The box plot of candidate heat units for the start day after all filtration has been performed including removal of the entries whose relative standard deviation is higher than 50% across years.

The red dots show M, the mean values that will be used as the required heat units.</p

Annual paper mulberry pollen count time-series for the years 2004–2018.

Each line represents a separate year. The main pollen seasons (periods with the highest pollen concentrations) are recorded between 10th and 31st March. Pollen concentrations rise again slightly between July and August during and after the summer rain.</p

The optimal parameter values along with mean average errors (MAEs) for phenological modelling under the 5% and 2.5% criteria.

Note that the optimal parameter values were derived from the training years while the MAEs indicate model performance on the test years.</p

The box plot of candidate heat units for the peak day after all filtration has been performed including removal of the entries whose relative standard deviation is higher than 50% across years.

The red dots show M, the mean values that will be used as the required heat units.</p

Mean Absolute Error (MAE) values for various durations of meteorological data for the peak day prediction under the 2.5% and 5% start day criteria.

This was done only for the training years as the testing years were reserved to evaluate the performance of the algorithm.</p

Mean Absolute Error (MAE) for the start and peak days of the testing years using the linear regression and phenological modelling approaches under the 5% and 2.5% start day criteria of main pollen season (MPS).

Mean Absolute Error (MAE) for the start and peak days of the testing years using the linear regression and phenological modelling approaches under the 5% and 2.5% start day criteria of main pollen season (MPS).</p

Fig 3 -

Mean Absolute Error (MAE) calculated over various time intervals using their corresponding meteorological data for the start day prediction under the 2.5% and 5% start day criteria: (A) the various starting points (B) the various ending points. The number of total combinations considered in this brute force optimization was 11 × 56. Only the combinations of starting points yielding the best ending points (and vice versa) are shown. This was only done for the training years as the testing years were reserved to evaluate the performance of the algorithm.</p

Pictorial representation of the pollen prediction system.

Here MPS denotes the Main Pollen Season (the time of the year with the highest pollen concentration).</p

Levels of intracellular metabolite pools in aerosol-exposed macrophages.

<p>Pools of (a) lactic acid, (b) succinic acid, and itaconic acid were measured. Levels represent the mean of 9 biological replicates. *** = p < 0.001. Error bars represent s.e.m.</p

Land cover attribute for Australia and New Zealand with climatological summaries for each major urban centre associated with an aerobiology study.

<p>Climate summaries include average monthly precipitation and minimum and maximum temperatures for each urban area (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097925#pone-0097925-t003" target="_blank">Table 3</a> for data sources). Data shown for Whangarei represents the Kaikohe pollen count site.</p