Fig 1.
Doñana National Park, southwestern Spain, bordering the Atlantic coast.
Red line = Park limit. White dots (A, B) indicate the location of the study plots at Matasgordas and Martinazo grasslands, respectively.
Table 1.
Vegetation physiognomy in seed arrival microsites at the two study sites.
Table 2.
Seed content (expressed per gram dry weight and per fecal unit; DW) in deposits from different ungulates at Martinazo and Matasgordas (mean values ± se). The seed content per fecal unit is calculated from average feces DW of different ungulates (S1 Table). Cumulated number of dispersed seeds is the sum of seeds in all deposits from each ungulate.
Fig 2.
(a) Relative abundance of different plant families (percentage of the seed pool) at the studied sites, and combined relative abundance of plan families (= black bars) and their frequency (percentage of samples where a family occurs = white squares) in Matasgordas (b) and Martinazo (c).
The sample S72 is excluded from computation. Plant families: VAL(Valerianaceae), FAB (Fabaceae), CYP (Cyperaceae), PLA (Plantaginaceae), RAN (Ranunculaceae), CAR (Caryophyllaceae), AST (Asteraceae), CIS (Cistaceae), POA (Poaceae), PRI (Primulaceae), ERI (Ericaceae), POL (Polygonaceae), BOR (Borraginaceae), API (Apiaceae), CHE (Chenopodiaceae), SCR (Scrophulariaceae), MAL (Malvaceae), ALI (Alismataceae), PLU (Plumbaginaceae), EUP (Euphorbiaceae).
Fig 3.
NMDS results showing deer samples from Martinazo and Matasgordas sites The analysis is based on seeds per gram DW.
Squares and purple area = Martinazo deer, triangles and pink area = Matasgordas deer. Initials next to dots are seed families positioned by abundance and frequency in each site. Initials of family names as in Fig 2.
Table 3.
Permanova results for general differences in the composition by families of dispersed seeds by different ungulate species in Martinazo site. Analyses were conducted on seed content expressed both, as seeds per gram DW (column A) and as seed per fecal unit (column B). Significant differences after Bonferroni corrected pairwise comparisons for the four ungulates are shown in bold font.
Fig 4.
NMDS results showing samples of different ungulate species (dots and areas of different colors) at Martinazo: Green = deer; yellow = cow; black = horse; blue = wild boar.
Seed content expressed per gram DW (a) and per fecal unit (b). Initials next to dots are families of seeds positioned by abundance and frequency in each ungulate. Initials of family names as in Fig 2.
Fig 5.
Mark correlation functions to evaluate potential spatial structure in total seed number dispersed by ungulates in Martasgordas (b,d,f) and Martinazo (a,c,e).
The r-mark correlation function (a, b) describes the mean number of seeds (mi) in a fecal unit at distance “r” of another unit. Schlather’s correlation function (c, d) quantifies the correlation between the number of seeds in two different units separated by distance “r”. Density correlation function (e, f) assesses the correlation between the number of seeds and the density of fecal units distance “r”. Observed functions = solid dots. Expected functions under the null model of random seed content distribution = black line. Simulation envelopes = grey lines (fifth lowest and fifth highest values of the functions created by 199 simulations under random labelling). Goodness-of-fit [58] is used to test the overall fit of the random marking null model for the entire distance up to 50 m. Significant p-value from GoF test in bold font indicates significant departures of the observed function from the random null model.
Fig 6.
Mark correlation functions to evaluate potential spatial structure in the seeds number of frequent plant families (in bracket) in Martasgordas (b, d, f) and Martinazo (a, c, e).
The r-mark correlation function (a,b) describes the mean number of seeds (mi) in a fecal unit at distance “r” of another fecal unit. Schlather’s correlation function (c, d) quantifies the correlation between the number of seeds in two different fecal units separated by distance “r”. Density correlation function (e, f) assesses the correlation between the number of seeds and the number of nearby fecal units at a distance “r”. Observed functions = solid dots. Expected functions under the null model of random seed content distribution = black line. Simulation envelopes = grey lines (fifth lowest and fifth highest values of the functions created by 199 simulations under random labelling). Goodness-of-fit [58] is used to test the overall fit of the random marking null model for the entire distance up to 50 m. Significant p-value from GoF test in bold font indicates significant departures of the observed function from the random null model.
Fig 7.
Mark correlation functions to evaluate potential spatial structure in the seed number of frequent plant families (in brackets) in Martasgordas (b,d,f) and Martinazo (a,c,e).
The r-mark correlation function (a,b) describes the mean number of seeds (mi) in a fecal unit at distance “r” of another fecal unit. Schlather’s correlation function (c, d) quantifies the correlation between the number of seeds in two different fecal units separated by distance “r”. Density correlation function (e, f) assesses the correlation between the number of seeds and the number of nearby fecal units at a distance “r”. Observed functions = solid dots. Expected functions under the null model of random seed content distribution = black line. Simulation envelopes = grey lines (fifth lowest and fifth highest values of the functions created by 199 simulations under random labelling). Goodness-of-fit [58] is used to test the overall fit of the random marking null model for the entire distance up to 50 m. Significant The p-value from GoF test in bold font indicates significant departures of the observed function from the random null model.
Fig 8.
Mark correlation functions to evaluate potential spatial structure in the seed number of frequent plant families (in brackets) in Martasgordas (b,d,f) and Martinazo (a,c,e).
The r-mark correlation function (a,b) describes the mean number of seeds (mi) in a fecal unit at distance “r” of another fecal unit. Schlather’s correlation function (c, d) quantifies the correlation between the number of seeds in two different fecal units separated by distance “r”. Density correlation function (e, f) assesses the correlation between the number of seeds and the number of nearby fecal units at a distance “r”. Observed functions = solid dots. Expected functions under the null model of random seed content distribution = black line. Simulation envelopes = grey lines (fifth lowest and fifth highest values of the functions created by 199 simulations under random labelling). Goodness-of-fit [58] is used to test the overall fit of the random marking null model for the entire distance up to 50 m. Significant The p-value from GoF test in bold font indicates significant departures of the observed function from the random null model.