The test can be performed on a numeric vector, or a data.frame with dates in the first column and the associated variable of interest in the second. A choice can be made between Mann Kendall, Pearson, or Spearman tests. The Spearman and Mann Kendall are based on ranks and will therefore have the same results whether dates are included or not. The default is Mann Kendall.
The default is to test for any trend (alternative = "two.sided"). For positive trend set alternative to "greater", and to test for negative trend set alternative to "less".
Interpretation: When testing for positive trend (alternative = "greater") the P_value is the probability of exceeding the observed statistic under the null hypothesis (that it is less than zero).
The vice versa is true when testing for negative trend (alternative = "less"). For alternative = "two.sided" the P_value is the probability of exceeding the absolute value of the observed statistic under the null hypothesis (that it is different from zero). Low P values indicate that the null hypothesis is less likely.