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# Data from: Evaluating the effects of cotton intercropping on cool-season perennial forage persistence, forage mass, and nutritive value in the southeastern United States This dataset was used to generate 3 figures and 5 tables in the publication, "Evaluating the effects of cotton intercropping on cool-season perennial forage persistence, forage mass, and nutritive value in the southeastern United States". All data was collected in Florence, South Carolina at the Clemson University Pee Dee Research and Education Center during 2021 and 2022. \#Description of dataset and file structure Data is presented in an Microsoft Excel Spreadsheet, with separate tabs for datasets related to each of the 3 figures/subfigures and 5 tables in the published manuscript. For all data the following treatment abbreviations are used: Fallow = weedy, unplanted treatment ARG = annual ryegrass RC+WC = 50/50 mixture of red and white clover ARG+RC+WC = 50% annual ryegrass, 25% red clover, and 25% white clover **Data for Figure 1** These data were used to generate Figure 1, featuring mean weather data for the study years, 2021 & 2022, along with 30-year mean weather data for the nearest NOAA weather station (Florence, SC Regional Airport). Units are provided in the column headers. **Data for Figure 2a & 2b** These data were used to generate Figures 2a and 2b, featuring the amount of spring forage mass accumulation preceding and in between cotton intercropping. Forage mass in the RC+WC and ARG+RC+WC treatments consited of a mix of weeds and clovers, while ARG and fallow treatments are entirely comprised of weedy biomass **Data for Figure 3a & 3b** These data were used to generate Figures 3a and 3b, featuring the red and white clover populations in each treatment for each year of the study. **Data for Figure 3c** These data were used to generate figure 3c, featuring the weedy species population changes from spring to fall before, between, and after two seasons of cotton intercropping in 2021 and 2022.Final data in the published figure was Weeds per square meter. **Data for Tables 1 and 2** These data were used to generate Tables 1 & 2, featuring height data for individual clover, annual ryegrass, and weedy species observed among different treatments. **Data for Table 3** These data were used to generate part of table 3, featuring the forage nutritive value data (crude protien, CP; acid detergent fiber, ADF; neutral detergent fiber, NDF; non-fibrous carbohydrates, NFC; total digestible nutrients, TDN; net energy of lactation, NEL; net energy of maintenance, NEM; net energy of gain, NEG) **Data for Tables 3, 4, and 5** These data were used to generate part of Table 3, and Tables 4 and 5, featuring nutrient compositions of the forage plant tissues collected during the trial. All data are in g/kg dry matter. ## Sharing Access Information These data were originated from the published manuscript: [https://doi.org/10.1002/agj2.21625](https://doi.org/10.1002/agj2.21625). This is digital research data corresponding to a published manuscript, Evaluating the effects of cotton intercropping on cool-season perennial forage persistence, forage mass, and nutritive value in the southeastern United States, in Agronomy Journal. Integrated forage–row cropping systems provide important agronomic and economic benefits to producers. However, little attention has been given to incorporating forages into row crop systems unique to the southeastern United States. This study assessed the viability of intercropping cotton (Gossypium hirsutum L.) on perennial, cool-season legumes during the summer months in the Southeast Coastal Plain over two production years. Treatments included a weedy fallow, annual ryegrass (ARG; Lolium multiflorum Lam.) monoculture, a red clover (RC; Trifolium pratense L.) and white clover (WC; Trifolium repens L.) mixture, and a three-species mixture of ARG, RC, and WC. Plots were established in fall 2020 with forage grown until May 2021 and 2022, when plots were strip-tilled and planted with cotton. Cotton was managed with minimal herbicide use to preserve perennial clovers. Data was collected over two years (October 2020 - October 2022) at the Clemson Pee Dee Research and Education Center near Florence, SC. Data was collected by field measurements of plant height, biomass accumulation, and species persistence and diversity, with laboratory assays conducted to collect plant nutritional composition. Forage nutrtitive value parameters and fiber content were conducted by a third-party laboratory (Dairy One LLC, Ithaca, NY).

# databases used for statistical analyses in manuscript WLB-2024-01345 [https://doi.org/10.5061/dryad.tht76hf7v](https://doi.org/10.5061/dryad.tht76hf7v) ## Description of the data and file structure **List of excel files used for GLMMs and other analyses in manuscript WLB-2024-01345.R1 – “Precipitation and female experience are major determinants of the breeding performance of Canarian houbara bustards”** ### Files and variables #### File: GLM2b2NestInitiatDate.xlsx **Description:** ** database for GLMM Nest Initiation Date (NIDF, see Supplementary Table S3)** ##### Variables * definitions as in other excel files #### File: GLM4aNestAttemptSuccess.xlsx **Description:** **database for GLMM Nest Attempt Success (see Supplementary Table S3)** ##### Variables * clutchOrder: order of the clutch (1 first, 2 second –replacement-, 3 third –replacement-clutch), chicksSurvived: chicks survived until productivity control (1= yes/0= no, see Methods), MeanTemp: during 23 days incubation + 2 months in nestings that have chicks on the control date, AvMaxTemp: average maximum temperature during 23 days incubation + 2 months in nestings that have chicks on the control date, AvMinTemp: average minimum temperature during 23 days incubation + 2 months in nestings that have chicks on the control date, pp: precipitation during 23 days incubation + 2 months in nestings that have chicks on the control date, other variables as defined in other excel files #### File: GLM4bFledSuccess.xlsx **Description:** **database for GLMM Fledging Success (see Supplementary Table S3)** ##### Variables * Variables:** **pp: precipitation during** **23 days since nesting start + 2 months in nestings that have chicks on the control date; 23+1 month, in nestings that do not have chicks on the control date, other variables as defined in other excel files #### File: GLM5ReClutchProb.xlsx **Description:** **database for GLMM Re-clutching Probability (see Supplementary Table S3)** ##### Variables * Variables: Reclutch: 1= has a replacement clutch/0= does not have a replacement clutch, DurationIncubation: duration of the incubation period (days), MeanTemp, AvMaxTemp, AvMinTemp, pp: measured over the incubation period, other variables as defined in other excel files #### File: Weighted\_precipitations.xlsx **Description:** **databases to calculate weighted precipitation amounts, periods of precipitation and nestings (see Methods for details)** ##### Variables * definitions as in other excel files #### File: GLM6a3FemaleProductivity.xlsx **Description:** **database for GLMM Productivity (see Supplementary Table S3)** ##### Variables * nClutches: number of clutches (1,2,3), NchicksSurvived (1,2 up to fledging), pp2: precipitation measured from one month before the first laying to the laying date of the last clutch, other variables as defined in other excel files #### File: GLM6bFemaleProductivity.xlsx **Description:** **database for GLMM Productivity (as GLM6a, but measuring precipitation over the same period for all years: from 1 September to 13 March [mean hatching start date of the latest year, which was 2022]; see Supplementary Table S3)** ##### Variables * as in GLM6a3FemaleProductivity.xlsx, but measuring precipitation over the same period for all years: from 1 September to 13 March [mean hatching start date of the latest year, which was 2022; other variables as defined in other excel files #### File: GLM7aLengthBreedSeason.xlsx **Description:** **database for GLMM Length of the Breeding Season (see Supplementary Table S3)** ##### Variables * daysBreeding: duration of the breeding season in days (see definition in Methods), temperature and precipitation (PP) measured from 1 month before the first day of incubation of that year in any female until the date of independence of the last chick (see Azar et al 2018: Total rainfall during the nesting period (the period between the first and last nest found each year). other variables as defined in other excel files #### File: GLM7bLengthBreedSeason.xlsx **Description:** **database for GLMM Length of the Breeding Season, same as GLM7aLengthBreedSeason.xlsx, but precipitation and temperature measured over an equal period for all years: from 1 September to 13 March (= average hatching starting date of the latest year, 2022) (see Supplementary Table S3)** ##### Variables * as in GLM7aLengthBreedSeason.xlsx, but precipitation and temperature measured over an equal period for all years: from 1 September to 13 March #### File: WeightedPrecipitationPeriods.xlsx **Description:** **database to calculate weighted precipitation periods and nestings (see Methods for details)** ##### Variables * as in other excel files #### File: GLM2cNestInitiatDate.xlsx **Description:** **database for GLMM Nest Initiation Date of First Clutches (NIDF2, see Supplementary Table S3)** ##### Variables * definitions as in other excel files #### File: GLM1bNestingRate.xlsx **Description:** **database for GLMM Nesting Rate (see Supplementary Table S3)** ##### Variables * indiv= individual female, year, femaleNests: 1=Yes/0=No, startNest = date when nesting started, pp30days: precipitation on the 30 days before (in mm), pp60ays: precipitation on the 60 days before (in mm), pp90days: precipitation on the 90 days before (in mm), TempMean30days: mean temperature on the 30 days before (in oC), TempMax30days: maximum temperature on the 30 days before (in oC), TempMin30days: minimum temperature on the 30 days before (in oC), TempMean60days: mean temperature on the 60 days before (in oC), TempMax60days: maximum temperature on the 60 days before (in oC), TempMean60days: mean temperature on the 60 days before (in oC), Weight: weight of the female (g), PC1p: Principal Component 1 of the PCA including weight, PC1sinP: Principal Component 1 of the PCA excluding weight, Breedingexperience: breeding experience of the female, as defined in Methods. #### File: GLM1cNestingRate2.xlsx **Description:** ##### Variables * indiv= individual female, year, femaleNests: 1=Yes/0=No, startNest = date when nesting started, pp30days: precipitation on the 30 days before (in mm), pp60ays: precipitation on the 60 days before (in mm), pp90days: precipitation on the 90 days before (in mm), TempMean30days: mean temperature on the 30 days before (in oC), TempMax30days: maximum temperature on the 30 days before (in oC), TempMin30days: minimum temperature on the 30 days before (in oC), TempMean60days: mean temperature on the 60 days before (in oC), TempMax60days: maximum temperature on the 60 days before (in oC), TempMean60days: mean temperature on the 60 days before (in oC), Weight: weight of the female (g), PC1p: Principal Component 1 of the PCA including weight, PC1sinP: Principal Component 1 of the PCA excluding weight, Breedingexperience: breeding experience of the female, as defined in Methods, pp_1sep_13mar: precipitation measured between 1st September and 13th March, T_1sep_13mar: temperature measured between 1st September and 13th March #### File: GLM2a2NestInitiatDate.xlsx **Description:** **database for GLMM Nest Initiation Date (NIDF, see Supplementary Table S3)** ##### Variables * ordinalDate: Ordinal date as defined in Methods, rest of variables: definitions as in other excel files #### File: GLM3HatchSuccess.xlsx **Description:** **database for GLMM Hatching Success (see Supplementary Table S3)** ##### Variables * : endNest: date when incubation finished, ppIncub: precipitation during incubation (23 days since start incubation), AvMaxTempIncub: average maximum temperature during incubation, AvMaxTempIncub: average maximum temperature during incubation, ppIncub: mean temperature during incubation, hatchSuccess: 1= incubation until hatching date is successful/ 0= incubation until hatching date is not successful, rest of variables: definitions as in other excel files ## Code/software data can be viewed using EXCEL; other files from the process of statistical analysis were obtained using package “lme4” (Bates et al. 2015) in R v.2.15.1 (R Development Core Team, 2015) Precipitation is one of the main triggers of reproduction in desert-breeding birds. The unpredictability of rainfall patterns in arid environments has led species to adapt their breeding effort to episodes of abundant food after rainfall. The response is not the same for all individuals in a population, and may vary especially with the age and experience of each female. Here we investigate the effects of precipitation, temperature, body size and breeding experience, among other variables, on reproductive parameters of 20 females of Canarian houbara bustard (Chlamydotis undulata fuertaventurae), an endangered desert bird endemic of the eastern Canary Islands. Precipitation and breeding experience were the main determinants of female breeding performance. Higher rainfall determined an increase in nesting rate, and earlier autumn rains caused an advancement of nesting to October, allowing the breeding season to be extended to eight months. This favoured an extraordinary increase in productivity in more rainy breeding seasons, with 15 times more females nesting in the two most rainy winters than in dry years. In addition, females with more breeding experience showed a higher tendency to breed, higher nest attempt and fledging success, and longer breeding season, which allowed them to rear more chicks. A female even double brooded successfully in the same season, which, considering that chicks remain with the mother for up to six months, indicates a great capacity to optimise reproductive investment, by adapting to highly variable rainfall regimes. In recent decades, the eastern Canary Islands have undergone a process of aridification, and climate models predict a medium-term increase in the frequency and duration of drought periods. Thus, Canarian houbaras are particularly vulnerable to climate change, so measures are urgently needed to reduce their mortality and improve the quality of their habitat, in order to favour their reproduction and prevent their extinction.  We used 5-year breeding phenology and breeding success data from 20 female houbara bustards captured in Lanzarote and equipped with backpack-mounted GSM/GPRS data loggers. The influence of predictor variables on breeding parameters was modeled by means of generalized linear mixed models (GLMMs) using package “lme4” (Bates et al. 2015) in R v.2.15.1 (R Development Core Team, 2015).