The authors introduce a method for extracting weather and climate data from a
historical plantation document. They demonstrate the method on a document
from Shirley Plantation in Virginia (USA) covering the period 1816–1842.
They show how the resulting data are organized into a spreadsheet that
includes direct weather observations and information on various cultivars.
They then give three examples showing how the data can be used for climate
studies. The first example is a comparison of spring onset between the
plantation era and the modern era. A modern median final spring freeze event
(for the years 1943–2017) occurs a week earlier than the historical
median (for the years 1822–1839). The second analysis involves developing an
index for midsummer temperatures from the timing of the first malaria-like
symptoms in the plantation population each year. The median day when these
symptoms would begin occurring in the modern period is a month and a half
earlier than the median day they occurred in the historical period. The final
example is a three-point temperature index generated from ordinal weather
descriptions in the document. The authors suggest that this type of local
weather information from historical archives, either direct from observations
or indirect from phenophase timing, can be useful toward a more complete
understanding of climates of the past.
Introduction
Weather data from historical periods are important for
understanding climates of the past. Instrumental weather data go back only a
few centuries but historical documents contain observations about the
environment that, as a collection, can be used to understand the climate in
previous centuries. In particular, plantation documents are an excellent
source of useful observations about the local environment. These
observations, when organized and collated, can enrich and extend our
understanding of local climates further into the past. In particular,
the data introduced here do this for the southeastern United States. They
complement other paleo- and historical climate data for the early 19th
century, providing a broader context in which to understand climate
variability and climate change.
Plantation documents, a source for considerable historical research, are
overlooked as a source for environmental research data, with a few notable
exceptions
().
Plantation documents often contain regular observations about the weather
(). Where they
have been used to study weather and climate, typically only a few ordinal
data points are used in support of historical instrumental data
(). Instrumental records
are indeed available at certain times and places in these documents. For
instance, Thomas Jefferson kept thermometer and barometer readings for his
Monticello Plantation for many years . But more
typically, weather observations come in the form of ordinal observations. For
instance, temperature might be described as “hot”, “freezing”, or
“mild”, to name a few (Table ). Similar observations
were made about wind conditions, cloud conditions, precipitation, and
hydrology.
Plantation documents contain regular observations about crops, which can
provide a proxy for the weather conditions under which they grow. For
example, studies have used records of phenophases – stages in the life cycle
– to study spring advancement or to reconstruct temperatures over past
centuries
(; ;
;
; ). These studies typically use one phenophase description
from a single species. As a result, they are restricted to one data point per
year. For instance, this might produce the number of days spring has advanced
in a location over time, spring mean temperatures, or summer mean
temperatures. In contrast, plantation documents typically contain multiple
phenophase observations for several crops each year, making them a
particularly rich resource for proxy weather data.
The goal of this paper is to make plantation documents approachable for
researchers interested in local weather conditions of the past by describing
the process of turning historical documents into accessible scientific data.
Here, we use a document with daily entries from Shirley Plantation located in
Charles City County, Virginia, USA, covering the period of 1816–1842. The
resulting database is then analyzed in three case studies. Replication of the
method for analyzing documents available from other plantations will likely
need some adjustments, but much of the organization structure should
translate. Importantly, data of this kind covering a wider range of dates and
other locations can be valuable for understanding our past climate for times
and places that have minimal coverage from other sources.
This paper expands on earlier efforts to use a plantation document as a
source for historical weather data and offers a structured method for turning
a plantation document into usable data for climate research
. Section 2 provides a brief history of
extracting weather data from historical documents. Section 3 describes how
information from a historical document of Shirley Plantation is organized as
a database. Section 4 discusses the agricultural variables that are included
in the database. Section 5 describes the resulting database and illustrates
how these data can be used for addressing scientific questions using case
studies. Finally, Sect. 6 provides a summary and some caveats and
considerations for future studies.
Weather data from the historical document
Historical documents have become an important source in climate research. The
breadth of document types that have been used is staggering. As an example,
researchers have used agricultural records, ship logs, port authority
records, municipal records for harvest dates, newspapers, poetry, paintings,
and financial reports, to just name a few. A wide array of observation types
can be found in these sources. Researchers have been as creative in finding
climate signals in documents as they have been in natural archives like ice
cores and tree rings .
Map of Tidewater, Virginia. Shirley Plantation is located
along the James River, 20 km (12 mi) southeast of the weather station
at Richmond International Airport. The inset includes the political
boundaries in Virginia during the period of 1816–1842.
The geographical range of these sources is also diverse. Historical
climatology is particularly well developed for China and Europe. By
comparison, research into North America is less robust. The state of
historical climatology for North America is the result of a couple of
factors. Compared to Eurasian documents, written records for North America
started up recently. For instance, administrative records are available for
China going back 2000 years, while records for the Western Hemisphere
mostly start up after European contact. Few records prior to the 16th
century survived. Those records that did exist prior to 1492 were
systematically purged by the Aztec Empire in approximately 1380, and again by the
Spanish Empire during the 16th century
.
As European empires colonized more of the Western Hemisphere, records began
to be produced for these locations. What is now the southeastern United
States, excluding Florida, was one of the last areas to see permanent
European colonies. These colonies were also less centralized, both in regards
to population and administration . This, combined
with a dispersed economy based on slavery and agriculture, means that there
is comparatively few sources to work with when studying this area
.
The Shirley Plantation document
This section describes how information from a particularly rich Shirley
Plantation document was organized into a database. Shirley Plantation is one
of the oldest and largest plantations in the modern United States. It is
located in Charles City County, Virginia, USA (Fig. ). Hill Carter
inherited it in 1806 and started documenting events occasionally in a log
book starting in 1816. He began keeping daily entries in 1820 that continued
until his death in 1875 (data for 1840 are not in the database; the records
exist for the year but have not been extracted into the database). Hill
Carter's son, Robert Randolph Carter (1825–1888), took over management of
the plantation and continued documenting events until his death. The Shirley
Plantation document refers to this single yet extensive log book.
Heat map of species mentioned in the Shirley Plantation
document. This heat map shows which years a crop was mentioned and how many
times it was mentioned that year.
Hill Carter's plantation document records many types of observations
including, but not limited to, a weather diary, plant-phenology observations,
ice-phenology observations, and the phenologies of other species that are
responsive to climate variation. These other phenologies include fungus,
nematodes, insects, and disease-causing parasites. These often came in the
form of crop pests, like wheat rust, cockle, and Hessian Fly, as well as well
public health factors that we now know as Anopheles mosquitoes and
Plasmodium vivax. Carter is a particularly good source because of
his naval background. While serving as a young officer during the War of
1812, he would have learned to keep consistent and accurate records. While he
did not immediately apply this skill set when he took over Shirley Plantation
in 1816, by 1820, he was making consistent daily entries
.
The primary crops grown on Shirley Plantation during this time as noted
in the log book included wheat, corn, and clover. Several other species were
grown intermittently (see Fig. for a full list of crops and the
years they were mentioned in the document). When and how often crops showed
up in the document varied. Staple crops like wheat and corn appeared every
year, while other species like beans were rarely mentioned. The set of crops
remained consistent over the period but it took a few years for Hill Carter
to begin regular entries concerning them, resulting in the years 1816–1819
having very few entries. The first 2 years of consistent entries
(1820–1821) were defined by infrequent observations. For instance, missing
are entries of when the first and last freezes occurred. Beginning in 1822,
Carter kept more consistent documentation. Entries became more common until
they were on a regular daily basis. The level of detail in the individual
entries increased over this period (Fig. ).
Observation type and subcategories used in the Shirley Plantation document.
Number of database entries in non-overlapping 30-day
periods extracted from the Shirley Plantation document.
Each year, the number of observations increased throughout the growing season,
culminating in the harvest of corn in the fall. This general cycle was
disrupted by business trips to New York by Hill Carter. These trips were
usually taken in October of each year, resulting in minimal entries for these
periods. This can be seen in Fig. , where the number of
entries usually dipped in October. Hill Carter had the overseer make entries
in his absence, with mixed results. Upon Hill Carter's return from these
trips, he often expressed dissatisfaction about the how things were managed
and documented by the overseer. After firing the overseer for this
mismanagement in 1824, and then taking him back on, more consistent entries
were kept during these trips, but these were still not up to the same
standards. He did not make the journey in 1825, leaving that year's entries
unbroken. After 1825, the trips resumed and the entries remained consistent
for the rest of the years.
Observation types
There
is a range of observations within the document (Table ). We group them into seven broad types. Weather
observations have the most entries followed by “labor and agriculture” (Fig. ).
Other categories include “operations”, “human”, “livestock”, and
“accounting”. Typically, multiple observations are made in a single day's log
entry. For this reason, there are multiple entries for a single day. A
“type of observation” variable allowed for filtering the data based on
activity (Fig. ).
Weather observations
The bulk of observations (13 461) made at Shirley Plantation were about the
weather. Most days had at least one weather observation, even on Sundays,
when there typically was no agricultural work done on the plantation. There
were often two weather observations per day. One observation would involve
temperature. The other would involve cloud conditions and precipitation. Most
temperature and precipitation observations were ordinal and subject to the
observer's definitions. Working with this type of data has been thoroughly
researched elsewhere . As mentioned earlier,
Carter's observations are notable for their consistency and reliability. Not
only were the entries made daily, but they were generally made first thing in
the morning with consistent language throughout the decades that are covered.
In aggregate, these weather observations can be used to develop ordinal
temperature indices and time series .
Number of database entries per month. Activity on the
plantation increased over the growing season and then diminished over the
fall and winter.
Agriculture observations
About one-third of observations were considered agricultural. Most of the
agricultural observations had to do with the work being done on the crops.
This included activities like sowing, weeding, and harvesting. There were
also discussions of problems encountered: for instance, weather-related
problems like blowovers and water damage from rain. There were also
observations about pests including wheat rust, chinch bugs, and cockle (see
Table for definitions and Table for
alternative terms and archaic spellings used in the document).
Direct observations of phenophases are rare. There are a few mentions of
phases such as the day that a crop emerged or when a field of grain started
heading. Other phenophases can be deduced from agricultural activity. For
instance, most entries do not explicitly say that the cotton crop had leafed.
However, cotton crops would be weeded regularly in their early stages. This
would continue until they leafed. At this point, the leaves would shade out
the weeds. Laborers, both free and enslaved, would be redirected, often to
weeding corn. There are other ways to determine that the cotton had achieved
the leafing stage. Mentions of weeding the cotton crop might end, or the
entry may say that the laborers were now weeding the corn
.
It is important to note that this was a period of agricultural change and
experimentation in Virginia, and Hill Carter participated heavily in these
experiments
.
Fortunately, he was also assiduous in documenting these efforts. He was
careful to specify when he was fallowing and which fields he was doing it to.
He experimented with several fertilizers and soil treatments to address soil
erosion and degradation, and experimented with many cultivars. He documented
when and where these experiments were conducted. He also noted when he tried
new cultivars. Throughout his experiments, he used a few main cultivars every
year. While the use of the various cultivars may have resulted in
inhomogeneities in the plant-phenological records, there is a consistent
reference variety that these can be compared to .
Labor and operation observations
While many entries are about weather and crops, there is also information on
operations and labor conducted on the plantation. Such activities were
performed before planting and after harvesting. Operations ranged from field
preparation like plowing, to thrashing out and delivering grain. Labor
covered activities like hauling and construction. While this may seem like a
straightforward part of plantation life, plantations were a confluence of
multiple agricultural traditions, coming from many regions and linguistic
origins. The result is a patchwork of synonyms, meanings, and spellings, and
terms came in archaic and modern forms.
Archaic terms encountered in the Shirley Plantation document.
TermDefinitionAguean archaic term for illness that is now typically diagnosed as malariaBaukstrip of land where corn is plantedBilious feveran archaic term for illness that is now typically diagnosed as malaria, believed to be caused by an imbalance of the bile tempers of early western medicineChincha pest insect speciesCocklea type of nematode that infects wheatDistemperterm for an illness believed to be caused by an imbalance of the four tempersLaying offsetting up drainage on a terraced fieldListinga partially mortared wall with turf on topLodgingstalk collapse, especially corn and wheatMarllimestone baked in kilns that is then crushed and spread on fields to decrease the acidity of the soil, similar to liming and plasteringRusta fungal crop pestStobfence postWindrowingcutting a row of hay or small grain
Entry type by observation category. The most common entry
was about the weather, followed by agriculture, operations, and labor. Other
categories had many fewer observations.
Multiple terms are used to describe similar preparation activities. Each is
typically associated with a particular crop. For instance, cutting, onioning,
and picking out were terms for harvesting associated with grains, onions, and
cotton, respectively. But picking out could also refer to things grown in
patches like peas and pumpkins (spelled in the archaic form “pumpions” in the
document). All of them refer to harvesting those crops. There were multiple
spellings for some words as well. For instance, “bauks”, strips of land
where corn was planted (Table ), was alternatively spelled as
“balks” and “baulks”. Plaster was sometimes spelled as
“plaister”. Table lists some of the more common terms
with alternative synonyms or spellings. Table contains
definitions for some of these less common and archaic terms.
During this period, plantation owners experimented with various soil
treatments. For instance, the enslaved laborers occasionally limed a field.
This practice of applying crushed limestone before planting would make the
soil less acidic. This could help plants grow more readily and combated soil
degradation. Marl was produced by altering the chemical structure of lime by
baking it. This made it more effective than lime but fulfilled the same
function. Plastering is a similar activity to liming, in which gypsum or some
other plaster is spread on the field to alter the pH balance or replace
depleted nutrients in the soil. Other treatments were intended to improve the
soil quality. Manuring was a common method. This referred to spreading manure
on a field as a fertilizer. It was usually done just prior to sowing
activities. Green manures and cover crops were also common. Peas and beans
were often plowed under instead of being harvested in an effort to improve
deteriorated fields. These preparatory activities are not directly related to
phenology but they can provide useful information. For example, in the
absence of detailed documentation, these preparatory activities can inform
the researcher that seeds have not been planted for that crop yet.
Additional entries
Entries throughout rest of the document fall into the less common categories.
These minor categories were grouped into “accounting”, “human”, and
“livestock” (Table ). For example, accounts of how much grain was
produced and sold can indicate how heavily impacted harvests were by weather
conditions. Human health and activities were often directly impacted by the
weather. Observations of when people were sick were made regularly. This
typically included how many people were sick and what they were believed
to be sick with. Illnesses, deaths, and other observations about the human
population can be useful for showing how often conditions for endemic
diseases like influenza and malaria occurred at the plantation.
Non-agricultural labor activities can inform the entries about prevailing
conditions, such as repairing flood and hurricane damage. While large animal
phenology tends not to be directly affected by spring advancement or other
aspects of climate change, secondary and tertiary impacts like trophic
mismatches can impact livestock and their phenophases
. Health problems and deaths among the livestock
from extreme heat also give insight into weather conditions.
This section discusses the agricultural variables that were put in the
database. We cover the specific information contained in each entry. The
species and cultivar variables provide information on the plant or animal
being observed. Description provides the account given in the plantation
document. The categorical and numerical variables contain the specific
information that can easily be used in quantitative analysis, such as how
many bushels were harvested, or that the plantation was experiencing drought
conditions. These translate into ordinal and interval data, respectively.
Species
Where the species was specified, the information was included. For non-agricultural
activity types, or when the species was not specified, a “not
available” (NA) value was entered. For instance, if the entry states that
corn is being resown, then the species value would be “corn”. Sometimes,
more than one species would be involved. The most common case of this was
when a pest was affecting one of the crops. In these cases, the crop being
grown would be put in the species variable. The pest species would be placed
in the categorical variable. Figure lists all species encountered
in the Shirley Plantation document and the years that species was mentioned.
Cultivar
Specific cultivars of species were occasionally mentioned. Table lists the cultivars mentioned within the document for the
years 1816–1842. Cultivar is part of the taxonomic nomenclature applied to
plant species that have been artificially selected. The nomenclature goes
from the more general to the specific, and is genus, species, subspecies,
cultivar. Tracking the cultivar is especially useful for the 19th
century. New cultivars were developed, experimented on, and further selected
for specific traits. These efforts resulted in significant modification of
the phenological and morphological traits in the crops. These modifications
probably resulted in many of the crop yield gains seen in the antebellum
period, as well as the expansion of the ranges of many crop species
.
Cultivars found in the Shirley Plantation document.
The specific observation or description was entered in this variable. For
instance, the specific phenophase being observed would go here. So, if corn
was observed to be tasseling on a certain day, the entry would read
“tasseling”. If the document noted that the cotton was weeded for the last time
and work began on weeding the corn, there would be two separate entries.
There would be one entry for the end of the cotton weeding and a separate
entry for the beginning of the corn being weeded.
Types of activity for non-agricultural observations are part of this variable
as well. Entries for agricultural operations were given with more specificity. If
some sort of soil treatment was being applied to a field, the type (such as
marl, plaster, manure, etc.) would be entered here. This was also where the
different types of weather observations were denoted. For instance, this
variable would specify if the weather observation was about temperature,
precipitation, or cloud cover. For health observations, the disease or cause
of death was placed here.
The variables “observation” and more general “type of observation”
make it easy to subset the descriptions. It is easy to just look at
descriptions of agriculture activity or to just look at when the human
population was sick. The structure of the data makes it easy to input all the
observations into a single database as the entries are processed. This makes
the data entry more efficient while still being comprehensive but easily
reducible to a subset needed to study a particular phenomena.
This is an improvement on previous methodologies that have been more ad hoc
. Instead of scouring the document for just the
last spring freeze event or the flowering of a particular species, this
method retains the robustness of the original document. This increases the
usability of the data. Within one file, there is information on extreme
weather events, phenology, public health, bioclimatology, and agronomy.
Beyond the immediate concern of studying the past climate, the data have great
interdisciplinary utility. They can be used in environmental and social
history, economic research, epidemiology, and other disciplines. The initial
investment of time is substantial, but the returns are worth it.
Categorical
The categorical or ordinal values of observations were placed here. This was
most important for weather. There was usually some sort of descriptor
accompanying the weather observation. For instance, if the document said that
there was mist on a certain day, the categorical value would be “mist”.
If an observation noted that it was “cold” on a certain day, it would be
entered as “cold”. This is also where freezes and frosts were entered.
This applied mainly to non-agricultural activity entries, but there were a
few exceptions. When a crop was damaged or destroyed by pests, the nuisance
species would be entered here. For instance, when a wheat crop was destroyed
by rust, the “observation” value would be pest, and the categorical value
would be the type of pest, in this case rust. When an agricultural activity,
such as sowing or weeding, would begin or end, that would be entered here as
well. Units for numerical values were made available here.
Numerical entries
Numerical values were occasionally available in the document. These values
are entered in the database. If 200 bushels of wheat were sold after
harvesting, “bushels” would be entered in the categorical variable, and
“200” would go in the numerical variable. This was used to enter a
variety of observations, including the number of people sick on a given day,
thermometer readings, accounting values, etc.
There were intermittent instrumental readings from a thermometer starting in
1822. Temperatures were entered on an irregular basis until the instrument
fell and shattered on 23 February 1824. It was not replaced for several
years. Thermometer readings did not start up again until 4 February 1835.
The document did not discuss the model of thermometer or where it was kept.
While the units were not explicitly stated, summer temperatures were recorded
as being as high as the nineties, clearly indicating that measurements were
in degrees Fahrenheit rather than degrees Celsius.
These thermometer readings were entered in short spurts at different times of
the year. When present, they were typically the first thing in that day's
entry. The entries' consistent location in the daily log suggests that the
instrumental reading was made first thing in the morning, when the daily
temperature is usually at its lowest. The end result is a fairly homogeneous
document of daily minimum temperatures during a few periods. The presence of
the thermometer at Shirley Plantation, as opposed to being read about in an
almanac or newspaper, was confirmed when it was noted that it fell to the
ground and shattered .
There were limits to the precision of the instrument itself. Without knowing
the details of its manufacture, it is not possible to tell how big of a
measurement error there may or may not have been. The placement of the
instrument, such as in the shade or direct sunlight, could also affect
readings. There could be a systematic bias in how the observer was reading
the instrument, such as if the mercury or alcohol in the instrument was
between two ticks, the observer might always round it up or down. It is also
possible for the observer to read the instrument differently from day to day,
or for their method to change over time. The documenting of observations
throughout the year was also inconsistent. The observer might only remember
to document the temperature when it is especially cold or hot. They might
also forget to make the entry if they are especially busy. This can be
random or systematic. During the calving season each year, when the observer
is working long and irregular hours, they might forget to enter the
temperature. They might also think to make an entry in response to extreme
weather events when they would not have usually remembered to. There can also
be more traditional inhomogeneities in the entries. If the instrument is
moved to a different location or height, a systematic bias can be introduced
from suddenly being in direct sunlight or being closer to the ground. For a
more detailed discussion of early instrumental records, see
.
Metadata
The database includes information on the time and place for each observation.
This comprised information like the location of the plantation, date of
observation, citation information, and the name of the location. While most of
these will not be directly used in the data analysis, they provide other
functions. The location data can be used to georeference the database.
Common names are useful for connecting the observations with mentions of the
location in other document such as correspondences. Citation information
allows for reproduction, confirmations of accuracy, and other forms of peer
review. Location information will later enable areal interpolation of the
data as the documents from additional locations are added to the database.
The database
In this section, we describe the resulting database and give three examples of
the types of analyses that can be done with it. The first compares final
spring freezes from the historical period to modern conditions to test for
spring advancement. The second analysis looks at historical accounts of
annual disease outbreaks of what is now thought to have been malaria. We use
modern data to reconstruct when these outbreaks would occur, and compare the
two sets of dates. A three-point temperature index is developed from the
ordinal temperature observations.
Description
Here, we provide some details about the database and then illustrate how it
can be used. The Shirley Plantation documents were scoured for weather and
agricultural information along the lines described in the previous section
and arranged into a database. The result is 22 019 observations in the
database. Table shows a small portion of the database
covering observations during the first week of July in 1838. Reading from
left to right, each successive variable becomes more specific. After the
date, the most general variable, “observation type”, is given. This is
followed by the more specific category, “observation”. For instance,
“agriculture” is one of the observation types. The agricultural observations
for this week included “shelling”, “harvesting”, “problem”, and “phenology”.
Wheat is the only species being worked on, and on four of the occasions it
was specified that the cultivar of wheat being worked on was “purple straw”.
We can see that on the first 2 days of the week, the wheat is harvested and
shelled, often referred to as thrashing (see Table for a
variety of terms that referred to a similar activity). Two problems with the
crop were noted: that it was too ripe and that part of the wheat had become
tangled, making it more difficult to harvest. On the third day, there were
more problems reported. A hurricane had gone through the area, causing the
loss of some of the wheat crop. Additionally, some of the wheat that had been
cut and left in rows (called windrows) had begun to open up and sprout. This
was a result of the crop being overripe and getting wet. For the rest of the
week, the observations focus on harvesting the wheat crop, while continuing
to note that it was too ripe.
There are also observations with the observation type “weather”. Under this
variable, 10 of these were about temperature, with three of these also
giving a thermometer reading. The other seven were ordinal observations,
describing 5 of the days as “hot”, 2 of the days as “cool”, and 1 day
as “warm”. There were observations about cloud cover and precipitation as
well. There were 5 “clear” days and 2 days with clouds and
thunderstorms. 6 July was described as windy. Rain was observed
on 1 and 2 July.
Example of the database extracted from the Shirley Plantation document covering the period 1–7 July 1838. Dates are
indicated in mm/dd/yyyy format.
DateObservation typeObservationSpeciesCultivarNarrativeCategoricalNumerical7/1/1838weathercloud conditionsclear7/1/1838weathertemperaturehot7/1/1838weathercloud conditionsthundering7/1/1838weatherprecipitationrain7/1/1838operationsshellingwheatshelling7/2/1838weatherprecipitationrain7/2/1838weathertemperatureto excesshot7/2/1838agricultureharvestingwheatpurple strawharvesting7/2/1838operationsshellingwheatshelling7/2/1838agricultureproblemwheatripe7/2/1838agricultureproblemwheattangled7/3/1838weathertemperatureFahrenheit877/3/1838weathercloud conditionsclear7/3/1838weathertemperatureto excesshot7/3/1838agriculturephenologywheatopening7/3/1838operationsshellingwheatshelling7/3/1838operationsproblemwheatwindrowssprouting7/3/1838agricultureproblemwheatdestroyed by hurricanelost7/4/1838weathertemperatureFahrenheit907/4/1838weathercloud conditionsclear7/4/1838weathertemperaturehottest day this summerhot7/4/1838weathercloud conditionsseveralthundering7/4/1838agricultureharvestingwheatharvesting7/4/1838operationsshellingwheatshelling7/4/1838agricultureproblemwheattoo ripe7/5/1838weathertemperaturehotter than yesterdayhot7/5/1838agricultureharvestingwheatpurple strawharvesting7/5/1838weathertemperatureFahrenheit927/6/1838weathercloud conditionscloudy7/6/1838weathertemperaturegreat changecool7/6/1838weatherwind conditionswindy7/7/1838agricultureharvestingwheatpurple strawharvesting7/7/1838weathercloud conditionsclear7/7/1838weathertemperaturewarm7/7/1838agricultureharvestingwheatpurple strawharvesting
The database can be examined from various perspectives. For instance, the
heat map in Fig. was constructed by using only database entries
with the observation type “agriculture”. The database closely reflects what
was written in the historical document. If the document said that it rained
and thundered, then two separate database entries would be entered: one for
the rain and one for the thunder, as is the case on 1 July 1838
(Table ). If something specific is required for analysis,
such as days with cloud cover, the database can be subset to include only
entries of “cloudy” and days with “precipitation”.
Earlier spring onset
Here, we illustrate how the database can be used for scientific studies. We
start with investigating spring onset. Here, we ask if the onset of spring
occurs earlier now than it did during the study period. Specifically,
given the warming climate due to greenhouse gases from industrialization, we
expect that the annual dates of the last spring freeze over the period
1822–1839 (before modern industrialization) will occur later, on average,
than the annual dates of the last spring freeze over the later period
1943–2017.
To examine this hypothesis, we use the last date on which there was a mention
of frost, freeze, or snow (after the winter) from the plantation document for
each year. The start year of 1822 is the first year that mentioned freezes.
We compare these dates with minimum temperature data from the nearest weather
station. The weather data were retrieved from the National Oceanic and
Atmospheric Administration's (NOAA) National Centers for Environmental
Information's (NCEI) online repository. Daily minimum temperatures from the
Richmond International Airport weather station (GHCND:USW00013740) over
the period of January 1943 to July 2017 are used. The station is
located 20 km to the northwest of Shirley Plantation (see Fig. for a map of the area).
Dates are expressed as number of days into the year (day of year), with
1 January equaling 1. It is possible that temperatures for the
historical decade dropped below 0 ∘C without frost or snow
being observed, so the given historical values are a more conservative
measurement of the last freeze (could have been later) relative to the
hypothesis. Figure is a histogram of last spring freeze
events in the instrumental period. The vertical black line represents the
median value for the historical period. The historical database had a median
end-of-freeze date of 107.5 (17 or 18 April). The modern median final spring
freeze event date was 100 (10 or 11 April), or a difference of 7.5 days.
Because the historical last spring freeze data constituted a small sample
size, a nonparametric one-sided Wilcoxon (Mann–Whitney) signed-rank test was
used to test the statistical significance of historical final spring freezes
coming later in the year than in the modern instrumental period
. The W value for the test was 797, with a
p value of 0.015. This indicates that the two groups' distributions
differed in a statistically significant way, with modern final spring freezes
occurring earlier than they did in the past. This indicates that spring onset
is occurring earlier than in the historical period. The difference in freeze
dates is smaller than the one found in a previous study that only covered the
historical period of 1822–1828. In that study, there was a difference of 23 days,
indicating much cooler temperatures in the 1820s compared to the
1830s . The example shows how the data might
be useful for comparing the past with the present. They can be used to study
how differing climate conditions have impacted crop survivability and yields,
and how agricultural practices have changed in response to climate variation.
Histogram of last spring freeze days. This figure shows
the distribution of last spring freeze days in Richmond, Virginia, from
1942 to 2017. The black vertical line shows the median last spring freeze
events in the data extracted from the Shirley Plantation document covering
the period 1822–1838. There was one year where no freeze events were
documented for the spring. This leaves 16 years in the historical set.
“Ague and bilious fever”: first new infection date as indicator of midsummer temperature
Before germ theory and microscopes, malaria was often diagnosed as “ague and bilious fever” (see Tables
and for related terms and their definitions). Figure shows the period each year when “ague
and bilious fever” symptoms were reported on Shirley Plantation. This covers the years 1823–1842, with 1839–1841 missing
data. The earliest reports of symptoms occur in mid- to late July, indicating especially warm years. Most years saw outbreaks
begin in September. A few years only saw mentions of ague and fever in the first few days of October. These are often reports
that there were very few or no cases that year. The season typically ends before Hill Carter left on his annual trips, resulting
in complete documentation for most years. The parasite Plasmodium is responsible for the disease known as malaria.
Plasmodium vivax is one of the mosquito-borne pathogens that cause malaria. Plasmodium falciparum is another,
more deadly, malaria-causing parasite. Plasmodium malariae is a third, though less common, Plasmodium pathogen
. This parasite has a complex life cycle and has specific environmental requirements that must be met
for it to be able to infect human hosts. The beginning of the Plasmodium season, when symptoms emerge, the end of the
Plasmodium season, marked by the last new case, and the length of the season between those two dates also offer important
information about weather conditions.
An index of midsummer weather conditions can be constructed using historical
public health data. The phenology of insects, and the parasites they carry,
is sensitive to temperature . Plant phenophases
like flowering and harvest dates have been used to study changes in climate
conditions . These types of indices,
models, and reconstructions can be applied to other temperature-dependent
phenologies .
Plasmodium parasite development response to temperature can be
modeled similarly to how crop phenology is, with degree days
, using the following formula:
DS=DDT‾-18,
where DS is the number of days it will take for the parasite to mature
(duration of sporogony), DD is the number of degree days required for
parasite to mature, T‾ is the daily mean temperature, and 18 is the
minimal temperature threshold for degree days to accumulate for the species
. The sporogony of Plasmodium vivax, the
type of malaria parasite common in the Tidewater region of Virginia during
the 19th century, requires 105 degree days to accumulate before it
becomes infectious . Both the
Anopheles mosquito and Plasmodium parasite respond to
temperature in their development .
It is not necessary to diagnose specific cases of Plasmodium
infection from the historical document. We know that it was endemic to the
area. We know that the population was affected nearly every year. We know
that the phenological constraints resulted in the infection season occurring
in the same time period each year, just like wheat harvests or cherry
blossoming
.
This produces the parameter for the new index: first new cases reported. This
can be represented as the day of year. There is a series of events that must
occur before the first symptoms are detected. The female Anopheles
mosquito must become infected while taking a blood meal from a human. The
mean daily temperature must be warm enough for the sporogony cycle to begin.
The mean temperature during sporogony must be high enough to complete the
cycle within the lifespan of the mosquito host. The mosquito host must
transmit it to a human. Finally, the parasite must incubate in the human host
for 12–18 days (for P. vivax and P. falciparum) before
symptoms appear .
Reports of ague and fever in the Shirley Plantation
document during the period 1823–1842. Data for 1839–841 have not been
generated yet. There are two decades of data, minus the missing years. Onset
of symptoms indicates that the mean daily temperatures had been above
18 ∘C (64.4∘F) long enough for the
sporological cycle of Plasmodium to complete in the host
Anopheles mosquito. The green line indicates when the first case
was reported. The red line indicates when the last report occurred.
By the time symptoms appear, the daily mean temperature in the area has been
above 18 ∘C (64.4∘F) for 2–4 weeks.
This can be further examined if we know what species of Plasmodium
are endemic to a region. For instance, P. vivax can survive in
cooler conditions better than others. Its lower temperature threshold for
development allows for it to complete its life cycle in regions that would be
too cold for P. falciparum. As a result, this is the dominant
species in temperate regions like southeastern England and Tidewater,
Virginia (USA) .
While malaria has been eradicated in Virginia, we can estimate by using
temperature data when the sporological cycle (P. vivax) would
complete. For instance, if malaria were present in Virginia today, the
Anopheles mosquito would become infectious after a sustained warm
period. Warm periods are defined using accumulated degree days. A degree day
in this case is defined as the difference between the daily mean temperature
and 18 when the daily mean exceeds 18 ∘C. A sustained warm period is
one in which the accumulated degree days over a consecutive 26-day period
exceed 105. Our interest is in the earliest sustained warm period date of
the year where the date is the last day of the 26-day period.
Using the Richmond International Airport Weather Station temperature data, we
compute the accumulated degree days above 18 ∘C in rolling 26-day
increments to determine the earliest sustained warm period each year over the
period 1942–2017. We add 18 days to this date to account for incubation
period (conservatively, as the incubation might be faster), giving us an
estimate of when we might get the first cases of malaria (onset date).
We then used the historical and expected modern onset dates as indicators of
summer temperature conditions. The median first date of symptoms being
documented on Shirley for the period 1822–1838 was the 230th day of the
year. The median date for when symptoms would begin occurring in the modern
period from 1942 to 2017 was the 185th day of the year (see Fig. ).
Median dates for malaria symptoms conditions occurred 45
days earlier in the modern period than they did in the historical period.
This indicates much warmer conditions in the modern period.
Histogram of expected first malaria symptoms in Richmond,
Virginia, using data from 1942 to 2017. The black vertical line shows the median
first malaria symptom reports in the data extracted from the Shirley
Plantation document covering the period 1822–1838.
It is important to recognize that temperature is not the only limiting factor
in the development of Anopheles and Plasmodium. For
instance, dry conditions can leave more water stagnating, providing ideal
development conditions for the larva and pupa stages of mosquitoes. Large
amounts of precipitation on the other hand can wash away water, making it
difficult for mosquitoes to complete their life cycles
.
Human activity can also alter the life cycles of Plasmodium and
Anopheles. Even factors like proximity of dwellings and work spaces
to areas where Anopheles eggs and larva develop can impact infection
rates and timing. The timing of labor activities can also influence this.
For instance, people on Shirley would be much more likely to get infected
while working on reclaimed swamp land. This part of the plantation had
trouble dealing with standing water and was in close proximity to the
remaining swamp land . Without having controlled
for these other environmental conditions, this analysis can only be
suggestive of changes in climate .
Like the comparison of final spring freeze events in the first analysis, this
allows a comparison to be made between ordinal data, commonly found in
historical documents, and numeric data from modern instruments. In this case,
we compared midsummer temperature conditions across epochs. Where the first
analysis allows us to compare temperatures by using observations of water
undergoing a state change at 0 ∘C, the analysis of malaria symptoms
allows us to analyze summertime temperatures. The later method can be
extended to any place and time where malaria was endemic and its effects
documented.
Temperature index categories.
HotNeutralColdexceptionally hotfairbelow freezingexcessively hotfinecoldhotmildcoolhottest day this yearmild and pleasantexceedingly coldhottest morning this yearmilderexcessively coldindian summermildest winter ever known this farexcessively cold for seasonsultrymoderatefirst frostvery hotnicefreezevery warmpleasantfrostvery warm for seasonvery mildfrost very slightviolently hotwarmfrozenworkers fainted from heatwarm and pleasantground frozenwarmericelight frostriver frozenriver hard frozenriver nearly frozensecond frostsevere frostsevere white frostseverest frost yetsmart frostturned colderturning coldvery coldvery cold violent changevery coolwhite frostwinteryThree-point temperature index
A three-point temperature index was created for the 1820–1842 period. This
style of temperature index was first developed by Hubert Horace Lamb
. It organizes ordinal descriptions from
historical records onto a three-point scale. Cold conditions are given a
negative value, hot conditions are given a positive value, and neutral
conditions were given the value of zero. Christian Pfister expanded on the method to
create a seven-point index. However, the seven-point method requires a
second dataset to validate the indexed data. Since this is not yet
available for the study region, we will be using the three-point index here
.
Three-point temperature index for the period 1816–1842.
See the text for a discussion of how the index was constructed.
Ordinal descriptions of temperature were organized into three categories:
hot, neutral, and cold. Table shows how the categorical
temperature values were broken down into the three-point index. There were
12 values assigned to hot, 13 values were assigned to neutral, and 29 were
assigned to cold. A rolling mean was taken for each day using the values for
the 30 days surrounding it (the day's value, as well as the previous 15 days,
and the 15 days after it). Figure shows the index covering
1820–1842. The rolling mean allows the data to be smoothed without losing
its daily resolution. The index is in line with what we expected. The
temperature index is at its highest during the summer months and lowest
during the winter. The temperature index data are available at
https://github.com/gdb12/Historical-bioclimatology (last access: 1 February 2019).
The daily resolution of this data has some advantages. Most ordinal
temperature indices developed from historical documents are at the seasonal
or annual level. Daily data will allow future research to investigate
day-to-day variability. It can also be used in conjunction with daily
thermometer readings and a Pfister scale to reconstruct temperatures at the
daily, weekly, or monthly temperatures. This can then be aggregated to
seasonal and annual levels so it can be used in conjunction with other
reconstructions .
Summary
We extracted historical environmental and weather data from a plantation
document written over the period 1816–1842 at Shirley Plantation in
Virginia, USA. We detailed the methods used to extract the data from the
document and made the resulting index available as a dataset. The method
provides a recipe for others interested in extracting data from similar
historical documents. The database covers 25 years of plantation entries,
resulting in 22 019 entries in the database. The majority of the entries are
ordinal observations of weather. Currently, the database contains more than
2000 entries about agriculture that can be used for phenological
studies of climate. There are also intermittent instrumental entries.
This database makes contributions in a few arenas. One use of historical
climate records is in conjunction with paleoclimate records, adding daily
resolution data to what is available from methods like dendrochronology
. These
records can also function as a Rosetta stone. Just within the Shirley
Plantation's record, there are thermometer readings, extensive plant, ice,
insect, and parasite phenological records, and ordinal weather observations.
Once these data are calibrated and validated, they can be used to extend our
understanding using these different types of data from other documents. For
instance, the ice-phenological information can be combined with observations
of the same type from other sources, such as other plantation records,
personal diaries, travel accounts, and ship logs (the James River is
navigable up to Richmond, Virginia). These records also allow us to study the
phenology of important agricultural species prior to the intensive
modification of these species over the past 200 years through
selective breeding and, more recently, genetic modification.
These data are also unusual for when they are being produced. By the mid-18th century,
most ordinal weather diaries had abruptly ended in favor
of instrumental observations from thermometers, barometers, and other newly
developed scientific instrumentation. As a result, there is very little
overlap between ordinal and instrumental weather data. Most sources for
historical climate data in Europe made this transition within a very short
time span. This same scientific turn can be seen in many North American
sources, such as in the records of Thomas Jefferson and James Madison
. With so little overlap to train in transfer functions,
it is often difficult to calibrate and validate ordinal data
. The Shirley Plantation document continues in the
ordinal tradition more than a century after most other such documents end.
This is concurrent with some of Hill Carter's own intermittent instrumental
measurements and other such records that were produced in the area. As a
result, this database represents an extraordinary opportunity to test
calibration methodologies .
Using the database, we compared historical and modern spring onset dates and
showed that the median spring onset occurs a week earlier in the modern
period. As the mean global temperature increases, measures of spring onset
have been shown to occur earlier. These changes in temperature regimes can
result in shifts in the phenology of plants and animals. Member species of an
ecosystem can respond differently to these changes. Some plants will respond
to spring advancement by flowering earlier in the year. Other plants are not
responsive to these changes. The pollinators will have their own responses to
the changing climate. The end result is disruptions to the flow of energy and
resources. This has been shown to cause loss of plant populations in places
like Walden Pond in Massachusetts . These
trophic mismatches have also increased the infant mortality rate among
caribou, which are dependent on plants being at their most nutrient rich
during calving season . Studies like this help
measure the severity of spring advancement. This can in turn be used to
predict where trophic mismatches are most common and have the greatest
impact. This type of information is key to planning mitigation strategies for
dealing with global climate change.
Using our database, we also showed how public health data can be used as an
index for summer temperatures. Because of the temperature sensitivity of the
Plasmodium parasite, the daily mean temperature in the area has to
remain above 18 ∘C (64.4∘F) for 2–4
weeks for the first new infections to begin. Thus, the first appearance of new
infections indicates how warm the midsummer period was each year. This in
turn can be used as a proxy to study the interannual variability of
temperature in the absence of instrumental records. A three-point
temperature index was developed using the data. Future research will expand
this into a validated seven-point index.
There are additional considerations to keep in mind when using the database.
Although we have already put approximately 3000 work hours into the database,
we are not yet halfway through the Shirley Plantation document. And there is
an additional 25 years of related documents maintained by Hill Carter's son.
There are also other similar documents from locations throughout Virginia and
the southeastern United States. It is also important to keep in mind how
these document were kept. The absence of a document does not ensure the
absence of the event. Hill Carter would write down the weather conditions in
the morning and update the entry with the work conducted throughout the day.
Changes in weather throughout the day would often be recorded, but it is not
certain that all such changes were documented. A common problem with
historical documents is that events in the night would not be observed. Hill
Carter often observed that there had been rain in the night (such details can
be found in the narrative variable of the database, as seen in Table ).
However, it is not clear how often this occurred without him
observing and documenting it. The descriptions themselves are often
subjective as well. A pleasant day in winter most probably has different
temperature conditions than a summer day that was described as pleasant.
Further, how plantation documents were kept can vary across space and time.
The way Americans kept these documents may have been very different from
other former British colonies. What was deemed important to creditors could
also influence this. If an area was more likely to be financed by British
banks than American, then there could be more similarities between American
cotton plantations and British sugar plantations, than with tobacco
plantations in the upper south. Different imperial metropoles could have
different expectations as well. The French Empire could have different
standards and practices compared to the British, Spanish, or others. Further
complicating and enmeshing these systems was the transfer of territory. What
became the Louisiana purchase changed hands between the French and Spanish
several times before becoming an American territory. This resulted in
documents from this area being in French, Spanish, Creole, and English, and
having influences from the French, Spanish, British, and American systems
. While
any analysis conducted using these documents needs to keep the limitations in
mind, they do not negate the value of these documents.
Future work will focus on validating the data, expanding the database, and
producing an in-depth analysis of the climate of Virginia. The most immediate
concern will be data validation and calibration. We will test to see how well
the data capture large-scale climate phenomena like the El Niño–Southern Oscillation (ENSO), tropical cyclone
activity, and the aftermath of the Mount Tambora eruption. Calibration has
proven to be more elusive. While there are a few thermometer observations in
the data, they are too rare to be used for calibration. None of the local
newspapers published temperature records for this period either. However,
additional plantation records from other nearby plantations, such as
Berkeley Plantation (9.65606 km southeast of Shirley Plantation) will allow for
content analysis validation . Thomas Jefferson's
temperature observations offer another possible dataset for validation and
calibration. During his tenure as ambassador to France, Jefferson confirmed
that his own thermometer was consistent with the official instrumental
records in France, and maintained twice daily instrumental and ordinal
weather observations during his 4-year residency there. This will allow us
to calibrate North American records to their European contemporaries and
validate other North American temperature records. Jefferson's own plantation
records, from his garden book, have already been extracted to a database by
our team . Work has begun on extracting
Jefferson's temperature records, including his time in Paris, France
.
Additional years at Shirley Plantation will be added to the available data.
Documents from additional plantations in Virginia will be analyzed as well.
Temperatures will then be reconstructed using the response of various species
to prevailing weather conditions. This can then be used to create a
“phenochronology”, similar to dendrochronology, but using historical
phenological observations of plants similar to what
have done with cherry blossoms, and what
have done with grape harvests. Because entries
for several different species (Fig. ) are available in the
database, they can be combined to refine reconstructions and fill gaps in the
document for individual species.
Code and data availability
The temperature index data and code for this project are available
at https://github.com/gdb12/Historical-bioclimatology (last access: 1 February 2019).
Author contributions
GB, JE, and RD designed the study; GB, JW, OL, and SD extracted the data and built the database; GB and JE
analyzed the data; GB wrote the initial draft; all authors contributed to writing and editing.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to acknowledge the financial support from the Florida
State University Robert B. Bradley Library Research Grant, Graduate School
Dissertation Research Grant, and the Undergraduate Research Opportunity
Program (UROP) and material grant.
Review statement
This paper was edited by Chantal Camenisch and reviewed by two anonymous referees.
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Series D. Selections from the Maryland Historical Society. 14 reels Series E.
Selections from the University of Virginia Library. Part 1, Virginia
plantations. 39 reels. Part 2. [without individual title] 26 reels. Part 3.
[without individual title] 30 reels. – Series F. Selections from the
Manuscript Department, Duke University Library. Part 1, The deep South. 23
reels. Part 2. South Carolina and Georgia. 16 reels. Part 3. North Carolina,
Maryland, and Virginia. 45 reels Series G: pt.1, Texas and Louisiana
Collections; pt.2, William Massie Collection. – Series H: Selections from
the Howard-Tilton Library, Tulane University, and the Louisiana State Museum
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Societies and Natural Increase in the Americas, Am. Hist. Rev., 105, 1534–1575, 10.2307/2652029,
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plantations in the antebellum South, PhD, Yale University, United
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available at: http://search.proquest.com/docview/305494325/abstract/33E11AFCF4C4AB8PQ/1?accountid=4840
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White, S., Pfister, C., and Mauelshagen, F.: The Palgrave handbook of climate
history, Palgrave Macmillan, London, oCLC: 934193528, 2018.Wilcoxon, F.: Individual Comparisons by Ranking Methods, Biometrics Bull., 1, 80–83, 10.2307/3001968,
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