“Forest science relies on the long-term data that scientists wring from forests over decades. Our chances of overcoming climate change are small, but they will diminish further if we forget the basics of monitoring our home planet” (Editorial in Nature—18th August 2022, 608: 449).

1 Introduction

Forests constitute an immense resource globally (FAO 2020) and are key for climate change mitigation (Jackson et al. 2008; Masera et al. 2003), protection of biodiversity, and providing a variety of services for people across the world (Díaz et al. 2015). In this context, the role of forest inventorying and monitoring (IM) programs is of paramount importance to obtain baseline data, track changes, provide data for modeling and model validation, and inform policy and management, so that science-based actions and strategies can be implemented and their results monitored (Ferretti and Fischer 2013; Forest Europe 2020; Lovett et al. 2007; Vidal et al. 2016). IM has become even more crucial at a time of rapidly evolving scientific and societal demands (Armstrong et al. 2023; European Commission, 2023; Hegetschweiler et al. 2020) and accelerated global change, for example, as a result of droughts, storms, pest and disease outbreaks, and invasive species (Frei et al. 2022; Jakoby et al. 2019; Liebhold et al. 2017; Rohner et al. 2021; Trumbore et al. 2015; Valentin et al. 2020).

While existing IM systems have led to substantial advances in evaluating the response of our forests to environmental changes (e.g., Alberdi et al. 2020; Liang et al. 2022; Jaime et al. 2022; van der Linde et al. 2018), they are now facing several interrelated challenges, including (i) their ability to provide timely information at the time of accelerated forest dynamics, (ii) using resources efficiently, and, (iii) having technological readiness. In part, the first two challenges reflect the different origins of and the disconnection among current IM initiatives. For example, sampling density, temporal resolution, and timing of current IM initiatives were designed decades ago and they were optimized to estimate the extent (in different respects) of forest resources and identify changes based on some assumption on their pattern of occurrence (e.g., rather faint changes due to forest management policy, background air pollution). Events outside these target patterns, for example, repeated drought episodes with a patchy spatial distribution as the one caused by the 2018 megadrought in Europe, may “fall through the mesh,” and not be immediately quantifiable by existing regular surveys (Rohner et al. 2021; Schuldt et al. 2020). Given that climate change–related disturbances will likely increase in frequency and dimension (e.g., pest outbreaks; Jakoby et al. 2019), the ability of a monitoring system to respond rapidly drawing on a wide array of measured attributes will become more and more important. In addition, although the terms inventorying and monitoring are frequently used synonymously (e.g., Morrison et al. 2008), they originally constituted two approaches with important differences, which, however, do have potential complementarities and some overlaps (Ferretti 2013). In Europe, this situation is typically represented by two distinct systems constituted by the international forest monitoring carried out under the United Nations Economic Commission for Europe (UNECE) ICP Forests (hereafter ICPF) (Ferretti 2010; Ferretti and Fischer 2013) and by national forest inventories (NFIs) coordinated under the European National Forest Inventory Network (ENFIN) (ENFIN 2021; Tomppo et al. 2010a). Differences (and therefore potential complementarities) include the origin (periodical assessment of national forest resources in NFIs; annual assessment of spatio-temporal changes in international forest condition and its response to environmental stressors in ICPF), sampling density (higher in NFIs), temporal resolution (higher in ICPF), statistical design (stronger in NFIs), ecological coverage measurements (broader in ICPF), scope of field methodologies, quality control, data access, and governance (nationally oriented in NFIs; internationally oriented in ICPF) (Ferretti 2013, 2021). Overlaps include the fact that in several countries NFI and the ICPF Level I networkFootnote 1 share the same sample plots (Travaglini et al. 2013), although in many cases they use different field teams who visit plots at different times. The differences/complementarities and overlaps between the ICPF forest monitoring and NFIs clearly show that the current situation is sub-optimal: as such, building synergies will create added value between different IM initiatives, improve understanding and efficient use of resource, and permit us to go beyond the obsolete distinction/segregation between forest inventories and forest monitoring (Ferretti 2013; Kovač et al. 2014; Wulff et al. 2012). Ultimately, this will also allow us to better evaluate the effectiveness of policy and forest management actions, respond to the parallel increase and diversification of societal demands (e.g., biomass, biodiversity, recreation) and the augmented impact of different stressors (e.g., droughts, storms, pest and disease outbreaks).

Together with evolving societal and scientific demands and accelerated ecological changes, rapid technological advances also create new needs and opportunities for IM to advance. Besides classical remote sensing approaches, traditional forest mensuration on IM plots can now be supplemented by, for example, close-range remote sensing tools and technologies (Abegg et al. 2017; Calders et al. 2020; Kukenbrik et al. 2022; Tomppo et al. 2021), environmental DNA (eDNA) (Sales et al. 2020) and in-site sensors (Zellweger et al. 2019; Zürcher et al. 2023; Zweifel et al. 2023). In short, and ideally, what is currently being measured on statistically representative networks on an annual (e.g., ICPF Level I) or multi-annual basis (e.g., NFIs), in the future should be (i) measured with higher temporal frequency, (ii) supplemented by additional measurements that today are typical only for case-studies (e.g., ICPF Level II plots), and, (iii) better connected and integrated with close-range and remote sensing and other novel techniques (Ferretti et al. 2013; Ferretti 2021). Conceptual and technological development towards a new generation of Advanced Inventorying and Monitoring programs (AIM) will favor a better connection and integration between existing systems, an option that deserves consideration in view of scientific, operational, political, and financial benefits (Ferretti et al. 2013; Noon et al. 1999).

Switzerland can be a useful working example for developing AIM systems. Firstly, there is a variety of IM initiatives covering Swiss forests (Rigling et al. 2015), including the Swiss National Forest Inventory (NFI) (Fischer and Traub 2019), the Long-term Forest Ecosystem Research (LWF), encompassing Sanasilva forest condition survey (Schwyzer et al. 2015), and the Biodiversity Monitoring Switzerland (BDM) driven by the Federal Office for the Environment (FOEN) (BDM Coordination Office 2014). Secondly, these programs have important connections and similarities but also differences. They are connected from the point of view of their design: they are all based on the original 1 × 1 km systematic sampling grid developed for the first Swiss NFI (NFI1) (EAFV 1988; Fischer and Traub 2019) but are now installed on different sub-grids with only partial overlap, have different frequencies of data collection (from 1 to 5 and 9 years) and different measurement timings within the year (Ferretti et al. 2021). Thirdly, as in many other countries, there is a substantial segregation between large-scale surveys and intensive studies, with LWF plots (i.e., the Swiss realization of ICP Forests Level II with installed monitoring instruments) being located on purposefully selected sites outside the NFI network. While these different IM approaches, grids, sites, measurement frequencies, and variable of focus can be ideal for individual surveys, they appear sub-optimal when considering the overall perspective of data integration and use of resources.

In summary, emerging environmental issues, accelerated forest dynamics, new information needs, novel technologies, changed spatial and temporal scales of concern and more efficient use of resources require the development of a new generation of transdisciplinary AIM programs. Such programs would be beneficial to incorporate comparable, long-term, multiscale, near-real-time high-quality data able to detect forest ecosystem status and changes with increased temporal resolution. Realizing this fact prompted a new initiative towards an Advanced Inventorying and Monitoring system for Swiss forests (SwissAIM) (Ferretti et al. 2021). This paper (i) summarizes the participatory processes undertaken to develop SwissAIM, (ii) describes the design concepts that emerged from the process, (iii) discusses the potential for relevance and transferability of SwissAIM concepts outside Switzerland, and, (iv) identifies relevant key messages that emerged from the process. We consider it useful and timely to share our experience and promote a dialog with those interested in developing future forest monitoring, especially when considering important initiatives like the proposal for a new regulation on a monitoring framework recently launched by the European Commission (see European Commission 2023).

2 Primary steps undertaken to develop SwissAIM

Envisioning, developing, and designing the SwissAIM initiative was a collaborative and participatory process (Fig. 1) with different steps including (i) a starting phase to conceptualize and develop a vision and long-term strategy involving scientists from different disciplines and with different backgrounds, (ii) a phase for collaborative design, (iii) a concurrent phase for prototyping and testing the design, and, (iv) a final phase, including starting developing a governance vision through the identification and engagement relevant stakeholders.

Fig. 1
figure 1

Development of the SwissAIM (Advanced Inventorying and Monitoring for Swiss Forest) initiative with the main steps undertaken in the design process. The colors indicate those years/events/phases with mostly internal institutional science-driven activity (green) and when/where actual interactions with different stakeholders took place (yellow). The steps are described in the text. “Design V1” and “Design V2” mean subsequent revision of the design after input and feedback from different stakeholders. (Ferretti et al. 2021b; Shackleton and Ferretti, 2022)

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Although SwissAIM was initially science-driven to explore its scientific and strategic relevance and technicalities (e.g., sample size, plot design, and survey methods), in subsequent steps, numerous stakeholders involved in policy and management (e.g., the Forest Department of the Swiss Federal Office for the Environment – FOEN; Cantonal forest offices) and environmental non-governmental organizations (NGOs) were also engaged in the conceptualization and design of SwissAIM.

2.1 Developing an innovative vision and long-term strategy

The vision for the SwissAIM initiative was developed taking into account the input of scientists from different disciplines (forest ecology, dynamic, management; forest health; forest inventory and monitoring; biodiversity; soil and biogeochemistry; remote sensing and land change science; social sciences—see Ferretti et al. 2021) and the following overarching requirements that can be considered of relevance for AIM initiatives in general:

  1. (i)

    Statistical perspective. AIM has to provide defensible results with known uncertainty. Here, a sound statistical perspective is essential for forest status and change estimation.

  2. (ii)

    Holistic and integrative nature. AIM should consider all compartments of forest ecosystems (e.g., atmosphere; vegetation—from trees to lichens; soil), the different trophic levels (from producers to consumers), and the social dimensions (e.g., recreation, cultural values, management, and policy needs). Therefore, AIM initatives need a transdisciplinary, multifaceted perspective and will make use of terrestrial, close-range and remote sensing observation, and advanced tools and techniques (e.g., sensor networks, eDNA).

  3. (iii)

    Temporal resolution. AIM should increase the temporal resolution of measurements as compared to the traditional, multi-annual NFI cycles (e.g., 9 years for the Swiss NFI), allowing for effective and timely detection of status and changes. For those attributes potentially subject to changes over the growing season (e.g., tree canopy and vegetation attributes) annual or even repeated intra-annual measurements should be considered. This will favor timely reporting, able to catch the pulse of forests, and tailor to the needs of all stakeholders for timely management and policy responses.

The overall SwissAIM vision then emerged as follows (Fig. 2):

“An integrated terrestrial and remote sensing observation system based on a permanent panel of enhanced NFI plots, that will provide high quality periodical (intra-annual, annual, multi-annual) results with known statistical errors for status, change and response of forests to biotic and abiotic drivers”.

Fig. 2
figure 2

Conceptual vision for the SwissAIM as an integrated inventorying and monitoring system. Moving from existing spatially and/or temporally segregated individual IM activity (bottom left, A) to co-located terrestrial measurements (middle, B) to highly integrated terrestrial, remote sensing, and model-oriented AIM (top right, C)

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The innovative part of this vision includes the idea of combining the statistical perspective (typical of the NFIs) with an expanded set of ecosystem-oriented measurements and with high temporal resolution (typical of ICPF) and integrating all these different terrestrial measures with close- and remote sensing in plots with enhanced design. Altogether, this will permit (i) expanding the scope of existing IM systems across ecosystem compartments and properties, (ii) closer connection with remote sensing and modeling, and, (iii) better validation, calibration, understanding, and prediction. In this vision, the role of the Swiss NFI is central, because it (i) offers a robust and consistent nationwide statistical framework, (ii) has an already well-installed remote sensing component, and, (iii) is based on a systematic grid that has been used as the basis for other monitoring initiatives, like the forest condition survey Sanasilva and the BDM initative (see above). In particular, the Sanasilva provides a direct connection with the international dimension, as it represents the Swiss realization of the ICPF Level I assessment. Potentially, connecting NFIs and ICPF would provide an additional benefit (Ferretti 2010; Ferretti et al. 2013; Gasparini et al. 2013; Travaglini et al. 2013). A further important aspect inherent to the above vision is related to the need for comprehensive data for model calibration and validation.

There are several features inherent to the above vision. They include the following:

  1. (i)

    SwissAIM should be a collaborative and participatory effort. On one side, development and implementation should include the perspectives and expertise of different stakeholders. On the other side, it will need, and will be conducive to, synergies and coordination between scientists of existing IM initiatives, and ideally result in enhanced scientific performance.

  2. (ii)

    SwissAIM intends to be based on a permanent panel of NFI plots with an enhanced design. While this will place some challenges in the design and operability dictated by the nature of the NFI (e.g., the need to keep plots anonymous, see Sects. 2.2.3 and 2.2.4), it will offer the basis for national-scale, annual data, and estimates for status and change of key attributes linked to forest response to biotic and abiotic drivers, including extreme events. With annual data on, e.g., growth, SwissAIM will also enhance the interpretation of changes detected between subsequent 9-year NFI cycles.

  3. (iii)

    SwissAIM has the ambition to be exemplary at the national/international level. Its vision, structure, and inherent collaborative nature will permit high-quality results and outputs, especially models relevant from local to national scales. It will be inspired by and will inspire development in the field of forest IM.

  4. (iv)

    SwissAIM intends to serve science, practice, and society at large and will help to respond to the challenges posed by climate and global change. It will open research opportunities and will permit timely and closer monitoring of forests from a broad range of scientific perspectives. This will desirably lead to faster identification, upscaling and reporting of possible problems and prompt science-based solutions to better promote management, resilience, and resistance of our forests to accelerated environmental changes.

2.2 Collaborative design

The design process started with the identification of scientific questions, the related variables of interest and associated methods, the sampling design (including sample size), and the plot design.

2.2.1 Identifying research questions of interest

Ninety-two research questions were identified by scientists from different disciplines (Shackleton and Ferretti, 2022) (Appendix). These questions of interest covered aspects related to both research and application and were categorized into three broad categories including (i) better quantifying forest status and changes (i.e., the most typical set of questions for IM programs) (total: 29 questions), (ii) improving the understanding forest processes and dynamics (especially relevant when considering the foreseen acceleration of several processes induced by global change issues) (44 questions), and (iii) questions related to developing enhanced monitoring and inventorying techniques (an enduring concern for any IM perspective) (19 questions). The 100 most common words relating to the original questions (overall, and for each of the above three categories) are in the world clouds in Fig. 3: besides terms that can be expected given the context (e.g., “Swiss”, “forests”, “NFI”, “LFI” – the German acronym for NFI), others like “status”, “change”, “biodiversity”, “climate”, “drought”, “ecosystem”, “biotic”, “abiotic”, “remote sensing”, and “close range” emerged in the various clouds. Examples of topics related to the various questions are reported in Table 1.

Fig. 3
figure 3

The 100 most common words relating to (A) the entire set of 92 questions, and the sets of questions related to the quantification of status and change (B), understanding processes and dynamics (C), and enhancement of inventorying and monitoring techniques (D)

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Table 1 Examples of topics/goals mentioned for the three broad categories of research questions. For the full-list questions of interest please see the Appendix
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2.2.2 Variables and methods

Table 2 provides a summary of the main categories of attributes to measure that were mentioned through participatory processes (see full list in Appendix). Although measuring at least parts of the “traditional” forest attributes on NFI and LWF/Sanasilva plots, which is considered necessary also for comparative purposes, SwissAIM is conceived to go far beyond this and will include a broad range of target measurements (from the atmosphere to trees, vascular plants, other taxa, and soils) and collection of specimens for dedicated investigations (e.g., eDNA). Accordingly, measurement methods will be diverse and based on different platforms, from terrestrial to close-range and remote sensing.

Table 2 Measurement targets, data needs and sources and nature of measurement/sampling mentioned during the design process
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Overall, we identified four priorities that measurements/activity to be undertaken for AIM initiatives should consider the following:

  1. (i)

    Permit building better links among close-range, “traditional” remote sensing and terrestrial measurements. This will enable more diverse, accurate, quantitative and repeatable ground measurements, integration of data from below and above the canopy for more complete information at plot level (e.g. habitats, structures, ecophysiology), calibration/validation of models, and upscaling.

  2. (ii)

    Improve/expand biodiversity-related assessments. Ground vegetation (at least vascular plants indicating changing site conditions) and other organismal groups, not just trees (e.g., insects, birds, bats, fungi, lichens, and bryophytes) should be considered to better evaluate biodiversity.

  3. (iii)

    Collect specimens to assess, for example, soil and tree nutrition via foliar sampling, past annual growth using tree cores, eDNA for biodiversity, and pests and pathogens for demography and damage evaluation, and detection of non-native invasive species. This point received large interest to better evaluate and understand forest dynamics and responses to current and past disturbances and extremes.

  4. (iv)

    Add in-site automated recording of environmental variables (e.g., atmosphere, soils) with near real-time access to data (i.e., via remote upload).

Whether all of these additions will be possible, and which trade-off will be necessary, will be clarified during the final steps of the design process and prototyping, especially in consideration of the need to protect NFI plots from bias due to visitation and monitoring activities and budget constraints (see 2.2.4).

2.2.3 Sampling design

Sampling and plot design drive the precision of estimates of status and changes in relation to the attributes being measured. The design is closely related to the spatial and temporal scales of interest, and the ecological targets scales (from genes to ecosystems) (Table 2). In particular, the possibility to draw conclusions valid for (i) the forest tree population, (ii) at the level of the entire country, and, (iii) in the short, medium, and long term were most frequently mentioned as important during the design process. Interest in deriving estimates at the level of biogeographic regions and/or over-defined environmental gradients was also mentioned. Related to temporal scales, there is the need to ensure the optimal frequency of measurements of different attributes in agreement with their expected rate of change. For this reason, SwissAIM will generate data with different temporal resolutions, ranging from continuous automated measurements (e.g., soil matric potential), to intra-annual and annual (e.g., tree diameter and crown condition) and to multi-annual measurements (e.g., soil solid phase, ground vegetation, tree genetics).

Three main aspects of sampling design were considered: the network scheme, its sample size in terms of number of plots and the plot design (see below). As for the network scheme, two main components were identified: a systematic component and a thematic component, both based on the NFI grid which offers a consistent operational framework across Switzerland. The systematic component would provide national-scale, statistically representative data and information on an expanded set of attributes and at higher time resolution than IM programs in place so far. The thematic component would concentrate on defined themes and stressors (e.g., drought). Both components would, however, be connected by using the same enhanced plot design (see below). This also represents an innovative feature, as it incorporates, since the beginning, the idea to use a common system for two purposes: status and change detection, and understanding of forests’ response to defined stressors.

In detail, the SwissAIM thematic component would be based on a sub-sample of the NFI plots selected according to defined environmental gradients/strata. As environmental gradients of interest can always vary according to changing priorities (e.g., disturbance, nitrogen deposition, and forest protection and conservation gradients), the selection of relevant NFI subsamples will happen only upon the definition of the gradient of concern and the required sample sizes on a case-by-case basis. These thematic sub-grids could therefore be included whenever necessary, can be temporary or permanent, will densify the SwissAIM systematic component, and will contribute to the flexibility of the entire SwissAIM system. As the thematic sub-grids will be developed upon demand, their individual design will not be discussed further here.

The SwissAIM systematic component would be based on a sub-sample of plots on the NFI grid selected to cover the whole of Switzerland. While the final layout and sample size of the systematic grid are currently being defined, the most favored option is to use plots on the currently active NFI grid over the use of "dormant" plots (Table 3).

Table 3 A summary of different sampling design options, with pros and con, as emerged from the participatory design process (Shackleton et al. 2023)
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Such a choice will permit better synergies between different IM initiatives in Switzerland using the same grid and allow SwissAIM to draw on existing long-term data. On the flip side, this option will limit destructive or invasive measures or excessive visitation which could introduce biases on the plots (e.g., Ferretti 2014; Semboli et al. 2014) and in the plot management and therefore affect the representativity of NFI estimates and potentially jeopardizing the 40-year long time data series (see below). Another option suggested to mitigate possible impacts on NFI plots is to use the current NFI grid, but add “satellite” plots nearby, enabling frequent, invasive/destructive measurements.

As for sample size, suggestions already exist to identify the minimum necessary sample size to assess the status of Swiss forests (e.g., forest health status based on tree crown defoliation, Köhl et al. 1994; Travaglini et al. 2013). Much less information is available about sample sizes needed to detect changes at defined probability levels. We conducted an ad hoc power analysis focusing on temporal changes and considered three attributes with different time windows for change detection and for which there were data available. The attributes included plant species richness (connected to biodiversity; changes over multiple years), basal area increment (connected to productivity and carbon sequestration; changes between subsequent years), and, tree crown defoliation (connected to forest health; changes between subsequent years). Using available data for each of the three attributes (species richness—Kull and Kuechler dataset; Thimonier et al. 2011; Küchler et al. 2015), basal area increment—RapiDbeeCH dataset (see details in Rohner et al. 2018), and annual changes in the frequency of trees with > 25% defoliation per plot—Sanasilva dataset), we calculated dz values (effect sizes), which were then used in the power analyses instead of more traditional Cohen’s d values. dz values account for high levels of correlation within paired sample designs (Lakens 2013). We used the open-source software R and G-Power for analysis. The preliminary results of the analysis suggest that ideally, the SwissAIM should have between 200 and 400 plots to achieve a reasonable statistical power of 80% to detect change for the considered variables at p = 0.05 (Table 4).

Table 4 Number of plots necessary to achieve different statistical power for detecting changes in different variables
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Two-hundreds plots correspond approximately to an 8 × 8 km grid for Switzerland (e.g., Fig. 4), which can be considered as the minimum acceptable sampling density. Table 4 also shows that higher power can be achieved with a considerable increase in the number of plots (and relevant denser grids) that will come with a major increase in the costs related to field work. With the above estimates of potential sample size, we can also conclude that if a bias will emerge after more intensive measurements on the selected plots, such a bias will affect ca. 200 plots, i.e., 3.3% out of the 6000 + plots of the NFI.

Fig. 4
figure 4

Map of Switzerland with an example of one possible layout of the systematic component of the SwissAIM on an 8 × 8 km grid sub-sample of the National Forest Inventory

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While the above sample size can be an acceptable trade-off in terms of statistical requirements, it will be necessary to achieve a sustainable balance (technically and financially) between spatial and temporal resolution. For example, since some measurements will require either frequent visits or relatively expensive technical equipment (e.g., soil sensors and their associated remote connection), it may become necessary to consider more relaxed grid densities for certain investigations.

2.2.4 Enhanced plot design

Plot design is a long-lasting challenge for forest IM initiatives (e.g., Häbel et al. 2019; Henttonen and Kangas, 2015; Kuhel et al. 1995; Zeide 1980), and there are various options and trade-offs that need to be considered in the development of any AIM initiative. The most favored option for SwissAIM was to enhance the design of NFI plots (Fig. 5) to accommodate more intensive and integrated monitoring.

Fig. 5
figure 5

Top: Comparison of current NFI plot design (a) with the enhanced design for the SwissAIM plots, with additional plot components in yellow (b). Bottom: list of plot components. For each plot component, its current use in NFI and the foreseen use in SwissAIM are described. NFI catalog refers to measurements already conducted by the Swiss NFI (Düggelin et al. 2020); the same applies to the Sanasilva catalog (Methods of the Sanasilva Inventory—WSL). See alphabetic capital keys (A, B, C, D) for connecting the top and bottom parts of the figure

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Current designs for NFI plots in Europe seldomly include frequent (annual, intra-annual) visits, invasive measurements/destructive sampling and/or automated measurements, and are very focused on tree growth, as opposed to multi-level integrated forest monitoring initiatives (e.g., ICPF , long-term ecological research) where such measures and considerations are more common (Ferretti 2013). By building on the AIM vision, we want to bridge this gap. As such, the option for an enhanced plot design will be to keep the traditional circular Swiss NFI plots as the base plus the current NFI interpretation area as a “large plot” for connections with remote sensing (which requires a larger area than the circular plots), drone-based measurements, TLS or MLS (terrestrial or mobile laser scanning) and their integration. The large plot can be supplemented with sub-plots for additional, minimally invasive or destructive measurements and specimen collection (e.g., tree coring, see Portier et al. 2023) (Fig. 5).

2.3 Prototyping and testing

The SwissAIM initiative is being prototyped and tested. This step is critical for guiding decision-making on many aspects of the design, especially those that come with constraints and trade-offs. In particular, this step is needed (i) to optimize methods and plot designs which are not yet fully tested (e.g., the use of terrestrial laser scanning to identify forest gaps for regeneration assessments; the sub-plots for semi-destructive measurements); (ii) to estimate costs, in order to prioritize options, assessing possible trade-offs in view of budget constraints, and developing strategies for co-funding between various institutions and stakeholders (see below); and, (iii) to have technological readiness, to ensure increased accuracy or efficiency of measurements, and to allow for better integration between measures and automated data analysis, also through Artificial Intelligence.

2.4 Engagement and governance

Identifying clear governance structures and mechanisms is critical to the long-term success of any collaborative initiative and these need to be adaptable in time to overcome challenges, improve and remain relevant (Lindenmayer and Likens 2009). While SwissAIM was prompted by a multidisciplinary scientific community, relevant stakeholders across academia, policy, and practice at the national and regional levels were engaged at an early stage to define and promote their involvement. For this purpose, we carried out a stakeholder mapping exercise to identify interests in and potential contributions to SwissAIM (Fig. 6). Overall, such an exercise showed that in Switzerland numerous institutions were perceived to have both, high power/influence and interest (38% of stakeholders listed), or high interest in SwissAIM (49% of stakeholders listed). Stakeholders identified with the highest power and interest included the Federal Office for the Environment (FOEN – national level policy and decision makers), several Research Units at WSL (WSL), existing forest IM programs (including the NFI, LWF/Sanasilva, BDM), MeteoSwiss (institution engaged in weather monitoring, forecast and plant phenology), forest protection managers in Switzerland, Swiss Universities, and the forest divisions of different Cantons (regional level decision makers) in Switzerland (Fig. 5). Of key interest for the further development and implementation of SwissAIM is to engage stakeholders with high power and/or high interest and a broad mix of stakeholders from different backgrounds (science, policy, and practice) interested in the initiative. The implementation of SwissAIM would build synergies and collaborations between different institutions and existing networks, and this needs to be reflected in the governance structure and its bodies. While in Switzerland inspiring governance models may come from, e.g., the Swiss NFI, at the international level, a good example of a combination of bottom-up and top-down approaches may come from the ICPF (see: Bodies & Structure—ICP Forests (icp-forests.net)).

Fig. 6
figure 6

Map of stakeholders and their power/influence on, and their interest in SwissAIM as emerged from an exercise carried out during a co-design workshop (Shackleton et al. 2023). Yellow dots: academic stakeholders; blue dots: policy/practice-related stakeholders; green dots: other stakeholders (e.g., Industry, NGOs). Note that stakeholders may have received more than one mention and different positioning by different workshop participants—in such a case, we have taken an average ranking between them. Only stakeholders specifically mentioned in the text are labeled (after Shackleton et al. 2023)

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3 Relevance and transferability of AIM initiatives outside Switzerland

The essential role of forests in mitigating climate change and achieving climate targets, and the augmented frequency and effects of disturbances have prompted a renewed interest and debate around forest IM (Bontemps et al. 2022; Ferretti 2021; Nabuurs et al. 2022; Päivininen et al. 2023). In Europe, for example, this renewed interest has resulted in the launch of several scientific projects under the Horizon Europe framework (e.g., PathFinder (pathfinder-heu.eu); Forwards – Healthy trees translate to healthy citizens (forwards-project.eu)), in the European Commission, a new proposal for a framework regulation on forest monitoring (European Commission 2023) as well as other initiatives (e.g., https://www.greens-efa.eu/en/article/event/forests-hidden-secrets). All these projects and initiatives involve many European countries (i.e., 15 in PathFinder; 11 in FORWARDS) plus the European Commission and its Joint Research Center. Thus, the timeliness and broad relevance of the subject and suggestions provided in this paper are obviously important beyond Switzerland.

Besides the relevance and timeliness of SwissAIM, the practical transferability of the concepts adopted here to other countries with largely different environmental, organizational, and political conditions is important. Here, it is worth noting that, like in Switzerland, many European countries, and several countries outside Europe (e.g., Breidenbach et al. 2021), have existing forest IM in place with, e.g., (i) both NFI and ICPF networks running, (ii) sometimes in connection, sometimes not (see Travaglini et al. 2013), but (iii) always with different time resolutions and (iv) with non-forest attributes almost always measured on different, segregated networks based on haphazard or ad-hoc sampling design. Under this situation, we believe that the concepts proposed here (clear statistical perspective, augmented time resolution, expanded data catalog, synergies among existing IM systems, improved connection and integration between terrestrial measurements, remote sensing, and models by means of enhanced plot design) are of general value and can be adopted (or adapted) in relation to the situation of individual countries: a typical example is the case of required sample size. It is important to acknowledge that since much of the process described here involved an intense dialogue among scientists from different disciplines and other stakeholders at various institutional levels, its practicability depends on the situation of individual countries. Yet, just because countries from across Europe and the European Commission itself are now demonstrating interest in the subjects (see above), we are also convinced that the above concepts reflect a generalized direction of development and can help inspire an international, pan-European vision about forest IM.

4 Key messages for the development of advanced inventorying and monitoring initiatives (AIM) emerging from our experience

We identified four main messages emerging from the SwissAIM design process which may be useful for developing AIM programs elsewhere:

4.1 Message 1: It is time to do it. There is ample interest in and a great need for advanced forest inventorying and monitoring (AIM)

There is a clear need and interest for AIM concepts and systems at both the Swiss and the international level. In scientific terms, the main drivers of interest were the potential for better detection and quantification of status and changes and improved understanding of forest dynamics that can be achieved by (i) highly integrative enhanced plots, combining “traditional” mensuration with cutting-edge technologies on (ii) a sound statistical basis, and, (iii) higher temporal resolution. In Switzerland, where for example the NFI is the basis also for other networks (e.g., the ICPF Level I and BDM survey), AIM can originate from concentrating investigations on (a selection of) NFI plots with enhanced design to expand the measurement catalogues, better connect with remote sensing, and improve models. In other countries, the statistical basis offered by locally existing networks (NFIs, ICPF, others) can play a similar role.

4.2 Message 2: Be transdisciplinary. Advanced inventorying and monitoring (AIM) initiatives should go across scales and disciplines and involve multiple stakeholders

There was a consensus that covering different spatial and temporal scales, environmental gradients, and different ecological and social targets by integrating different expertise through multi-, inter-, and transdisciplinary approaches were essential for any AIM initiative (see also below). For example, assessing status and change in the short as well as in the long-term was the focus of most scientific questions, especially in relation to climate change, and AIM could help to fulfill these shorter-term needs which are a big gap in current IM initiatives. Furthermore, the inclusion of several other organismal groups (e.g., ground vegetation, insects, birds), social aspects (e.g., recreation and management) and ecosystem compartments (e.g., atmosphere, soil) was seen as a desirable addition for AIM to improve overall understanding and to obtain baseline data also from other perspectives such as biodiversity conservation, forest use and management, cultural services and invasions by non-native species. On the same line, together with the national scale, other administrative scales (from enterprises to Cantons) and environmental gradients (e.g., drought sensitivity, nitrogen deposition gradients, forest protection, conservation, and management) were mentioned. The extent to which a single initiative can actually address all stakehoholder needs and scales is unclear. However, it is unlikely that SwissAIM will be able to cover all possible scales at all levels with acceptable statistical confidence and sustainable cost, and, trade-offs will likely be necessary.

4.3 Message 3: Promote integration. Integrated measurement approaches are increasingly necessary

The set of measurements and observations carried out under the traditional IM is large, but it still suffers some limitations and disconnection. There is a need to overcome existing limitations to better understand broader forest dynamics and processes and to improve models. The starting vision for SwissAIM also highlighted the intention to better integrate ground and remote measures. Similarly, the need to collect specimens (e.g., soil, cores for tree ring measurements) and install measurement devices (e.g., meteorological sensors, soundscape recorders for biodiversity) in or nearby NFI plots was mentioned several times during the workshops. Such activity would provide valuable additional data and information to better interpret the current and future development of the Swiss forest. However, destructive sampling and devices may collide with the fundamental need to protect NFI plots from disturbances related to monitoring and from visible installation that can also introduce unwanted bias as plots become visible to managers. For this, the design process considered this issue carefully and defined what can be done, and where.

4.4 Message 4: Be statistically sound. A robust sampling design is needed

For any AIM initiative to provide relevant scientific evidence, there is a need for robust statistical designs. This point was reiterated as important by various stakeholders across the entire design process. NFIs and ICPF Level I with their probabilistic sampling design offer a solid basis for building AIM initiatives upon, although we still recommend that dedicated studies are undertaken on the topic. An enhanced plot design should be adopted—and has been defined for the SwissAIM—to accommodate measurements traditionally not carried out, or not with the necessary temporal resolution, and the collection of samples into a consistent, optimized statistical framework (see Message 3).

5 Conclusions

There is an urgent need for timely and comprehensive information on the status, changes and drivers of forest health, productivity, biodiversity, and conservation in Europe. This information is relevant to address key challenges for our forests and our society, such as climate change mitigation and adaptation, energy and the biodiversity crisis, and, is necessary to better inform and evaluate policy and management responses to these challenges. Much has been already accomplished by running IM programs. Yet, addressing the above information needs involves overcoming the obsolete distinction between forest inventorying and monitoring programs by favoring their operational integration, expanding the suite of measures taken, and promoting the combination of terrestrial measurements, close-range and remote sensing, and modeling. The SwissAIM initiative has the ambition to put this into practice. It intends to be a collaborative effort to concentrate key measurements on a statistically representative set of plots to cover a wide range of attributes across all trophic levels and ecosystem properties at increased temporal resolutions. This will mark progress towards a new generation of forest AIM programs that—while keeping a probabilistic approach—are able to provide multi-level (atmosphere, vegetation, soil), multi-source (terrestrial, close-range-, aerial-, and space-borne remote sensing) data and information. AIM will permit addressing an augmented range of scientific questions beyond the traditional tasks of forest IM and will open new avenues for scientific investigation, enhanced reporting, data integration, and modeling, which will benefit both scientific understanding and developing policy responses - enabling us to better respond to global change challenges.

We identified a series of scientific questions at a variety of temporal, spatial, environmental, and ecological scales (from single sites to the entire country and from single cells to ecosystems) and developed a comprehensive list of possible novel measurements and sampling approaches that can be useful for inspiring other AIM initiatives. At the international level, several recent initiatives (see above) clearly highlight the need for more effective IM to be able to evaluate changes in carbon sequestration, forest health, productivity, and biodiversity including the causes and time dynamics of these changes. The extent to which synergies among different IM systems are actually considered across Europe is not clear yet. For this reason by favoring a better integration and dialogue between IM programs, SwissAIM is timely and may also promote development, advancements, connections and cooperation at the international level.