All species are adapted to certain climatic conditions, outside of which they cannot survive. Changes in the climatic environment therefore force species to either adapt to the new conditions or move to areas where suitable conditions are still present in order to avoid extinction. Several studies have shown that species from various taxa are currently moving their ranges polewards and to higher elevations to keep up with shifting climate regimes. However, species differ widely in their dispersal abilities. In addition, natural landscapes are becoming increasingly human-dominated, further hindering dispersal by decreasing permeability. Anthropogenic climate change is therefore expected to become one of the major drivers of species extinctions by the end of the 21st century. Species range shifts are problematic in conservation planning, because dynamic biodiversity patterns hamper our ability to identify priority areas for protection. Because protected area networks are geographically fixed, climate change may also drive species out of reserves, foiling past conservation efforts. In this thesis the different risks and opportunities of conducting conservation planning under climate change are investigated. This research focuses on the uncertainties that arise from working with unknown future events, technical challenges of observing and predicting species range shifts, and using (or ignoring) information about future impacts in conservation planning. The major findings of this thesis are that climate change is already rapidly reshaping species distributions in Finland and that ignoring future dynamics can lead to misguided and potentially inefficient conservation decisions. The results presented here show that modelling future impacts using so-called niche modelling techniques, despite their inherent uncertainties, can provide useful information about how species distributions and conservation statuses will be affected by climate change. For example previously created models for Finnish breeding birds predicted well recently observed changes in species distribution sizes. More importantly, the observed changes seem to match best with predictions that follow the most extreme climate change scenario. A key factor for successfully measuring and predicting climate change impacts are good monitoring data, the role of which should be more widely acknowledged by decision-makers. Uncertainty in climate change research is pervasive and cannot ever be entirely eliminated. This work offers tools to assist in both spatial prioritization and decision making when scarce conservation resources need to be allocated under uncertain future conditions. The findings of this thesis strongly encourage using proactive approaches that account for future impacts. The results also suggests that while striving to reduce epistemic uncertainty is important in climate change and conservation research, other sources of uncertainty such as socio-political factors or volitional human behaviour might constitute far larger determinants of successful conservation actions, and therefore merit stronger focus in research.

In a world of competing interests and increasing land use pressures, the allocation of limited resources for biodiversity conservation need to be prioritized. Spatial conservation prioritization deals with the cost-efficient and well-balanced identification of priority areas for biodiversity, as well as with the allocation and scheduling of alternative conservation actions. Finland is the most forested country in Europe, but more than 90 percents of Finland s forests are under commercial management. A history of widespread and relatively intensive forest management has led to many specialist species and habitats becoming threatened. At the same time, the protected area network is unequally distributed over the country, with largest areas in the north where species diversity is lowest. Consequently, the current main priority for conservation action for forest habitats is expanding the protected area network in the southern parts of the country in an ecologically justified way. In this thesis, I have three specific objectives. First, I examine the suitability of commonly available forest inventory data for informative high-resolution spatial conservation prioritization. Second, I clarify the effects of spatial scale and connectivity on spatial conservation prioritization at regional and national extents. Finally, I develop, demonstrate, and implement a practical workflow for regional- and national-scale forest conservation management planning in Finland, using the Zonation framework and software for spatial prioritization. I show how habitat quality indices based on forest inventory data and expert knowledge can be used as a basis of conservation prioritization. Comparison against validation datasets reveals that the analyses do indeed produce informative priorities. Case studies involving the expansion of the national protected area network both on public and private land demonstrate how the results can be applied in the context of a national forest conservation program, METSO. The spatial resolution of input data should closely match those of the planning objectives and the ecological processes involved. Furthermore, the level of detail in the forest inventory data defines how well the prioritization is able to identify small occurrences of important forest types and key habitats. The quality and the quantity of suitable habitat between protected areas are important for many forest species. Accounting for connectivity in the prioritization analyses produces spatially more aggregated priority patterns. However, emphasizing connectivity will lower the relative value of locally high quality, but poorly connected sites. Therefore, the balance between connectivity and local habitat quality merits careful consideration in spatial prioritization. The thesis highlights important factors. First, data availability often restricts the types of prioritization analyses that can be undertaken. Therefore, long-term development of high-quality open access data is crucial for making best use of spatial prioritization approaches. Second, establishing a conceptual model for the prioritization process can help formulate the right questions, to select the most suitable tools, and to estimate the costs and benefits involved. Finally, a successful conservation prioritization requires participation of experts and stakeholders. Methods, analyses, workflows and visualization techniques summarized in this thesis can serve as starting points for other similar applications elsewhere and support meeting local, regional and global conservation goals.