Background of the special issue

From the early stage of the discipline’s development, landscape ecologists have been collaborating with researchers from neighboring fields (Kienast et al. 2021), embracing frameworks and approaches of interdisciplinarity. Modern landscape ecology, however, has been characterized by its paramount emphasis on spatial heterogeneity (Turner et al. 2005, Wu 2006). This requires integrative approaches, involving diverse scientific disciplines, ranging from ecology and life sciences to the social sciences. Moreover, the integration of local actors or decision makers has fostered the development of a transdisciplinary character (see Pătru-Stupariu and Nita 2022). Overall, landscape ecology highlights the necessity of accounting for different disciplines, actors, and communities, ranging from scientific approaches to stakeholders and wide public involvement. Thus, it has become an arena that integrates all of them and that can find solutions through the application of scientific principles.

The representation and analysis of spatial patterns, handling huge databases or the interaction between scientists and practitioners rely on suitable methodologies and appropriate instruments. On the other hand, it is acknowledged that the recent decades brought outstanding technological developments, together with trans and multidisciplinary interactions. Both the diversity of technological instruments and the number of users experienced substantially increased. Artificial intelligence, augmented reality or social media are only a few examples of methods and technologies that left a decisive mark in the recent scientific developments. Landscape ecology, as well as other research areas, can benefit from the emerging technological advances. It is therefore necessary to bring to the attention of the landscape ecology community recent developments and potential tracks for the future. Thus, this issue gathers both review papers focusing on specific topics and exemplifications of how novel technologies and interdisciplinary approaches can be applied in landscape ecology. The findings and approaches presented in these contributions can enhance existing research directions, stimulate new ones, and pave the way for new interdisciplinary approaches, altogether contributing to the advance of landscape ecology.

Contents of the special issue

The Special Issue includes eight papers. Two of them are review papers that highlight the potential of landscape ecology for interdisciplinary and transdisciplinary studies, and four articles are case studies focusing on specific research areas (biodiversity, species or urban landscapes). One of the articles presents very recent approaches related to virtual reality.

The review, “Impacts of the European landscape convention on interdisciplinary and transdisciplinary research”, brings attention to an international treaty (the European Landscape Convention—ELC) that has created a framework for the development of inter- and transdisciplinary studies. This treaty has profoundly influenced the analysis, planning and management of the landscape in all the countries where it has been implemented (Pătru-Stupariu and Nita 2022). The existence of the ELC for 20 years has shown through its application that Landscape Ecology is a research area where inter- and transdisciplinary approaches can develop and evolve, and where new innovative methods can be applied. For instance, virtual technology has become a useful tool for engaging both stakeholders and decision-makers (Pătru-Stupariu and Nita 2022).

The second review in the issue is entitled “Machine learning in landscape ecological analysis: a review of recent approaches” (Stupariu et al. 2022). The topic is directly related to the manner in which novel technologies and methodologies—in this case Machine Learning (ML)—interface with Landscape Ecology. The systematic literature analysis investigates which ML methodologies have been applied to landscape ecological studies, delineates the main topics, and assesses the principal trends. The findings reference both quantitative and qualitative components of ML. There has been a significant increase in the number of landscape ecological problems that benefit from suitable artificial intelligence approaches. On the other hand, the methods used have become more sophisticated and there is a risk of these tools becoming “black boxes” that obscure inference (Holm 2019). Overall, there is a high degree of synchronization between the application of ML in landscape ecological analyses and the general ML. This proves the openness of Landscape Ecology to novel techniques and methodologies, indicating a maturing of the field.

An example on how appropriate algorithms can be applied for a practical problem is the paper, entitled “A new agent-based model provides insight into deep uncertainty faced in simulated forest management” (Sotnik et al. 2022). The application area is forest management and the uncertainties that arise when forecasting long-term landscape change. The solution proposed by the authors is an agent-based model that enables the simulation of alternative approaches to estimate the degree of uncertainty in forest management. The agent-based technique applied in the paper was proposed as an extension to an existing landscape-change model. The innovative method outlined in the paper highlights that landscape ecology is a field where challenges and practical problems stimulate the development of new analysis tools.

The paper, “The scale effects of landscape variables on landscape experiences: a multi-scale spatial analysis of social media data in an urban nature park context” (Chang and Olafsson 2022), analyzes landscape experience reflected in the social media, which is a particular expression of the digital technologies’ democratization. The paper investigates in a multiscale context the relationship between landscape variables and categorized nature experiences reflected in social media data (Flickr photos). The application of a novel spatial regression model made it possible to better explore various types of interactions of humans and the environment, by considering spatial heterogeneity and scale.

An application of another particular novel technology, Virtual Reality (VR), is presented in the paper, “Immersive landscapes: modelling ecosystem reference conditions in virtual reality” (Chandler et al. 2022). VR is a tangible example of an emerging technology, relying both on the hardware advances, complex algorithms and data structures, and on suitable software capabilities. In the paper, the authors describe the potential advantages of immersive VR for understanding the complex dynamics of ecosystems and for building 3D fauna and flora models. Of particular importance is the direct engagement of stakeholders and policymakers, facilitated by the VR experience, thus showing the potential of virtual technology as a tool for public participation.

The paper, “Sex-specific connectivity modelling for brown bear conservation in the Carpathian Mountains” (Garcıa-Sanchez et al. 2021), highlights a methodological framework based on interdisciplinary approaches and modelling tools for assessing landscape connectivity combined with novel spatial analysis. Telemetry data combined with GIS analysis and forest management approaches helped the authors to develop a new way of identifying high-priority areas of movement pathways potentially used for dispersal by the species. Moreover, through this study in which interdisciplinary approaches are combined, it offers practical solutions to managers and decision makers, once again showing the usefulness and applicability of these studies with a focus on landscape ecology.

The paper, “Problems seeded in the past: lagged effects of historical land-use changes can cause an extinction debt in long-lived species due to movement limitation” (Jimenez-Franco et al. 2022), is another contribution in which the authors show the importance of interdisciplinarity in relationship to landscape ecological topics including land use change, landscape simulations, and GIS approaches. Thus, the authors use landscape modeling to develop an interdisciplinary study that shows the effects of land use change may have a greater impact than has been known so far, with previous studies referring mainly to observational studies.

The paper, “Integrating life cycle assessment into landscape studies: a postcard from Hulunbuir” (Wu et al. 2022), is an illustration of an emerging topic that could become more integrated into future landscape studies. The authors demonstrate how suitable technologies for spatializing elementary flows and characterization factors could enhance the agricultural life cycle assessment. Because the output of the workflow includes interactive maps, the aggregated information will be more immediately useful to stakeholders and practitioners.

Concluding remarks

Landscape ecology has profoundly transformed landscape research by its inter- and transdisciplinary nature. Recent trends indicate a convergence towards new research directions within Landscape Ecology that emphasizes sustainability science and research on social-ecological systems (Li et al. 2021; Wu 2021). Particularly with regard to key societal challenges such as climate change adaptation and mitigation, and biodiversity losses, landscape ecological research can enhance the connections of natural sciences with society by contributing to a systemic understanding of drivers and on the efficiency of decision and policy alternatives (Opdam et al. 2009; Mayer et al. 2016; dos Santos et al. 2021).

To sustain the continued evolution of landscape ecology, we must embrace novel technologies and approaches. Landscape ecology has always embraced the latest technologies from GIS, to remote sensing, to simulation modeling. As those technologies have become mainstream, we need to further push the boundaries of knowledge in order to achieve true interdisciplinary science. Furthermore, the Anthropocene presents new challenges that requires new technologies: How can we use landscape ecological principles and knowledge to envision a spatial re-allocation of biodiversity and artificial ecosystems? How do we build compromises among the food, energy and water demands of a growing society and the need to halt critical biodiversity losses?

For example, we need to improve our use of qualitative research methods from social science to include perceptions, experiences, local and indigenous knowledge. Doing so can contribute to the development of landscape plans that account for trade-offs among different societal priorities. Citizen science approaches, participatory impact assessment, and scenario development, for instance, could enrich our knowledge at different scales, from ecosystem to landscape, and could incorporate the local or inherited perception of nature’s values (Adler et al. 2020; Peter et al. 2021).

As demonstrated in this special issue, the combination of social science approaches within a virtual environment (e.g., Huang et al. 2020) is a promising step towards translating landscape ecology into meanings for individuals. This will enable better understanding how individuals perceive, consciously and unconsciously, about a given environment and how changes at ecosystem or landscape scales could affect their physical and mental health (e.g., Zhu et al. 2021) and can improve community-based decision-making (Chandler et al. 2022).

Transdisciplinary landscape ecology research (in which all stakeholders co-develop landscape plans) requires innovations to support communication and consensus building. Such methods need to be able to permanently support negotiation and consensus building processes while accounting for the complex influences of socio-economic, cultural and political development. Communicating the temporal dimensions of ecosystem and landscape development, ranging from seasonal variations to long term trends, must be integrated into spatial scenario modelling. Stakeholders often do not realize that their envisaged landscapes will require decades to develop, while the needs of future generations might not coincide with the landscapes we design today. Consequently, technologies need to inform the status of ecosystems and landscapes into the future, but also capture the intermediate and transitory story.

In summary, we are excited to report that landscape ecology continues to thrive at the vanguard of technological developments, supporting the transdisciplinary research that will be required for the coming era of unrelenting social and ecological change.