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