the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Nov 2024
Public granaries as a source of proxy data on grain harvests and weather extremes for historical climatology
Abstract. Public granaries served as key infrastructures to improve food security in agrarian societies. Their history dates to the oldest complex societies, but they experienced a boom period during the 18th and early 19th centuries in Europe. In Bohemia and Moravia (modern-day Czech Republic), numerous granaries were established by decree in 1788 to provide serfs with grain for sowing in the face of fluctuating weather. Here, we analyze granary data from 15 out of a total of 17 considered domains in the Sušice region (southwest Bohemia) from 1789 to 1849 CE. We use the documented annual values of grain borrowed by serfs, their grain depositions, total grain storage, and the total debt of serfs at the end of the year as proxies for harvest quality and size. Based on the series of these four variables, we calculate weighted grain indices, considering the balance between borrowed and returned grain: a weighted bad harvest index (WBHI), a weighted good harvest index (WGHI), a weighted stored grain index (WSGI: WSGI-, more borrowed than returned; WSGI+, more returned than borrowed), and a weighted serf debt index (WSDI: WSDI+, more borrowed than returned grain; WSDI-, more returned than borrowed grain). WBHI, WSGI-, and WSDI+ were used to select years of extreme bad harvests, and WGHI, WSGI+, and WSDI- to identify years of extreme good harvests. We tested selected extreme harvest years against documentary weather data and reconstructed temperature, precipitation, and drought series from the Czech Lands. We discuss the uncertainty of the data and the broader context of the results obtained. The findings document the potential of this new methodology, using widely available public granary data as proxies for historical climatological research.
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RC1: 'Comment on cp-2024-69', Anonymous Referee #1, 21 Nov 2024
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This is a well-organized and thorough case study, which examines how granary records may reveal the impacts of climate variability on harvests. To my knowledge, it is the first study of its kind, and the methods developed here could be useful in other regional contexts as well.
Before publication, I would like the authors to address the following:
First, since past studies have usually examined the impacts of climate variability on harvests by looking at grain prices, could the authors specifically address what the study of granaries contributes to our understanding of climate/weather and harvests that the study of prices does not? For example, does this study indicate more vulnerability or less vulnerability of farmers’ harvests and livelihoods to climate variability than the grain price data indicate? Does it indicate the same or different patterns and trends in climate/weather impacts on harvests?
Second, the study should discuss (at least briefly) how granaries might have interacted with grain markets or with farmers’ behavior. Currently, the study seems to assume that farmers used the granaries only as intended—that is, they borrowed when times were bad and paid back when times were good. But might farmers have used the granaries in other ways? Did they come to rely to some extent on the granaries and take greater risks? Were the grains that were grown from seed corn taken from the granaries used primarily for consumption, or were they sold to buy other food, pay rent, etc.? Could farmers have tried to borrow seed to expand production in expectation of higher prices? Might farmers have willingly maintained a debt to the granary in order to plant or sell more grain and thereby improve their financial condition during average or good years? If there is no evidence that farmers did any of these things, then it would help to add a couple of sentences explaining this.
Third, the visualization of the results (i.e., presentation of the various indices) could be improved for greater clarity and utility. The way results are presented in tables 2 and 3 makes it very difficult to identify the evolution of good and bad years, to identify periods of frequent or consecutive harvest failures, and to compare the performance of different grains to one another. It is also hard to judge the reliability of good/bad harvest determinations based on data from only 1-2 domains. (E.g., how should I compare the third worst year based on only one domains’ data with the fourth worst year based on seven domains’ data?) Therefore, the ranked lists of the worst and best harvest years for different grains were not especially helpful.
It might have been helpful to see a single timeline showing all index values for all grains each year (or at least whether each index was >1, 0.5–1, -0.5–1, <-1). If such a figure would be too messy, then the authors should determine some other appropriate way to visualize the data so that the evolution of good and bad years, the periods of frequent or consecutive harvest failures, and the comparative performance of different grains is easier to see.
I would have also liked to see some brief discussion of the correlation among harvests for different grains in the same years, and whether there were lags or autocorrelation in the indices (possibly indicating persistent agricultural problems or economic hardships following especially bad harvest years).
Fourth, when discussing the relationship between climate/weather and harvests, the paper considers only those years which had a good or bad harvest and then examines the range of weather conditions for those years. This is useful, but this approach can only investigate one kind of causal relationship: how necessary were certain climate/weather conditions for a good or bad harvest [i.e., the probability of good or bad weather given a good or bad harvest, or p(weather|harvest)]. Sometimes, we might want to know how sufficient certain climate/weather conditions were for a good or bad harvest instead [i.e., the probability of a good or bad harvest given some good or bad weather, or p(harvest|weather)]. In fact, for some kinds of studies, the question of causal sufficiency will be more important than causal necessity. For example, it would be interesting to know whether or not very cold wet summers consistently brought bad harvests (a question of causal sufficiency), even if most harvests failures might have happened for other reasons (a question of causal necessity). To address causal sufficiency, we would have to start by examining the years with good or bad climate/weather conditions and then see how often they brought good or bad harvests, which is the reverse of the current discussion in section 4.4.2. This should not require a lengthy analysis, but only a test of the most likely patterns, or even some simple counting: e.g., “of x summers with below average temperature and above average precipitation, y were followed by a poor harvest, as indicated by z indices.”
Citation: https://doi.org/10.5194/cp-2024-69-RC1 -
RC2: 'Comment on cp-2024-69', Anonymous Referee #2, 27 Nov 2024
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General comments
Thank you for the opportunity to review this manuscript. To my knowledge, this is a first in a European (if not global) context and introduces an important new proxy for the documentary analysis of historical grain storage and hence climate variability.
The paper is beautifully written, clearly structured, contextually rich and well supported through references to previous studies. The historical context for the data is recorded clearly and succinctly, and at a level suitable for an international audience. Other than the specific point below, the methodology is clear and straightforward. The results are well presented and explained, and the statistical analysis clear and appropriate.
I really value the transparency over data availability from granaries shown in Figure 5, the corroboration of good and bad harvests from more general documentary evidence in section 4.4.1, and the comparison with wider regional studies. The discussion of the links between grain harvests and climate is strong, reflecting the multiple possible causes of a good vs. bad year. The reflections on the challenges of using grain harvest data are discussed honestly and openly. In short, aside from one relatively minor comment, I have no hesitation in recommending the manuscript for publication.
Specific comments
Lines 168-173. I’m interested to hear more about how well this methodology deals with multi-year (as opposed to single-year) poor harvests. Did multi-year runs of crop failure occur during the study period and, if so, what happened as a result in granaries? I notice at least one instance of this mentioned in the results. There is also mention in Lines 444-446 of granaries being empty – an obvious limitation of the proxy – due to factors in addition to harvest levels.
Line 525. Anthropogenic would be better than man-made.
Citation: https://doi.org/10.5194/cp-2024-69-RC2
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