Social-ecological interactions in a disaster context: Puerto Rican farmer households’ food security after Hurricane Maria

Abstract

Islands are uniquely vulnerable to extreme weather events and food insecurities, and have additional response challenges due to their limited territories and economies, isolation, colonial legacies, and high dependence of food imports. Domestic farmers have a key role in producing food for island communities like Puerto Rico, which can safeguard food security when food importation may be challenging. Nevertheless, in the context of disaster, farmers themselves may be vulnerable to food insecurity and unable to contribute to domestic markets. This paper examines Puerto Rican farmers households’ food security in the aftermath of 2017’s Hurricane Maria using a social-ecological lens. Survey data from 405 farmers gathered eight months after Maria, coupled with biophysical data from the hurricane’s impacts (winds, rains, and landslides), was analyzed. Overall, 69% of farmers experienced at least one month of food insecurity in the aftermath of Hurricane Maria, and 38% reported persistent food insecurity (three months or more). A multinomial logistic regression suggests that biophysical impacts, but especially social factors, such as age and constraint access to external sources of support, are linked with persistent food insecurity. This suggests that the biophysical impacts of the hurricane interact with existing infrastructure and social resources to affect farmer vulnerability and the food environment in different ways. Thus, strengthening adaptive capacity in multiple domains can help farmers and vulnerable populations better navigate the disruptions faced during disasters to alleviate food insecurity.

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Environ. Res. Lett. 17 (2022) 044057 https://doi.org/10.1088/1748-9326/ac6004
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LETTER
Social-ecological interactions in a disaster context: Puerto Rican
farmer households’ food security after Hurricane Maria
Luis Alexis Rodríguez-Cruz1,2,3,∗, Nora ´
Alvarez-Berríos1and Meredith T Niles2,3,4
1International Institute of Tropical Forestry, United States Forest Service, Río Piedras, Puerto Rico
2Food Systems Graduate Program, University of Vermont, Burlington, VT, United States of America
3Gund Institute for the Environment, University of Vermont, Burlington, VT, United States of America
4Department of Nutrition and Food Science, University of Vermont, Burlington, VT, United States of America
∗Author to whom any correspondence should be addressed.
E-mail: lrodrig2@uvm.edu
Keywords: small island developing states, food insecurity, extreme weather events, vulnerability, adaptive capacity
Abstract
Islands are uniquely vulnerable to extreme weather events and food insecurity, and have additional
response challenges due to their limited landmasses and economies, isolation, colonial legacies, and
high dependence of food imports. Domestic farmers have a key role in producing food for island
communities like Puerto Rico, which can safeguard food security when food importation may be
challenging. Nevertheless, in the context of disaster, farmers themselves may be vulnerable to food
insecurity and unable to contribute to domestic markets. This paper examines Puerto Rican
farmers households’ food security in the aftermath of 2017’s Hurricane Maria using a
social-ecological lens. Survey data from 405 farmers gathered eight months after Maria, coupled
with biophysical data from the hurricane’s impacts (winds, rains, and landslides), were analyzed.
Overall, 69% of farmers experienced at least one month of food insecurity in the aftermath of
Hurricane Maria, and 38% reported persistent food insecurity (three months or more). A
multinomial logistic regression suggests that biophysical impacts, but especially social factors, such
as age and constraint access to external sources of support, are linked with persistent food
insecurity. This suggests that the biophysical impacts of the hurricane interact with existing
infrastructure and social resources to affect farmer vulnerability and the food environment in
different ways. Thus, strengthening adaptive capacity in multiple domains can help farmers and
vulnerable populations better navigate the disruptions faced during disasters to alleviate food
insecurity.
1. Introduction
Extreme weather events, such as hurricanes, are
becoming more intense in the growing climate crisis
[1,2]. These events can trigger disasters, often
prompting disruptions in the built and natural envir-
onments affecting livelihood activities [3–6]. Such
disruptions can generate a period of transitory or
episodic food insecurity, where people’s consecutive
access to adequate food that supports their wellbeing
is hindered [7,8]. During these periods, often unex-
pected or seasonal [9–11], people lack or have diffi-
culty accessing nutritious and culturally-appropriate
foods [7]. The length of these effects on people’s
food security may vary, due to the magnitude of the
impact, coupled with an affected populations’ vulner-
ability stemming from social-ecological characterist-
ics, such as race, sex, geography, economics, polit-
ics, ecosystem services, and biophysical aspects of a
place, among others. Social-ecological characterist-
ics may predispose some populations to be at higher
risk of harm, and may reduce their ability to recover
from disaster impacts [5,12–14]. This assertion is
increasingly true of small island developing island
states (SIDS) and territories (as well as low-income
societies), which have higher exposure and sensitivity
to extreme weather events [1,15–18].
In island systems, physical and economic access
to food at all times is often challenging due to sev-
eral characteristics: high dependence on imports and
© 2022 The Author(s). Published by IOP Publishing Ltd

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
marine supply chains, limited land to produce food,
small economies, high costs of food, critical infra-
structure and high population density in coastlines,
as well as trade and colonial histories with power
inequities [16,19–28]. Furthermore, most SIDS are
located in the tropics, and are facing the climate
crisis’s effects disproportionately [1]. These char-
acteristics may shape people’s adaptive capacity—
the assets and abilities that allow people to mitigate
and prepare for shocks, as well as to recover from
them, and transform their environment to better sus-
tain impacts [12,29–34]—which may contribute to
lengthening negative effects on food security after an
extreme weather event [35]. Yet, despite the unique
social-ecological characteristics of SIDS, very little
research has explored island food security following
disasters [20,27,28,36]. This paper examines Puerto
Rican farmer households’ food security in the after-
math of 2017’s category four: (Saffir-Simpson Hur-
ricane Wind Scale) Hurricane Maria. The analysis is
focused on farmers, who face high vulnerability to
natural hazards’ impacts due to their dependence on
natural resources, which mediates the sensitivity and
exposure they face to shocks [37].
Prevalent social (e.g. structural inequities, income
inequality) and biophysical conditions (e.g. hous-
ing disruption due to hurricane damage) generate
obstacles for people to have consecutive access to
food following a disaster [8,38–41]. For example, risk
factors, such as gender or poor physical health, as well
as difficult access to social or structural support, were
linked to food security levels after Hurricane Katrina
in the United States [39]. Impacts to infrastructure
and agricultural landscapes also shape the length of
negative effects to food security by hindering local
production, and household’s food access and sources
of income [35,42,43]. In the case of SIDS and other
net-importers, their susceptibility to market fluctu-
ations and impacts of extreme weather events abroad
also have an impact on food security [44,45]. As
such, understanding food security following a disaster
must encompass the multidimensionality of food
security in a social-ecological system, where natural
(e.g. climate patterns, ecosystem services, agricultural
resources) and social components (e.g. economic,
inequality, colonial legacies) intertwine and influence
individual outcomes [46–51]. Assessing farmers’ food
security over time during the recovery period from
an extreme weather event can provide an understand-
ing of how social-ecological dynamics shape disasters
[37,52,53], and what may contribute to reducing vul-
nerability to future extreme weather events and other
natural hazards more broadly [48,54]. This is import-
ant in SIDS where domestic production can buffer
against supply chain challenges following a disaster
[36,44,55].
Farmers are an important unique group of focus
to understand disasters and food security, given their
livelihood reliance on natural resources and their
potential ability to provide locally available food post-
disasters. Studies focused on continental smallholder
farmers, who often farm less than 10 hectares—
while employing different approaches and measures
of food security—show that farmer food security out-
comes are driven by a combination of social (e.g. sup-
port networks, income), physical (e.g. infrastructure
assets), agricultural (e.g. farm size), and demographic
characteristics (e.g. gender, income) [10,53,56–
59]. For example, agricultural diversity—production
diversity, as well as access to different markets and
sources of support—have been shown to decrease
farmer household food insecurity [10].
Research on Caribbean farmers has shown
that social factors play a key role in food secur-
ity outcomes. Studies have shown that Carib-
bean farmers with land tenure, access to diverse
markets and sources of income and support, see
less negative effects on their food security and
thus, cope better with extreme weather events
[19,36,60–63]. Yet, studies in the Caribbean have
mainly focused on Cuba, and the Caribbean Com-
munity (CARICOM)—to which Puerto Rico is not
a part of [19,60,61,64,65]. It is important to note
that the Caribbean is compose of islands of diverse
landmasses, many of which are not sovereign and
that are embedded in neocolonial relationships with
former metropolis [21,22,27]. Hence, studying this
issue in Puerto Rico, an unincorporated territory of
the United States, can increase our understanding of
how food security manifests in the context of disaster
beyond sovereign SIDS.
Besides the general research on (smallholder)
farmer food security, there is a growing body of evid-
ence exploring food security more generally during
and after extreme events, such as drought [66,67],
monsoon and floods [68], and hurricanes or cyclones
[59]. Many studies have shown clear links between
experiencing natural hazards and decreased food
security or diet diversity. Findings show that a com-
bination of household assets coupled with broader
structures of support play a key role in people’s access
to food when a shock creates a disruption in liveli-
hood activities [9,47–50]. Most of the existing work
on food security and extreme events is focused on
continental countries, not in SIDS. The limited stud-
ies that have been done in the context of disaster in
Latin America and the Caribbean mostly focus on
farm resiliency and recovery (e.g. returning the farm
to production or to pre-event state), showing that
production diversity, access to diverse markets and
sources of support, correlate with better farm recov-
ery from extreme weather events [45,54,55].
Given the dearth of research focused on farmer
food security in SIDS following extreme events, this
paper will assess farmer households’ food security
in the aftermath of Hurricane Maria in Puerto Rico
2

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
to understand the social-ecological components that
relate to adaptive capacity in an island setting. This
paper combines farmer survey data with biophys-
ical and climate data from Hurricane Maria to assess
the factors associated with short and long-term food
insecurity. Especially, after extreme weather events
and the disasters they trigger, where food security is
understudied in island contexts. The research ques-
tions are the following:
(a) How food secure were Puerto Rican farmer
households after Hurricane Maria? (RQ1). It is
expected that food security will decrease fol-
lowing Hurricane Maria, and persist for several
months, given extreme weather events’ role in
triggering transitory food insecurity (H1).
(b) How do socioeconomic, political, agricultural
factors of farmers and farms versus the biophys-
ical impacts of Hurricane Maria predict food
security outcomes? (RQ2). Following findings
from the Caribbean (mainly CARICOM coun-
tries) and Latin America [31–35], it is expec-
ted that farmers with higher levels of education,
income, and access to external resources will be
more food secure (H2). It is also expected that
farm assets, such as size and level of produc-
tion will be linked positively to better food secur-
ity outcomes (H3). Lastly, given the extensive
nature of Hurricane Maria’s impact to the built
environment (e.g. infrastructure), it is expected
that social and agricultural factors, rather than
geographical and biophysical factors, will predict
food security outcomes (H4).
2. Materials and methods
2.1. Place and context
Puerto Rico is an archipelago in the Caribbean that is
part of the Greater Antilles and is an unincorporated
territory of the United States. Similar to the broader
islands of the Caribbean, Puerto Rico’s food system
focuses mostly on domestic markets, and has seen a
decline in farms in the past 20 years. From producing
around 45% of its food in the 1980s, the US territ-
ory produces 15% today, with the majority of food
imported from the continental United States. Most
Puerto Rican farmers’ household income is less than
$20 000, according to the recent agricultural census
[69]. That contrasts with their counterparts’ house-
hold income in the United States, which averages over
$60,000 [70]. A 2019 report found 33% of Puerto
Rican adults to be food insecure prior to Hurricane
Maria [71].
Hurricane Maria had widespread impacts across
Puerto Rico’s agriculture and infrastructure. It
decimated 80% of Puerto Rico’s agricultural pro-
duction and infrastructure, is linked to 2975 deaths
[21,72], and triggered the longest blackout in United
States history [73]. All 3.4 million Puerto Ricans
faced a general power outage [74]. In many places,
power was not restored for more than a year; after
15 months, only 65% of Puerto Rico had electricity
[74]. Other prominent effects over the agricultural
sector included loss of phone, internet communic-
ation, access to farms, and impassable roads. Farm
management issues, electricity, and fuel shortage, as
well as obstacles for access and transportation dif-
ficulted farmlands’ recovery after Hurricane Maria
[29,75,76].
2.2. Survey development and data collection
A survey was developed in collaboration with
the Extension Service of the University of Puerto
Rico-Mayagüez (UPRM), and focused on under-
standing how Hurricane Maria impacted farmers,
and their perceptions around climate change, adapta-
tion, policy, and food security, among other elements
of adaptive capacity [77]. The survey was built fol-
lowing other farmer surveys related to climate change
[56,78]. The research was conducted in accordance
with the principles embodied in the Declaration
of Helsinki and in accordance with local statutory
requirements. The Committees on Human Subjects
Serving the University of Vermont and the UVM
Medical Center at the Research Protections Office
approved this study on 04 December 2017 (CHRBSS:
18-0258). It received Exemption Category 2. The sur-
vey booklet included a statement of consent that was
facilitated to participants by the enumerators. A pilot
study was conducted in February 2018 with a pool of
farmers (n=31), which resulted in survey refinement
and clarifications on structure and language. Puerto
Rican farmers were surveyed across the archipelago
in May-June 2018 by agricultural agents of the UPRM
Extension Service. Paper copies of the surveys were
distributed to central offices of the five regions of
the Puerto Rican Extension Service (Arecibo, Caguas,
Mayagüez, Ponce, and San Juan). Based upon Exten-
sion’s recommendation to assess diverse farmers
(e.g. dairy, plantain, coffee, mixed, etc.), all regions
received 100 copies, except Arecibo and Mayagüez,
which received 70 copies, based on the distribution
path of the hurricane (i.e. this area of Puerto Rico was
impacted less by the Hurricane, which made landfall
in the southeast of the main island). Extension agents
randomly surveyed farmers within their regions that
receive or had received services from Extension. Over-
all, 405 farmers (87% response rate) responded to the
survey.
2.3. Variables
This paper uses a subset of variables from the
deployed survey. To assess respondents’ experiences
with food security (dependent variable), the survey
asked, ‘In which months, if any, does your household
tend to not have enough food to consume or have
3

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
struggled to acquire food. Please select the month
for which you have face a struggle to acquire food
or a shortage of it.’ This question was based on the
baseline survey developed by the Climate Change,
Agriculture, and Food Security (CCAFS) Program,
and allows for assessing the time frame in which food
security was affected (period of transitory or episodic
food insecurity). Respondents were given the option
to select between 12 binary variables representing
months (May 2017—April 2018) [78,79]. Months
before September 2017 were not included in the ana-
lysis due to minimal response (<1%) of people indic-
ating food insecurity. Food security was categorized
in three groups: (a) food secure (0 reported months);
(b) immediate food insecurity (1–2 months); (c) per-
sistent food insecurity (three months or more).
To assess factors associated with food secur-
ity outcomes among farmer households, a suite of
questions from the survey which represent social-
ecological components were selected (table 1)
[29,30]. These variables reflect several social-
ecological factors that correlate with Caribbean farm-
ers’ food security [29,60,62–64,80], and are relevant
to food security in disaster contexts [38,40,80,81]. In
some cases, new variables were generated or simpli-
fied. For example, the variable ‘education’ was mod-
ified to have a reduced set of options (from ten to
two). The variable ‘network’ is an aggregated variable
of the number of organizations and groups farmers
reported having received information and services
regarding climate change adaptation, which serves
as a proxy for access to social and support networks.
‘Farm production’ is also an aggregate variable of the
number of agricultural products farmers reported to
be producing before Hurricane Maria, which serves
as a proxy for agricultural diversity, ecosystem ser-
vices, and economic aspects of a farm operation. The
variable ‘damages’ aggregates farmers who reported
‘total loss’ and ‘significant damages or less’ in a binary
variable. Farm size is shown in cuerdas, Puerto Rico’s
traditional land measurement, which is also how the
U.S. Department of Agriculture (USDA) Agricultural
Census for Puerto Rico reports farm size. This vari-
able is also a proxy for agricultural and economic
assets. One cuerda is approximately 0.97 acres or
0.39 hectares. The binary variable bona fide describes
a farmer who is certified as a bona fide farmer by
the Puerto Rico Department of Agriculture. To be
bona fide, a farmer must show evidence that 51% or
more of their income comes from farming. This cer-
tification provides farmers with direct access to the
Puerto Rico Department of Agriculture’s incentives
and farming assistance programs. This variable was
positively highly correlated with household income.
The ‘metropolitan’ (binary) variable was created
based on the municipality where farmers reported
their farming operations. Using a guide by the Puerto
Rico Planning Board, municipalities were categorized
as ‘metropolitan’ (significant population centers and
proximity to metropolitan areas) or as ‘not metropol-
itan’ (less population, closer to rural areas). Coastal
and metropolitan municipalities in Puerto Rico have
higher access to highways, critical infrastructure, and
governmental institutions. The variable ‘food assist-
ance’ (binary) describes people that participate in the
Puerto Rico Nutrition Assistance Program (Programa
de Asistencia Nutricional, PAN in Spanish). This pro-
gram provides eligible members nutrition assistance
benefits to the purchase of food in certified retailers
and cash for the purchase of food in certified and
non-certified retailers through the governments elec-
tronic transfer system. This program is funded by a
block grant, different from the USDA’s Supplemental
Nutrition Assistance Program (SNAP) that US states
receive.
To account for the effect of critical, hurricane-
related biophysical features on the reported level of
food security, two additional independent variables
were included. First, the straight-line distance from
the municipalities where a farm is located to the
tracking line of the hurricane’s eye (‘distance to eye’)
was evaluated, an indicator for the intensity of wind
force and other indirect effects associated with the
proximity to the most severe disturbances caused
by the hurricane’s passage [82]. Second, the dens-
ity of hurricane-induced landslides at the municip-
ality level (number of landslides per square kilo-
meter or ‘landslides’) was included to account for
their in-situ impacts on farmlands and surrounding
areas as well as the challenges they pose for access
to and from the farms (e.g. road blockages). Land-
slides are also related to total storm precipitation [83],
another potential hurricane effect on food security.
These spatial variables were derived from official or
peer-reviewed layers and summarized at the muni-
cipality level using geographic information systems
(table 1). ‘Landslide’ data was retrieved from the Sci-
ence Base-Catalog of the United States Geological Ser-
vice [84]. It was developed using a spatial invent-
ory of Hurricane Maria landslides points. ‘Distance
to eye’ data was retrieved from the tropical cyclone
tracks data from the NOAA National Hurricane Cen-
ter portal [85].
2.4. Statistical analysis
A multinomial logistic regression was carried out
to understand how different social-ecological factors
relate to food security outcomes because the depend-
ent variable is categorical (three unordered categor-
ies of food security status). Moreover, the data use
does not follow multivariate normality, which this
model resolves because it does not assume normal-
ity, linearity, or homoscedasticity. The model was
carried out in Stata 15.1 using maximum likelihood
and clustered robust errors [86,87]. The dependent
variable compares food insecure groups with people
4

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
Table 1. Variables included in the analyses of this study.
Variables Question/Statement or description Measure Rationale
Dependent variable
Food insecurity In which months, if any, does
your household tend to not have
enough food to consume or
have struggled to acquire food.
Please select the month for
which you have face a struggle to
acquire food or a shortage of it.
Categorical (1 =no
food insecurity,
2=immediate
food insecurity,
3=persistent food
insecurity)
Time frame of food security
outcomes in relation to the
event (Hurricane Maria).
Independent survey
variables
Age In what year were you born? Continuous Vulnerability
Bona fide Are you a ‘bona fide’ farmer of
the [Puerto Rico] Department
of Agriculture?
Binary (0 =No,
1=Yes)
This program provides farmers
with economic incentives and
tax exemptions. The variable
was also positively correlated
with household income.
Damages How would you describe the
damages, if any, caused by
Hurricane Maria to your farm?
Binary/Dummy
(0 =not total loss,
1=total loss)
Proxy for infrastructure and
farm damage (e.g. physical
assets).
Education What is the highest level of
education you have completed?
Mark one:
0=High school
diploma or less
1=Some college or
more
Formal education attainment
reflects economic and social
network assets.
Farm production What agricultural products have
you produced, currently
produce or plan to produce in
the future on your farm? Check
all that apply.
Count Proxy for agricultural
diversification, relates to higher
ecosystem services and access to
diverse markets or diet diversity.
Farm size How many cuerdas of terrain do
you manage in your farm?
Continuous Farm size can reflect physical
and economic assets, as well as
agricultural outputs.
Food assistance Do you receive services from the
Nutrition Assistance Program
(PAN)?
Binary (0 =No,
1=Yes)
Proxy for preexisting obstacles
to household food security. This
program is based on household
income.
Gender What is your gender? Binary (0 =Male,
1=Female)
Vulnerability
Metropolitan In what municipality your farm
is located?
Binary (0 =Not
metropolitan,
1=Metropolitan)
To reflect population, urban
centers, and access to critical
infrastructure.
Network Which of the following
organizations and institutions, if
any, have you received or would
like to receive information from
related to adapting to
climate-related impacts? Check
all that apply.
Count Proxy for social networks of
support.
Independent added
biophysical variables
Distance to eye Straight-line distance (in km)
from municipality centroid to
the hurricane Maria track line.
Continuous Wind speed and potential
damages or impacts.
Landslides Number of landslides
normalized to the km2of the
municipality.
Continuous Incidence related to rainfall
intensity and infrastructure
impacts.
not experiencing any food insecurity (reference/base
group). Kruskal–Wallis rank tests (for continuous
dependent variables) and Chi Square tests (for cat-
egorical dependent variables) were used to evaluate
differences between groups.
3. Results
3.1. Participants’ characteristics
Descriptive statistics for all independent variables of
all respondents are shown in table 2. Respondents are
5

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
Table 2. Descriptive statistics of study’s variables. Frequency, mean, standard deviation (SD), and responses (n) are included.
Variables Scale Frequency (%) Mean ±SD n=
Survey variables
Age Continuous — 54.0 ±13.5 391
Bona fide Yes
No
210 (52.8%)
188 (47.2%)
— 398
Damages Total loss
Not total loss
170 (42.6%)
229 (57.3%)
— 399
Education Less than high school
High school diploma
Some college
Technical/Associate degree
Bachelor’s degree or more
49 (12.2%)
82 (20.5%)
42 (10.5%)
66 (16.5%)
162 (40.4%)
— 401
Farm production Count — 3.1 ±2.5 402
Farm size (cuerdas) Continuous — 58.1 ±99.0 383
Food assistance Yes
No
65 (18.0%)
294 (82.0%)
— 359
Sex Female
Male
55 (14.0%)
340 (86.0%)
— 395
Metropolitan Metropolitan
Not metropolitan
229 (57.5%)
169 (42.5%)
— 398
Network Count — 2.3 ±2.1 398
Biophysical variables
Distance to eye (km) Continuous — 21.7 ±14.0 379
Landslides (km2) Continuous — 9.8 ±13.4 338
comparable to Puerto Rico’s agricultural census data
on sex, farm size, income, and education levels [69].
However, data shows an overrepresentation of bona
fide farmers (53%, compared to 24% in Puerto Rico
[88]). Respondents had an average age of 54; 53%
were 55 years or older. The majority were male (86%).
Average farm size was 58 cuerdas (55 acres or 22 ha).
Moreover, the majority reported attending some col-
lege or more formal education (67%). Almost half of
farmers reported total loss of their farms due to Hur-
ricane Maria’s impact (43%). The majority of farm-
ers farmed in metropolitan municipalities (58%),
produced two or more agricultural products (65%),
and had a network of one or more organizations
and groups (75%). On average, municipalities cor-
responding to the location of the respondents’ farms
are 22 km from the passage of Hurricane Maria and
had ten hurricane-triggered landslides per squared
kilometer.
3.2. Food security
Figure 1shows the number of months farmer
households experienced negative effects on their
food security prior and after Hurricane Maria’s
landfall. Overall, farmers reported an average of
2.0 ±2.1 months of negatively impacted house-
hold food security (n=401). Most farmer house-
holds (69%) reported at least one month of not hav-
ing enough food to consume or having struggled to
acquire food. High levels of affected food security
were reported in the month of September 2017, when
Hurricane Maria hit Puerto Rico (September 20,
2017; two weeks after category 5 Hurricane Irma hit
the eastern side of Puerto Rico), increasing in October
(59%), and slowly decreasing in November (49%),
December (30%), and the following months (all
<15%). Among respondents, 31% reported immedi-
ate food insecurity (1–2 months of affected household
food security), 38% reported persistent food insecur-
ity (three months or more), and 31% of farmers did
not report experiencing any negative effects on their
food security. These results support H1.
The characteristics of households reporting vary-
ing levels of food security differed significantly
(table 3). Low levels of food security were significantly
(p⩽0.05) more prevalent among older respond-
ents, those that were not bona fide farmers, those
with smaller land holdings, those outside of metro-
politan areas, and those with closer distance to the
eye of the hurricane. These results suggest that a
number of social, agricultural and biophysical factors
affected food security in the months following Hur-
ricane Maria, largely supporting H2 and H3. Farmers
in the persistent food insecurity category were closer
to Hurricane Maria’s track, and farmed in municipal-
ities that experienced higher volume of landslides in
comparison to the other two groups (table 3, figure 2),
partially supporting H4.
3.3. Multinomial model
Table 4shows the results of the multinomial logistic
regression in which the comparison reference group
are food secure. The multinomial logistic regres-
sion shows that farmers receiving food assistance
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Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
Figure 1. Percent of farmer households that reported negative effects on their food security prior to and after Hurricane Maria
(n=401). The hurricane made landfall on 20 September 2017, two weeks after category 5 Hurricane Irma impacted Puerto Rico.
Table 3. Descriptive statistics and statistical analyses by food security categories.
Food insecurity category Statistical test significance (p)
Variables
Food secured
(n=124; 31.0%)
Immediate
food insecurity
(n=123; 31.0%)
Persistent food
insecurity
(n=154; 38%) Kruskal–Wallis Chi Square
Survey variables
Age 52.5 ±13.5 52.6 ±13.0 56.4 ±13.0 0.053 —
Bona fidea
Being bona fide
No
79 (37.6%)
43 (22.9%)
65 (31.0%)
57 (30.3%)
66 (31.4%)
87 (46.3%)
— 0.002
Damages
Total loss
Significant loss or less
57 (33.5%)
67 (29.3%)
50 (29.4%)
71 (31.0%)
62 (36.5%)
91 (39.7%)
— 0.630
Education
Some college or more
High school diploma
or less
84 (31.1%)
40 (30.0%)
85 (31.5%)
36 (27.5%)
100 (37.0%)
54 (41.2%)
— 0.644
Farm production 3.4 ±2.5 2.8 ±2.2 3.3 ±2.7 0.227 —
Farm sizea75.6 ±118.5 58.0 ±95 45.1 ±81.6 0.029 —
Food assistance
Participant of PAN
Not participant
15 (23.1%)
105 (35.7%)
22 (33.8%)
86 (29.3%)
28 (43.1%)
102 (34.5%)
— 0.139
Sex
Female
Male
17 (30.9%)
105 (31.0%)
18 (32.7%)
102 (30.0%)
19 (34.5%)
132 (38.8%)
— 0.846
Metropolitana
Metropolitan
municipality
Not metropolitan
72 (31.4%)
52 (30.8%)
40 (17.5%)
81 (47.9%)
76 (33.2%)
75 (44.4%)
— 0.016
Network 2.6 ±2.6 2.5 ±2.0 2.0 ±1.8 0.140 —
Biophysical variables
Distance from eyea25.3 ±15.1 21.5 ±14.2 18.9 ±12.3 0.001 —
Landslides 9.1 ±11.6 7.7 ±10.3 12.2 ±16.4 0.208 —
Note: Percentage of categorical variables is based on the total nof each variable.
aSignificant variable (p< 0.05).
7

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
Figure 2. Map of study area highlighting, at the municipality scale, the distribution of respondents within the three groups of
food security, the density of hurricane-triggered landslides, and the relative distance to Hurricane Maria eye track.
(Programa de Asistencia Nutricional or NAP) were sig-
nificantly more likely to be immediately food insec-
ure, as compared to food secure (β=0.09330,
p=0.040).
Multiple variables predicted persistent food insec-
urity, as compared to the food secure reference group,
including older respondents (β=0.0224, p=0.030),
bona fide farmers were less likely to be food insecure
(β=−0.0570, p=0.034), and further distance from
the eye of Maria (β=−0.0341, p=0.017). Having a
larger network was weakly associated (p< 0.10) with
less likelihood of being persistently food insecure.
8

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
Table 4.: Multinomial regression model results predicting food insecurity. Results for immediate food insecurity and persistent food
insecurity categories are presented in comparison to the food secure category (reference group). Coefficients (β), robust clustered
standard errors (SE), and significance (p) are reported.
Variable Categories βSE p
Age Immediate food insecurity
Persistent food insecuritya
−0.0017
0.0224
0.0110
0.0103
0.877
0.030
Bona fide
Being bona fide Immediate food insecurity
Persistent food insecuritya
0.1360
–0.0579
0.3702
0.3752
0.325
0.034
Damages
Total loss Immediate food insecurity
Persistent food insecurity
0.0761
0.0834
0.2639
0.3579
0.773
0.816
Education
Some college or more Immediate food insecurity
Persistent food insecurity
0.1360
–0.0579
0.3223
0.3522
0.673
0.869
Farm production Immediate food insecurity
Persistent food insecurity
−0.0444
0.0751
0.0665
0.0701
0.504
0.284
Farm size Immediate food insecurity
Persistent food insecurity
−0.0003
–0.0030
0.0019
0.0018
0.890
0.109
Food assistance
Participant of PAN Immediate food insecuritya
Persistent food insecurity
0.9330
0.4729
0.4533
0.4970
0.040
0.341
Sex
Female Immediate food insecurity
Persistent food insecurity
0.0764
0.1919
0.4983
0.3882
0.878
0.621
Metropolitan
Farm in a metropolitan
municipality
Immediate food insecurity
Persistent food insecurity
0.1670
–0.1964
0.5657
0.5568
0.768
0.724
Network Immediate food insecurity
Persistent food insecurity
−0.0366
–0.1308
0.0689
0.0768
0.596
0.089
Distance to eye Immediate food insecurity
Persistent food insecuritya
−0.0139
–0.0341
0.0119
0.0144
0.243
0.017
Landslides Immediate food insecurity
Persistent food insecurity
−0.0139
0.0182
0.0180
0.0175
0.427
0.300
aStatistically significant (p< 0.05).
4. Discussion
4.1. Farmer households, island food security, and
disaster
The results of this study validate claims that extreme
weather events can trigger transitory food insecur-
ity, and that its length is dependent on both the
biophysical impacts from an extreme weather event,
but more prominently on other social and infra-
structure factors. While less than 1% of farmers in
this study reported low food security prior to Hur-
ricane Maria’s landfall, 69% of Puerto Rican farmer
households reported at least one month of not hav-
ing enough food to consume or having struggled to
acquire food in the aftermath of Maria, with 31%
experiencing immediate (1–2 months) and 38% per-
sistent (three months or more) food insecurity. Find-
ings suggest that household food security outcomes,
in light of disaster, is compounded on individual risk
factors and access to sources of support, which aligns
with previous research [3,54,56]. Furthermore, given
islands local food systems’ importance in buffering
impacts from extreme weather events [16,44,55],
farmers adaptive capacity must be strengthened in
order to safeguard local food security [29].
Results showed that farmers who were farther
from Hurricane Maria’s track were less likely to
report persistent food insecurity. Though landslides
were not significant in predicting food security out-
comes, those in the persistent food insecurity cat-
egory resided in municipalities with higher number
of landslides, which were the causes of road block-
ages and slowing farm operations in Puerto Rico
[29,75,83,84]. The eye of the hurricane is char-
acterized by sustaining the strongest winds, coupled
with sustained rains, which in turn cause more infra-
structure damages [74,89]. Infrastructure damages
in Puerto Rico due to Hurricane Maria surpassed the
billions of dollars, and many food retailers through-
out Puerto Rico were permanently closed or had dis-
rupted operations due to damages [21,80,90,91].
Furthermore, lack of electricity and water catalyzed
longer recovery periods [29,75].
Social and natural circumstances of each place,
such as urban and economic levels, as well as topo-
graphy, for example, play an important role in gen-
9

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
erating obstacles and buffers to natural hazards and
to have a sustainable food system [76,92]. Res-
ults suggest that farming in a metropolitan muni-
cipality was associated with food security outcomes.
Coastal municipalities in Puerto Rico and those near
high urban sectors were more likely to have utilit-
ies restored quickly due to higher adaptive capacity.
Spatial distribution of food sources and critical infra-
structure is key in providing food access, availabil-
ity, and stability. Disruption in critical components
within a network, combined with a place’s levels of
vulnerability, play a key role in food security after an
extreme weather event [42].
Within a set of disruptions, those prone to
risk factors and lower adaptive capacity—access to
individual assets or structural support—face more
obstacles in buffering the impacts of extreme weather
events [21,42,80,91,93]. Evidence from this study
suggests that older farmers, and those already with
low food security, were more likely to report more
months of food insecurity. Puerto Rican farmers aver-
age age is 61, and reflects a broader Puerto Rican
population that is aging, which points to diverse risk
factors that may play a role in food security outcomes
[69,94,95]. Results also align with others that have
found that those food insecure before an extreme
weather event or other sudden shock, such as in the
current COVID-19 pandemic [96], are likely to exper-
ience food insecurity afterwards [9,39]. Being parti-
cipant of the Puerto Rico Nutrition Assistant Program
(PAN in Spanish) also increased the risk of report-
ing immediate food insecurity. PAN participants can
use their funds through an electronic benefit transfer
card. Given that Puerto Rico faced the longest black-
out in United States history [73], and communica-
tions where down for several months, it is likely that
PAN participants struggled to access those funds.
Results also showed that higher levels of adapt-
ive capacity provide a buffering effect. Farm size was
associated with food security groups in this study, and
farmers that were part of the bona fide program were
less likely to report persistent food insecurity. Bona
fide farmers in Puerto Rico are recognized by the local
Department of Agriculture and have access to finan-
cial and agricultural services, as well as to govern-
mental tax exemptions and incentives. This variable
was positively and highly correlated with income, and
those who were bona fide reported a higher average
of network institutions and organizations. This result
aligns with other studies that suggest that, in the con-
text of disaster, external sources of support, whether
institutional or financial, can support farmers’ adapt-
ive capacity to navigate recovery [29,54,97]. These
variables also point out to how these individual attrib-
utes in ‘normal times’ may build the resistance and
resilience of farming systems [49,98,99], in light of
compounding shocks in the ongoing climate crisis.
Future studies focusing on transitory or epis-
odic food insecurity should develop new instruments
or consider approaches that capture people’s lived
experience in acquiring food, beyond nutritional
or quantity values [47,80,100,101]. While food
security is traditionally considered through an eco-
nomic lens (e.g. enough money) [46,101,102], dis-
asters create new circumstances or impacts that are
not always safeguarded by economic access [40,80].
Such circumstances may be especially pronounced in
island communities where the biophysical impacts
of an event may be widespread, and the safety nets
available may be physically and economically distant
[16,44,45]. This study shows that Puerto Rican farm-
ers, who in general are mainly commercial and focus
on domestic markets, may have faced similar struggles
as the broader population to support their household
food security. Understanding the hurdles that people
face in acquiring the foods they need to prepare an
adequate meal that fits their physiological and emo-
tional needs could provide a more complete picture
of how social-ecological dynamics shape food secur-
ity during and after an extreme weather event.
Hurricane Maria made visible that in a cata-
strophic event, food transportation to and from one
main source generates difficulty in maintaining food
security [25]. In Puerto Rico, like other SIDS, food
is frequently imported into a single port, increasing
vulnerability. Thus, a robust local island food system
contributes to buffering such disruption by provid-
ing island food sources [44,76,103]. SIDS diverse
topographic, infrastructure, and climatic gradients’
shape how impacts from extreme weather events
are experienced. This study’s findings, considering
Puerto Rico’s narrow resource base and high depend-
ence on imports, similar to many other SIDS, under-
lines the critical role of local food systems in disaster
response and recovery. Understanding the drivers and
barriers to strengthening farmers’ adaptive capacity is
key in safeguarding local food systems, which are reli-
ant on farmers and farm workers’ work, as well as on
other key agents of the food system. Nonetheless, the
role of broader structures of support, coupled with
individual adaptive capacity must be further con-
sidered.
4.2. Moving beyond the household level
The full survey report used in this study found that
less than 14% of farmers think that Puerto Rico
has the necessary policies to protect and support
local agriculture [104]. Moreover, more than 85%
disagreed with the statement that imports are not
an obstacle to increase the access of local products
in the Puerto Rican markets [104]. Future studies
could further inquire about the relationship of struc-
tural components to individual food security out-
comes. Given how critical imports are to island food
10

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
security, SIDS’s embeddedness in a globalized world
and their food systems’ susceptibility to volatile mar-
kets must be considered when examining island food
security [26,44,45,92,105]. In the case of Puerto
Rico as a US territory, future studies could assess the
extent to which structural elements within US policy
frameworks influence island food security outcomes.
For example, a comprehensive study of the Mer-
chant Marine Act of 1920 (commonly known as the
Jones Act, which control shipping between US ports)
could inform how to incorporate structural variables
(e.g. related to imports) to food security assessment
instruments [25,106]. That law received attention
after Hurricane Maria, and other extreme weather
events, such as 2017’s Hurricane Harvey, because it
is waived to permit more flexible maritime supply
chains. Less than 11% of Puerto Rican farmers sup-
port the Jones Act or think it does not affect local food
security [104].
Extreme weather events can create local impacts,
as Hurricane Maria did, but they also can trigger
disruptions from afar. Thus, future research should
explore the extent to which local island food systems’
dependence on external forces shape their adaptive
capacity, and the factors beyond farmers’ individual
adaptive capacity that contribute to the local food sys-
tem’s ability to feed its people. Put succinctly, what
are the limits of adaptive capacity in island food sys-
tems? Of the 58 recognized islands nations and territ-
ories by the United Nations, 27 are in the Caribbean
[107]. Almost half of those are not United Nation
members, such as Puerto Rico, which is an Unincor-
porated Territory of the US. Hence, island food secur-
ity assessment must incorporate that reality into their
approaches.
4.3. Looking forward
Future studies should build upon this study’s
approach of combining social and biophysical data to
better understand how people navigate disaster, and
the degree to which reinforcing the adaptive capacity
of vulnerable populations can be supported, so that
recovery efforts can be effective. Given our limited
data on variables related to structural components,
such as import rates, access to important utilities
related to storing and preparing food(e.g., electricity,
water, gas, etc.), infrastructure descriptors, and other
political aspects, future studies could develop multi-
dimensional frameworks (e.g. combination of ethno-
graphic and modeling approaches) that assess food
security in varying levels within a social-ecological
system (e.g. from the household to the national level).
This study is limited in the way that it assesses
food insecurity since it only asked the months farm-
ers struggled to have enough food rather than ask-
ing a series of food insecurity questions (see the Food
Insecurity Experience Scale), and highlights the need
for better instruments that consider the drivers and
barriers for people to access food while navigating
disaster. Future studies could generate a more con-
textualized approach based on Household Hunger
Scales [108] and the Food Insecurity Experience Scale
[109,110], among other tools, that take into account
the subjective or lived experience of people in acquir-
ing and preparing foods. Furthermore, given that
disruptions are lived differently, and recovery peri-
ods vary, promptly approaches that consider these
early obstacles and experiences may provide a more
nuanced understanding of how people navigate such
states.
5. Conclusion
This study found that Hurricane Maria triggered
a period of transitory food insecurity among
Puerto Rican farmer households, and that its length
depended on individuals’ risk factors, suffered bio-
physical impacts, and levels of adaptive capacity. Res-
ults suggest that navigating disruptions in the natural
and built environment can be constrained or allevi-
ated by a combination of broader structures of sup-
port and adaptive capacity. As island food systems
play a key role in providing local food; therefore,
safeguarding farmers from extreme weather events
and their impacts—as reflected here by the number
of months of food insecurity—must be effectively
addressed to safeguard local food security. How-
ever, island food security does not depend solely on
farmer productivity and therefore, cannot be assessed
only through a supply or production approach. Thus,
future studies should better consider islands’ embed-
dedness in globalized systems, and the extent to which
volatile markets and power imbalances influence local
food security. This goal could be achieved by devel-
oping new mixed-methods approaches that better
assess how different social-ecological components
interact and connect in relation to food security at
varying levels (from the household to the national
and regional levels) in the context of disasters. Vari-
ables that better reflect or represent disruptions lived,
as well as incorporating qualitative approaches that
grasp lived experiences in relation to acquiring, stor-
ing, producing, and preparing food after extreme
weather events, could present more nuanced solu-
tions and understanding to safeguarding island food
security. Moreover, future research can better explore
the limits of local island food systems’ adaptive capa-
city, and the degree to which local food systems can
meet local food demands, while balancing SIDS’s
limitations.
Data availability statement
The data that support the findings of this study are
available upon request from the authors.
11

Environ. Res. Lett. 17 (2022) 044057 L A Rodríguez-Cruz et al
Acknowledgments
We acknowledge the farmers who answer the surveys
used for this study, and the University of Puerto Rico-
Mayagüez’s Extension Service’s agricultural agents,
who enumerated them. This study was facilitated
thanks to Dr Aníbal Ruiz-Lugo and the University
of Puerto Rico Extension Service’s administration.
Data entry was supported by Maritzabel Morales and
Olivia Peña. We also acknowledge several colleagues
who supported this study in different capacities: Amy
Trubek, María del Carmen Rodríguez Rodríguez,
Maya Moore, Robinson Rodríguez, Teresa Mares, and
Ernesto Méndez. Funding for this study was provided
by the Food Systems Program, the College of Agri-
culture and Life Sciences of the University of Ver-
mont, and by the University of Vermont Agricul-
tural Experiment Station (USDA Hatch) Project VT-
H02709. This research was also supported in part by
an appointment to the United States Forest Service
(USFS) Research Participation Program administered
by the Oak Ridge Institute for Science and Education
(ORISE) through an interagency agreement between
the U.S. Department of Energy (DOE) and the USDA.
ORISE is managed by the Oak Ridge Associated Uni-
versities (ORAU) under DOE Contract Number DE-
SC0014664. All opinions, findings, and conclusions
expressed in this paper are the authors’ and should
not be construed to represent the officials, policies
and views of USDA, DOE, or ORAU/ORISE.
ORCID iDs
Luis Alexis Rodríguez-Cruz 
https://orcid.org/0000-0002-2229-8448
Nora ´
Alvarez-Berríos https://orcid.org/0000-
0001-7556-3156
Meredith T Niles https://orcid.org/0000-0002-
8323-1351
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