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Fig. 1 in Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape

Fig. 1. Map representing the location of the study area. The middle of the main tall sedge meadow is found at the DMS coordinates 46°11'24.4"N 5°57'30.1"E. The study area is situated in the Department Ain, in Eastern France, near the French-Swiss border.

Fig. 3 in Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape

Fig. 3. Set up of the INRA traps, installed in mid-August of 2017 on 60 cm tall sticks, and baited with sunflower seeds. The transect represented here was located in the sedge patch on the South side of the stream la Chanvière. The yellow flowers behind the Caricion elatae are the American goldenrod extending nearly to the edge of the forest.

Appendix 1 in Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape

Appendix 1 Secondary transects (red lines) placed in late October to early November of 2017, after the radiotracking event. These transects were set up in areas to which harvest mice appeared to migrate to. Nest-searching was also done (grey areas). The aim was to know if other individuals were present or not in these areas.

Fig. 4 in Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape

Fig. 4. Accumulated number of marked individuals captured during the CMR event. In the first 5 CMR days, the 71 traps were open 4 h in the evening during the dusk, and 4 hours in the morning during the dawn. The 8 following days (from day 6 to day 14), the traps were open 4 h during the day and 4 h at dusk. The population estimate levelled at 12 individuals, which corresponds to the total number of marked individuals captured during the 14 trapping days.

Figure 6 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608

Figure 6 Gantt chart showing tasks (T), milestones (M), and deliverables (D) as well as involvement of human resources according to the time plan – T, M and D are described in the text.

Figure 4 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608

Figure 4 Example classifications of tradeoffs from the perspective of regional stewardship programs: Distributed: each ecosystem service category is 20-30% (exclusive); Emphasized: ≥ 1 category is 30-50% (exclusive); Dominant: one categories is >50%.

Figure 2 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608

Figure 2 Two hypotheses regarding drivers of adaptation, illustrated by simulated effects of individual drivers on an adaptation index (see below Tasks 1.1, 1.2, 3.2 in the Work Plan). Categories of drivers distinguished by symbols: diamond (u) = science; square (■) = culture; circle (●) = climate; triangle (▲) = cross-border; and × = regional program capacity. Whiskers represent 95% Bayesian credibility intervals; open symbols illustrate significant positive effects. Cx = communication.

Figure 3 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608

Figure 3 Two hypotheses regarding drivers of adaptation, illustrated by simulated values representing absence (A) or presence (B) of interactions between effects on an adaptation index (see below Tasks 1.1, 1.2, 3.2 in Work Plan). Simulated effects include progress toward adaptation by countries of focal regions and by neighbors of these regions. Categories of progress toward adaptation defined as 'more advanced' (at or above median index value) or 'less advanced' (below median index value). Whiskers represent 95% Bayesian credibility intervals; non-overlapping whiskers illustrate statistically significant contrasts.

Figure 1 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608

Figure 1 Candidate drivers of adaptation by a program working at a regional scale, partially adapted from Figures 1.1 and 3.1 in Swart et al. (2009). This conceptual framework provides a basis for constructing hypotheses in this project. Each dashed border encapsulates a category of putative drivers. Neither relationships among individual drivers nor feedbacks between categories of drivers and adaptation actions are shown. Bolded boxes represent drivers that will be examined in this study. Underlined drivers can be at least partly informed from literature sources, whereas the remainder will be based solely on surveys and interviews with regional program administrators. (*Communication can also include coordination of adaptation planning/implementation in other regions).

Figure 5 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608

Figure 5 Hypothetical result of an emphasis on regulating and cultural services consistent with the diverse value tradeoffs hypothesis. General classes of value tradeoffs distinguished by shapes: distributed (u), dominant (●) and double emphasis (■).Whiskers represent 95% Bayesian credibility intervals; open symbol illustrates a significant difference.