D2) Evidence-Based Management

Evidence-based biodiversity management of forests

Carsten Dormann
Doctoral researcher: Carlos Miguel Landivar Albis (since 2019) & Elizabeth Baach
(since 2022)

University of Freiburg, Faculty of Environment & Natural Resources, Institute of Earth & Environmental Sciences,
Chair of Biometry and Environmental System Analysis

Background

Any kind of causal comprehension requires a model, be it formally defined as mathematical or rule-set algorithm, or informally as mental representation or unacknowledged gut feeling. Decision-making builds on a formal, or more often informal, representation of the causal functioning of the system in one's head: increasing, for example, forest structural heterogeneity by management will lead to increases in bird diversity because birds feed in different layers of the forest. To purposefully manage forests for diversity requires that the mechanisms linking a management and the outcome in terms of, say, insect abundance and richness are present in such a model. Otherwise, the outcome of a management would only be linked by chance to biodiversity. The second phase of D2 will focus now on how the processes that link management activities and species abundances and richness for different groups of forest organisms are actually represented in models.

Research questions and hypotheses

D2 attempts to explore the scientific basis of management principles for conservation in forests (e.g. Lindenmayer et al. 2006). One challenge is the plethora of specific studies of different design and quality, sometimes yielding equivocal conclusions about causal links between management and biodiversity responses. Human experts integrate the information available to them into a belief that may or may not be a reasonable summary of the state of knowledge overall. Are the scientifically demonstrated causes of forest biodiversity present in practitioners intentions and actions? How are processes that affect biodiversity at the landscape scale represented when taking actions at the stand level? Which are the effect of retention forestry related forest features on biodiversity composition and interactions?

Approach, methods and linkages

D2 compared three representations of the understanding of how biodiversity in forests is affected by the environment and by management: (1) general causal knowledge with high levels of evidence present in the scientific literature; (2) specific causal assumptions represented in mathematical and computer models with biodiversity as a state variable (e.g. Mönkkönen et al. 2014); and (3) intuitive causal belief of biodiversity-generating processes in forest scientists and forest managers (e.g. Raivio et al. 2001). In all approaches, different groups of organisms are regarded as target organisms, both in their abundance and species richness.

Literature review of which mechanisms (are hypothesised to) link forestry and diversity. Investigation of forest growth models for the explicit presence of these mechanisms in the code (light regime, disturbance, connectivity, stand heterogeneity, etc). Elicit the mental biodiversity model of practitioners, e.g. from observation of practice, through interviews, online image evaluation or by trick-questioning, to explore whether these diversity-affecting mechanisms are present (see attempt by Hauhs and Lange (2008) to do so: present a management and ask what is wrong with that; why?).

D2 will link to B-modules for approaches (1) and (2), and to all projects for the causality workshop. In particular, D2 will integrate with the approaches and experience of D1 for eliciting causal knowledge in practitioners.

Findings

In the first three years of D2-research, the focus was on defining and applying an evidence scale for scientific statements about the effect of deadwood on species richness in managed forests. Fabian Gutzat also evaluated potential reservations of forest managers against evidence-based guidelines for forest management, as modelled on evidence-based medical treatment guidelines. His meta-analyses demonstrates the feasibility of approach (1), i.e. summarising scattered knowledge in the scientific literature into quantitative and into systematic reviews.

Since 2019, Carlos Miguel Landivar will identify scientifically demonstrated drivers of species richness (for different groups of organisms,) and match these to processes represented in predictive diversity and forest growth models (both correlative and mechanistic; links to C1). In cooperation with C2, we will continue to link scientific knowledge to foresters intuitive or trained knowledge and its implementation. This can be evaluated using the visual information contributed by A1 and the actual biodiversity data of the B-projects. We hope to identify potential gaps in forest practitioners ecological knowledge and suggest strategies to build a more complete biodiversity management intuition.

ConFoBi publications by D2

Gustafsson, Lena; Bauhus, Jürgen; Asbeck, Thomas; Augustynczik, Andrey Lessa Derci; Basile, Marco & Frey, Julian et al. (2020). Retention as an integrated biodiversity conservation approach for continuous-cover forestry in Europe. Ambio, 49, 85–97. www.doi.org/10.1007/s13280-019-01190-1.

Gutzat, Fabian & Dormann, Carsten F. (2018). Decaying trees improve nesting opportunities for cavity-nesting birds in temperate and boreal forests: A meta-analysis and implications for retention forestry. Ecology and evolution, 8, 8616–8626. www.doi.org/10.1002/ece3.4245.

Knuff, Anna Katharina; Staab, Michael; Frey, Julian; Dormann, Carsten F.; Asbeck, Thomas & Klein, Alexandra-Maria (2020). Insect abundance in managed forests benefits from multi-layered vegetation. Basic and Applied Ecology, 48, 124–135. www.doi.org/10.1016/j.baae.2020.09.002.

Storch, Ilse; Penner, Johannes; Asbeck, Thomas; Basile, Marco; Bauhus, Jürgen & Braunisch, Veronika et al. (2020). Evaluating the effectiveness of retention forestry to enhance biodiversity in production forests of Central Europe using an interdisciplinary, multi-scale approach. Ecology and evolution, 10, 1489–1509. www.doi.org/10.1002/ece3.6003.