ARPITA SHARMA - FishAdapt · ARPITA SHARMA PRINCIPAL SCIENTIST ICAR-CIFE, MUMBAI INDIA. 01/11/2016...
Transcript of ARPITA SHARMA - FishAdapt · ARPITA SHARMA PRINCIPAL SCIENTIST ICAR-CIFE, MUMBAI INDIA. 01/11/2016...
01/11/2016
1
ARPITA SHARMA
ICAR-Central Institute of Fisheries EducationMumbai, India
POTENTIAL EFFECTS OF CLIMATE CHANGE IN RESERVOIR
FISHERIES: A GENDER ANALYSIS
POTENTIAL EFFECTS OF CLIMATE CHANGE IN RESERVOIR FISHERIES:
A GENDER ANALYSIS
ARPITA SHARMAPRINCIPAL SCIENTIST
ICAR-CIFE, MUMBAI
INDIA
01/11/2016
2
Climate change refers to any significant change in the measures of
climate lasting for an extended period of time→ temperature,
precipitation & wind patterns
Impacts of Climate change will not be uniform across the globe due to
differences in bio-physical & socio-economic conditions
(IPCC, 2007)
01/11/2016
3
Magnitude of impacts of climate change depends on vulnerability of
individual nations & adaptive capacity to face consequences.
vulnerability →degree to which a system is susceptible & unable to
cope with the adverse effects of climate change , including climate
variability & extremes.
Developing countries → more vulnerable → structural weaknesses & low
levels of resilience & adaptive capacity → South Asia → most vulnerable
region of the world.
Adaptive capacity → potential or capability of a system to adjust
to climate change , including climate variability and extremes to cope
with consequences
(Vincent, 2004 and IPCC, 2001)
India → severely impacted countries by climate change as the Indian
economy is well tied to natural resources & climate-sensitive sectors →
Agri, Fisheries & Forestry (Chung et al, 2006 )
India → 2nd largest producer of fish → 5.43% to global fish
production (FAO 2015)
Rural fishing population → largely depends on reservoir fisheries
→ livelihood (Bene 2003)
Karnataka → 3rd highest area of total inland water bodies → production
potential of 264000 MT/year → 9th position in inland fish production
(DAHD, 2013)
Bhadra reservoir is the 3nd largest reservoir in Karnataka
01/11/2016
4
Karnataka is likely to be more vulnerable to climate change than other
states
In terms of areas prone to drought, Karnataka is next only to
Rajasthan; 54% of Karnataka's geographical area is drought prone,
with drought affecting state's 176 taluks and 18 of its 30 districts.
Most parts of Karnataka could experience 1.5–2 °C warming →by as
early as 2030s under the likely high-emissions scenario(industrial
emission)
(Indian Institute of Science, 2014)
Climate change with reference to gender
Climate change is not gender neutral
Gender matters when it comes to vulnerability to climate change
Women and men play different roles in household livelihoods & therefore they experience the impacts of climate change differently
Household livelihood comprises of capabilities, assets & activities of individual
(CARE, PECCN, 2011)
01/11/2016
5
01/11/2016
6
Objectives
• To assess the vulnerability of fisheries
dependent livelihoods on climate change with
reference to gender
• To study potential effects of climate change on
livelihood of fishers
Locale of study
01/11/2016
7
Geographical mapping
Karnataka
60 Fishermen
60 Fisher
women
Bhadra reservoir
Village1
Village2
Village3
Village4
Village9
Village8
Village7
Village6
Village5
Total 120 samples
Sampling design
01/11/2016
8
Material and Methods used to study
objective 1
To assess the vulnerability of fisheries
dependent livelihoods on climate change
with reference to gender
Material and Methods used for assessing vulnerability of fisheries dependent livelihoods on climate change
• Composite livelihood vulnerability index approach→computes vulnerability indices by aggregating data for set of indicators
• Indicators used → exposure, sensitivity & adaptive capacity
• Under each indicator set of questions were asked to fishers (separately for fisher men and fisher women)
Exposure=10
Sensitivity =10
Adaptive capacity=10 (Rahman,2014)
01/11/2016
9
• Respondents were asked to rank each question on a scale
ranging from 0-4
• Quantitative assessment of indicators was done to compute vulnerability
scores using formula V=E*S*(1-AC)
Where,V= Vulnerability E= ExposureS= Sensitivity AC =Adaptive capacity
0 1 2 3 4
no climate change effect
less climate change effect
moderate climate change effect
high climate change effect
extremely high climate
change effect
Primary data →indicator → normalized (rescaled
from 0-1) by using equation
Where,
IndexSi = normalized value of an indicator
Si=actual value of the same indicator
Smin & Smax = minimum & maximum values of same
indicator respectively
After normalization sub indices were used to compute
vulnerability scores.
01/11/2016
10
• To test is there any significant difference between
perception of men and women about vulnerability due to
Climate change → Mann-Whitney U test
Hypothesis:
Ho: There is no significant difference between perception
of men and women about vulnerability due to Climate
change
H1: There is a significant difference between perception of
men and women about vulnerability due to Climate change
• To test any significant difference between perceptions
about Climate change between the villages →Friedman
test
Hypothesis:
• Ho: There is no significant difference between
perceptions about Climate change between the villages.
• H1: There is a significant difference between
perceptions about Climate change between the villages.
01/11/2016
11
In addition to this, study was done on
• Rainfall
• Temperature
• Water level
• Evaporation
details of Bhadra reservoir by the guage data obtained
from irrigation department of Bhadra reservoir,
Karnataka
Water level
TemperatureRainfall
Material and Methods used to study
objective 2
• To study potential effects of climate
change on livelihood of fishers
01/11/2016
12
Livelihood →adequate stock & flow of food and cash to meet basic needs.(conway 2002)
• Human capital: Labour capacity; education; skills.
• Natural capital: Land; Access to common property
resources.
• Financial capital: wages; access to credit.
• Physical capital: water supply; housing; Fishing crafts &
gears.
• Social capital: social status; discrimination against women;
strong links with family & friends; traditions of reciprocal
exchange.
Respondents were asked to score these questions on a scale ranging from 0-4
Where,0 −no effect
1−less effect
2−moderate effect
3−high effect
4−extremly high effect
In each capital different number of questions were asked to both
fishermen & women i.e.., questions were taken from livelihood framework
by CARE Human capital -8
Natural capital -9
Financial capital -6
Physical capital -10
Social capital -5
01/11/2016
13
Scores obtained from respondents were average to study the potential effects of climate change on livelihood of fishers
Scores of fisher men & fisher women were averaged separately to study who is more effected due to climate change
Total of both the scores were taken to measure the overall climate change effects on livelihood of fishers dependent on Bhadra reservoir
• To test is there any significant difference between perception
of men and women about effects of climate change on livelihood
capitals → Mann-Whitney U test
Hypothesis
Ho: There is no significant difference between perception of men
and women about potential effects of climate change on livelihood
capitals
• H1: There is significant difference between perception of men
and women about potential effects of climate change on
livelihood capitals
01/11/2016
14
To assess the vulnerability of fisheries dependent
livelihoods on climate change with reference to
gender
Results of objective 1
Primary data →indicator → normalized (rescaled
from 0-1) by using equation
Sub-indices → combined to create a composite vulnerability
index by using a multiplicative approach i.e..,
Where,
V= Vulnerability
E= Exposure
S= Sensitivity
AC =Adaptive capacity
01/11/2016
15
Parameters Men Women TotalExposure 0.66 0.75 0.71Sensitivity 0.64 0.72 0.68
AC 0.80 0.72 0.76Vulnerability
scores 0.34 0.40 0.370=No vulnerability
Above 0-0.2=Less vulnerability
0.2-0.4=Moderately vulnerable →Men
0.4-0.6=Highly vulnerable →Women0.6-0.8=v. high vulnerable
0.8-1=extremely vulnerable
V scores
AC
SensitivityExposure
Vulnerability scores
Limited ACSocial inequalities
Dependency onmen
Financial dependency
Unequal accessto reservoir
No decisionmaking power
Reasons
women are more vulnerable to climate change
(Arora, 2011)
01/11/2016
16
Parameters Z value P value Decision
Exposure -0.970 0.332 Accept Ho
Sensitivity -2.872 0.004 Reject Ho
Adaptive capacity -3.504 0.000 Reject Ho
Mann-Whitney U test
Hypothesis:Ho: There is no significant difference between perception ofmen and women about vulnerability due to climate change
H1: There is a significant difference between perception ofmen and women about vulnerability due to climate change
N 5
Chi-Square 6.061
df 8
Asymp. Sig.(P) 0.640
Friedman test
Hypothesis:
Ho: There is no significant difference between perceptions
about CC between the villages.
H1: There is significant difference between perceptions
about CC between the villages.
01/11/2016
17
050
100150200250300350
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Cms
Years
Average annual rainfall
“Region wise annual rainfall characteristics at Bhadra area- a case
study” → there is an uneven distribution of average annual normal
rainfall & rainy day in Bhadra reservoir area
Future higher intensity rainfall events with lesser rainy days are expected(Gowda and Kiran, 2013)
Source: Irrigation department, Karnataka
22
23
24
25
26
27
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Degr
ee ce
lsius
Years
Annual average Temperature
Over the years, reduction in size of Indian Major Carps is noticed by
fishers in Bhadra reservoir Eg: average size of Catla reduced from 8-9 kgs to 3-5 kgs
Reduced fish sizes due to increase in temperature →predicted, with
reductions individual maximum body weight projected from 2000 to 2050
under a high increase in temperature scenario (Cheung et al., 2012)
Source: Irrigation department, Karnataka
01/11/2016
18
http://www.nereusprogram.org/cop21-where-have-all-the-fish-gone-how-climate-change-is-displacing-marine-species/
-50
0
50
100
150
200
250
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
MFT
C
Years
Water Level
88.5
99.510
10.511
11.512
12.513
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
MFT
C
Years
Average Evaporation
Source: Irrigation department, Karnataka
01/11/2016
19
2006, 2008 and 2012 water level in the reservoir →reached below
dead storage level (dead storage of 8.50 BCF at RL of 631.54 mtrs above MSL)
Fast depletion of water levels →report say only 13.5tmc ft of water left
in the reservoir & the situation is worse in 2016 which are considered as
the indication of drought condition in near future of Bhadra reservoir.
(Times of India 2016, May 25)
Till last summer → maintain water dead storage level up to 140 to
145 ft → 113.4 ft ≈ reduction in water level of 31ft
(Bhadra CADA)
Environmental flows in Bhadra River, Karnataka → fishing activities
are reduced & existing riverine water flows leads to changes in
livelihood options.
•Even native fish, fish habitat and riverine fisheries have been
severely impacted by changes in the hydrological regime and water
quality.
•Fish catches have declined drastically, which badly affected the fishers
who are highly dependent on fishing for food and income.
•Large fish have apparently more affected → Fish diseases have also
increased. (Harish Kumara et.al..,2010)
01/11/2016
20
Inference → objective 1• Study has shown result that fisher women are more effected
compared to fishermen in Bhadra reservoir.
• When asked about present situation fishers responded that,
many fishers have migrated due to deficit fish catch observed
in Bhadra reservoir.
• Even in the media report (2015) it was mentioned that Bhadra
fishers livelihood is at stake fearing to which fishers are
vacating the villages (Vijaya Karnataka newspaper)
To study potential effects of climate change on
livelihood of fishers
Results of objective 2
01/11/2016
21
LivelihoodCapitals
Men Women All
Human 2.89 2.93 2.91
Social 2.68 2.60 2.64
Physical 2.69 3.06 2.88
Natural 2.59 2.93 2.76
Financial 3.16 3.16 3.16
Effects of climate change on livelihood capitals of fishers
0 −no effect; 1−less effect; 2−moderate effect; 3−high effect; 4−extremly high effect
Moderate to high effectWomen (Human, Physical, Natural ) > Men
0.00
1.00
2.00
3.00
4.00Human
Social
PhysicalNatural
Financial
Men
0.000.501.001.502.002.503.003.50
Human
Social
PhysicalNatural
Financial
Women
Effects of climate change on
livelihood capitals of fishers
Radar graph representation of livelihood capitals
01/11/2016
22
ParametersZ value P value
Decision
Human capital -0.244 0.808 Accept Ho
Physical capital -3.634 0.000 Reject Ho
Natural capital -2.585 0.010 Reject Ho
Social capital -2.513 0.012 Reject Ho
Financial capital -0.240 0.810 Accept Ho
Mann-Whitney U test
Hypothesis was framed and tested as follows;
Ho: There is no significant difference between perception of men and
women about potential impact of climate change on livelihood capitals
H1: There is significant difference between perception of men and
women about potential impact of climate change on livelihood capitals
Potential effect on livelihood capitals• Overall score for potential effect on livelihood capitals was 2.87.• Fishers perceived climate change to have a moderate effect on their
livelihood capitals. • Score for men was 2.80 and it was 2.94 for women • Women perceived that climate change will have more effect on
livelihood capitals.• Both men and women perceived that financial capital will be
affected more than other livelihood capitals with a score of 3.16.• Women perceived that natural and human capitals will have more
effect due to climate change with a score of 2.93. • Significant difference between the perception of men and women
about potential effect of climate change with reference to livelihood capitals i.e., natural, physical and social capitals for which P value is less than 0.05.
01/11/2016
23
Conclusion• Climate change affects fishing community making them
vulnerable. • Among the fishing communities, women are more
vulnerable. • This information should be applied to design climate
change interventions and programmes. • The unique vulnerabilities and needs of fishers and women
need to be mainstreamed into climate change policies. • Such mainstreaming of gender issues would help ensure
that policy and operational responses to climate change go further in terms of meeting the needs of one of the most vulnerable sectors of society.
01/11/2016
24
01/11/2016
25
Reference Allison, E. H. and Horemans, B., (2006). Putting the principles of the sustainablelivelihoods approach into fisheries development policy and practice. Marine policy , 30(6):757-766.
Alkire, S., & Seth, S. (2015). Multidimensional poverty reduction in India between 1999and 2006: World Development, 72, 93-108..
Arora-Jonsson, S. (2011). Virtue and vulnerability: Discourses on women, gender andclimate change. Global Environmental Change, 21(2), 744-751.
Bene, C. (2003). When fishery rhymes with poverty: a first step beyond the oldparadigm on poverty in small-scale fisheries. World development, 31(6), 949-975.
CARE (2011) Poverty, Environment and Climate Change Network (PECCN)
Cheung, W. W., Sarmiento, J. L., Dunne, J., Frölicher, T. L., Lam, V. W., Palomares, M. D.,... & Pauly, D. (2013). Shrinking of fishes exacerbates impacts of global ocean changes onmarine ecosystems. Nature Climate Change, 3(3), 254-258.
01/11/2016
26
Conway, T., Moser, C., Norton, A., & Farrington, J. (2002). Rights and livelihoods approaches: exploring policy dimensions. Natural Resource Perspectives, 78(May).
FAO (2009) State of the World Fisheries and Aquaculture 2008 Fisheries and Aquaculture Department, Rome.
Islam, M. M., Sallu, S., Hubacek, K., & Paavola, J. (2014). Vulnerability of fishery-based livelihoods to the impacts of climate variability and change: insights from coastal Bangladesh. Regional Environmental Change, 14(1), 281-294.
Gowda, K. K., & Kiran, K. K. (2013, November). Region Wise Annual Rainfall Characteristics at Study Bhadra Command Area–A Case Study. InInternational Journal of Engineering Research and Technology (Vol. 2, No. 3 (March-2013)). ESRSA Publications.
Manasi, S., Latha, N., & Raju, K. V. (2009). Fisheries and livelihood in Tungabhadra Basin, India: Current status and Future possibilities.
Rahman, M. M. (2014). Community perceptions and adaptation to climate change in coastal Bangladesh.
Solomon, S. (Ed.). (2007). Climate change 2007-the physical science basis: Working group I contribution to the fourth assessment report of the IPCC(Vol. 4). Cambridge University Press.
Online references
http://timesofindia.indiatimes.com/city/mysuru/Bhadra-dam-water-
at-dead-storage-level/articleshow/52426441.cms
http://www.thehindu.com/todays-paper/tp-national/tp-
karnataka/waterlevel-in-bhadra-dam-touches-184ft/article4972402.ece
http://www.thehindu.com/news/national/karnataka/cada-to-release-
bhadra-waters-into-canals-s-for-79-days-fromjan1/article7882460.ece
http://dmc.kar.nic.in/RL.pdf
http://www.nereusprogram.org/cop21-where-have-all-the-fish-gone-how-climate-change-is-displacing-marine-species/
01/11/2016
27
Stop climate change before it changes you