{"paper_id":"2aaeb109-9236-4c1c-9c4b-86fc20b4e1d4","body_text":"1\n1 Evolution and paradigm shift in forest health research: A review on \n2 global trends and knowledge gaps\n3\n4 Cristina Acosta-Muñoz 1,2 *, Rafael M. Navarro-Cerrillo 2, Francisco J. Bonet-García 1, Francisco \n5 J. Ruiz-Gómez 2, Pablo González-Moreno 2.\n6\n7 1 Department of Botany, Ecology and Plant Physiology. Ecology Area. University of Cordoba, \n8 Campus de Rabanales, Crta. IV, km. 396, E-14071 Córdoba. Spain.\n9 2 Department of Forestry Engineering, Research Group Evaluation and Restoration of \n10 Agroforest Systems - ERSAF. University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-\n11 14071 Córdoba. Spain.\n12\n13 * Corresponding author: Cristina Acosta-Muñoz, cristina.acosta@uco.es\n14\n15 ORCID:\n16 Cristina Acosta-Muñoz 0000-0002-9796-6367\n17 Rafael M. Navarro-Cerrillo 0000-0003-3470-8640\n18 Francisco J. Bonet-García 0000-0002-4627-1442\n19 Francisco J. Ruiz-Gómez 0000-0002-1999-3415\n20 Pablo González-Moreno 0000-0001-9764-8927\n21\n22\n23\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n2\n24 Abstract\n25 Forests provide key ecosystem services to human society, and the ability to provide these \n26 services depends on their overall health. Forest health is an attractive and interesting concept \n27 in forestry research, which environmental, social and political interests have shaped. Assessing \n28 forest health is crucial, but finding a single definition of the concept is complex. It is determined \n29 by the aim of the forest study, different areas of knowledge, scales of work, technology, \n30 methodologies, historical moment or source of funding, among others. With almost a century \n31 of scientific evidence, the aim is to identify and contextualise temporal changes in the relevance \n32 of this key concept. Trends are analysed through the construction of three main descriptors \n33 (state variables, drivers and methods) and the main conceptual subdomains (themes). This \n34 review reveals the significant geographical bias in the research, which the Global North \n35 predominantly conducts. We observe the evolution of forest health research driven by diverse \n36 needs and interests, ranging from air pollution to the multifaceted impacts of climate change. \n37 Methodologies applied in this field have also evolved from traditional crown condition \n38 inventories to the use of advanced tools such as remote sensing or ecophysiology, improving \n39 the characterisation of forest health patterns at both global and individual scales. Forest health \n40 research has evolved towards more holistic and multidisciplinary approaches, reflected in the \n41 broadening and integration of methodologies and technologies, influenced by historical context, \n42 which influence what is being researched today and future scenarios. We identified key \n43 knowledge gaps in the scientific literature, in particular the concepts of ecosystem services, \n44 Essential Biodiversity Variables (EBVs) and the concept of ‘One Health’. These findings highlight \n45 the need for future research to incorporate these critical but often overlooked areas, potentially \n46 reshaping future directions and scenarios for forest health research.\n47 Keywords: Research trends; multidisciplinary approaches; global change drivers; global \n48 environmental challenges; technological advances.\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n3\n49 1. Introduction \n50 The transformation of forests by human activity underscores the imperative need to focus on \n51 their preservation and health (1). Forests are essential for sustaining fundamental ecosystem \n52 services for biogeochemical cycles and humanity (2). This link between forest health and the \n53 capacity of forests to provide such services highlights the importance of understanding and \n54 maintaining the ecological integrity of these ecosystems. Recognising and responding on forest \n55 health is crucial to ensure their continued contribution to environmental and human well-being.\n56 The concept of forest health is an umbrella concept encompassing a wide range of conceptual \n57 subdomains (3,4), adopted by practitioners to understand health status (5).  This reflects the \n58 complexity inherent in the investigation of forest ecosystems, their interaction with human \n59 activities and environmental changes. As a result, researchers have used different study \n60 perspectives, definitions and research terms over time depending on the focus, scale of work \n61 and other aspects considered such as priorities [6], [7]. \n62 Researchers have adopted various terms related to forest health such as forest dieback, forest \n63 decline or forest decay, associating these processes with the presence of diseases or pests, \n64 observing symptoms at tree level (8). At larger scales, forest managers and researchers have \n65 traditionally focused on characterizing the potential causes and spatio-temporal patterns (9). \n66 Thus, the terms reflect not only tree mortality, but also a general loss of vigour and yield that is \n67 spread over relatively large areas and is often related to high environmental stress (10). \n68 Recently, the term forest health has evolved including also structural and functional aspects \n69 (11). For instance, some authors define a healthy forest as one that includes a mosaic of \n70 successional patches representing all development stages (12). At the same time, other more \n71 holistic terms such as forest condition, forest state and forest integrity have been proposed. \n72 Among them, forest integrity has been one of the latest suggestions, defining the overall \n73 capacity of a forest system to sustain composition, structure and function within the historical \n74 range of variation (13,14). \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n4\n75 Beyond the different conceptual subdomains we have listed above (used to define or assess \n76 forest properties), we argue that the science and research has changed over time, with different \n77 themes and associated terminology. We determine significant changes in recent decades based \n78 on the following three main descriptors: a) attributes to measure forest condition; b) drivers \n79 impacting on forest health condition (i.e., biotic or abiotic); and c) technologies and \n80 methodologies associated with measurement and analysis of the two previous aspects. \n81 With the expansion of science, the ever-deepening knowledge and the rapid pace of publication \n82 seen in almost all scientific disciplines (15), this review emphasises the critical importance of \n83 understanding what has brought us to the present. Understanding the historical context of the \n84 discipline lends depth to current perceptions of forest health and is crucial to addressing the \n85 challenges ahead. We not only value the foundations of our knowledge, but also recognise the \n86 importance of following a deliberate and informed path for the future and innovation in forest \n87 ecosystem research.\n88 The inherent dynamic of constantly evolving research approaches is also related to changes in \n89 the methodologies and technologies. The most frequent measurements have been crown \n90 condition and tree damage (e.g. defoliation and discoloration), or growth in terms of biomass \n91 and diameter increments (16,17). More holistic approaches go beyond the tree level to \n92 characterize population, community, and ecosystem properties such as biodiversity and \n93 regeneration dynamics. Regarding the drivers, forest health is affected by several disturbance \n94 agents of different origin, and which can impact forest systems in a complex and interactive way \n95 (11,18). In addition, context-dependency of the relevance of different abiotic and biotic agents \n96 affects the overall research outputs, with bias towards scientist’ geographical regions and \n97 specific taxa (19). \n98 Forest researchers have put enormous effort into forest observation and monitoring to \n99 understand forest health in relation to forest condition and related drivers (20). These \n100 encourage the development of a wide range of methodologies aiming to characterize forest \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n5\n101 ecosystem trends to inform policy and management decisions. These methodologies include \n102 direct measures of vegetation such as physiological (e.g. photosynthesis, pigments, water \n103 transport, respiration), structural measures derived from traditional forest inventories (e.g. \n104 growth, dendrochronology), measures related to external agents, but with implications on \n105 vegetation (e.g. drought, changes in land cover and land use), or measurements related to the \n106 role and functioning of forest as an ecosystem (e.g. nutrient cycling and productivity) (9,21). \n107 Lately, an increasing relevance of measurements derived from remote sensors deployed at \n108 satellite and unmanned aerial vehicles has been observed for the detection of non-visible \n109 phenomena in the forest  (22–24). The convergence of these advanced methodologies together \n110 with technological innovation allows for an ever deeper understanding of forests and their \n111 dynamics.\n112 Searches in the main scientific information databases (e.g. Web of Science or Scopus) show that \n113 current knowledge on forest health is fragmented across several research disciplines (forestry, \n114 environmental sciences, ecology, entomology, plant sciences, remote sensing, biodiversity \n115 conservation, geosciences, agricultural and biological sciences, earth and planetary sciences, \n116 social sciences, computer sciences, biochemistry, genetics and molecular biology, and others). \n117 Several attempts have been made from different disciplines to review and describe these \n118 changes in forest research (25) and to synthesize the conceptual frameworks around forest \n119 health (11) without having a complete picture of the temporal dynamics of the concept. \n120 Systematic and bibliometric reviews of scientific literature is key to synthesize a research field \n121 and to understanding the conceptual trend. We used this approach to understand the temporal \n122 and regional trends, research conceptual subdomains and methods used on forest health \n123 assessment and monitoring at global scale. \n124 Exploring the evolution of approaches to scientific research in forest health, to better \n125 understand trends, developments and challenges, and the implications this has for the way \n126 science is conducted globally, is of relevance [8]. In our study, we aimed to i) contextualise the \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n6\n127 status of and approaches used in forest health research (i.e. scientific output, main contributors, \n128 issues and keywords), ii) assess the temporal evolution of recurrent terms in forest health \n129 research (i.e. a complete temporal map of relevant keywords), and iii) understand temporal \n130 trends in the main conceptual subdomains encompassing forest health (i.e. topics) and the three \n131 descriptors of forest health introduced in this study: condition (variables used to measure the \n132 state or condition of forests), drivers (abiotic or biotic agents causing changes in forest \n133 condition) and methodologies (techniques used to assess forest health). \n134 We conducted a scientific literature search in academic databases covering a wide spectrum of \n135 forest health terminology (26). Data mining was applied to extract information and patterns \n136 from large bibliographic datasets that qualitatively, quantitatively and graphically allow a deeper \n137 understanding of scientific production (27–29). Using a systematic review, we contributed to \n138 temporally characterise the forest health concept to provide a holistic definition. Finally, we \n139 discuss the gaps and future potential conceptual subdomains and descriptors that seem to arise \n140 in the research field.\n141 2. Material and methods\n142 The workflow carried out for the analysis included (Fig 1): data collection, scientometric and \n143 bibliometric analysis and visualization (all of these are detailed below). Specifically, to generate \n144 the results of the first objective we performed a descriptive analysis of scientific production, a \n145 bibliometric analysis of maps in terms of co-occurrence of keywords, and an analysis of \n146 publications and contributions. To achieve the second objective, we provided a time trend \n147 analysis of recurrent terms. And for the third objective we performed a temporal trend analysis \n148 on a semantic clustering of the keywords (obtained from the previous objectives) in the three \n149 forest health domains established in this study: forest condition, drivers and methods.\n150 Figure 1. Graphical summary of the bibliographic and bibliometric review workflow for the study of forest \n151 health concepts evolution.\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n7\n152 2.1. Scientific Data Base Search\n153 The Web of Science (WoS) and Scopus database was chosen as high-impact search engines for \n154 formal scientific publications, excluding non-conventional literature (grey literature). In January \n155 2024, we carried out a preliminary search with a single keyword linear strategy using “forest \n156 health” in Title, Abstract and Keywords fields, for all recording times in the database. The \n157 temporality of the search was not limited, as the aim was to know completely all the existing \n158 records in the databases from their origin to the present. The search was refined to include only \n159 disciplines related to biological, environmental, forestry, earth sciences or methodological \n160 sciences, excluding humanities or medical sciences. \n161 Titles and abstracts of the 100 most relevant articles from each year were read and reviewed \n162 for the state of the art of forest health research and scientific production. Potential articles that \n163 could contain definitions or different terminology of forest health were read in detail (i.e. \n164 reviews and highly cited papers). From this preliminary review, a list of conceptual subdomains \n165 for the umbrella term forest health was compiled and used in the final database query. \n166 The following search strategy was used to obtain the corpus: Title / Abstract / Keyword = [\"forest \n167 health\" OR \"forest mortality\" OR \"tree mortality\" OR \"forest integrity\" OR \"forest state\" OR \n168 \"forest decline\" OR \"forest decay\" OR \"forest dieback\"]\n169 2.2. Descriptive analysis of the status of forest health research\n170 The records obtained from the final query were analysed using the quantitative bibliometric \n171 analysis algorithms of the R package Bibliometrix and the associated application Biblioshiny (26). \n172 First, we conduct a descriptive analysis that characterises the scientific production over time, \n173 main contributing authors, the co-authorship network, country publication impact, \n174 geographically contextualising the main journals and funding agencies. Secondly, Sankey \n175 diagrams were used to focus the analysis on keywords to identify patterns and trends in the \n176 main terms used to describe forest health research in the above context (30).\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n8\n177 2.3. Temporal evolution in forest health issues\n178 An analysis of relevance and development in research topics based on the initial systematic \n179 review separated the selected keywords into four main groups: a) “motor themes”, that is, \n180 themes well developed and important for the structure of the research field, b) “emerging or \n181 declining topics” when they are both weakly developed and marginal, c) “basic and transversal \n182 topics” which are important for a research field but are not developed and d) “niche with a \n183 specialized character”, which are peripheral and specific topics for the research field.\n184 Temporal changes in the concept and application of forest health were assessed by an automatic \n185 keyword network analysis using WOSviewer (29), based on the previous review and debugging \n186 of retrieved words. We used co-occurrences of keywords that appeared together in the title, \n187 abstract or keyword list, and that were mentioned at least 10 times, giving a total of 1,731 \n188 keywords. We then plotted the top 1,000 keywords in a network and recurrence map. Finally, \n189 this network was overlaid with the year of publication to identify temporal trends in keyword \n190 association. \n191 2.4. Clustering of conceptual sub-domains and temporal trends\n192 We also implemented an approach considering a manual semantic keyword clustering to \n193 understand temporal trends across the three domains of forest health considered in this study \n194 (e.g., condition, drivers and methods) and main topics or definitions of forest health. From the \n195 bibliographic search and subsequent download of references, for each year, the 50 most \n196 relevant author and recommended keywords were extracted (keyword PLUS - index of terms \n197 automatically generated from the titles of cited articles). This set of keywords went through a \n198 process of cleaning up duplicates, normalising or removing special characters, reviewing \n199 compound words and reducing some words to their basic roots. From this list of keywords for \n200 all years, duplicated words were removed and grouped semantically. These terms were \n201 classified into descriptors of topic (theme or discipline in forest health concept), condition (i.e., \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n9\n202 variables used to measure forest state or condition), drivers (abiotic or biotic agents causing \n203 changes in the forest condition) and methodologies (techniques used to assess forest health). \n204 Within each descriptor type, we grouped the terms according to similar semantic meaning \n205 (Table S1 Supplementary Material). In addition, when reviewing the list, other words were \n206 proposed for being particularly relevant for the analysis based on the preliminary review \n207 indicated in section 2.1. For each term, we compiled their occurrence in the abstracts of each of \n208 the scientific records retrieved and calculated their frequency per year. All analysis were carried \n209 out with R version 4.3.2. (31).\n210 3. Results\n211 3.1. Descriptive analysis of scientific production in forest health research\n212 3.1.1 General findings\n213 Scientific evidence in forest health from 1934 to 12/2023 shows an exponential publication \n214 trend (as in most scientific disciplines), with an annual growth of 7.8%, although there was a \n215 decline during the COVID-19 pandemic (Fig S1; Table S2 Supplementary Material). We analysed \n216 10,338 papers from 1,511 sources, with 26,025 authors, highlighting that the 20 most prolific \n217 authors account for 9.37% of the publications, indicating that forest health research is highly \n218 diversified in terms of researchers involved in this topic. The top 4 authors stand out, with more \n219 than 60 publications each (Fig S2 Supplementary Material). The leader in publications, Camarero \n220 J.J., uses growth ring analysis and remote sensing to study the interaction between forests and \n221 their environment, underlining the importance of longitudinal studies for conservation policies. \n222 The first recorded publication was by Veblen T.T. in 1983, focusing on forest instability and tree \n223 mortality using dendrochronology. The most cited authors are Allen D.C. and Breshears D.D. in \n224 2010, for investigating global forest decline and drought.\n225 3.1.2. Publication impact countries\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n10\n226 Considering the 10 countries with the highest publication record on forest health, USA marks a \n227 significant difference with the rest of the world throughout the whole period studied (Fig S3 \n228 Supplementary Materials). Next, Germany was the country with the longest track record in \n229 related research. Canada increased its relevance in last decades, overtaking Germany in 2007, \n230 and reaching the second position. Since 2010, China obtained an exponential increase in the \n231 number of publications, reaching currently the third top position. \n232 In terms of cross-country collaborations, 5 clusters were observed. A first cluster (Fig S5 \n233 Supplementary Materials) related by spatial continuity and ecological similarities, including \n234 countries in North America (USA, Canada, or even Mexico); they in turn also related to other \n235 countries by their latitude (Russia), or by the problems raised and methodological challenges to \n236 cover large countries (such as China or Australia). A clear cluster was observed where South \n237 American countries seem to be very closely aligned and related to the United Kingdom, the \n238 Netherlands and Japan. The last distinct cluster related Eastern and Northern European \n239 countries to New Zealand. \n240 Despite the bibliometric reflection, the literature review shows that the geographic origin of \n241 affiliation of the main authors of the publications does not determine the area of study in the \n242 research. Collaborative research and international co-authorship favours diversification of the \n243 study regions addressed beyond their own borders. Origin of funding agencies was largely \n244 consistent with the most productive countries (Fig S6 Supplementary Materials). \n245 3.1.3. Research approaches and issues\n246 The search returned 13,677 keywords proposed by authors and 10,399 KeyWords Plus. The \n247 Sankey diagram (Fig 2) shows boxes of different sizes and colour intensities allowing to identify \n248 the areas of greatest activity and connection, among the 10 most common keywords (themes), \n249 the 10 countries with the highest scientific output and the top 10 thematic journals (Fig S7 \n250 Supplementary Materials).\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n11\n251 The results highlight that the top countries publish most frequently in journals related to forest \n252 management and also ecology. There are variations in keyword priority between countries, with \n253 a general focus on climate change, although Spain and Australia also highlight drought.\n254 Fig 2. Sankey diagram showing the relationships between frequent journals (left) from the top 10 \n255 publishing countries (middle) and the top 10 most mentioned keywords (right) in forest health-related \n256 research.\n257 Co-occurrence analysis showed the 50 most frequently mentioned keywords (Fig S9, supplementary \n258 material), revealing \"mortality\" as the most common term, linked to climate change and drought, and \n259 associated with forest vulnerability, climate responses, forest health and growth. Clusters were identified \n260 focusing on forest decline due to stress, nitrogen deposition and soil problems, specifically related to pine \n261 and spruce. Another cluster emphasises forest management dynamics, impacts and biodiversity. A final \n262 cluster addresses the effects of fire and pests on specific species and sites.\n263 3.2. Temporal keyword analysis\n264 We grouped the keywords on the x-axis showing the relevance of the topics and on the y-axis the degree \n265 of research development (Fig 3). We found that the core group of most relevant topics contains research \n266 related to ‘climate change’, ‘tree mortality’, ‘drought’ and ‘fire’.  Another group of core themes, although \n267 less detailed (compared to the previous one), are ‘forest health’, ‘remote sensing’, ‘dendrochronology’, \n268 ‘bark beetle’ and ‘biodiversity’. Of the relevant core themes with the highest level of development, the \n269 keyword ‘disturbance’ is the most developed, followed by ‘forest management’, ‘wildfire’, ‘prescribed \n270 fire’ and ‘Pinus ponderosa’. The results show that in general, the most developed topics with a high level \n271 of specialisation are those related to the physiological processes of the forest, containing keywords such \n272 as: ‘water stress’, ‘hydraulic failure’, ‘photosynthesis’, ‘carbon starvation’. Finally, in the group of \n273 underdeveloped or unused keywords was ‘forest decline’ when talking about more concrete process \n274 words, as well as ‘atmospheric pollution’ and ‘ozone’, issues that were relevant but already little studied.\n275 Fig 3. Word grouping map by themes of relevance and development in research on forest health: a) \n276 “motor themes”, well developed and important for the structure of the research field, b) “emerging or \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n12\n277 declining topics” weakly developed and marginal, c) “basic and transversal topics” important but not \n278 developed and d) “niche with a specialized character”, peripheral and specific topics for the research field.\n279 The temporal network analysis of the top 1000 keywords showed a total of four clusters over \n280 the study period (1934-12/2023) (Fig 4). Although the entire period analysed was included in \n281 the graphical representation, due to the low number of publications recorded before the mid-\n282 1980s in the databases consulted, the first cluster (purple colour) appears from this initial stage \n283 of scientific production. It was closely linked to the concept of “forest decline”, especially in \n284 topics related to “air pollution” (“nitrogen”,  “ozone” or “acidification”). Around late 1990s and \n285 early 2000s, the diagram showed a second broad cluster (in blue-green) highly associated with \n286 the term \"growth\" and \"forest health\". These terms were mostly related to monitoring and \n287 development-related terms (e.g. “stands”, “competence”, “deforestation”, or issues related to \n288 “biomass” and “carbon sequestration”). Approximately in 2010, a new cluster (in green) appears \n289 with quite wide range of terms of similar importance but related to ecosystem processes and \n290 characteristics: (e.g. \"biodiversity\", \"dynamics\", \"disturbance\", \"management, \"conservation\", \n291 “restoration” and topics associated with “fire ecology”). This cluster seem to converge into the \n292 concept of \"tree mortality\", peaking around 2015. Finally, in the most recent period (in yellow), \n293 the research activity focused on “climate-change”, showing a great interest in the variables \n294 measured and the tools related to “ecophysiology” and “remote sensing”. \n295 Fig 4. Temporally normalised co-occurrence of most frequent keywords related to forest health research \n296 (VOSviewer graph). \n297 3.3. Clustering and trends in forest health descriptors\n298 Manual classification of keywords in forest health reveals four sets of issues clustered into the \n299 four established categories: topic, condition, drivers and methodologies (Fig 5), with fluctuations \n300 in the 1970s to mid-1980s due to low production and thematic dispersion (removed from the \n301 graphical representation), stabilising since the 1990s. Interest in \"forest decline\" has declined, \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n13\n302 being replaced by \"tree mortality\", and \"forest health\" had a peak around 2005, followed by a \n303 recent decline in the last decade. The attributes measured to characterise forest condition \n304 reflect evolving environmental concerns, from \"pests and diseases\" and \"air pollution\" to a \n305 growing interest in \"climate\" and \"fire\", which have become a constant concern. \n306 Methodologically, understanding the functionality of organisms based on \"ecophysiology\" has \n307 declined in relevance, while tools such as \"inventories\" remain constant. Since the 1990s, the \n308 use of \"Geographic Information Systems\" and \"remote sensing\" has grown significantly, just as \n309 modelling-based methodologies have increased in importance in recent years, although to a \n310 lesser extent than the former.\n311 Fig 5: Proportion of occurrence of keywords per year considering four different aspects of forest health: \n312 5a) topic (theme or discipline in forest health concept), 5b) condition (variables used to measure forest \n313 state or condition), 5c) drivers (abiotic or biotic agents causing changes in the forest condition) and 5d) \n314 methodologies (techniques used to assess forest health).\n315 4. Discussion\n316 Over the last 90 years, we have seen a remarkable increase in the publication of research on \n317 forest health, which underlines the need for an assessment of its evolution. The study \n318 synthetically contextualised the accumulated body of knowledge, identifying substantial \n319 changes in the ways in which forest research is approached, studied, measured and the \n320 technologies associated with it. The results obtained showed aspects related to how science has \n321 been done so far, detecting new emerging concepts or trends. Particularly noticeable are the \n322 changes in scientific production, together with variations in the concepts and methods \n323 employed by the forest health research community, reflecting how these aspects have been \n324 linked to the main environmental concerns of each period, to funding or to the geographical \n325 area of influence of the researchers.\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n14\n326 Following this bibliographic and bibliometric review, we aim to further explore the rationale for \n327 temporal trends, highlighting their importance and implications at each point in time. The study \n328 allows us to identify both significant advances and gaps in knowledge, contributing to the \n329 configuration of new lines of research that respond to emerging challenges in forest health.\n330 4.1 Scientific production on forest health\n331 As with many other concepts in various disciplines (32,33), research on \"forest health\" is \n332 experiencing exponential growth in terms of the number of articles published. Leaving aside the \n333 general trend in academic production, the exponential growth observed denotes that the \n334 concept under study remains dynamic and continues to be of interest to researchers. This \n335 vigorous increase in the production of scientific literature reflects not only the growing global \n336 concern for the state of our forests but also the recognition of the complexity and \n337 multidimensionality that characterises them (34). As such, there remains a need for a collective \n338 effort to understand and mitigate the impacts of threats such as climate change, tree diseases \n339 and deforestation (35,36). \n340 The affiliation origin of the researchers revealed important information on how the knowledge \n341 is created regarding the topics about forest health. Our findings show that USA, Canada, and \n342 Germany are the countries of affiliation origin for most of the researchers working in the target \n343 topic. These results unveil two important biases:\n344  First, there is a mismatch between the most publishing countries and those which harbour a \n345 higher percentage of forests worldwide. According to the latest Food and Agriculture \n346 Organisation (FAO) report on global forest resources (37), more than half of the world's forests \n347 are concentrated in 5 countries: Russia (815M ha - 20%), Brazil (497M ha - 12%), Canada (347M \n348 ha - 9%), USA (310M ha - 8%) and China (220M ha - 5%). Only Canada and the USA are among \n349 the countries with large areas of forest with substantially more forest health articles compared \n350 to the others. \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n15\n351 Second, there are not countries located in the tropics in the list of the higher publishing records. \n352 This situation is more remarkable if we consider that the largest percentage of forest (45%) is in \n353 tropical areas. This uneven distribution of publications between the Global North and the Global \n354 South has been described in other disciplines such as ecology (38): most of the research is done \n355 in the Global North although both the biodiversity and the forests are mainly in the Global South. \n356 This geopolitical situation impacts very deeply in the completeness of the “forest health” \n357 concept since it does not consider the views of researchers from the countries with more forest \n358 cover.\n359 4.2 Evolution of the most relevant keywords on forest health research \n360 4.2.1. Integrating Keywords: Uncovering patterns\n361 The total number of keywords found in “Climate change”, “tree mortality” and “drought” were \n362 the topmost common keywords mentioned in forest health related research (Fig 3 and S9 \n363 Supplementary Materials). In fact, a large set of forest health studies have built on the delicate \n364 situation of forest ecosystems worldwide with large-scale mortality processes driven by climate \n365 drivers (9,39). Interestingly, the relevance and development analysis considered these terms as \n366 \"Basic Theme\" showing a high relevance and a medium degree of development, which indicates \n367 their current popularity but also further room for development compared to themes such as \n368 disturbance or wildfire.\n369 In this \"Basic Theme\" group, the analysis also highlighted terms such as \"remote sensing\", \n370 \"defoliation\", \"dendrochronology\" and \"biodiversity\", revealing a multidisciplinary and multi-\n371 scale approach to capture the complexity and dynamism of forest ecosystems. This approach \n372 demonstrates a broad perspective on integrated, multi-scale forms of forest measurement: such \n373 as defoliation as a measure of forest response at the leaf level, dendrochronology as a measure \n374 of growth rate at the tree level, the use of remote sensing allowing extensive monitoring of \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n16\n375 forests at the landscape level, or biodiversity as a manifestation of forest structure and \n376 functioning at the community level (40–42).\n377 Among the “Niche Themes” (high density and low relevance), we identified three main groups \n378 that seem rather peripherical or with regional interest to the research field. From the initial \n379 reading and bibliographic review, we found that the research field of invasive species and beetle \n380 outbreaks mostly concentrated in North America on conifer forests (43–45) and on the other \n381 side pure ecophysiological studies (46). The former group reinforces the idea of the bias toward \n382 the Global North: P. ponderosa is a heavily timbered species typically found in temperate areas \n383 of North America (47). Besides, concerns about bark beetles and prescribed fire are a \n384 management activity also frequently used in temperate areas of the Northern Hemisphere (48). \n385 Regarding the “Emerging or Declining Themes” with low development and relevance, it is \n386 remarkable how the clustering process identifies forest decline, pollution and ozone as themes \n387 that are no longer mainstream regarding forest health. These topics refer mainly to the events \n388 of acid rain that were relatively common in Europe and North America during the second half of \n389 20th Century and even nowadays in China (49). \n390 4.2.2. Origins and context of paradigm shifts\n391 The temporal change in the proportion of keywords tells a history very useful to understand the \n392 research topic of “forest health”. The analysis of the temporal evolution of keyword clusters \n393 reveals two main patterns (Fig. 4): a) there is a consistent trend towards a higher level of \n394 knowledge integration across the time series and b) there is a clear link between the evolution \n395 of global research and environmental challenges at each point in time and the changes in forest \n396 health research. Based on this analysis, we identify four different temporal clusters that have \n397 occurred sequentially (Fig.6):\n398 Fig 6: Historical and thematic analysis of nearly a century of advances in forest health research, illustrating \n399 key international environmental and socio-political milestones (to the right of the figure) that align with \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n17\n400 shifts in prevailing themes and scientific terminology (evidenced by the word clouds to the left of the \n401 figure).\n402 I)  The arise of global environmental problems linked to atmospheric pollution. At the \n403 beginning of the time series, we found monocausal approaches to forest health \n404 disturbances, where the most important drivers were “pests and diseases” as well \n405 as “air pollution”. This earliest cluster contains concepts, which are attributable to \n406 well defined scientific disciplines: “nutrients”, “forest soils”, “fertilization”, “ozone”, \n407 “seedlings”, “calcium”, etc. This pattern indicates the low level of discipline \n408 integration that the target concept experienced prior to 1990. Furthermore, it \n409 shows clear links with the first modern environmental movements worldwide took \n410 place between the 1960s and 1970s, focusing on nature conservation and \n411 environmental protection. Predecessor events are the book \"Silent Spring\" by \n412 Rachel Carson (1962), which denounced the harmful effects on the environment of \n413 the massive use of chemicals such as pesticides. The first \"Earth Day\" (1970), the \n414 United Nations Conference on the Human Environment in Stockholm (1972), and \n415 the \"Energy Crisis of 1973\" awakened awareness of the dependence on oil and the \n416 search for alternative sources. A central forest health topic in this cluster is “forest \n417 decline” with strong links to acid deposition, air pollutants, and ozone. In fact, \n418 “forest decline” was a terminology commonly used to depict the research concern \n419 about forest deterioration due to air pollution mostly in Northern Europe and North \n420 America (51). This forest problem gained international relevance in the 1980s with \n421 “The Geneva Convention on Long-Range Transboundary Air Pollution” (1979), “The \n422 Vienna Convention for the Protection of the Ozone Layer” (1985) or the signing of \n423 “The Montreal Protocol on Substances that Deplete the Ozone Layer” (1987). This \n424 environmental problem kept research strongly active until the end of the 20th \n425 century. It is from the 1990s onwards that the evidence on the effects of pollution \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n18\n426 began to be related to human health and ecosystems, and although the global \n427 burden of pollutants has been increasing in the first two decades of the 21st century, \n428 efforts are being made to continue reducing them (49). \n429 II) Global environmental conservation. The second cluster is dominated by the decline \n430 and physiology of the forest, appearing in late 1990s and early 2000s. Thus, the \n431 methodologies mainly used are related to ecophysiology and forest inventories. This \n432 period shows concepts with a higher level of integration among disciplines and \n433 knowledge bodies: “growth”, “competition”, “forest health”, “ecosystems”, \n434 “carbon sequestration”, etc. It also reflects the arise of current environmental \n435 problems such as carbon emissions and deforestation. This may be mainly due to \n436 the events that took place during the 1990s, where concerns with a more holistic \n437 and multidisciplinary view of nature conservation and the environment began to \n438 broaden. At this time, among others, the most famous world summits took place: \n439 “The United Nations Conference on Environment and Development” or better \n440 known as “The Rio de Janeiro Summit\" (1992), laid the first foundations for the \n441 signing of the United Nations Framework Convention on Climate Change and the \n442 signing of the treaty “The Convention on Biological Diversity”, being the first global \n443 agreement to promote aspects of international cooperation in the conservation and \n444 sustainable use of biodiversity. The famous “Kyoto Protocol” (1997) on the \n445 reduction of greenhouse gases that cause climate change is also approved in this \n446 period. Almost simultaneously, the FAO publishes a report that highlights the \n447 deforestation of large tracts of tropical forests in Latin America, Africa and Asia (52). \n448 At the same time, the achievements of the international policy on air pollutants \n449 reduced to some extent the pressure of air pollution on forest ecosystems (53) and \n450 consequently in the forest health research field. In summary, this temporal cluster \n451 represents the initial foundations for a more holistic and larger-scale view of the \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n19\n452 planet’s global problems, evidenced among the key words in scientific publications \n453 of the time, leading to the use of more multidisciplinary, integrative and \n454 comprehensive concepts.\n455 III) Multi-causality  and tree mortality. The research that begins with the 21 st century \n456 shows a multi-causal thinking in the problems that occur in the deterioration of \n457 forests and the environment. This group shows a wide range of concepts, where the \n458 words that stand out the most are “patterns”, “dynamics” and “disturbances”. Now \n459 the forest problems are based on multi-causality, a more complex vision that can be \n460 studied not only at the tree level but at different scales and in a multidisciplinary \n461 way. The characterization of ecosystem dynamics is based on classification, offering \n462 scales, intensities or patterns that measure diversity, fragmentation, deforestation, \n463 succession, competition, susceptibility, regeneration, among other processes (54–\n464 56). Furthermore, other concepts such as “management” and “restoration” also \n465 emerge as a key concept suggesting a more applied vision in the forest health \n466 research agenda (57). \n467 At the end of this period, the research agenda converge on the topic of “tree \n468 mortality” with numerous links to a wide range of concepts. Other highly integrative \n469 concepts also appear (e.g. restoration, resilience) reinforcing the paradigm of multi-\n470 causality in forest health research (58,59). “Wildfires”, its consequences, and some \n471 methods used to monitor them, are present here to explicit the environmental \n472 issues addressed in that time. It is no longer enough to quantify the causes of \n473 disturbances in the system, but rather the effects of the disturbances themselves, \n474 in search of solutions and to assess both the damage and the improvement in the \n475 global balance.\n476 IV) Climate change driven-research. The most recent cluster contains mainly concepts \n477 related to “climate change” (e.g. “vulnerability”, “adaptation”, “change impacts”, \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n20\n478 etc.). Interestingly, this cluster seems to reduce the degree of knowledge integration \n479 as scientists are focusing mostly on understanding the consequences of climate \n480 change on forests; although this challenge is much more complex than those \n481 described previously. This is evidence of the greater environmental awareness, both \n482 social and political, in the mitigation of climate change. One example is the approval \n483 of the \"The Paris Agreement\" (2016), which establishes a global framework on \n484 climate change focused on concrete aspects such as curbing global warming and \n485 achieving carbon neutrality before the end of the century, where the use of the best \n486 available science and technology are directly included to improve the conditions of \n487 the planet. In fact, “climate change” can be considered a so called wicked problem \n488 (60): multifaceted problems with fuzzy definition, elusive and complex solutions. \n489 This explains why the current distribution of words within the drivers becomes more \n490 equative. It is also the boom in technological development that derives part of these \n491 efforts in generating instruments, methods and measurement and evaluation \n492 techniques that are increasingly more accurate, reliable, and accessible. The \n493 emergence of portable electronic equipment or geospatial technologies like remote \n494 sensing, were a breakthrough to obtain continuously and efficiently data across \n495 different spatio-temporal scales. This idea is supported by the presence within this \n496 cluster of methods of assessment (e.g. carbon-isotope, dendroecology) and a great \n497 amount of forest condition variables (e.g. evapotranspiration, water-use efficiency, \n498 stomatal conductivity, hydraulic failure, etc.) currently measured with sophisticated \n499 ecophysiological sensors (e.g. “gas-exchange” related to Eddy covariance towers or \n500 photosynthesis sensors).\n501 4.3 Trends topics, concepts and methodologies on forest health research\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n21\n502 We also found similar temporal patterns from the temporal analysis of the four different \n503 descriptors (topic, condition, drivers, and methodologies; Fig 5). First, we have identified a \n504 temporal trend towards higher complexity. In the case of drivers, there is a clear trend from \n505 monocausal to multicausal drivers of interest. From the predominance of “air pollution” and \n506 “pest and diseases” during the first decades, to the emergence of other concepts: \n507 “competition”, “land use”, “management”, and “fire”, which ultimately end in steep increase of \n508 climate related drivers related to the “climate change” paradigm (Fig 5C). This could mean that \n509 the drivers of change in the “forest health” research domain are more complex now than they \n510 used to be decades ago. A similar pattern can be found in the group of “topics” words (Fig 5A). \n511 The predominance of forest decline leads to a richer scenario where tree mortality, forest health \n512 and still forest decline have certain importance. Regarding the condition words, the last decades \n513 show also the rise of terms that imply a richer and more integrative approach: community, \n514 mortality, growth, etc (Fig 5B). They coexist in a scenario more equitable than the existing at the \n515 beginning of the time series. \n516 On a second note, methods have followed the divergence and increased in complexity of the \n517 other forest health aspects (Fig 5D). Finding appropriate methods to measure forest condition \n518 has been always a major challenge in forest health research. Different types of methodologies \n519 and techniques to assess forest status have been continuously evolving. Historically and up to \n520 the present day, classical inventories have been an objective measure of forest species \n521 composition, quantity and distribution of trees, as well as tree quality based on simple structural \n522 measures (61,62). These inventories have become more complex as measurement tools have \n523 evolved, although in general they are techniques that require little instrumentation, they are \n524 limited in the amount of land that a team of people can cover. In this sense, important forest \n525 monitoring programmes emerged in the 1980s. \n526 Some of these programmes are the International Co-operative Programme on Assessment and \n527 Monitoring of Air Pollution Effects on Forests (ICP Forests) of the United Nations Economic \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n22\n528 Commission for Europe (UNECE), since 1985 (63); or the Forest Health Monitoring (FHM) of the \n529 United States, which began in 1990 (64). Many of these inventories were accompanied by \n530 physiological measurements of the plants as reliable methods of direct observation to monitor \n531 the \"vital signs\" of the plants (65,66). Figure 4 (D panel) shows this first stage with the \n532 predominance of ecophysiology methods, in which definitions of physiological factors and \n533 vegetation damage, pollution prevalence, pests and nutrients appear as drivers of forestry \n534 research in the literature (67,68). \n535 On the other hand, the spatio-temporal perspective of forest health is currently under \n536 development, constantly incorporating new methodologies mainly focused on the “massive \n537 data approaches” at spatial level. These massive data monitoring tools does not only refer to \n538 the use of remote sensors for landscape scale assessment, but also other methodologies \n539 developed in the last decades in field of ecophysiology and the molecular biochemistry, such as \n540 the assessment of gas fluxes at ecosystem level (Eddy co-variance towers), the use of high \n541 throughput molecular techniques for microbial communities evaluation or genomic approaches \n542 at individual and community levels (e.g., soil proteome, biogechemical cycling, etc…) (69,70). \n543 Forest modelling, GIS and remote sensing are needed to manage efficiently and in a sustainable \n544 way forest resources (71). These methods allow us to explore the spatial dimension of forest \n545 health. In turn, forest modelling allows us to explore the temporal dimension of forest health \n546 via long-term and short-term forecasting processes. All these modeling methods have \n547 particularly increased in the last two decades becoming especially useful to improve forest \n548 management in areas with scarce economic resources. \n549 4.4. The way forward: future vision for the forest health concept\n550 In this section we envision how forest health research might evolve in the coming years based \n551 on similar disciplines and the gaps found. First, we did not find any article combining the idea of \n552 forest health with the concept of “essential biodiversity variable” (EBV) (72). This is one of the \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n23\n553 most prolific frameworks in the last decade for ecosystem monitoring, but it has not been found \n554 among the relevant keywords of our analysis. We believe that the research field of forest health \n555 would be very benefited from embracing the EBV framework, especially when considering the \n556 description of forest condition. Using EBVs to describe forest health can be useful to increase \n557 the comparability of studies carried out in different places. \n558 Similarly, the term “ecosystem services” is also missing in the forest health literature. This \n559 concept was introduced in the scientific literature several decades ago (73,74), but it seems to \n560 have gone unnoticed in the “forest health” research field (75). We believe that the link between \n561 “healthy forests” and their capability to provide ecosystem services might emerge as a new and \n562 interesting field of research. While EBVs can help to homogenize the ways of assessing forest \n563 health, ecosystem services can contribute to standardizing how we quantify the outcomes \n564 provided by forests.\n565 Finally, to integrate the current meaning of the target concept and to transcend it using the \n566 above-mentioned proposals, we envision a conceptual and operational alignment between the \n567 concepts of “forest health” and “one health” (76). The concept of one health has reached a very \n568 holistic meaning in the present time. It used to be focused on single aspects of the health: pain, \n569 infection, symptoms, etc. The current meaning put the focus on the concept of health far beyond \n570 the absence of illness. One health aims to put together human, animal, and environmental \n571 health. This holistic view is slowly moving from the academia into practice (77). This process \n572 requires to increase our efforts in transdisciplinary collaboration (78). \n573 Despite the large number of scientific articles related to forest health, the initial literature review \n574 found that although they use the term, few authors dare to give a clear and comprehensive \n575 approach in their manuscripts. After what we have learned, we recognise that this is a qualitative \n576 concept that encompasses the overall state of a complex system studied from various \n577 disciplines. According to this holistic approach, we might agree in defining forest health as the \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n24\n578 capacity of a forest to sustainably provide a wide range of ecosystem services while maintaining \n579 biodiversity, natural rhythms and resilience to disturbances inherent in forest dynamics (79–82). \n580 Therefore, whether a forest is healthy or not will depend on its natural functioning, buffering \n581 capacity and resilience, for which integrated monitoring and management with a vision of \n582 conservation of the vital constants and functions of the system is essential. As forest ecosystems \n583 are complex systems, assessing and understanding the totality of their functioning is a constant \n584 challenge. This means that research on forest health continues to change according to the \n585 knowledge needs and concerns observed in forests by scientists and experts, according to \n586 available techniques and technologies, policies and social concerns, and the availability of \n587 resources, mainly.\n588 5. Conclusions\n589 Forest health research has experienced exponential growth in the number of authors and \n590 publications, reflecting its relevance and dynamism within the scientific community. We have \n591 found a geographical bias in knowledge creation and research focus, as it does not align with \n592 the countries that host the largest percentage of the world's forests (such as tropical countries). \n593 This disparity between the Global North and the Global South raises concerns about the integrity \n594 and inclusiveness of this field of study.\n595 Concepts and research in forest health demonstrate an evolution towards integration of \n596 knowledge over time, and global environmental challenges.  Keyword analysis revealed a \n597 thematic paradigm shift from the effect of air pollution to current interests in climate change \n598 impacts, tree mortality and drought, increasingly integrated with remote sensing technologies \n599 and specialised topics such as invasive species and ecophysiology. \n600 The temporal analysis of clustering by descriptors reveals a transition towards complexity and \n601 multidisciplinary approaches, showing an evolution from mono- to multi-causal factors. This \n602 reflects an effort to understand interactions in complex systems. The integration of advanced \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n25\n603 methodologies, including remote sensing, forest modelling and big data analysis, has \n604 significantly improved the capacity for forest monitoring and management.\n605 Finally, we envisage a conceptual and operational alignment between the concepts of \"forest \n606 health\" and \"one health\". The holistic “one health” perspective, which integrates human, \n607 animal, and environmental health, can provide a comprehensive approach to forest health. \n608 Transdisciplinary efforts and collaboration are needed to bridge the gap between academia and \n609 practical implementation.\n610 Funding: \n611 This research was funded by:\n612 - Project DesFutur funded by Fundación Biodiversidad del Ministerio para la Transición Ecológica \n613 y el Reto Demográfico (MITECO) and European Union (“NextGenerationEU”/PRTR).\n614 - Grant RYC2021-033138-I, funded by MCIN/AEI/10.13039/501100011033 and European Union \n615 (“NextGenerationEU”/PRTR).\n616 - Project Evidence (ref 2822/2021) funded by Red de Parques Nacionales (OAPN y MITECO).\n617 Contributions: \n618 CAM: Conceptualization, Methodology, Investigation, Formal analysis, Data Curation, Writing - \n619 Original Draft, Writing - Review & Editing, Figures 1,2,3,4,6 and Supplementary Material, \n620 Supervision; RMNC: Conceptualization, Writing - Review & Editing; FJBG: Conceptualization, \n621 Resources, Writing - Original Draft, Writing - Review & Editing; FJRG: Writing & Review; PGM: \n622 Conceptualization, Methodology, Investigation, Formal analysis, Writing - Original Draft, Writing \n623 - Review & Editing, Figure 5, Supervision.\n624 Acknowledgments: \n625 Thanking Pablo Salazar-Zarzosa for his detailed reading and constructive comments for \n626 improvement.\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n26\n627 Conflict of Interest: \n628 The authors declare that they have no conflict of interest.\n629 Declaration of competing interest: \n630 The authors declare that they have no known competing financial interests or personal \n631 relationships that could have appeared to influence the work reported in this paper.\n632 Supplementary Materials: \n633 Table S1: Clustering of the main keywords of the publications search results for forest health, \n634 Fig S1: Evolution of the annual scientific production related to Forest Health, Table S2:  Main \n635 information of the results of the bibliographic search in Web of Science related to Forest Health \n636 (Bibliometrix R information), Fig S2: The most relevant 20 authors with the highest number of \n637 publications and their evolution of the scientific production evolution, Fig S3: Spatial distribution \n638 of the number of publications in different countries on forest health 1934-12/2023 (Graph R \n639 from Bibliometrix), Table S3: Scientific production related to forest health 1934-12/2023 by \n640 continent, Fig S4: Spatial distribution of the number of publications in different countries on \n641 forest health 1934-12/2023 (Graph R from Bibliometrix), Fig S5: Evolution of scientific \n642 production related to forest health in the 5 main countries (Graph R from Bibliometrix), Fig S6: \n643 Thematic categories of the journals to forest health 1934-12/2023 (WoS graph), Fig S7: Most \n644 relevant funding agencies in forest health studies by number of works supported (WoS), Fig S8: \n645 Co-occurrence network to 50 most mentioned keywords in the scientific literature (1934-\n646 12/2023) (WoSviewer).\n647 Data availability: \n648 The data used to generate the analysis in this article are fully reproducible. They were extracted \n649 from the Web of Science database through the query and time period indicated in the \n650 methodology.\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n27\n651 6. References\n652 1. Camarero JJ. The drought‒dieback‒death conundrum in trees and forests. Plant Ecol \n653 Divers. 2021;14(1–2):1–12. doi: 10.1080/17550874.2021.1961172.\n654 2. Deuffic P, Garms M, He J, Brahic E, Yang H, Mayer M. Forest Dieback, a Tangible Proof of \n655 Climate Change? A Cross-Comparison of Forest Stakeholders’ Perceptions and Strategies \n656 in the Mountain Forests of Europe and China. Environ Manage. 2020;66(5):858–72. doi: \n657 10.1007/s00267-020-01363-9.\n658 3. Bailin A. 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It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted June 5, 2024. ; https://doi.org/10.1101/2024.06.03.597256doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}