Assessment of biodiversity representation by protected areas mostly uses biological information to prioritise unrepresented features. Use of socio-economic factors (e.g. land use, ownership) is less prominent, even though they influence biodiversity distribution and reserve implementation. In regions with little protection, socio-economic factors may be more sensitive to prioritising risk among unprotected features: many biological priorities will exist but not all are threatened by land use. In an intensively managed region of New Brunswick, Canada, we conducted an ecosystem-based representation assessment and prioritised the unprotected elements with a combined biological and socio-economic ranking criteria. Biological data were the distribution and rarity of at-risk plants. Socio-economic data described land use intensity. Ecosystem units were fine-scale polygons resolved across topographical and edaphic gradients.We asked: 1) how adequately are units with rare plant hotspots protected? and 2) what are the relative risks to unprotected units from land use? Nineteen of twentyeight ecosystems were preserved inadequately. Based on the combined ranking procedure, however, not all were equally at-risk. High risk units with rare plant hotspots were fertile, of gentle slopes or bottomlands, privately owned, and agriculture-dominated. Rare plants were concentrated in highly isolated forest remnants. Low risk units were infertile, poorly drained or topographically rugged, and owned by government or the forest industry; some contained rare plants but were well protected. Several unprotected and disturbed units were not ranked highly due to biological data base inconsistencies, and due to the weighting of the ranking criteria itself. Such problems, common to representation analyses, were highlighted by our use of multiple ranking criteria; affected units will require supplemental risk assessment. Our results indicate that high risk ecosystems will be difficult to protect because of habitat conversion and mostly private ownership. At the same time, socio-economic impacts, driven by forestry, appear to be shifting away from ecosystems now considered high priority. Tracking shifts in socio-economic pressure may anticipate future biodiversity impacts indiscernible using assessments based on species presently at-risk.

Ecological land classification, gap analysis, New Brunswick, private land, rare plants