Predictive power of the morphotype test in different contact zones.

• Main Authors: Vadim Khaitov (2589874), Julia Marchenko (11177903), Marina Katolikova (2589880), Risto Väinölä (2589886), Sarah E. Kingston (3608393), David B. Carlon (11177906), Michael Gantsevich (2589877), Petr Strelkov (2589883)
• Format: Still Image
• Language: unknown
• Published: 2021
• Subjects: Evolutionary Biology; Ecology; Inorganic Chemistry; Environmental Sciences not elsewhere classified; Biological Sciences not elsewhere classified; morphotype; trossulu; White Sea; semi-diagnostic conchological character; Arctic Barents Sea; species identification; mussels Mytilus edulis L; Baltic Sea; unstudied contact zones; Arctic; Barents Sea
• Online Access: https://doi.org/10.1371/journal.pone.0249587.g004

(A) Dependence of proportion of M . trossulus ( Ptros ) on proportion of T-morphotypes ( PT ). Dotted lines are empirical regressions (Model 4). Solid gray lines–predictions of “ Ptros by PT calculator” ( Eq 3 ). Solid black lines represent Y = X dependence. (B) Probability to find a mussel with a T-morphotype among M . edulis ( P(T|edu) ) (empty points), and M . trossulus ( P(T|tros) ) (filled points) as a function of Ptros . Lines are empirical regressions (Model 5). (C) Probability of correct species identification by the morphotype test: M . trossulus by T-morphotype, P(tros|T) (filled points) and M . edulis by E-morphotype, P(edu|E) (empty points) as a function of Ptros . Dotted lines are empirical regressions (Model 6). Sold lines–predictions of “genotype by morphotype calculator” for M . trossulus ( Eq 1 , red line) and M . edulis ( Eq 2 , blue line). On each graph, dots represent the observed proportions in samples, and shaded areas around regression lines– 95% CI of regressions.