Predict fish year-class strength by calibration
  regression analysis of multiple recruitment index series.

Implements a comprehensive suite of statistical tests for
    evaluating the accuracy of forecasting models against a benchmark.
    The package is grounded in the reality check framework of White
    (2000) <doi:10.1111/1468-0262.00152>, extended by Hansen (2005)
    <doi:10.1198/073500105000000063> for Superior Predictive Ability
    (SPA), 'Giacomini' & White (2006) <doi:10.1111/j.1468-0262.2006.00718.x>
    for Conditional Predictive Ability (CPA), and 'Corradi' & Swanson
    (2006) <doi:10.1016/j.jeconom.2005.07.026> for predictive density
    evaluation via the 'Kullback'-'Leibler' Information Criterion ('KLIC') and
    'ZP' Quantile Loss test, the Continuous Ranked Probability
    Score ('CRPS') ('Gneiting' & 'Raftery', 2007)
    <doi:10.1198/016214506000001437>, coverage tests ('Kupiec', 1995)
    <doi:10.3905/jod.1995.407942>, 'HAC' covariance estimation ('Newey' &
    West, 1987) <doi:10.2307/1913610>, and Moving Block Bootstrap
    resampling ('Kunsch', 1989) <doi:10.1214/aos/1176347265>.

Provides an 'R' interface to the 'C-TOOL' soil carbon turnover model
    for simulating soil organic carbon dynamics in agricultural systems. The
    package supports the definition of carbon inputs, management schedules, soil
    parameters, and temperature forcing, and includes tools for scenario analysis
    and calibration of selected model parameters against observed soil organic
    carbon stocks. The 'C-TOOL' model and related modelling framework are
    described by Petersen et al. (2002) <doi:10.1016/S0304-3800(02)00034-0>,
    Petersen et al. (2005) <doi:10.1016/j.soilbio.2004.08.006>, Petersen et al.
    (2013) <doi:10.1016/j.jclepro.2013.03.007>, and Taghizadeh-Toosi et al.
    (2014) <doi:10.1016/j.ecolmodel.2014.08.016>. Further applications and
    developments are described by Taghizadeh-Toosi et al. (2016)
    <doi:10.1016/j.agsy.2016.03.004>, Keel et al. (2017)
    <doi:10.1111/ejss.12454>, Taghizadeh-Toosi et al. (2020)
    <doi:10.1007/s11104-020-04500-9>, and Taghizadeh-Toosi and Christensen
    (2021) <doi:10.1038/s41598-021-97744-z>.