TITLE: NDVI Predicts Birth Seasonality in Historical Baja California
Sur, Mexico
AUTHORS: Shane J Macfarlan1,2,3(shane.macfarlan@anthro.utah.edu),
Ryan Schacht4(schachtr18@ecu.edu),
Izabella Bourland1,5(izabella.bourland@utah.edu),
Savannah Kapp1(savannah.kapp@utah.edu),
Trevor Glad6(u0960974@utah.edu), Lauren
Lewis1(lewis.lauren.abbey@utah.edu),
Nathan Darmiento2,7(u0892197@utah.edu), Tanner
Clegg8(tannernoahclegg@gmail.com),
Cole Thorpe2,10(colethorpe96@gmail.com),
Taylor Peppelar1(taypep@gmail.com), Melissa
Santiago4(santiagom15@ecu.edu),
Celeste Henrickson1,11(celestehenrickson@gmail.com),
Kenneth Blake Vernon1(kenneth.b.vernon@utah.edu)
1 Department of Anthropology, University of Utah, Salt
Lake City, UT 84112
2 Center for Latin American Studies, University of
Utah, Salt Lake City, UT 84112
3 Global Change and Sustainability Center, University
of Utah, Salt Lake City, UT 84112
4 Department of Anthropology, East Carolina
University, Greenville, NC 27858
5 Environmental and Sustainability Studies, University
of Utah, Salt Lake City, UT 84112
6 Department of Music, University of Utah, Salt Lake
City, UT 84112
7 Department of History, University of Utah, Salt Lake
City, UT 84112
8 College of Humanities, University of Utah, Salt Lake
City, UT 84112
10 Department of Linguistics, University of Utah, Salt
Lake City, UT 84112
11 General Education, Nightingale College, Salt Lake
City, UT 84111
Short Title: NDVI Predicts Birth Seasonality
Keywords: Birth Seasonality; NDVI; Baja California Sur; Mexico;
Behavioral Ecology; Adaptive Strategies; Historical Demography; Mexican
History
Article Type: Letters
Abstract Word Count: 150
Text Word Count: 3316
Number of References: 81
Number of Figures: 1
Number of Tables: 3
Corresponding Author:
Shane Macfarlan, 260 Central Campus Drive, Department of Anthropology,
University of Utah, Salt Lake City, UT 84112
Email:
shane.macfarlan@anthro.utah.edu
Office Phone: (801) 587-3432
SJM conceived of the study and performed all the analyses. SJM, IB, SK,
TG, LL, ND, TC, CT, TP, MS, CH, KBV collected the data. SJM and RS wrote
the first draft of the manuscript.
ABSTRACT
Birth seasonality is a phenomenon whereby populations can be
characterized by a single month or season in which births peak. While
non-human animal research suggests seasonal birth-pulses are related to
variation in climate and local energy availability, social scientists
debate the mechanisms responsible for it in humans. Here we investigate
the role of precipitation, temperature, and energy availability on
seasonal birth pulses using a historical dataset from the Baja
California peninsula - a hot, arid desert that experiences seasonal
fluctuations in temperature, precipitation, and energy associated with
the North American Monsoonal. Analyses suggest that local energy
availability (as measured through NDVI) predicts seasonal birth pulses,
while temperature and precipitation do not; however, both are indirectly
related to it through their direct effects on NDVI. Our analyses
demonstrate the importance of local energy availability on human
reproductive timing and suggest that human birth seasonality is a form
of traditional ecological knowledge.
INTRODUCTION
Birth seasonality [one aspect of breeding phenology (Forchhammer et
al. 1998; Sinclair et al. 2001)] is a common trait among many
viviparous species whereby parturition events peak in a single season or
month (Ellison et al. 2005; Wittemyer et al. 2007; Martinez-Bakker et
al. 2014). Birth seasonality is particularly common among iteroparous
organisms (those that reproduce more than once during their lifetime)
residing in seasonal habitats (Pettorelli 2013). Comparative research in
animal ethnology and evolutionary ecology indicate that breeding
phenology is strongly associated with both climate and temporal
variation in food availability across animal taxa (Drent & Daan 1980;
Kennish 1997; Forchhammer et al. 1998; Sinclair et al. 2001; Rubenstein
& Wikelski 2003; Wittemyer et al. 2007; Pettorelli 2013; Drake &
Martin 2018). There are clear payoffs for organisms to synchronize
reproduction with local energy availability, especially among mammals
with obligate pre- and post-natal parental investment (e.g. gestation,
lactation, and resource provisioning) – offspring born during peaks in
energy availability are heavier and have higher survival rates than
those born before or after those peaks (Pettorelli 2013; Plard et al.
2014).
Seasonal birth pulses are not unique to non-human animals and were first
identified in humans nearly 200 years ago through early epidemiological
research (Villerme 1831). However, despite being recognized as a near
universal feature of human populations today (Cowgill 1965; Bronson
1995; Ellison et al. 2005; Dahlberg & Andersson 2019), social
scientists continue debate the mechanisms responsible for this
patterning (Condon & Scaglion 1982; Bobak and Gjonca 2001; Ellis et al.
2005; Herteliu et al. 2015; Dahlberg & Andersson 2018, 2019). While
some have favored non-adaptive socio-cultural explanations for single
case studies (see review in Ellis et al. 2005), recent large-scale,
cross-national datasets suggest that human birth seasonality may be
related to seasonal variation in local energy availability
(Martinez-Bakker et al. 2014). For example, across the northern
hemisphere, human birth seasonality has a latitudinal gradient, with
populations residing between the equator and 30 degrees North Latitude
typically peaking in births between the fall and early winter (i.e.,
September through December) and those between 30 degrees North Latitude
and the Arctic peaking between the spring and summer (i.e., April
through August) (Martinez-Bakker 2014). The patterning of latitudinal
distribution of seasonal birth pulses generally tracks ecosystem-level
energy availability, which has similar seasonal variation based on a
latitudinal gradient (Becker & Boyd 1957; Lindsey 2009). Mothers who
give birth during peaks in seasonal local energy availability have
children with higher birth weights, larger head circumferences, and
greater gestational ages, all of which are indicators of child health
and survivorship (Dadvand et al. 2012; Case et al. 2016; Bakhtsiyarava
et al. 2018).
Local energy availability is impacted by a number of bio-physical
factors, including temperature and precipitation (Wu et al. 2001;
Pettorelli 2013; Yan et al. 2015; Gilbert 2019). Not surprisingly, a
large body of research has linked seasonal variation in precipitation
and temperature to birth seasonality in humans (Condon & Scaglion 1982;
Lam & Miron 1998; Ellis et al. 2005; Lawlor et al. 2005; Torche &
Corvalan 2010; Osei et al. 2016). However, these aspects of climate
serve as proxy variables for local energy availability (Pettorelli 2013)
and no one has examined the direct impact of local energy availability
on human birth seasonality.
Accordingly, here we investigate the role of all three (precipitation,
temperature, and energy availability) on monthly birth pulses in a
19th century dataset from Baja California Sur, Mexico.
Performing this research on a historical, rather than modern, dataset
has several advantages. First, as global populations have become
increasingly industrialized, societies have generally become reliant on
infrastructure that smooths out localized environmental variability and
consequent resource scarcity (e.g. drought). Hence, this reduces
variability in local energy availability thereby lowering the incidence
of monthly birth pulses (Dahlberg & Andersson 2018, 2019). Conversely,
subsistence-level populations are more likely to be impacted by seasonal
variability in local bio-physical processes (Moran 2018). Second, as
human populations continue to undergo demographic transition (i.e.,
lower fertility), the ability to detect birth seasonality is diminished
(Dahlberg & Andersson 2018). Historical datasets cover time periods
that typically promoted early female reproduction and higher fertility
(Kaplan 2006; Kaplan et al. 2000, 2001; Galor 2012; Macfarlan et al.
2019). Consequently, research on these data allow for more reliable
tests of birth seasonality than among modern populations with lower
fertility due to widespread contraception, public education, and the
advent of scientific medicine.
MATERIALS AND METHODS
Study Site: Baja California Sur (hereafter, BCS) is one of two Mexican
states that comprises the Baja California Peninsula (Krutch 1986)
(Figure 1). Climatologically much of BCS is characterized as a hot, arid
desert (Köppen-Geiger BWh) (Rebman & Roberts 2012); however, portions
of the southern tip of the peninsula, known as the “Cape Region”, is
characterized as hot and semi-arid (Köppen-Geiger BSh) (Rebman &
Roberts 2012; Flores-Cárdenas et al. 2018; Maldonado-Enriquez et al.
2020). Both regions are subject to the North American monsoon (Barron et
al. 2012), a climatological phenomenon whereby an onshore wind shift
occurs between July and September that is associated with an increase in
temperature and precipitation (Hasting & Turner 1965; Diaz et al. 2001;
Rebman & Roberts 2012; Barron et al. 2012). This climatological system
has been estimated present for the last 7500 years (Barron et al. 2012).
Directly following the monsoonal rain season, biological energy
availability increases, resulting in a September through December
growing season (Maldonado-Enriquez et al. 2020). Minor rain events
continue through January; however, between March and June, life becomes
increasingly difficult as precipitation virtually vanishes and
temperatures rise (Salinas Zavala et al. 1990. Numerous historical
accounts attest to the difficulty of surviving this arid ecosystem
(Clavigero 1937; Baegert 1952).
Figure 1 approximately here
Population History: The Baja California peninsula has been inhabited by
indigenous peoples for at least the last 12,000 years (Fujita; Des
Lauries et al. 2015; Macfarlan & Henrickson 2010); however, peoples of
Euro-American descent began to permanently occupy the region after the
Jesuits founded mission Loreto in 1697 AD (Martinez 1960; Crosby 1994).
The Jesuits brought with them soldiers and their families who performed
a number of economic roles to assist with the mission building process
such as smithing, farming, and herding. The descendants of these initial
colonists make up a portion of the peninsular population today (Martinez
1960, 1965; Crosby 1981, 1994). After 70 years of tight administrative
control, the Jesuits were expelled from the Spanish Kingdom (1768 AD)
and the Baja California peninsula was opened to those seeking to settle
the land, resulting in a second population influx (Martinez 1960). Two
additional waves of in-migration later occurred; one following Mexican
Independence (1821 AD) and another that occurred throughout the
Presidency of Porfirio Diaz (the Porfiriato Period: 1875-1910 AD)
(Trejo Barajas 1994, 2005). Across all four migratory events, the
majority of people came from Sonora and Sinaloa; however, they also
included people from Asia, Europe, and North and South America (Martinez
1965; Macfarlan et al. 2019).
Throughout the 19th century, the Baja Californian
economy was largely insular, with economic ventures focusing on cattle
and goat ranching, crop production (largely based on Jesuit introduced
species), and mining (Trejo-Barajas & Gonzalez 2002). Indeed, herding
and horticulture still predominate throughout the rural, mountainous
ranching communities today (Crosby 1981). While crop production was made
possible through the irrigation of desert springs (the only permanent
source of surficial fresh water that exists in BCS) (de Grenade et al.
2016), ranching was (and still is) dependent on seasonal rains to
provide animal fodder. Because the Baja California peninsula was poorly
integrated into the larger Mexican nation-state throughout the
19th century (Martinez 1965; Trejo-Barajas & Gonzalez
2002), people were highly reliant on local climatic conditions and
ecology for making a living (Crosby 1981).
Data: Birth records were extracted from the, Guía Familiar de Baja
California: 1700-1900 (Martinez 1965). This repository represents the
largest source of vital records for the Baja California peninsula prior
to the first systemic, nation-wide censuses that were initiated at the
beginning of the 20th century (Platt 1998). Due to
weathering and neglect over 200+ years, some of the vital records were
damaged and not transcribed. However, data loss is unbiased and does not
favor (or disfavor) any particular group or time period (Macfarlan et al
2020). In all, this repository represents the single best source for
reconstructing demographic process on the peninsula during the
19th century (Macfarlan et al. 2019).
A total of 9111 birth, baptismal, and registration records were
extracted from ten communities spanning the modern state of BCS (Loreto,
Santiago, Santa Rosalía, Mulegé, Comondú, Todos Santos, La Paz, San Jose
del Cabo, San Antonio, San Ignacio) (Figure 1). Records included a
variety of information including: 1) the first and last name of the
individual, 2) the day, month, and year of birth, baptism, and/or
registration, 3) the location where the individual was born, baptized,
and/or registered, 4) parental first and last names, and 5) additional
notes about the individual who was born. Some records included
information on individuals who were baptized or registered in one
location (e.g. Santa Rosalía) but were born in a different location
(e.g. Todos Santos). As such, we organized the record such that they
were associated with the correct birth location. When individuals were
born in locations not directly associated with one of the ten identified
communities, we searched for the location using a variety of published
sources (e.g. Gerhard & Guilick 1964; Secretaría de Desarrollo Social
2020; Instituto Nacional de Estadística, Geografía e Informática 2020)
and placed them into the closest community. Finally, we filtered the
data to include only those records where month and year of birth were
available (n=8905).
Community-level climatological data were aggregated from Mexican
National archives (Ruiz et al. 2006). The data are presented as monthly
temperature and precipitation averages that are based on daily
measurements collected from weather stations over a 41-year period
spanning 1961 and 2002 in each community (Table 2). While the time frame
for weather and birth data do not overlap, the modern climatological
system has been stable for at least the last several hundred years, if
not longer (Baegert 1952; Diaz et al. 2001; Barron et al. 2012).
Community-level energy availability data are presented as average
monthly Normalized Difference Vegetation Indices (NDVI). NDVI values
(which range from negative one to one) quantify the spatio-temporal
variability in green biomass (i.e., vegetation) by measuring the
difference between remotely sensed red and near-infrared light (which
vegetation reflects and absorbs, respectively) (Hamel et al. 2009;
Pettorelli 2013). Data were queried from the MODIS/VIIRS Global Subsets
Tool using a 16-day interval, 250-meter resolution across a 19-year
period (January 1, 2001 through December 31, 2019) (Didan 2015). For
each of the ten communities, we used three square-kilometer polygons to
assess intra-annual energy availability (Table 2) (ORNL DAAC
2018a,b,c,d,e,f,g,h,i,j). To account for urbanization in the communities
of San Jose del Cabo and La Paz, we offset our polygons to non-developed
plots immediately adjacent to the community (ORNL DAAC 2018a,e).
Although the NDVI data does not overlap temporally with our birth data,
and NDVI values may be lower than that observed during the historical
period due to urbanization, the seasonal change in NDVI values within
communities should be comparable based on the stability of the climatic
regimes over the last several thousand years (Baegert 1952; Diaz et al.
2001; Barron et al. 2012).
Tables 1 and 2 approximately here
Analytic Modeling: All statistical modeling was run in STATA/IC 16.1
(StataCorp 2019) and can be replicated using the associated Stata “do
file” (see Supplemental Information). To examine whether precipitation
and temperature or local energy availability impact monthly birth
pulses, our birth record database was transformed into a monthly birth
pulse database, whereby each row represented the number of births
recorded in a particular community, in a particular month, in a
particular year (See Data Supplement). The outcome variable was the
number of births within a month. The independent variables included
average precipitation by month, average temperature by month, average
NDVI score by month, and the year of birth. To deal with the fact that
some communities did not have births in some months and/or years, we
employ a Zero-Inflated Poisson model which accounts for those cases
where no births were recorded. Because data are nested within
communities, we use clustered-robust standard errors at the level of the
community.
RESULTS
As an initial data check, we perform OLS regression to assess the impact
of average monthly precipitation and temperature on NDVI. Because the
data are nested at the level of the community, we employ clustered
robust standard errors around community. We find that both climatic
variables are significantly related to monthly average NDVI
(R2=0.51; p<.001; n-observations=120;
n-groups=10), with NDVI positively associated with precipitation
(B=0.003; p<.001) and negatively associated with temperature
(B=-0.006; p=.002).