change. Farmers cultivating
crops such as banana and plantains as well as rubber,
coffee and cocoa have been noted to use live fences/
hedges and windbreaks like Eucalyptus, cypress and
bamboo. Plantation crop-based agroforestry practices
like coffee, banana, rubber, oil palm and cocoa are also
very common. They are increasingly being intensified by
farmers faced with the adversities of climate variability
and change in Cameroon. These plantation crop-based
agroforestry practices are increasingly integrating more
biofertilizing tree/shrub species, fruit trees as well as
windbreaks which make the systems more resilient to
extreme climate events. Fodder banks are also increasingly
being used by farmers in the face of climate variability
and change. Owing to the scarcity of food to feed animals
like pigs, goats, sheep, rabbits and fowls, farmers have
resorted to fodder banks/cut and carry systems in order to
meet the food needs of the livestock being reared.
The aforementioned agroforestry practices can be
classified into three major agroforestry systems including:
agrosilvicultural, silvopastoral and agrosilvopastoral
systems. Agrosilvicultural agroforestry systems are
systems that integrate trees/shrubs and crops. Examples
of practices that fall under this system are: home gardens
without livestock, scattered trees on croplands, improved
fallows, plantation crop-based agroforestry practices etc.
Silvopastoral systems are those that integrate trees/shrubs
with livestock/pasture with the main examples being
trees on pasturelands and fodder banks. Agrosilvopastoral
systems are those that integrate trees/shrubs with crops as
well as livestock/pasture with examples being plantation
crops with livestock/pasture as well as home gardens
with livestock. These different agroforestry systems and
practices are increasingly being intensified by farmers all
over Cameroon in a bid to mitigate the impacts of climate
change, enhance resilience, reduce vulnerability and
improve adaptation.

Journal of Atmospheric Science Research | Vol.5, Iss.1 January 2022

Journal of Atmospheric Science Research | Vol.5, Iss.1 January 2022

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Journal of Atmospheric Science Research | Vol.5, Iss.1 January 2022