







































Ecology, Economy and Society–the INSEE Journal 6(2): 33-57, July 2023 

RESEARCH PAPER 

Wetlands and Ecosystem Services: Empirical 
Evidence for Incentivising Paddy Wetlands 

M. Manjula, Girigan Gopi and Vipindas P  

Abstract: Wetland paddy agro-ecosystems are recognized as important human-
made wetland systems. Realizing that paddy lands are important ecological systems, 
the state of Kerala in southern India passed an act in 2008 preventing their 
conversion to other uses. The state provides subsidies and production bonuses to 
encourage paddy farmers and imposes penalties for non-compliance. However, the 
economic benefits associated with the conversion of paddy lands are considerably 
higher than the current subsidies and bonuses. As such, the conversion of paddy 
lands continues unabated despite the incentives and disincentives provided in the 
act. This study examines the ecological rationale for preventing paddy land 
conversion through a comparative assessment of the ecological health of paddy 
lands against that of lands with competing uses. Ecological health is assessed in 
terms of the amphibian population—specifically, frog abundance and diversity 
across different land uses, as frogs are considered bio-indicators of ecological 
health. The results reveal that the conversion of paddy lands adversely affects the 
survival of amphibians, especially frogs, thus emphasizing the role of paddy lands 
in maintaining the ecological health of a region. The study also provides empirical 
evidence for creating “Pigouvian subsidies” or ecological incentives for paddy 
farmers.  

Keywords: Ecological health, Pigouvian subsidy, Amphibian diversity, Paddy 
wetlands, Kerala, India 

 

 

 
 Faculty, School of Development, Azim Premji University, Bengaluru, Karnataka. 
manjula.m@apu.edu.in  

 Principal Development Coordinator, CAbC, M.S. Swaminathan Research Foundation, 

Wayanad, Kerala. girigan@mssrf.res.in  

 Development Coordinator, CAbC, M.S. Swaminathan Research Foundation, Wayanad, 
Kerala. vipindas@mssrf.res.in  

Copyright © Manjula, Gopi and Das 2023. Released under Creative Commons Attribution © 

NonCommercial 4.0 International licence (CC BY-NC 4.0) by the author.  

Published by Indian Society for Ecological Economics (INSEE), c/o Institute of  Economic 

Growth, University Enclave, North Campus, Delhi 110007.  

ISSN: 2581–6152 (print); 2581–6101 (web).  

DOI: https://doi.org/10.37773/ees.v6i2.985  

 

mailto:manjula.m@apu.edu.in
mailto:girigan@mssrf.res.in
mailto:vipindas@mssrf.res.in
https://doi.org/10.37773/ees.v6i2.985


 Ecology, Economy and Society–the INSEE Journal [34] 

 

1. INTRODUCTION 

Wetlands, both natural and human made, are a rich source of ecosystems 
services (Maltby and Acreman 2011; MEA 2005). They are critical natural 
resources that provide various socio-economic and environmental benefits 
to local communities (Dixon and Wood 2003). The role of wetlands in 
contributing to the Sustainable Development Goals (SDGs) has been well 
documented (Jaramillo et al. 2019). The SDG targets that have considerable 
relevance to wetlands are those related to “improving water quality”, 
“sustainable food production”, and “sustainable management of resources”. 
Wetlands are a potentially valuable agricultural resource (McCartney and 
Houghton-Carr 2009). Wetland agriculture, if sustainably managed, could 
play a significant role in promoting food security and income (Dixon and 
Wood 2003). The maintenance of wetlands’ ecosystem services depends on 
their ecological character. Any changes in the ecological character of 
wetlands alters the ecosystem service delivery, impacting human well-being 
(MEA 2005). Hence, the conservation of wetlands—both natural and 
human made—is essential to maintain the ecosystem services flow, which 
will contribute to achieving the SDGs.  

The state of Kerala in southern India enacted The Kerala Conservation of 
Paddy Land and Wetland Act (KCPLW Act), 2008, with the twin objectives 
of promoting agricultural growth and preserving ecological systems (Chitra 
2016). This act prohibits the conversion of wetlands and paddy lands for 
other land uses—agricultural or non-agricultural. The law directs the state 
to provide incentives to paddy farmers, and accordingly, the state extends 
special subsidies (US$15 per hectare [ha]) and production bonuses to the 
tune of US$67 per ha per season to paddy farmers, to encourage them to 
continue paddy cultivation. The penalty for non-compliance includes 
imprisonment for 6 to 11 months and a fine in the range of US$610 to 
US$1,220. But such a carrot-and-stick approach has been unsuccessful in 
preventing paddy lands from being converted to other lands, as the forgone 
benefit or opportunity cost of conservation is very high. From 1985–1986 
to 2019–2020, an estimated 75% of the area that had been under paddy 
cultivation was converted for other land uses in Kerala (GoK 2021). The 
major competing crops in Kerala are banana and areca nut, both of which 
have high commercial value.1 

 
1 The sequence of conversion of paddy lands in Kerala is as follows: first it gets converted to 

banana, and after the cultivation of banana for more than five consecutive years, areca nut 
is planted. Conversion to banana is considered a reversible one, while conversion to areca 
nut, a plantation crop, is irreversible. Once paddy land gets converted to areca nut, it loses 
its wetland characteristics and can be easily put to non-agricultural uses. 



[35] Manjula, Gopi and Das 

 

Paddy wetlands are privately owned agro-ecosystems and often the only 
source of livelihood for most farmers. Any private land use choice by paddy 
farmers involves a trade-off between short-term profitability and long-term 
environmental sustainability. A study on the relative profitability of crops, 
carried out by the State Department of Agriculture, reveals that the average 
cost of cultivating2 paddy is in the range of US$8263 to US$907 per ha 
across the three cropping seasons in a year. The average costs of cultivating 
banana and areca nut are US$2,680 per ha and US$1,262 per ha, 
respectively.4 The average net return per ha for paddy is in the range of 
US$418 to US$742, while for banana and areca nut, the returns are 
US$3,723 and US$1,918 per ha, respectively—six and three times higher 
than that of paddy (GoK 2022). 

The production bonus and subsidy given by the government, which 
amounts to US$82 per ha of paddy land, neither compensates for the cost 
of cultivating paddy, nor bridges the huge profit gap between paddy and its 
competing crops. Thus, paddy remains an economically unviable option for 
farmers despite the state’s focused support for paddy cultivation. 
Nevertheless, the KCPLW Act, 2008, mandates that paddy farmers 
continue paddy cultivation to sustain the ecological system of the state (a 
positive externality), which results in high private costs for the farmers. 
Given this background, the study compares the ecological health of wetland 
paddy vis-à-vis that of competing land uses and critically examines the 
rationale for conserving paddy lands to sustain the ecological system of the 
state. This assessment provides empirical evidence in support of the 
rationale behind offering ecological incentives to paddy farmers, who bear 
the costs of providing this social benefit. 

1.2. Rationale for the Study 

Environmentalists and ecologists worldwide have contrasting views on the 
utility of paddy wetlands. One section recognizes paddy lands as human-
made wetlands that play a significant role in groundwater recharge, water 
regulation, flood and drought control, and conservation of biodiversity, in 
addition to their primary role in food production (Iwasaki et al. 2012; 
Blackwell and Pilgrim 2011; Shivakoti and Bastakoti 2010). They emphasize 
that paddy systems are landscapes that are not only integral to the food and 
livelihood security of people but are also a valuable source of ecosystem 
services. The habitat services and biodiversity conservation services offered 

 
2 The cost presented here is Cost A, which includes all kind of expenses (paid out costs) 

actually incurred by the cultivators. 
3 US$1 = ₹82. 
4 Banana is an annual crop and areca nut is a perennial, while paddy is a 60- to 90-day crop. 



 Ecology, Economy and Society–the INSEE Journal [36] 

 

by wetland paddy fields are well documented as are their regulating services 
in terms of eco–disaster risk reduction (Naoki et al. 2015; (Osawa. Nishida, 
and Oka 2020). Hence, wetland paddy is also increasingly being touted as 
valuable green infrastructure (Osawa, Nishida, and Oka 2022). However, a 
section of environmentalists’ view paddy lands as contributing to 
greenhouse gas emissions and thereby to global warming (Singh et al. 2022; 
Bautista and Saito 2015; Wang et al. 2017). 

In short, there exist conflicting views regarding the 
ecological/environmental utility of paddy wetlands, and land use decisions 
involve trade-offs between short-term profitability and long-term ecosystem 
sustainability. A key determinant of the ecosystem services potential of 
wetlands is their ecological health. An important ecosystem service of 
paddy fields is their role in facilitating biodiversity—both flora and fauna 
(Edirisinghe and Bambaradeniya 2006). The loss of paddy ecosystems is 
said to have a profound influence on biodiversity, inevitably disturbing the 
ecological balance (Luo, Fu, and Traore 2014). Hence, in studies comparing 
land use changes involving paddy, a key element of comparison is the 
gain/loss in useful biodiversity. The present study adopts a similar 
approach. Although paddy lands are home to various flora and fauna, our 
study quantifies the amphibian diversity, with a specific focus on frogs. 

1.3. The Frog as a Bio-indicator for Ecosystem Health and Services 

Among the faunal species found in paddy lands, frogs are common and 
representative of the health of the ecosystem (Sato and Azuma 2004). They 
are natural enemies of crop pests and are, therefore, good bio-control 
agents. Frogs are considered keystone species in food webs as they prey on 
arthropods, while they in turn are prey to snakes, birds, and even humans 
(Tsuji et al. 2011; Naito and Ikeda 2007). A decline in their population is 
bound to have a significant impact on other organisms in the food web. 
Several studies have established that frogs provide regulatory and 
supporting services in tropical ecosystems, playing a major role in nutrient 
recycling, bioturbation, seed dispersal, and biological control, in addition to 
being a source of medicine and food (Hocking and Babbitt 2014). Most 
importantly, frogs are used as bio-indicators of ecological health as they are 
highly sensitive to changes in ecosystems (Baharuddin, Ramli, and Othman 
2015; Duré et al. 2008; Parmar, Rawtani, and Agrawal 2016; Samantha et al. 
2015; Simon et al. 2011). The response of frogs to ecosystem changes has 
been used as an indicator in studies on the impacts of anthropogenic 
activities, habitat fragmentation, and general ecosystem stress (Beebee and 
Griffiths 2005; Cochard, Maneepitak, and Kumar 2014; Loumbourdis et al. 
2007). Furthermore, among the faunal species observed in paddy lands, 



[37] Manjula, Gopi and Das 

 

frogs are unique in that they need both aquatic (e.g., paddy) and terrestrial 
habitats (e.g., banana and areca nut) to complete their life cycle (Matsuno et 
al. 2006; Parmar, Rawtani, and Agrawal 2016). Thus, using frogs as an 
indicator of ecosystem health for a comparative analysis across land uses is 
justified. 

The impact of land use changes and the effect of environmental 
management in paddy fields on frog species has been studied earlier by 
Naito et al. (2012) and Tsuji et al. (2011) in Japan. These studies showed a 
striking decline in frog distribution due to the conversion of paddy fields. 
Such studies linking land use changes to amphibian decline are scarce in 
India. In this context, our study establishes causality between land use 
changes and amphibian abundance and diversity. The results of this study 
show a strong association between paddy land conversion and decline in 
frog abundance and species diversity, thereby lending credence to the 
ecological argument in the KCPLW Act, 2008, for conserving paddy lands. 

2. MATERIALS AND METHODS 

This section describes the study area, methodology adopted, sampling 
framework, the data and details on the individual variables used in the 
study.  

2.1. Study Area 

This study was carried out in the Wayanad district5 in the state of Kerala in 
southwest India, which is in the ecologically fragile Western Ghat region 
(Figure 1). The district covers 2,131 sq km and is divided into three taluks 
and four blocks. Each block is further divided into panchayats, and each 
panchayat into wards.6  

The district has undergone major land use changes since the mid-1980s, 
with the area under paddy cultivation declining by more than 75% between 
1985–1986 and 2019–2020 (GoK 2022). Paddy farming in Wayanad, as in 
the rest of Kerala, is not remunerative, with net returns per ha from banana 
cultivation being three to four times that of paddy. However, several studies 
have shown that the conversion of paddy lands leads to adverse ecological 
outcomes like ground water depletion (Vinayachandran and Joji 2007), loss 
of diversity of wild edibles from paddy fields (Narayanan, Swapna, and 
Kumar 2004), and a loss of genetic diversity of rice (Kumar, Gopi, and 

 
5 A district is an administrative division within the state. 
6 Taluks and blocks are divisions within districts, and panchayats are local administrative 

divisions within blocks. 



 Ecology, Economy and Society–the INSEE Journal [38] 

 

Prajeesh 2010) in the district. The Western Ghat region is rich in amphibian 
fauna and is home to almost 60% of the known amphibian species in India 
(117 out of 224). Of this, 89 species are endemic to the region (Daniels 
1992; Myers et al. 2000). 

Figure 1: Wayanad District Map 

 

Source: Authors’ creation based on Google Maps, accessed on 16 December 2022. 

2.2. Methodology 

The study adopted a functional form to estimate the ecosystem services 
gain/loss due to land use changes. The ecosystem services being measured 
are frog abundance and frog species diversity. The functional form is 
broadly denoted as ES = f(LU, Xn) + u, where  

• ES is the ecological service measured in terms of frog abundance 
and species diversity 

• LU is the land use (paddy, banana, and areca nut in this study) 

• Xn are the other plot-level explanatory variables like (i) biophysical 
parameters, (ii) agronomic practices, (iii) boundary effect, (iv) plot 
history 

• u is the error term. 
Visual encounter surveys and male call recording methods were used to 
make plot-level measurements of frog abundance and species diversity 
across the different land uses. Measurements were taken between 7 and 11 
pm on two occasions: (i) during peak monsoon (July–August) and (ii) when 



[39] Manjula, Gopi and Das 

 

the monsoon was receding (September–October). Along with the number 
of frogs and the species diversity, plot-level biophysical variables like 
temperature, humidity, pH, and water levels in fields were measured. Apart 
from the ecological measurements, other plot-level details that are expected 
to have an influence on these measurements were collected using a survey 
schedule. 

The outcome variables—frog abundance and frog species diversity—are 
non-negative count data. Hence, following Das (2011), a Poisson regression 
was used to estimate the impact of land use change and other plot-level 
explanatory variables on frog abundance and diversity. The details of the 
Poisson regression are given in Annexure A. 

2.3. Sampling Framework 

The sampling framework is provided in Annexure B. Plots are the units of 
sampling. A stratified purposive sampling procedure was adopted to select 
the plots. The strata are (i) agro-climatic zones, (ii) panchayats, (iii) wards 
within the panchayat. The district has three agro-climatic zones, and one 
representative panchayat from each of the zones was selected. Following 
this, wards were ranked in descending order by acreage and extent of 
equitable distribution of the crops being studied. Two or three wards with 
the highest ranks were selected from each panchayat. 

Contiguous plots of one acre and above under paddy, banana, and areca nut 
were included in the sample. GPS marking of the plots was done, and plot 
latitude and longitude coordinates, plot boundaries, and the distance from 
the next sample plot were recorded to ensure the required spatial distance 
between the sampled plots. Of the total sample of 178 plots, 62 were under 
paddy, 68 under banana, and 48 under areca nut cultivation. Ecological 
measurements like frog abundance and species diversity were recorded for 
the plots. Details regarding agronomic practices, plot history, and boundary 
details were also collected from the farmers working the plots.7 

2.4. Data and Variables 

Table 1 gives details regarding the variables, their nature, and their expected 
role in determining frog abundance and species diversity. 

 

 

 
7 If the land was on lease, details on agronomic practices were collected from the tenant 

farmers. 



 Ecology, Economy and Society–the INSEE Journal [40] 

 

Table 1: List of Variables, Definitions, and Expected Role in Frog Abundance and 
Species Diversity 

Name of Variable Nature of 
Variable  

Expected Role in Frog 
Abundance/Species 
Diversity 

Outcome Variable 

Frog abundance (numbers) Count data  

Frog species diversity (numbers) Count data  

Explanatory Variables 

(i) Land use 

Paddy, banana, or areca nut 
(paddy = 1; banana = 2, and 
areca nut = 3) 

Categorical  Shift from paddy is expected 
to exert a negative influence 

(ii) Biophysical Parameters 

Temperature (ºC) Continuous Negative/positive 

Humidity (percentage) Continuous Negative/positive 

pH (the degree of acidity or 
alkalinity of the soil in the plot) 
(numbers) 

Continuous Negative/positive 

Water level (cm) Continuous Negative/positive 

(iii) History and Boundary Effects 

History: Number of years that 
the plot has been under the 
particular land use 

Continuous Positive 

Boundary effects   

Road as border to the plot (1 if 
yes, 0 otherwise) 

Categorical Negative 

Fallow land as border to the 
plot (1 if yes, 0 otherwise) 

Categorical Negative/positive 

Water body as border to the 
plot (1 if yes, 0 otherwise) 

Categorical Positive 

(iv) Plot-level Agronomic Details 

Farmyard manure (1 if yes, 2 
otherwise) 

Categorical Positive 

Per-acre fertilizer use (kg) Continuous Negative 

Per-acre pesticide use (litres) Continuous Negative 

Per-acre man-days (numbers) Continuous Negative 

Source: Analytical Framework Proposed in the Study by Authors  

3. RESULTS 

This section presents the summary statistics of the outcome and 
explanatory variables used in the analysis. 

 



[41] Manjula, Gopi and Das 

 

3.1. Frog Abundance and Diversity across Land Uses 
Among the various plots, paddy fields had the highest abundance of frogs 
as well as species diversity (Table 2). The least abundance and species 
diversity was observed in banana plots. The coefficient of variation (CV) 
for frog abundance and species diversity was lowest for paddy and highest 
for banana plots. This indicates that paddy lands in Wayanad exhibit lesser 
variation in abundance and diversity across plots, compared to banana and 
areca nut plots. Frogs were observed to be “breeding”, “calling”, and 
“foraging” in paddy wetlands, while mostly “calling” and “foraging” in 
banana and areca nut plots. 

Table 2: Summary Statistics of Outcome Variables 

Outcome 
Variables 

Land Use Minimum Maximum Mean CV 

Frog 
abundance 

Paddy 3.0 56.0 30.0 0.41 

Banana 0.0 18.0 4.0 0.81 

Areca nut 3.0 21.0 10.0 0.48 

Frog species 
diversity# 

Paddy 1.0 5.0 3.0 0.32 

Banana 0.0 3.0 1.0 0.54 

Areca nut 1.0 4.0 2.0 0.47 

Source: Field-level ecological measurements. 
Notes: Paddy (N = 62); banana (N = 68); areca nut (N = 48). 
#Species diversity reported refers to the total number of species observed per plot 
across land uses and does not represent the actual number of different species 
observed across land uses. 
 

3.2. Plot-level Biophysical Parameters 

Not much variation was observed in temperature, humidity, and pH across 
land uses, with soils being generally acidic (Table 3). Variation in water 
depth was observed to be in the range of 4 to 11 centimetres (cm), with 
paddy reporting the greatest water depth. 

3.3. Plot-level Input Intensiveness and Plot History 

Input intensiveness and agronomic practices adopted have an impact on the 
floral and faunal diversity of plots. The intensive use of chemical inputs like 
synthetic fertilizers and pesticides and extravagant intercultural operations 
might negatively affect the abundance and diversity of faunal species 
(Cochard, Maneepitak, and Kumar 2014). 

Manure is used extensively by both paddy and banana farmers, with a 
higher proportion of banana farmers reporting the application of manure. 
The per-acre manure use for paddy is in the range of 0.5–2 tonnes, while 



 Ecology, Economy and Society–the INSEE Journal [42] 

 

Table 3: Plot-level Biophysical Parameters 

Explanatory 
Variable 

Land 
Use 

Minimum Maximum Mean CV 

Temperature 
(ºC) 

Paddy 22.8 27.8 25.0 0.03 

Banana 23.5 28.1 25.0 0.04 

Areca 
nut 

24.0 27.0 26.0 0.04 

Humidity 
(percentage) 

Paddy 62.0 85.0 73.0 0.09 

Banana 64.0 82.0 74.0 0.08 

Areca 
nut 

64.0 88.0 75.0 0.08 

Water depth 
(cm) 

Paddy 1.0 24.0 10.5 0.50 

Banana 1.0 16.0 4.0 0.54 

Areca 
nut 

2.0 8.0 4.3 0.37 

pH (numbers) Paddy 4.1 5.0 4.4 0.06 

Banana 3.9 5.3 4.7 0.07 

 Areca 
nut 

4.1 5.6 4.6 0.07 

Source: Field-level ecological measurements and farming practice survey. 
Note: Paddy (N = 62); banana (N = 68); areca nut (N = 48). 
 

for banana, it is in the range of 1–8 tonnes. In the case of paddy, the 
manure mainly consists of cow dung, either from livestock at home or 
bought from the market. In the case of bananas, the manure is largely 
bought, and consists of cow dung, bone meal, and pig and poultry manure. 

Fertilizer and pesticide use are also highest in banana plots (Table 4). The 
least amount of fertilizer and pesticide use is reported in paddy plots. On 
average, about five to six different fertilizers are used in banana plots, of 
which many are complex fertilizers.8 In paddy plots, however, there is a 
predominant use of straight fertilizers9 like urea and potash. The frequency 
of fertilizer application per season ranges from three to seven times for 
banana, while for paddy, fertilizer is applied only once or at most twice. 
Pesticide use is higher for banana, especially during fruit maturation. It has 
been observed that many farmers drench the banana bunches with 

 
8 Complex fertilizers or compound fertilizers have more than one primary nutrient. 

The primary nutrients are nitrogen, phosphorous, and potassium. 
9 Straight fertilizers have only one primary nutrient. 



[43] Manjula, Gopi and Das 

 

pesticides. In addition, they apply phorate to the soil to ward off rodents. 
Areca nut cultivation also involves high use of Bordeaux mixture, a 
fungicide. Paddy plots use the least quantity of pesticides. 

Table 4: Input Use and Plot History 

Crop Minimum Maximum Mean CV Total 

Per-acre Fertilizer Use (Kg) 

Paddy 0.0 300.0 78.0 0.93 62.0 

Banana 200.0 3,600.0 1,203.0 0.49 68.0 

Areca nut 0.0 900.0 94.0 1.90 48.0 

Per-acre Pesticide Use (Litres) 

Paddy 0.0 30.0 0.7 5.7 62.0 

Banana 0.0 210.0 8.1 3.6 68.0 

Areca nut 0.0 67.4 6.0 2.0 48.0 

Per-acre Labour Man-days (Numbers) 

Paddy 0.0 140.0 51.0 0.54 62.0 

Banana 5.0 221.0 90.0 0.56 68.0 

Areca nut 0.0 126.0 42.0 0.91 48.0 

History of the Plot (Years) 

Paddy 15.0 66.0 51.0 0.19 62.0 

Banana 2.0 42.0 17.0 0.48 68.0 

Areca nut 10.0 35.0 23.0 0.27 48.0 

Source: Plot-level farming practice survey. 

Bananas require the highest number of man-days—the labour includes 
making drainage channels, applying fertilizer, applying pesticide, protecting 
the crop from the wind, and harvesting. Unlike in the case of paddy, those 
employed in banana cultivation are mostly male. Paddy cultivation creates 
employment for local women, as key operations like transplanting and 
harvesting are done by them. 

3.4. Plot History and Boundary Effects 

The number of years that the land has been under a particular land use, and 
the type of land use within the boundary of the plot, is said to influence the 
ecological measurements of the plot. The number of years a plot has been 
constantly under a particular crop (plot history) range from 2 years for 
banana to 66 years for paddy. Note that prior to banana and areca nut 
cultivation, the plots were invariably under paddy (Table 4). 



 Ecology, Economy and Society–the INSEE Journal [44] 

 

The commonly observed boundaries for plots are roads, water bodies 
(streams, rivers, or canals), vacant/fallow plots, and other cropped fields 
(Table 5). Having a road as a boundary is expected to have a negative 
influence on the abundance of frogs, as there are chances of them being 
crushed to death by passing vehicles (Dhanukar and Padhye 2005). The 
presence of a water body is expected to positively influence the abundance 
and diversity of frogs. 

Table 5: Border Effect (Number of Plots) 

Crop  Road   

Water 
Bodies 

Fallow 
Land 

Other 
Crops 

 
Total 

Paddy 8.0 16.0 23.0 15.0 62.0 

Banana 35.0 11.0 6.0 16.0 68.0 

Areca 
nut 13.0 6.0 5.0 

24.0 48.0 

Source: Plot-level farming practice survey. 

Of the 62 paddy plots, 8 had roads as boundaries, 16 had water bodies, and 
23 had fallow lands. In the case of banana, 35 plots had roads on at least 
one or all sides, 11 had water bodies, and 6 had fallow land. Six areca nut 
plots had water bodies, 13 had roads, and 5 had fallow land as borders. 

3.5. Regression Results 

Sections 3.6 to 3.10 present the results from the Poisson regression analysis. 
To effectively tease out the impact of land use change on frog abundance 
and species diversity, a stepwise Poisson regression was run with a new 
variable added at each step. Altogether, five regression models were run. 
The results are presented in the subsequent sections. 

3.6. Frog Abundance 

Table 6 gives the Poisson coefficients for the explanatory variables on frog 
abundance. Sequential building of the Poisson regression with explanatory 
variables resulted in five Poisson regression outputs. Paddy is the reference 
land use category in the Poisson outputs. 

Banana and areca nut plots negatively influence the abundance of frogs, 
unlike paddy plots. This result is consistent across the five models and is 
significant at the 1% level. Plot water levels are observed to influence frog 
abundance positively and significantly across the models. 

 

 



[45] Manjula, Gopi and Das 

 

Table 6: Poisson Coefficients—Results of the Poisson Regression on Frog 
Abundance 

Outcome Variable 
(Frog Abundance) 

Model 1 Model 2 Model 3 Model 4 Model 5 

Explanatory Variables 
Banana (2) −2.124*** 

(0.116) 
−1.565*** 

(0.131) 
−1.242*** 

(0.141) 
−1.311*** 

(0.201) 
−1.394*** 

(0.237) 

Areca nut (3) 
(Paddy is the reference 
land use category) 

−1.141*** 
(0.084) 

−0.600*** 
(0.103) 

−0.501*** 
(0.101) 

−0.588*** 
(0.162) 

−0.577*** 
(0.166) 

Temperature (ºC)  0.045 
(0.035) 

−0.022 
(0.033) 

−0.022 
(0.031) 

−0.020 
(0.031) 

Humidity (%)  −0.017*** 
(0.006) 

−0.011** 
(0.005) 

−0.008 
(0.006) 

−0.008 
(0.006) 

Water level (cm)  0.061*** 
(0.009) 

0.055*** 
(0.010) 

0.052*** 
(0.011) 

0.052*** 
(0.011) 

pH (numbers)  −0.468*** 
(0.140) 

−0.560*** 
(0.137) 

−0.507*** 
(0.141) 

−0.507*** 
(0.139) 

Frog species diversity    0.198*** 
(0.038) 

0.212*** 
(0.037) 

0.209*** 
(0.038) 

Years under the crop 
(numbers)  

   −0.001 
(0.004) 

−0.001 
(0.004) 

Road as border (1 if 
yes, 0 otherwise) 

   −0.038 
(0.082) 

−0.038 
(0.085) 

Water body as border 
(1 if yes, 0 otherwise)  

   0.021 
(0.080) 

0.027 
(0.079) 

Fallow land as border 
(1 if yes, 0 otherwise) 

   −0.170** 
(0.086) 

−0.166* 
(0.088) 

Farmyard manure (1 if 
applied, 2 otherwise) 

    (0.083) 
0.000 

Per-acre fertilizer 
quantity (kg) 

    (0.000) 

−0.001 

Per-acre pesticide 
quantity (litres) 

    (0.002) 

−0.000 

Per-acre man-days 
(numbers) 

    (0.001) 

Constant 3.414*** 
(0.061) 

4.889*** 
(1.126) 

5.984*** 
(1.051) 

5.667*** 
(1.083) 

5.618*** 
(1.082) 

Pseudo R2 0.54 0.64 0.66 0.66 0.66 
Observations 178 178 178 178 178 

Source: Based on analysis of primary data collected in the project  
Note: Robust standard errors are in parentheses. 
***p<0.01; **p<0.05; *p<0.1. 
 



 Ecology, Economy and Society–the INSEE Journal [46] 

 

This result is also significant at the 1% level. Biophysical variables like soil 
pH have a negative influence on frog abundance, and the effect is 
significant at the 1% level across the models. Humidity also has a negative 
effect on frog abundance, but this variable is significant only in two of the 
Poisson regression models. Humidity is significant at the 1% level in one 
model, while it is significant at the 5% level in the other. 

The other explanatory variable—namely, frog species diversity—is positive 
and significant at the 1% level across models, wherever included. However, 
having a fallow border is observed to negatively influence frog abundance, 
and the effect is significant at the 1% level. Input intensiveness—captured 
through the variables per-acre use of fertilizer, pesticide, labour, and 
farmyard manure—is observed to have no effect on frog abundance across 
the models.  

3.7. Frog Species Diversity 

Table 7 has the Poisson regression results for frog species diversity. Here, 
again, paddy is the reference land use category. It can be observed that a 
shift from paddy to banana has a negative impact on frog species diversity 
across all the models, and the effect is significant at the 1% level. A shift 
from paddy to areca nut significantly and negatively affects frog species 
diversity only in Model 1. This is the model that has land use as the only 
explanatory variable. Once we add other explanatory variables, the impact 
of the shift to areca nut from paddy on frog species diversity is statistically 
insignificant. 

Biophysical variables like plot-level temperature, humidity, and water level 
have a significant influence on species diversity across all the models in 
which they are included. Plot-level temperature has a positive and 
significant impact on species diversity across models. This effect is 
significant at the 1% level across all models. Humidity has a negative impact 
on species diversity, and the effect is significant at the 1% level across the 
models. 

Water level in the plot and the consecutive number of years that a plot is 
under a particular land use (plot history) has a positive and significant 
influence on frog species diversity. The influence of water level is significant 
at the 5% level, while the number of years under the land use is significant 
at the 1% level across the models. Farmyard manure application has a 
negative influence on species diversity in the two models where it is 
included as an explanatory variable. The effect is significant at 5% in one 
model and 10% in the second model. 

 



[47] Manjula, Gopi and Das 

 

3.8. Marginal Effects: Frog Abundance and Species Diversity 

The Poisson coefficients reflect the nature of influence of the explanatory 
variables on the outcome variables, namely, abundance and species 
diversity. The coefficients of the variables cannot be directly interpreted as 
the magnitude of the effect. Hence, marginal effects are estimated to 
capture the magnitude of impact of the explanatory variables on the 
outcome variables. Table 8 lists the marginal effects of the explanatory 
variables on frog abundance and species diversity. 

3.9. Marginal Effects: Frog Abundance 

A shift to banana from paddy results in a reduction in frog abundance by 
16%, while a shift to areca nut results in a reduction in frog abundance by 
9%. A one-unit increase in water level increases the number of frogs in the 
plot by 0.8%. If the adjoining plot is fallow, it reduces frog abundance by 
3%. A one-unit increase in soil pH reduces frog abundance by 7%, whereas 
a one-unit increase in frog species diversity increases frog abundance by 
3%. 

3.10. Marginal Effects: Frog Species Diversity 

Shifting from paddy to banana would reduce the species diversity by 0.7%. 
A one-unit increase in temperature and water level in the plot would 
increase frog species diversity by 0.3% and 0.04%, respectively. However, a 
one-unit increase in humidity would reduce abundance by 0.02%. One 
more consecutive year under the same land use (plot history) would 
increase species diversity by 0.02%. Farmyard manure application would 
reduce species diversity by 0.3%. 

4. DISCUSSION 

From the Poisson regression results, it follows that shifting from paddy to 
banana or areca nut has adverse effects on both frog abundance and species 
diversity. Frog abundance is negatively impacted by shifting away from 
paddy to either banana or areca nut, while the impact on species diversity is 
more robust for a shift to banana when compared to a shift to areca nut. 
Paddy lands are not only important as breeding sites due to the presence of 
standing water but also as foraging sites (ecological data sheets). Cultivated 
paddy lands, compared to banana and areca nut lands, offer an advantage to 
frogs in terms of foraging, as insects and microorganisms thrive on them. 
This can also be attributed to the fact that of the three crops, paddy is 
associated with the lowest pesticide use, thus providing a conducive 
environment for the sustenance of faunal biodiversity in general. 
Furthermore, even the terrestrial frogs found in banana and areca nut plots 
need water bodies for their sustenance. Thus, the presence of cultivated  



 Ecology, Economy and Society–the INSEE Journal [48] 

 

Table 7: Poisson Coefficients (Poisson Regression Results)- Frog Species Diversity 

Outcome Variable: 
Species Diversity 

Model 1 Model 2 Model 3 Model 4 Model 5 

Explanatory Variables 
Banana (2) −0.848*** 

(0.077) 
−0.763*** 

(0.089) 
−0.474*** 

(0.163) 
−0.393** 
(0.180) 

−0.383** 
(0.178) 

Areca nut (3) 
(Paddy -reference 
category) 

−0.209*** 
(0.106) 

−0.134 
(0.155) 

0.112 
(0.251) 

0.123 
(0.261) 

0.125 
(0.259) 

Temperature (ºC)  0.117*** 
(0.035) 

0.109*** 
(0.033) 

0.113*** 
(0.031) 

0.118*** 
(0.030) 

Humidity (%)  −0.010* 
(0.005) 

−0.012** 
(0.006) 

−0.010* 
(0.006) 

−0.010* 
(0.006) 

Water level (cm)  0.015** 
(0.007) 

0.016** 
(0.008) 

0.017** 
(0.008) 

0.017** 
(0.008) 

pH (numbers)  −0.050 
(0.104) 

−0.058 
(0.110) 

−0.064 
(0.121) 

−0.065 
(0.124) 

Years under the crop 
(numbers) 

  0.009*** 
(0.003) 

0.009*** 
(0.003) 

0.009*** 
(0.003) 

Road as border (1 if 
yes, 0 otherwise) 

  0.079 
(0.078) 

0.064 
(0.076) 

0.070 
(0.079) 

Water body as 
border (1 if yes, 0 
otherwise) 

  −0.061 
(0.078) 

−0.057 
(0.082) 

−0.067 
(0.079) 

Fallow land as 
border (1 if yes, 0 
otherwise) 

  0.005 
(0.069) 

0.003 
(0.074) 

0.007 
(0.075) 

Farmyard manure (1 
if applied, 2 
otherwise) 

   −0.140** 
(0.071) 

−0.137* 
(0.072) 

Per-acre fertilizer 
quantity (kg) 

    −0.000 
(0.000) 

Per-acre pesticide 
quantity (litres) 

    −0.000 
(0.001) 

Per-acre man-days 
(numbers) 

    −0.001 
(0.001) 

Constant 1.082*** 
(0.041) 

−1.096 
(1.120) 

−1.124 
(1.090) 

−1.128 
(1.128) 

−1.287 
(1.139) 

Pseudo R2 0.08 0.10 0.10 0.10 0.11 
Observations 178 178 178 178 178 

Source: Based on analysis of primary data collected in the project  
Note: Robust standard errors are in parentheses. 
***p<0.01; **p<0.05; *p<0.1. 

 



[49] Manjula, Gopi and Das 

 

paddy fields with standing water for a large part of the year helps with the 
multiplication and sustenance of the amphibian population and promotes 
diversity within the agro-ecosystem. This is further corroborated by the fact 
that the level of water in the observation plots positively influenced frog 
abundance and species diversity across all regression models. 

Table 8: Marginal Effects of the Explanatory Variables  

Explanatory Variable Frog Abundance Frog Species Diversity 
Banana (2)     −15.81*** 

(2.56) 
−0.73* 
(0.34) 

Areca nut (3)    −9.26*** 
(2.65) 

0.31 
(0.36) 

Temperature (ºC) −0.35 
(0.47) 

   0.25*** 
(0.07) 

Humidity (%) −0.09 
(0.08) 

  −0.022* 
 (0.012) 

Water level (cm)     0.76*** 
(0.16) 

 0.037* 
(0.16) 

pH (numbers)    −6.78** −0.140 
  (0.59) (0.27) 
Frog species diversity     3.07*** 

(0.57) 
 

Years under the crop 
(numbers) 

−0.007 0.019** 

 (0.06) (0.06) 
Road as border (1 if yes, 0 
otherwise) 

−0.97 
(1.20) 

0.15 
(0.18) 

Water body as border (1 if yes, 
0 otherwise) 

0.72 
(1.13) 

−0.14 
(0.16) 

Fallow land as border (1 if yes, 
0 otherwise) 

−2.58* 
(1.18) 

0.015 
(0.16) 

Farmyard manure (1 if 
applied, 2 otherwise) 

−0.49 
(1.19) 

−0.30* 
(0.16) 

Per-acre fertilizer quantity (kg) 0.002 
(0.002) 

−0.00 
(0.00) 

Per-acre pesticide quantity 
(litres) 

−0.016 
(0.028) 

−0.00 
(0.002) 

Per-acre man-days (numbers) −0.008 
(0.02) 

−0.003 
(0.002) 

Source: Based on analysis of primary data collected in the project  
Notes: Standard errors are in parentheses.  
***p<0.01; **p<0.05; *p<0.1. 
Paddy is used as the reference land use category. 
 



 Ecology, Economy and Society–the INSEE Journal [50] 

 

Other biophysical variables like soil pH negatively influenced the 
abundance, but pH had no significant influence on species diversity. Paddy 
lands had the lowest mean soil pH, which could partly explain the decline in 
abundance that would be triggered by a shift away from paddy. However, 
the humidity of the microenvironment had a significant negative influence 
on species diversity, but its impact on abundance was not significant in 
models that included other explanatory variables such as plot history, 
boundaries, and agronomic details. Paddy lands reported the lowest mean 
humidity compared to banana and areca nut plots, thereby providing a 
conducive microenvironment for amphibians like frogs. 

Soil temperature had a positive and significant influence on species 
diversity. Areca nut plots had the highest mean soil temperature. This could 
explain to some extent the lack of significant impact of a shift away from 
paddy to areca nut on frog species diversity once soil temperature was 
included as an explanatory variable in the relevant Poisson regression 
models. The positive influence of temperature on species diversity is also 
corroborated by the number of species reported from areca nut plots in the 
sample. Descriptive statistics reveal that after paddy lands, areca nut plots 
had the largest number of species (Table 3). This could be because the soil 
temperature of areca nut plots is conducive to sustaining the life cycles of 
different species of frogs. Nevertheless, the number of individuals reported 
per species in areca nut plots was much lower compared to that in paddy 
plots. The fact that the number of individuals per species was highest in 
wetland paddy ecosystems is significant evidence of the role of paddy lands 
in maintaining the amphibian population density and species diversity, 
which was not seen with banana and areca nut. 

The positive, significant, and consistent influence of the explanatory 
variable “years under the crop”—which is reflective of plot history—on 
species diversity explains to some extent the reason for observing the 
highest diversity of species in paddy lands, followed by areca nut. Paddy 
lands had been used for the highest average number of consecutive years 
(51 years) without any change in land use, followed by areca nut (23 years). 
An interesting result is the negative influence of “presence of a fallow plot” 
adjacent to the observation plot on frog abundance. Fallow lands are mostly 
overgrown with weeds and shrubs and have poorly maintained bunds. 
Thus, they do not have adequate standing water for calling and breeding. 

To sum up, our empirical results suggest that paddy lands play a significant 
role in supporting frog abundance and diversity. Amphibian conservation 
through the conservation of paddy wetlands gains significance in 
Wayanad—the study area—as this district in Kerala is situated within the 
Western Ghats, a highly ecologically sensitive region and one of the eight 



[51] Manjula, Gopi and Das 

 

“hottest hotspots” of biodiversity (GoI 2011; Myers et al. 2000) in the 
world. Conservation of frogs, a key bio-indicator and keystone species in 
the food web, will help conserve the macro- and micro-biodiversity within 
the Western Ghat agro-ecosystems. The study results conform with those 
of Naito et al. (2012) and Tsuji et al. (2011), which showed a decline in frog 
abundance due to the conversion of paddy lands. The result provides 
strong empirical evidence for the role of paddy lands in sustaining 
ecosystem health and providing ecosystem services. Furthermore, paddy 
lands being human-made wetlands with all the characteristics of natural 
wetlands offer valuable ecological and environmental benefits to society 
(Iwasaki et al. 2012; Blackwell and Pilgrim 2011). The results of the study 
lend credence to the legislation in Kerala that regulates the conversion of 
paddy lands on grounds of ecological sustenance. 

Still, paddy farmers across Kerala incur significant personal losses by 
continuing with paddy cultivation, as is reflected in the benefits forgone due 
to conservation. The regulatory mechanism restricting paddy land 
conversion in the state of Kerala penalizes paddy farmers without 
adequately compensating them for private economic losses. In light of the 
results of the study, we argue that the current regulatory mechanism needs 
to be complemented by market-based policy instruments over and above 
the prevailing subsidy and production bonus to incentivize conservation 
efforts. This recommendation is in line with suggestions that call for the 
payment of an “ecological incentive” to paddy farmers, which were put 
forth in the draft Kerala State Agricultural Development Plan of 2013, and 
the Gadgil Committee recommendation to pay a “conservation service 
charge” to farmers who adopt environmentally sustainable farming 
practices in the Western Ghat region. The market-based policy instrument 
could be a “Pigouvian subsidy” or an “ecological incentive” that is at least 
equivalent to the opportunity cost of conservation, which is the “economic 
rent” forgone by paddy farmers who do not shift to banana—the first stage 
of conversion, which is still reversible. A shift to areca nut is considered a 
permanent conversion as paddy lands brought under areca nut lose their 
wetland characteristics, making it impossible to bring the land under paddy 
again. Hence, it is important to stop conversion when it is still reversible. 
Having said this, it is also important to acknowledge that an appropriate 
value for the Pigouvian subsidy or ecological incentive can only be arrived 
at through an economic valuation of the non-market ecosystem services 
provided by wetland paddy. 

5. CONCLUSION 

This study investigated the ecological rationale behind the restrictive 
regulations on paddy land conversion in Kerala, India. To accomplish this, 



 Ecology, Economy and Society–the INSEE Journal [52] 

 

a comparative analysis of the ecological health of paddy wetlands and its 
competing land uses—banana and areca nut—was done. Frog abundance 
and diversity were used as proxies to assess the ecological health of plots 
with alternate land uses because frogs are bio-indicators of ecological 
health. The study results establish that a shift away from paddy to banana 
and areca nut can have adverse effects on frog abundance and diversity. 

The role of paddy lands in sustaining frog populations goes beyond its 
provisioning services, such as food and feed. The ability of paddy lands to 
support frogs is reflective of their capacity to bolster ecological health. The 
results of the study provide evidence of the significance of paddy agro-
ecosystems in sustaining ecological health, which has larger societal 
benefits. 

However, paddy farming is estimated to be less economically viable, and 
paddy farmers, who supply valuable non-market ecosystems services, as 
also evidenced in this study, need to be compensated for their private losses 
if a socially desirable and environmentally responsible land use system is to 
thrive. The state, in addition to promulgating legislations controlling land 
use, should pitch in with a Pigouvian subsidy (ecological incentives) to 
encourage paddy farmers to continue to cultivate paddy, at the risk of 
personal economic losses, for larger societal benefit. This Pigouvian subsidy 
should be in addition to the existing production bonuses and subsidies for 
paddy farmers in Kerala. It should at least match the opportunity cost of 
conserving paddy lands and provide the “economic rent” forgone by not 
shifting to banana. As indicated earlier, a shift to banana is considered an 
intermediary conversion as it is still reversible. The aim of the Pigouvian 
subsidy would be to arrest the intermediary conversion. This suggestion is 
also in line with the idea of ecological/conservation incentives referred to in 
previous state policy documents. As indicated earlier, estimating the 
Pigouvian subsidy is an area of future research and necessitates an 
economic valuation of ecosystem services from paddy wetlands. 

Ethics Statement: I hereby confirm that this study complies with 
requirements of ethical approvals from the institutional ethics committee 
for the conduct of this research.  

Data Availability statement: The data used in this paper is available on 
request under condition that it will not be used for research or commercial 
purposes without the knowledge or prior consent from the authors. 

Conflict of Interest Statement: No potential conflict of interest was 
reported by the author. 

ACKNOWLEDGEMENTS 



[53] Manjula, Gopi and Das 

 

The authors acknowledge research funding from The South Asian Network 
for Development and Environmental Economics (SANDEE). A special 
acknowledgement is due to Subhrendu Pattnayak, Professor at Duke 
University, North Carolina, USA. 

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ANNEXURES 

Annexure A: Poisson Regression Function Equations 

The probability density function of a Poisson distribution is given by 

 

where  is the probability that the variable  takes a non-

negative integer value , and  is the mean (and the variance) of the 

variable , which is assumed to have a Poisson distribution. 

The marginal effect of variables on the probability of non-zero 
abundance/diversity can be estimated using the following equation: 

=  = – = exp (- ) , 

where  is the marginal effect of the jth variable on the expected 

abundance and species diversity of the ith plot. The marginal effects 
measure the expected change in probability of the outcome variables—frog 
abundance and species diversity—with respect to unit change in the 
explanatory variables. 

https://doi.org/10.3390/hydrobiology1030023
https://doi.org/10.1016/j.landurbplan.2011.08.005
https://doi.org/10.1371/journal.pone.0169254


[57] Manjula, Gopi and Das 

 

Table A1: Stepwise Poisson Regression Model Used in the Study – Variables 
Added in Each Model  

Outcome Variables Frog Abundance and Frog Species Diversity 

Models Explanatory Variables 

1 Land use 

2 Land use, biophysical parameters 

3 Land use, biophysical parameters, plot history, boundary effect 

4 Land use, biophysical parameters, plot history, boundary effect, manure 
use 

5 Land use, biophysical parameters, plot history, boundary effect, manure 
use, per-acre fertilizer use, per-acre pesticide use, and per-acre labour use 

Source: Analytical framework proposed in the study by the authors  

Annexure B: Sampling Framework  

Table A2: Sampling Framework 

No. Agro-climatic 
Zone 

Representative 
Panchayat 

Ward Numbers 

1 AES 1 (drought 
area) 

Nenmeni (block: Sulthan 
Bathery) 

18, 19, and 23 

2 AES 2 (valley 
paddy area) 

Kaniyambatta (block: 
Mananthavady) 

9 and 14 

3 AES 3 (humid, 
high-altitude area) 

Pozhuthana (block: 
Kalpetta) 

1, 2, 4, and 5 

Source:  Wayanad district data, Government of Kerala.  


