Predicting the occurrence of rocky reefs in a heterogeneous archipelago area with limited data

Predicting coexistence and predominance patterns between the introduced Manila clam (Ruditapes philippinarum) and the European native clam (Ruditapes decussatus)

“…Moreover, with respect to assessing the importance of each variable, ENFA results are more straightforward to interpret than other presence-only models such as Maxent (Phillips et al, 2006) based on heuristic and jackknifing estimates outputs (e.g. Tittensor et al, 2009;Rinne et al, 2014).…”

“…The application of predictive models to obtain the potential distribution of marine species has increased, covering areas such as aquaculture (Longdill et al, 2008), fisheries management (Galparsoro et al, 2009), habitat management (Valle et al, 2011;Vasconcelos et al, 2013;Rinne et al, 2014) and conservation of a wide range of species such as cetaceans (Praca et al, 2009), migratory birds and turtles (Tian et al, 2008), polychaetes (Willems et al, 2008) and corals (Tittensor et al, 2009). With regards to bivalve species, habitat suitability predictions have been mainly focused on commercial species such as oysters and clams in order to improve management models or to restore habitats for aquaculture purposes (Soniat and Brody, 1988;Vincenzi et al, 2006a,b).…”

Evaluation, Gap Analysis, and Potential Expansion of the Finnish Marine Protected Area Network

“…Of the listed habitat types, 69 occur in Finland, of which eight are associated with marine environments: (1) Baltic esker islands (1610), (2) Boreal Baltic islets (1620), (3) Boreal Baltic narrow inlets (1650), (4) Coastal lagoons (1150), (5) Estuaries (1130), (6) Large shallow inlets and bays (1160), (7) Sand banks (1110), and (8) Reefs (1170). Here, we utilized the existing models for (1), (2), (7), and (8) (Rinne et al, 2014;Kaskela and Rinne, 2018) and GIS datasets for other marine habitats, based on expert knowledge reported for the EU in 2013 (EEA, 2013). Existing data on fish reproduction areas (Kallasvuo et al, 2016) were also used in the conservation prioritization part (see the section "Spatial Prioritization"), and are considered here as a proxy for biodiversity of juvenile fish.…”

The distribution of deep-sea sponge aggregations in the North Atlantic and implications for their effective spatial management

“…Where both approaches have been used results suggest that predicted habitat distribution is a highly restricted subset of predicted species distribution (Howell et al, 2011, Rengstorf et al, 2013. Where a 'habitat' is composed of a distinct assemblage of species, the distribution of that assemblage may be modelled (Degraer et al, 2008, Gonzalez-Mirelis and Lindegarth 2012, Piechaud et al, 2015, alternatively the distribution of key indicator species may be modelled and the resulting maps overlaid highlighting areas of overlap as potential habitat distribution (Ferrier and Guisan 2006;Rinne et al, 2014) This study uses Maximum Entropy Modelling, considering both species and habitat based approaches, to address the following questions: 1) What environmental factors drive the broad-scale distribution of ostur and Pheronema carpenteri sponge grounds?…”