DOI: 10.5061/dryad.brv15dvj5
title: Data from: Disentangling the effects of temperature and rainfall on the population dynamics of Kalahari meerkats

description: In arid habitats, recent increases in summer temperatures associated with
 global warming are adversely affecting many animal populations. However,
 annual rainfall also varies widely in many of these areas, and we do not
 yet fully understand the relative impact of variation in temperature and
 rainfall on the demography of arid-zone species. Here, we examine the
 effects of temperature and rainfall variation on the demography of
 meerkats (Suricata suricatta) in the southern Kalahari over the last 25
 years. During this period, average maximum monthly air temperatures at our
 study site increased by around 1.5ºC to 3.2ºC, while annual rainfall
 fluctuated without a consistent trend. We show that annual changes in
 female fecundity and recruitment were more closely correlated with
 variation in rainfall. Increasing air temperatures were associated with
 reductions in the recruitment of pups and the survival of some age classes
 but, in most cases, the demographic consequences of high temperatures were
 modest compared to the effects of low rainfall, which in some years led to
 the near cessation of successful reproduction and the extinction of many
 smaller groups. For instance, exceptionally low rainfall in 2012-2013 was
 associated with low recruitment and with declines in group size and
 population density, which fell by over 50%. Unusually hot years did not
 have similar consequences. Following the 2012-2013 drought, intermittent
 years of low rainfall and frequent droughts continued to suppress
 recruitment and slowed the population’s recovery. Future changes in
 temperature may affect the dynamics and size of the meerkat population,
 but our work suggests that over the last 25 years, annual changes in
 rainfall have exerted a stronger influence on meerkat demography. Our
 study demonstrates the importance of long-term, individual-based data for
 determining how changes in climate affect the dynamics of animal
 populations, especially in arid environments where bottom-up processes
 often dominate.
description: The data was collected as part of a long-term study of meerkats
 in the southern Kalahari Desert. All methods of data collection are
 outlined in the paper and are also summarised in Clutton-Brock and Manser
 (2016). The project's data is stored on a centralised SQL database
 and was processed for analyses by the lead author using R.  
 Clutton-Brock, T.H., & Manser, M.B. (2016) Meerkat:
 cooperative breeding in the Kalahari<em>. In Cooperative breeding in
 vertebrates</em>. (eds, W.D. Koenig, & J.L. Dickinson), pp.
 294-317. Cambridge University Press, Cambridge, UK.
 https://doi.org/10.1017/CBO9781107338357.018
description: # **Disentangling the effects of temperature and rainfall on the
 population dynamics of Kalahari meerkats**
 [https://doi.org/10.5061/dryad.brv15dvj5](https://doi.org/10.5061/dryad.brv15dvj5) The R code and data sets in the repository can be used to replicate the analyses in our paper "**Disentangling the effects of temperature and rainfall on the population dynamics of Kalahari meerkats**" ([https://doi.org/10.1111/oik.10988](https://doi.org/10.1111/oik.10988)) The aim of the study was to explore the relative impact of variation in rainfall and temperature on the demography and population dynamics of meerkats, a cooperatively breeding mongoose that lives in the semi-arid regions of southern Africa. #### The analyses are contained within four distinct R scripts. **(1) Analysis 1 - Climate and vegetation productivity trends and relationships.R** **(2)** **Analysis 2 - Trends in demographic parameters and adult body mass.R** **(3) Analysis 3 - Effects of climate on demographic parameters.R** **(4)** **Analysis 4 - Group extinctions.R** #### **All data sets are also contained within the repository.**  **(1)** **MeerkatMonthlyRain.csv** - Long-term rainfall data for the Kalahari * rain_noaa: monthly total rainfall (mm) from the Climate Prediction Center’s global preciptation product (NOAA, 2023) - rain_gpcp: monthly total rainfall (mm) from the Global Precipitation Climatology Project v3.2 (Huffman et al., 2023) * rain_onsite: monthly total rainfall (mm) measured onsite at the Kalahari Research Centre. **(2) MeerkatDailyTemp.csv** - Long-term temperature data for the Kalahari *  tempmin_noaa: daily minimum near-surface air temperature (°C) from the Climate Prediction Center’s global temperature product (NOAA, 2023) -  tempmax_noaa: daily maximum  near-surface air temperature (°C) from the Climate Prediction Center’s global temperature product (NOAA, 2023) * tempmid_noaa: daily mean near-surface air temperature (°C) from the Climate Prediction Center’s global temperature product (NOAA, 2023) **(3) MeerkatSPEI.csv** - Long-term drought index for the Kalahari *      SPEI-1: 1-month Standardized Precipitation-Evapotranspiration Index (SPEI), taken from the global SPEI database (Beguería et al., 2014) -      SPEI-2: 2-month Standardized Precipitation-Evapotranspiration Index (SPEI), taken from the global SPEI database (Beguería et al., 2014) *      ...SPEI-X: Further X-month SPEI values, taken from aken from the global SPEI database (Beguería et al., 2014) **(4) MeerkatSIVofNDVI.csv** - Annual vegetation productivity in the Kalahari  * SIV_NDVI_mean: The mean small integral value of NDVI across the meerkat population in each breeding season*. The SIV of NDVI, which provides a measure of total vegetation productivity per season, was calculated with the TIMESAT software v3.3 (Jönsson and Eklundh, 2004) on using NDVI time series data taken from the MODIS MOD13Q1 product (Didan et al., 2015).  * AnnualRainfall_GPCP: Total annual rainfall (mm), as measured by the GPCP project, in each breeding season.  * AnnualRainfall_NOAA: Total annual rainfall (mm), as measured by the CPC product, in each breeding season.  * AnnualRainfall_Onsite: Total annual rainfall (mm), as measured onsite, in each breeding season.  **(5) MeerkatPopulationDensity.csv** - Monthly population size and density  * nGroups: Number of meerkat groups contributing to the populaiton size and density measures. In this paper, only established groups provided high resolution GPS data were considered. From these groups we could estimate individual or group-level density.  * PopulationSize: The number of meerkats in the population each month. Mean of daily counts.  * MeanGroupSize, l95GroupSize, u95GroupSize: The mean group size in each month, with associated confidence intervals estimated through bootstrapping. * IndDensity_KDE, l95IndDensity_KDE, u95IndDensity_KDE: The mean population density (individuals/km²) in each month, with associated confidence intervals calculated through jack-knifing. The KDE refers to the fact that density was estimated by aggregating the 95% Kernel density estimate of each group's space use, before dividing the number of individuals over this area.  * GroupDensity_KDE, l95GroupDensity_KDE, u95GroupDensity_KDE: The mean group density (groups/km²) in each month.  **(6) MeerkatAgeStructure.csv** - The age structure of the population of time * AgeClass: Either pups (&lt; 90 days), Juveniles (90 days - 6 months), Subadults (6 months - 1 year), Adults (&gt; 1year) * Proportion: Proportional representation of the age class in the population **(7) MeerkatTrends.csv** - Annual demographic rates in the population (per breeding season*) * ngroups: number of groups followed across the year * mean_pregnancies: mean number of pregnancies recorded per group (± SD, ± SEM) * mean_dompregnancies:  mean number of dominant female pregnancies recorded per group (± SD, ± SEM) * mean_subpregnancies: mean number of subordinate female pregnancies recorded per group (± SD, ± SEM) * mean_subpregnancies_percapita:  mean number of subordinate pregnancies recorded per group per capita (± SD, ± SEM) * mean_litters: mean number of litters born per group (± SD, ± SEM) * mean_domlitters: mean number of litters born to subordinate females per group (± SD, ± SEM) * mean_sublitters: mean number of litters born to dominant females per group (± SD, ± SEM) * mean_fecundity*_*pergroup: mean number of pups born per group (± SD, ± SEM) * mean_recruitment_pergroup: mean number of pups recruited to 90 days per group (± SD, ± SEM) * totaladult/subadult/juvenile/pupsurvival: Total survivorship of individuals in each of the four age classes. For adults, subadults, and juveniles, survival was assessed from the start of one breeding season to the next breeding season. For pups, it was estimated for all pups born in the year, between emergence to recruitment at 90 days.  * meanadult/subadult/juvenile/pupsurvival_pergroup: As for the former, but averaged per group (± SD, ± SEM).  **(8)** **MeerkatPopulationAnnualBodyMass.csv** - Long-term variation in adult body mass * nind: Number of adults weighed in the population in the breeding breeding season.  * nwtsperind: Number of times each adult was weighed across the breeding season, on average.  * avgMass: The mean of each individual's mean mass across the year (± SD, ± SEM) **(9) MeerkatPopulationSeasonalBodyMass.csv** - Long-term variation in adult body mass across seasons * As for (8) but separated into three climatically distinct seasons, early summer (Sep-Nov), late summer (Dec-Apr), and winter (May-Aug).  **(10) MeerkatDemography.csv** * A streamlined version of dataset (7) that was used in analysis (3). All column headers follow that used in dataset (7). **(11) MeerkatGroupExtinction.csv** - Annual survivorship of meerkat groups ~ group size.  * GroupRef: Unique group identifier * FinalEndDate: On what date did the group end.  * breeding_season: The breeding season * GroupSize: Group size at the start of the breeding season*.  * Fate: How did the group end (Failed/FollowEnded/Current2023).  * FinalYear: Was is the group's last year in the population (N/Y) * Failed: Did the group fail and thus go extinct in the given year.  If you would also like further information on other aspects of the paper, including additional code that I used to generate the datasets (e.g. climate data, SIV of NDVI, home range sensitivity analyses), then I can be contacted at [jackthorley1@gmail.com](mailto:jackthorley1@gmail.com).  The code and data sets are also available at: [https://github.com/JThor1990/Meerkat-Population-Regulation](https://github.com/JThor1990/Meerkat-Population-Regulation) Missing data; NA #### **References:**  Beguería, S., Vicente-Serrano, S.M., Reig, F. and Latorre, B. 2014. Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. – *Int. J. Climatol.* 34(10): 3001-3023. Didan, K., Munoz, A. B., Solano, R. and Huete, A. 2015. MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V006. NASA EOSDIS Land Processes DAAC. – [https://doi.org/10.5067/MODIS/MOD13Q1.006](https://doi.org/10.5067/MODIS/MOD13Q1.006).  Huffman, G.J., Adler, R.F., Behrangi, A., Bolvin, D.T., Nelkin, E.J., Gu, G. and Ehsani, M, R. 2023. The new version 3.2 Global Precipitation Climatology Project (GPCP) monthly and daily precipitation products. – J.  Climate, 32(21): 7635-7655. Jönsson, P. and Eklundh, L. 2004. TIMESAT- a program for analysing time-series of satellite sensor data. – Comput. Geosci. 30(8), 833-845. National Oceanic and Atmospheric Administration NOAA. 2023. CPC Global Daily Temperature & Global Daily Precipitation – [https://www.psl.noaa.gov/data/gridded/data.cpc.globaltemp.html](https://www.psl.noaa.gov/data/gridded/data.cpc.globaltemp.html). [https://www.psl.noaa.gov/data/gridded/data.cpc.globalprecip.html](https://www.psl.noaa.gov/data/gridded/data.cpc.globalprecip.html).  *Note that breeding seasons cover the period from July 1st to June 30th in the following year. This best reflects rainfall patterns in the Kalahari, where most rain falls in the austral summer, between October and April.