**1. Introduction**

Biodiversity issues in sustainable forest management (SFM) are changing, which brings along the need for new analytical tools. A major change is that sustainability is increasingly defined through connected ecological and social complex systems at multiple scales [1]; this adds adaptive capacity and resilience among key qualities of SFM, along with traditional expectations to sustain a supply of specific forest goods and services [2–4]. Thus, biodiversity concerns have transcended traditional nature conservation to become an integrative issue that underpins ecological resilience, adaptive capacity of ecosystems, and many ecosystem services [5–8]. It is yet unclear how such a perspective will be put into practice (e.g., [9–11]). However, given the schism between broad political acceptance of SFM and of forest protection [12,13] versus the continuing loss of forest biodiversity [14], there is an unprecedented need for clear biodiversity targets and tools.

An obvious goal in sustaining biodiversity is to manage harmful environmental pressures and threats rapidly, proactively, and effectively. Geospatial models have long been used to anticipate futures by spatial planning of forests, including biodiversity targets [15–20]. Many modeling approaches and techniques have been developed for depicting and accounting for biodiversity across forest landscapes (e.g., [21–23]). Recent technological progress enables mass recording of biodiversity variables, e.g., by combining molecular sampling, observations, and remote sensing (e.g., [24–26]). However, such advances in biodiversity modeling are not easily picked up by forestry and conservation planners to specify general ecological guidance (e.g., [27,28]). Thus, biodiversity assessment practices for SFM or in protected forest habitats are based mostly on convenient landscape metrics and woody vegetation proxies ([29–34], but see [35,36]). The species included in the landscape-scale predictive models of forestry scenarios are defined case-wise for specific purposes (see Section 2.2), while legitimate procedures of setting aside forest stands for biodiversity tend to require laborious field documentation (e.g., [37]).

In this paper, we highlight a biodiversity response variable as a critical issue for useful geospatial models in SFM. The large and diffuse literature on such variables (e.g., [38–40]) indicates a narrow disciplinary focus of most spatial models. We identify at least four 'interdisciplinary gaps' (sensu [41]) to be considered by the biodiversity modeling community (see also [23,42–44]).


In brief, geospatial predictive models can be irreplaceable tools for biodiversity issues in SFM, given the large area of forests, long temporal scales of forest development, and the vast nature of biodiversity. However, there are apparently communication boundaries between the modeling community and other stakeholders (biodiversity researchers; policy-makers; forest and conservation managers; wider public). For example, the first two interdisciplinary gaps above together reflect 'biodiversity concerns' that have been recognized as difficult to model [46]. Social and governance studies suggest that the failure to manage communication boundaries by meaningful simplification makes biodiversity difficult to grasp even for professionals [52,53]. The question is how to build models that clarify biodiversity issues and help to plan a meaningful and understandable future.

Here, we revisit the conservation concept of 'focal species' as proposed by Lambeck [54,55], who proposed setting environmental standards in a specific context according to the most sensitive species to each threatening process in the environment. Managing for a full set of such species might then encapsulate the biodiversity conservation aim of a landscape. We elaborate this concept in a spatial modeling perspective to demonstrate how it can—mostly through the binding element of 'threatening process'—operationalize multiple issues of ecological sustainability and bridge the interdisciplinary gaps listed above. We retain Lambeck's original term for 'focal species', while acknowledging that it has been loosely used in the literature and must be routinely rechecked against the original definition [56] (pp. 17–22).

The paper is organized as follows. We first explain the concept and review the literature on spatial habitat modeling of focal species for SFM. We assess the coverage of the current research in terms of biodiversity and the forestry problems it might address. We then illustrate an approach that focuses on the threatening process, conceptualizing it through major dimensions of habitat change. We list the main merits of such an approach from a practical modeling perspective, including parameterizing the model as habitat quality and quantity estimates for focal species. The latter is a well-established modeling field. Finally, we illustrate our approach based on recent additions to the forest reserve network in Estonia, where the practical question is the time scale and expected spatial pattern of recovery of degraded habitats and allocation of management to enhance this.
