Finalize n_species, deprecate/defunct other functions, add CITATION.cff

[damianooldoni]

This pull request includes several changes to the codebase, focusing on:

• finalizing n_species() and its tests
• deprecating some functions
• improving documentation

Finalizing n_species() and its tests

Up to now, tests were not really taken into account as we were way far from getting the functions ready to the new format. From this PR we can start using them 🥳 as the very first function, n_species(), is ready! So, please run devtools::test(filter = "n_species") as check. Its related tests have been simplified without losing testing power. Notice that we only consider event based observations for the standard functions of camtraptor v1.0.0 (#332).

Deprecation of functions

• Deprecated the get_species() function in favor of taxa() (fix Deprecate get_species()  #343)
• get_scientific_name() and check_species() functions are defunct in favor of taxa() (fix Remove check_species(), get_scientific_name() #235). So, check_species() and get_scientific_name() functions are moved to defunct.R.

Metadata

• Added CITATION.cff (fix Add CITATION.cff #345) (using cffr::cff_write()).

Documentation updates

• Updated references in multiple R files to inherit arg description from n_species instead of the deprecated get_species. This has been done by using @inheritParams n_species instead of @inheritParams get_n_species.
• Updated the NEWS.md file to reflect the deprecation/defunct of several functions, the introduction of new replacements and new citation file.

Other code improvements

• Simplified get_n_individuals() and get_n_obs() functions by removing the species parameter and associated logic: we do not filter anymore within such functions, only via filter_observations(). IMPORTANT: these functions are still not finalized and do not follow the new data standard still. So, they will fail or return a non tested result.

[sannegovaert]

Nice!
I have 1 remark about filtering on observationLevel & a suggestion for simplification.

[sannegovaert]

I suggest:
x <- filter_observations(.data$observationLevel == "event")
and using observations(x) instead of observations.

Because what if there is a deployment with only media-based observations?
It would now not be noticed in L33: deployments_no_obs <- get_dep_no_obs(x).

And last, why is the count reduced by NA-values in a mutate-function, and not like this?:

n_species <-
   species %>% 
   dplyr::filter(!is.na(.data$scientificName)) %>% 
   dplyr::group_by(.data$deploymentID) %>%
   dplyr::count() %>%
   dplyr::ungroup()