Forest structural changes after tree dieback affect dung beetle communities and dung removal rates

Forest structural changes after tree dieback affect dung beetle communities and dung removal rates | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Forest structural changes after tree dieback affect dung beetle communities and dung removal rates Julian Lunow, Katja Wehner, Matteo Trevisan, Michael Heethoff, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6878459/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Forest ecosystems are currently experiencing the consequences of climate change, particularly increasing tree damage and mortality due to higher temperatures and longer droughts. This leads to changes in forest structure, with consequences for the abundance, diversity, and composition of organisms, as well as their provision of ecosystem functions. However, relatively little is known about how dung beetles, which are important for decomposition, respond to recent changes in forest characteristics and tree dieback. We monitored dung beetles and dung decomposition in 67 forest plots in Darmstadt, Germany. The structure of these plots varied considerably due to tree mortality caused by several years of drought and heatwaves, as well as former forest management practices in the study region. The total biomass, diversity, and species composition of dung beetles were strongly related to changes in forest structure, such as mean canopy openness, mean diameter at breast height, and forest ground cover. However, they were less related to within-plot structural heterogeneity. Higher dung beetle biomass was related to a higher dung decomposition rate, but changes in dung beetle diversity and community composition did not correlate with dung decomposition. Our results suggest that changes in forest structure result in changes in the biomass, diversity, and composition of dung beetle communities. The relationships between dung beetles and structural heterogeneity were not particularly pronounced. This indicates that the effects of tree mortality on dung beetles and subsequent changes in dung decomposition are mediated by directed shifts in mean forest structure rather than structural heterogeneity. dung decomposition forest heterogeneity forest structure Geotrupidae Scarabaeidae Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Forests cover a significant proportion of Europe's land area, and the proportion of forests designated primarily for biodiversity conservation is increasing (FAO, 2020 ). This is promising for biodiversity and ecosystem functioning in forest ecosystems. However, forests are currently experiencing the effects of heat waves and drought (Allen et al., 2010 ; Senf et al., 2020 ). Severe weather events, which are caused by human-induced climate change, pose physiological challenges for trees and can result in tree dieback (Albrich et al., 2020 ; Menezes-Silva et al., 2019 ; Schuldt et al., 2020 ). Consequently, forest structure is changing, resulting in smaller trees and a different vertical structure compared to old-growth forests (Höwler et al., 2024 ; Pretzsch et al., 2022 ). Large-scale changes, such as forest habitat degradation and fragmentation affect biodiversity (Brockerhoff et al., 2017 ; Newbold et al., 2015 ; Seibold et al., 2019 ; Tittensor et al., 2014 ). Additionally, tree dieback has been shown to alter community composition and the diversity of different animal taxa, as well as plant cover (Cours et al., 2022 ; Kirby et al., 2022 ; Sire et al., 2022 ). Furthermore, small-scale changes resulting from forest management affect the species richness of different taxonomic groups or functional groups (Chaudhary et al., 2016 ; Lelli et al., 2019 ; Paillet et al., 2010 ; Spake et al., 2015 ), with variations observed at local and regional scales (Schall et al., 2018 ). Forest management can introduce monocultures and a high proportion of non-native trees, as well as making other changes to forest characteristics. Overall, forest management and tree dieback directly impact both forest structure and small-scale structural heterogeneity, subsequently affecting biodiversity (Heidrich et al., 2020 ; Leidinger et al., 2021 ; Staab et al., 2023 ). For arthropod communities, forest structure and heterogeneity are key ecological features that influence their diversity and composition. As environmental change continues to alter forest structural features, understanding their differential effects on different taxa remains a key research objective. Furthermore, the provision of ecosystem services and functions is under threat, which could lead to economic and environmental crises (Felipe-Lucia et al., 2018 ; Malhi et al., 2020 ; Millar and Stephenson, 2015 ), posing challenges to ecosystems and humanity (Cardinale et al., 2012 ; Chapin III et al., 2000 ; Sala et al., 2000 ). In this study, we explicitly distinguish between average forest structure in a plot (e.g. mean tree diameter at breast height (DBH) of trees on a plot) and small-scale heterogeneity of forests structures within a plot (e.g. variability in mean DBH of trees in a plot). The diversity of trees or other resources for organisms can also be viewed as a measure of heterogeneity. Both, mean conditions (mirrored by an average structure) as well as heterogeneity of the conditions (variation in structures, or diversity of resources) are known to shape the abundance, diversity and community composition of different taxa (Knuff et al., 2020 ; Larrieu et al., 2019 ; Penone et al., 2019 ; Staab et al., 2023 ). Important aspects of forest structure that are related to arthropods are mean canopy opening, microclimate, deadwood volume, tree size and tree identity (Doerfler et al., 2018 ; Penone et al., 2019 ; Staab et al., 2023 ). An increased canopy opening leads to a warmer and drier microclimate, as well as increased light penetration on the forest ground (Thom et al., 2020 ). Depending on their ecological characteristics and habitat preferences, arthropod communities react differently to those aspects (Gandhi et al., 2008 ; Lettenmaier et al., 2022 ; Perry et al., 2018 ; Staab et al., 2022 ). Tree size and deadwood volume are two other important structural components. Whereas tree size had no consistent effect on beetle communities (positive: (Knuff et al., 2020 ), neutral: (Penone et al., 2019 )), an increase in deadwood volume has consistently positive effects on the abundance and diversity of beetles (Doerfler et al., 2018 ; Larrieu et al., 2019 ; Penone et al., 2019 ; Rothacher et al., 2023 ). Furthermore, the proportion of non-native trees is an important structural element of forests and plays a crucial role in shaping the ecological dynamics of forest arthropod communities, particularly in terms of diversity, community composition and temporal changes (Penone et al., 2019 ; Staab et al., 2022 ). The effects of forest structural heterogeneity on arthropod communities, including vertical heterogeneity, deadwood diversity and tree diversity, have been investigated in fewer studies, with inconsistent results (Heidrich et al., 2020 ; Knuff et al., 2020 ; Larrieu et al., 2019 ; Staab et al., 2023 ). Increasing deadwood diversity positively affects saproxylic beetle diversity (Chamagne et al., 2016 ; Heidrich et al., 2020 ), while higher tree diversity positively influences insect abundance trends over time (Staab et al., 2023 ). Given the importance of arthropods in terms of biomass and diversity for the functioning of ecosystems (Buse and Entling, 2020 ; Lefcheck et al., 2015 ), it is crucial to identify the habitat characteristics that support arthropod communities in temperate forests. Much is known about insects that decompose deadwood, but little is known about dung-decomposing beetles' reactions to changes in forest structures and structural heterogeneity. Dung beetles (Coleoptera: Geotrupidae; Scarabaeidae) play an important role in ecosystem functioning because they can improve soil quality and nutrient cycling, thereby increasing plant growth (Anderson et al., 2024 ; Nichols et al., 2008 ; Slade et al., 2016 ). In a full-factorial experiment, Staab et al. ( 2022 ) found differences in dung beetle diversity, biomass, and dung removal rates between forest gaps and closed forests. This demonstrates that changes in structural features, such as the creation of forest gaps following total tree mortality or clear-cutting, are associated with a decrease in dung beetle biomass and, consequently, their functional role in ecosystems. This is comparable to changes in dung beetle biomass between old and young forests (Hülsmann et al., 2020 ). The key function of dung removal is mainly influenced by habitat type and dung beetle biomass (Buse and Entling, 2020 ). Numerous studies have demonstrated that the species Anoplotrupes stercorosus accounts for the greatest biomass and plays a pivotal role in dung decomposition in temperate European forests (Buse and Entling, 2020 ; Hülsmann et al., 2020 ; Staab et al., 2022 ). The harm caused to a pivotal species by changes in mean forest structure and structural heterogeneity highlights the need to analyse the responses of individual species, as well as those with similar morphological traits, which could fulfil its important functional role in forest ecosystems. This is particularly pertinent in forests where the structure and small-scale heterogeneity are currently changing due to increasing tree mortality. In this study, we examined a variety of forest plots that differed in terms of environmental characteristics such as tree size, canopy openness, proportion of non-native trees and forest ground cover. Some of the forest plots in our study area were severely damaged by heatwaves and drought in 2018 and 2019, and all plots have remained unmanaged since 2019. Our study examined the impact of variations in mean forest structure and structural heterogeneity between forest plots on dung beetle communities and dung removal. In doing so, we aimed to answer the following research questions: (1) Does the strong variation in forest structure correspond to altered dung beetle biomass, diversity and community composition? (2) Do effects correspond to average site conditions (mean structural parameters) or to their small-scale heterogeneity (variability of the structural parameters, tree diversity), or both? (3) Do changes in the dung beetle community translate to altered dung decomposition rates? Methods Study site and forest characteristics The study was carried out in two different regions (East and West orientation) of the municipal forest of Darmstadt (Hesse, Germany). The soil conditions differ between the regions, with nutrient-poor and water-deficient sandy soils dominating in the western part and water-retaining loamy soils in the eastern part (Wehner et al., unpubl.). The forest plots in the study area are characterised by different native and non-native main tree species. The native main tree species are beech ( Fagus sylvatica ), oak ( Quercus petraea/robur ) and black alder ( Alnus glutinosa ). In addition, planted pine ( Pinus sylvestris ), planted Norway spruce ( Picea abies ) and self-seeding mountain black cherry trees ( Prunus serotina ) dominate other plots. In the Darmstadt municipal forest, 320 inventory points (250 m apart) are inventoried annually according to the guidelines of the German National Forest Inventory (Meining, S., 2024 ). We established study plots of 30 x 30 m around 67 of those inventory points (Figure S1 ). On the plots we identified all living trees (> 7 cm in diameter) and measured their diameter at breast height (DBH) (~ 1.3 m). These data were used to calculate mean DBH, coefficient of variance (CV) of DBH and total basal area ( \(\:{\sum\:}_{i=\:1}^{n}\pi\:*({\frac{{DBH}_{i}}{2})}^{2},\) in cm²) per plot. Mean and CV of tree height per plot were estimated using stand height curves derived from measurements of selected trees per plot and tree species. Individual tree heights were measured using a laser distance meter (Bosch UniversalDistance40C). For each plot we also calculated tree species richness and tree diversity (e H ) (Jost, 2006 ) based on the basal area of each tree species per plot. The proportion of non-native trees ( Pinus strobus, Pinus sylvestris, Picea abies, Larix europeana, Prunus serotina, Quercus rubra, Robinia pseudoacacia, Alianthus altissima, Aesculus hippocastanum ) was computed by dividing the sum of the basal area of the non-native tree species by the overall tree basal area. We considered Scots pine ( Pinus sylvestris ) and European spruce ( Picea abies ) as non-native tree species because they would be very rare (Scots pine) or absent (European spruce) in the study region without human introduction. To calculate the volume of deadwood, we inventoried all standing dead trees on the plots with a DBH > 7 cm by measuring DBH and height. For stumps and lying deadwood (> 25 cm in diameter) all pieces were measured by three diameters (beginning, mid, ending or top, middle, bottom) and height/length. Volume of smaller dead stumps and lying deadwood (7–25 cm in diameter) was estimated using both diagonal lines from one corner of the plot to the other (~ 42 m) following the line-intersect method of van Wagner ( 1982 ). Canopy openness was assessed by densiometer measurements (Forestry Suppliers, Inc, Jackson, Mississippi, USA.) at the SW corner, NE corner and centre of each plot. At each measurement point, three different people measured canopy openness for each of the four compass directions. Canopy openness per plot was then calculated as the mean of these 36 measurements. We also calculated the CV of canopy openness based on the 36 measurements. We used estimates of stand age and visible tree damage in the crown [%] (hereafter defoliation) for the eight biggest trees around the plot midpoint, as reported in the annual forest inventory report (Meining, S., 2024 ). Defoliation values were estimated in 5% increments by visual inspection of the tree crown. Forest ground cover was inventoried in five 2 x 2 m squares, oriented on a diagonal line from the southeast to the northwest corner of the plots and approximately 10 m apart. In these squares we estimated the cover of moss, foliage, herbs, deadwood, small and large trees and bare ground and measured the height of the foliage. In order to obtain a value for all forest ground parameters per plot, we calculated a mean value for each cover parameter from the five squares per plot. Based on the mean cover values for each plot, we also calculated the evenness of the ground cover. All measurements of forest characteristics were taken in 2023 and 2024. Dung beetle and dung decomposition survey Dung beetles were sampled in two surveys in June 2023 and June 2024 using baited pitfall traps. We placed one baited pitfall trap on each of the 67 plots. We used water with a drop of soap as the trapping fluid in these traps. The traps, with an opening of 9 cm in diameter and a volume of 400 ml, were filled with 250 ml of the trapping liquid. We used tea bags filled with cow dung as bait. The dung was filled into tea bags (~ 30 g) and each tea bag was placed ~ 5 cm above the trap by attaching the bag to a wooden stick with a rubber band. Prior to deployment, the filled tea bags were frozen at -18°C and removed approximately one hour before deployment. The traps were set out over two days. All dung beetles sampled were preserved in 70% ethanol and identified to species level. The protocols of Frank et al. ( 2017 ) and Staab et al. ( 2022 ) were used for the dung decomposition survey. We weighed 190 g of fresh cow dung (mean 189.07 ± 6.37 g SD) in separate plastic bags. These bags were frozen at -18°C. On the plots, the cow dung from one plastic bag was placed on cellulose paper. After 48 h, the dung was collected and the attached debris was carefully removed. The dung was then oven-dried (60°C) and reweighed. To calculate the pre-exposure dry weight, we dried four additional dung samples and calculated their mean weight loss. This mean weight loss was used as a conversion factor from fresh to dry dung weight. Dung removal was calculated as the difference between the pre-exposure dry weight and the post-exposure dry weight divided by the pre-exposure dry weight. Removal was only calculated for samples with holes in the cellulose paper. If no holes were detected, dung removal was set to 0 but included in the analysis. Cow dung for the traps and the dung decomposition survey was provided by an organic farm (Hofgut Oberfeld, Darmstadt, Germany) where no vermicides are used and the cows are fed only grass and hay. Statistical analysis Analyses were performed using R 4.3.1 (R Core Team, 2023). We computed two principal component analyses (PCAs): one PCA for the 16 mean structural parameters (Fig. 1 a, Table S1 ), and one PCA for the 6 small-scale structural heterogeneity parameters (e.g. the spatial CV of DBH in a plot) (Fig. 1 b, Table S1 ). Before calculating the PCA, each parameter was scaled (mean = 0, SD = 1). We extracted the first two axes for each PCA for further analysis. The two PCA axes for the mean forest structure explained 46.23% of the variance (axis 1: 31.56%, axis 2: 14.67%) and the two PCA axes for the structural heterogeneity explained 59.8% (axis 1: 37.22%, axis 2: 22.58%). We assessed the significance and association with the PCA axes of the variables fitted to the PCA ordination space using a post-hoc permutation test (999 permutations) (Table S1 ). The dry biomass in g for each dung beetle species was derived from mean species specific biomass calculations of Frank et al. ( 2017 ). The total dry biomass of dung beetles [g] per plot was calculated by summing the products of the mean species specific biomass and the number of individuals of each species in each plot. The diversity of the dung beetle community was calculated as the exponential Shannon diversity (e H ) (Jost, 2006 ). To test for differences in community composition, we calculated Bray-Curtis distance matrices on the basis of proportional abundance and on the basis of proportional biomass values (sqrt-transformed) per plot. Species abundances for Anoplotrupes stercorosus , Trypocopris vernalis and Volinus sticticus were converted to presence-absence data due to a high proportion of zero counts, which limited the applicability of abundance-based models. We decided to keep A. stercorosus and T. vernalis in the analysis because large tunneling dung beetle species are the most effective group for dung removal in Central Europe (Buse and Entling, 2020 ; Milotić et al., 2019 ). In addition, we kept V. sticticus as a small dung-dwelling and very abundant species in temperate European forests (Buse et al., 2018 ). There were only moderate correlations (Pearson's r < 0.4, Figure S2) between the four different PCA axes, none of which were significant based on the cor.mtest function of the corrplot package (Wei et al., 2017 ) (Table S2). To account for the effects of the PCA axes on biomass and diversity per plot, we modelled their interrelationship using linear models with biomass (sqrt-transformed) or Shannon diversity (e H ) as response, mean forest structure and structural heterogeneity PCA axes 1 and 2 as explanatory variables, and year as a random factor. To analyse the influence of the four PCA axes on the dung beetle community ordinations, we correlated the scores of the first two non-metric multidimensional scaling (NMDS) axes with the four environmental PCA axes in a post-hoc permutation test (999 permutations) using the vegan package (Oksanen et al., 2022 ). We used generalized linear mixed models ( glmmTMB function from glmmTMB package (Brooks et al., 2017 )) with a binomial distribution and year as a random factor to test the effects of the four PCA axes on the occurrence of individual species on the plots. The effects of dung beetles and the environment on dung removal were analysed using linear models with dung beetle biomass (sqrt-transformed), Shannon diversity (e H ) and the four PCA axes as explanatory variables. The correlation between the two dung beetle community ordinations and dung removal was tested using a post-hoc permutation test (999 permutations) with the vegan package (Oksanen et al., 2022 ). As dung removal was only assessed in 2024, we only used the dung beetle community data from 2024 in this analysis. The analysis including both years was performed on 133 data points (67 plots in 2023 and 66 plots in 2024), but the analysis of dung removal in 2024 was only performed on 66 data points due to a trap failure in one plot. All model residuals were checked for normal distribution, heteroscedasticity and spatial autocorrelation, and the models themselves for overdispersion. Model assumptions were always met after transforming some of the variables and including region as a random factor in the model of A. stercorosus occurrence due to prior spatial autocorrelation of the model residuals. Results In both years together, we sampled 10743 dung beetle individuals of 15 species (3 Geotrupidae, 12 Scarabaeidae) with a total calculated dry biomass of 370.91 g. The most abundant species was the small scarabeid Volinus sticticus (62.48% of all individuals), and the large geotrupid Anoplotrupes stercorosus contributed 70.75% of the total dry biomass (Table S3). Total dry biomass of dung beetles was negatively related to mean forest structure PCA axis 1, i.e. dung beetle biomass decreased from native forests with taller trees, a larger tree basal area and a higher canopy cover to forests with lower trees, a higher proportion of non-native trees and a higher ground cover of herbs (Fig. 2 , Table S4). Total dung beetle biomass also responded to changes in forest structural heterogeneity (forest structural heterogeneity PCA axis 2), because decreases in total dung beetle biomass were associated with a less diverse tree community, more heterogeneous ground cover and greater canopy diversification (Fig. 2 , Table S4). In contrast to the total dry biomass, Shannon diversity of dung beetles increased from native forests with taller trees, a larger tree basal area and a higher canopy cover to forests characterised by lower tree height, a higher proportion of non-native trees and a higher ground cover of herbs (mean forest structure PCA axis 1; Fig. 2 , Table S4). Those mean forest structures (mean forest structure PCA axis 1) and forest structural heterogeneity parameters (forest structural heterogeneity PCA axis 2) were also associated with changes in the dung beetle community calculated on the basis of biomass (Fig. 3 , Table S5). The two most abundant species ( A. stercorosus , V. sticticus ) and Trypocopris vernalis as the functionally almost similar species to A. stercorosus responded to changes in mean forest structure, but not to structural heterogeneity. The probability of occurrence of A. stercorosus and V. sticticus was high in forests with larger tree basal area, more native trees, taller trees, and higher canopy cover, and decreased in forests characterised by opposite structural conditions (mean forest structure PCA axis 1; Fig. 4 a, 4 e, Table S6). Furthermore, the occurrence of A. stercorosus and V. sticticus was negatively associated with increasing tree defoliation and mean canopy openness (mean forest structure PCA axis 2; Fig. 4 b, 4 f, Table S6). The responses of T. vernalis were contrasting to responses of A. stercorosus and V. sticticus along both mean forest structure PCA axes (Fig. 4 c-d, Table S6). Dung removal increased with higher dung beetle biomass, but was lower in forests characterised by a high proportion of non-native trees and high herb cover on the forest ground compared to forests characterised by tall and native trees, a large tree basal area and a high canopy cover (mean forest structure PCA axis 1; Fig. 5 , Table S7). Changes in dung beetle diversity and community composition did not correlate with dung removal rates (Table S8). Discussion This study provides insights into the response of dung beetles and dung removal to changes in forest characteristics, some of which are altered by tree mortality. Our results indicate that the biomass, diversity and community composition of dung beetles are related to changes in mean forest structure. Furthermore, shifts in the heterogeneity of canopy opening and ground cover, as well as variations in tree diversity, are linked to changes in dung beetle biomass and community composition. Individual dung beetle species responded differently to changes in mean forest structure, while changes in forest structural heterogeneity had no effect. Dung removal rates were higher in forests with high dung beetle biomass and in forests with taller trees, a higher proportion of native trees and a larger tree basal area. Effects on dung beetle biomass, diversity and community composition In forests with a more open canopy, a lower tree basal area, a higher proportion of non-native trees and a thinner litter layer, dung beetle biomass is lower compared to other forests in the study region. Additionally, our results show that a decrease in dung beetle biomass is associated with greater heterogeneity in canopy openness and forest ground cover, and lower tree diversity. Other studies have also found that recent forests and more open habitats have lower dung beetle biomass (Buse and Entling, 2020 ; Frank et al., 2017 ; Hülsmann et al., 2020 ). As dung beetles are not directly dependent on trees, we expected only indirect effects of the proportion of non-native trees on dung beetles (e.g. through changes in canopy openness). In temperate European forests, dung beetle biomass is mostly driven by the forest specialist Anoplotrupes stercorosus (Frank et al., 2017 ; Hülsmann et al., 2020 ), as it is in this study. An important factor possibly driving the avoidance of more open and younger forests by dung beetles is predator avoidance (Goßmann et al., 2023 ). Using various techniques to prey on dung beetles in and on animal faeces, birds are probably the most efficient predators on dung beetles (Young, 2015 ), and their efficiency may even increase in disturbed and more open forests. As predation risk increases with body size (Nakazawa et al., 2007 ; Remmel and Tammaru, 2009 ), the large-bodied A. stercorosus may avoid more open habitats with smaller trees and thinner litter layers because of the higher risk of predation. It is also possible that factors such as physiological constraints are driving the negative response of dung beetle biomass to younger, more open forests with higher herbaceous cover. In more open habitats with higher sunlight penetration, forest-adapted dung beetles show lower reproductive rates (Vessby, 2001 ) and probably cannot cope with the physiological challenges in such drier and lighter habitats (Nervo et al., 2024 ; Verdú et al., 2019 ). In contrast to the negative effects on overall dung beetle biomass, forests with a more open canopy, a lower tree basal area, a higher proportion of non-native trees and a thinner litter layer favour a higher diversity of dung beetles in the study region. Open forests are known to have a greater variety of dung beetles because species adapted to open habitats are recruited there (Ambrožová et al., 2022 ). Such areas may resemble forest edges, which typically have greater taxonomic diversity due to the combination of open and forest habitat communities (Pinksen et al., 2021 ; Vanneste et al., 2024 ). The diversity of dung beetles did however not consistently respond to changes in forest structural heterogeneity, although such effects have been shown for the diversity of other organisms such as bryophytes, vascular plants, other arthropods or birds (Heidrich et al., 2020 ; Hekkala et al., 2023 ; Uhl et al., 2024 ). While changes in forest structural heterogeneity from forests with a diverse tree community, homogeneous forest ground cover and canopy openness to forests with opposite forest conditions did not affect dung beetle diversity, they affected the community composition of dung beetles. In addition, our results show that the dung beetle community composition responds to changes in mean forest structures. These changes range from more closed, native forests with taller trees, a larger tree basal area, to more open forests with lower tree heights, a higher proportion of non-native trees, and higher herb cover on the forest ground. The occurrence of the species studied individually strongly responds to the mean structure of the forest plots but not to their structural heterogeneity. The occurrence of Trypocopris vernalis is favoured by forests with lower tree height, lower tree basal area and higher proportion of non-native tree species, while the same forest characteristics lead to a decrease in the occurrence of A. stercorosus (only marginally significant) and Volinus sticticus . Our results provide new insights into the three species’ preferences for forest structures, in addition to known positive dominance effects of A. stercorosus over T. vernalis with increasing forest stand age (Marczak, 2013 ). In line with other studies, the probability of occurrence of the forest specialists A. stercorosus and V. sticticus decreases with increasing tree defoliation and canopy openness (Frank et al., 2017 ; Koch, 1992 ; Rössner, 2012 ). This is particularly important given the predicted increase in heat waves, droughts and associated tree mortality (Dai, 2013 ; Senf et al., 2020 ; Trenberth et al., 2014 ), as A. stercorosus is the most common tunneling dung beetle species in Central Europe (Buse and Entling, 2020 ; Staab et al., 2022 ). T. vernalis responds in the opposite way, showing a higher probability of occurrence on plots with increasing defoliation and canopy openness. Effects on dung removal The lower dung removal rate in more degraded forests correlates with a lower dung beetle biomass. Together with the aforementioned effects on dung beetle biomass, this finding is consistent with the results of other studies (Buse and Entling, 2020 ; Staab et al., 2022 ). With lower tree height, a higher canopy openness, a lower tree basal area and a higher proportion of non-native tree species one can expect higher temperatures and dung removal rates (Ehbrecht et al., 2019 ; Nervo et al., 2024 ). However, we did not observe an increase in dung removal with rising temperatures, instead we observed lower dung removal rates in degraded forests, likely due to lower densities of A. stercorosus . This is probably because temperatures near the soil surface on the degraded plots sometimes exceed 40° C (personal observation), which is the temperature at which A. stercorosus experiences complete paralysis (Nervo et al., 2024 ). Even though the morphologically nearly identical T. vernalis has a higher probability of occurrence in the degraded and more open forests it does not occur in the same densities as A. stercorosus , probably due to the risk of predation and the ability of A. stercorosus to switch to litter as an alternative food source to dung (Byk and Semkiw, 2010 ). In temperate regions, habitat continuity is important for dung beetles (Hülsmann et al., 2020 ) and the colonisation of degraded forests by species adapted to open habitats that can subsidise A. stercorosus could be hampered by the lack of habitat quantity and continuity in the surrounding area and the patchy and unpredictable availability of dung as a food source (Hanski and Cambefort, 1991 ). Lighter and warmer conditions could also explain the negative effects on dung removal in forests with a more open canopy, lower tree height and a higher proportion of non-native trees. Dung beetles as important dung decomposers prefer a water content of more than 75% in their resource (Holter, 2016 ), but under higher solar radiation the water loss of dung could be too fast and dung beetles do not process the resource after shorter time periods. Changes in total dung beetle biomass, diversity, and community composition are related to variations in forest characteristics following tree dieback in the study region. Dung beetle responses were more pronounced through shifts in mean forest structure than through small-scale structural heterogeneity. In summary, the lower biomass of dung beetles in younger and degraded forests may be due to a combination of factors, including higher predation risk, reduced continuity and availability of open habitats in the surrounding area, physiological constraints, and the need for faster decomposition due to accelerated water loss in dung. This highlights that changes in forest characteristics, particularly mean forest structures, lead to changes in the dung beetle community and subsequently affect dung decomposition rates. In addition to forest management, climate change is having an increasing impact on forest characteristics. Our results suggest that, if climate change continues to affect mean forest structures in the coming years, ecosystem functioning may be severely impaired. Declarations Acknowledgements We thank Andrea Hilpert, the ecology master courses of 2023 and 2024 at TU Darmstadt and all student helpers for their help with the work in the laboratory and in the field. Funding The work is supported by funds from the Federal Ministry of Agriculture, Food and Regional Identity by decision of the German Bundestag (2220NR244A). Conflicts of interest The authors declare that they have no conflict of interest. Ethics approval All applicable institutional and/or national guidelines for the care and use of animals were followed. Consent to Participate Not applicable. Consent for publication Not applicable. Availability of data and material Upon acceptance, all underlying data, derived data, and statistical code pertinent to the results will be made publicly available in https://zenodo.org/. Data for review is available using https://zenodo.org/records/15646611 Code availability Not applicable. Authors contribution JL, NB, MH, KW and NKS conceived the ideas and developed the methodology. JL, MT and KW conducted the fieldwork. JL analysed the data with the help of NB and NKS and wrote the manuscript. All authors provided editorial advice. References Albrich, K., Rammer, W., Seidl, R., 2020. Climate change causes critical transitions and irreversible alterations of mountain forests. 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Vanneste, T., Depauw, L., De Lombaerde, E., Meeussen, C., Govaert, S., De Pauw, K., Sanczuk, P., Bollmann, K., Brunet, J., Calders, K., Cousins, S.A.O., Diekmann, M., Gasperini, C., Graae, B.J., Hedwall, P.-O., Iacopetti, G., Lenoir, J., Lindmo, S., Orczewska, A., Ponette, Q., Plue, J., Selvi, F., Spicher, F., Verbeeck, H., Zellweger, F., Verheyen, K., Vangansbeke, P., De Frenne, P., 2024. Trade-offs in biodiversity and ecosystem services between edges and interiors in European forests. Nat Ecol Evol 8, 880–887. https://doi.org/10.1038/s41559-024-02335-6 Verdú, J.R., Cortez, V., Oliva, D., Giménez-Gómez, V., 2019. Thermoregulatory syndromes of two sympatric dung beetles with low energy costs. Journal of Insect Physiology 118, 103945. https://doi.org/10.1016/j.jinsphys.2019.103945 Vessby, K., 2001. Habitat and weather affect reproduction and size of the dung beetle Aphodius fossor . Ecological Entomology 26, 430–435. https://doi.org/10.1046/j.1365-2311.2001.00331.x Wei, T., Simko, V., Levy, M., Xie, Y., Jin, Y., Zemla, J., 2017. Package ‘corrplot’. Statistician. Young, O.P., 2015. Predation on Dung Beetles (Coleoptera: Scarabaeidae): A Literature Review. Transactions of the American Entomological Society 141, 111–155. https://doi.org/10.3157/061.141.0110 Supplementary Files MSforstrdungbeetlessuppmaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6878459","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476827843,"identity":"d8814f80-2513-4416-a201-090933f58a3c","order_by":0,"name":"Julian Lunow","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0002-2762-2507","institution":"Julius Maximilians University Wurzburg Faculty of Biology: Julius-Maximilians-Universitat Wurzburg Fakultat fur Biologie","correspondingAuthor":true,"prefix":"","firstName":"Julian","middleName":"","lastName":"Lunow","suffix":""},{"id":476827844,"identity":"bcbf7d99-34e1-4306-9363-3cdb7ede6561","order_by":1,"name":"Katja Wehner","email":"","orcid":"","institution":"Technical University of Darmstadt: Technische Universitat Darmstadt","correspondingAuthor":false,"prefix":"","firstName":"Katja","middleName":"","lastName":"Wehner","suffix":""},{"id":476827845,"identity":"6393a313-9937-4a56-9ae4-6f2f5c47a6f1","order_by":2,"name":"Matteo Trevisan","email":"","orcid":"","institution":"Technical University of Darmstadt: Technische Universitat Darmstadt","correspondingAuthor":false,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Trevisan","suffix":""},{"id":476827846,"identity":"3177caed-77f9-4766-a5e0-36a242447845","order_by":3,"name":"Michael Heethoff","email":"","orcid":"","institution":"Technical University of Darmstadt: Technische Universitat Darmstadt","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Heethoff","suffix":""},{"id":476827847,"identity":"8ab0e8d5-142a-4323-9889-f2590dee9d81","order_by":4,"name":"Nico Blüthgen","email":"","orcid":"","institution":"Technical University of Darmstadt: Technische Universitat Darmstadt","correspondingAuthor":false,"prefix":"","firstName":"Nico","middleName":"","lastName":"Blüthgen","suffix":""},{"id":476827848,"identity":"0790dcf5-0dfd-44f6-a82b-df937d327d99","order_by":5,"name":"Nadja K. Simons","email":"","orcid":"","institution":"Julius Maximilians University Wurzburg Faculty of Biology: Julius-Maximilians-Universitat Wurzburg Fakultat fur Biologie","correspondingAuthor":false,"prefix":"","firstName":"Nadja","middleName":"K.","lastName":"Simons","suffix":""}],"badges":[],"createdAt":"2025-06-12 08:56:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6878459/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6878459/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85724406,"identity":"6d27d83a-5806-4860-88ab-70f0429a052d","added_by":"auto","created_at":"2025-07-01 06:22:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":421858,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) ordination of the studied plots for mean forest structure (a) and structural heterogeneity (b). The colours represent the two different regions (E = East, W = West) in the municipal forest of Darmstadt, DE. The variables included in each of the PCAs can be found in Table 1. In the mean forest structure PCA only significant variables with an association of \u0026lt; -0.9 and \u0026gt; 0.9 to one of the axes are depicted. In the structural heterogeneity ordination, all included variables were significant and depicted. Full details on the variables can be found in Table S1. Percentage in the axis titles values represent the explained variance of each PCA axis. With the abbreviation “gc” is “ground cover”.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6878459/v1/a862a885c5a746038fe5daa2.png"},{"id":85724409,"identity":"277245cd-a3f4-4d7a-a5d4-d56c778e9295","added_by":"auto","created_at":"2025-07-01 06:22:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":382450,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of mean forest structure and structural heterogeneity PCA axes on total dry dung beetle biomass [g] (sqrt-transformed) and Shannon diversity (e\u003csup\u003eH\u003c/sup\u003e). a) Effect of mean forest structure PCA axis 1 on dung beetle biomass. b) Effect of structural heterogeneity PCA axis 2 on dry dung beetle biomass [g] (sqrt-transformed). c) Effect of mean forest structure PCA axis 1 on dung beetle Shannon diversity. The coloured points represent the two different study areas (blue = eastern forest, orange = western forest). The full model results are given in Table S4.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6878459/v1/a68d08b6241494f3ee07af9e.png"},{"id":85724410,"identity":"7420d31a-9ef8-42c4-869c-1009b9423382","added_by":"auto","created_at":"2025-07-01 06:22:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":208455,"visible":true,"origin":"","legend":"\u003cp\u003eNMDS on biomass-based dung beetle community composition (stress = 0.093). The colours represent the two different study regions, the rectangles communities sampled in 2023 and the triangles communities sampled in 2024. The arrows depict significant effects in the PERMANOVA of mean forest structure PCA axis 1 (str. PCA ax1) and structural heterogeneity PCA axis 2 (het. PCA ax2) on the community composition. The full model results are given in Table S5.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6878459/v1/1261093894fea0c60d5cbe0a.png"},{"id":85724407,"identity":"77e8d7fb-d101-4744-9255-2e74cb648998","added_by":"auto","created_at":"2025-07-01 06:22:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":254241,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of mean forest structure PCA axis 1 (a, c, e) and mean forest structure PCA axis 2 (b, d, f) on the occurrence of \u003cem\u003eA. stercorosus\u003c/em\u003e (a, b), \u003cem\u003eT. vernalis\u003c/em\u003e (c, d)\u003cem\u003e \u003c/em\u003eand \u003cem\u003eV. sticticus\u003c/em\u003e (e, f). The solid lines represent significant effects and the dashed line marginal significant effects. Light grey colours indicate the 95 % confidence intervals. The coloured points represent the two different study areas (blue = eastern forest, orange = western forest). The full model results are given in Table S6.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6878459/v1/3458423bb7f88b29fb0c00cd.png"},{"id":85724412,"identity":"76f0fb6c-2059-46db-b21e-02d3576a03c8","added_by":"auto","created_at":"2025-07-01 06:22:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":179954,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of total dry dung beetle biomass [g] (sqrt-transformed) (a) and mean forest structure PCA axis 1 (b) on dung removal. The solid lines represent significant effects. Light grey colours indicate the 95 % confidence interval. The coloured points represent the two different study areas (blue = eastern forest, orange = western forest). The full model results are given in Table S7.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6878459/v1/f15439b02eb9ce41aea9e83c.png"},{"id":87887779,"identity":"e30538f9-60c7-4513-a0bd-45ca043bab30","added_by":"auto","created_at":"2025-07-30 05:44:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1740520,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6878459/v1/057e6c94-2c54-4eeb-a7ef-71b82ba5d9a2.pdf"},{"id":85725698,"identity":"e2918413-c2d3-4635-a790-b87aeca26943","added_by":"auto","created_at":"2025-07-01 06:38:07","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1037969,"visible":true,"origin":"","legend":"","description":"","filename":"MSforstrdungbeetlessuppmaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6878459/v1/d377c7d1bc53bf78f4e32520.docx"}],"financialInterests":"","formattedTitle":"Forest structural changes after tree dieback affect dung beetle communities and dung removal rates","fulltext":[{"header":"Introduction","content":"\u003cp\u003eForests cover a significant proportion of Europe's land area, and the proportion of forests designated primarily for biodiversity conservation is increasing (FAO, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This is promising for biodiversity and ecosystem functioning in forest ecosystems. However, forests are currently experiencing the effects of heat waves and drought (Allen et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Senf et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Severe weather events, which are caused by human-induced climate change, pose physiological challenges for trees and can result in tree dieback (Albrich et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Menezes-Silva et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Schuldt et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Consequently, forest structure is changing, resulting in smaller trees and a different vertical structure compared to old-growth forests (H\u0026ouml;wler et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pretzsch et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Large-scale changes, such as forest habitat degradation and fragmentation affect biodiversity (Brockerhoff et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Newbold et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Seibold et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tittensor et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Additionally, tree dieback has been shown to alter community composition and the diversity of different animal taxa, as well as plant cover (Cours et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kirby et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sire et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, small-scale changes resulting from forest management affect the species richness of different taxonomic groups or functional groups (Chaudhary et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Lelli et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Paillet et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Spake et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), with variations observed at local and regional scales (Schall et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Forest management can introduce monocultures and a high proportion of non-native trees, as well as making other changes to forest characteristics. Overall, forest management and tree dieback directly impact both forest structure and small-scale structural heterogeneity, subsequently affecting biodiversity (Heidrich et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Leidinger et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For arthropod communities, forest structure and heterogeneity are key ecological features that influence their diversity and composition. As environmental change continues to alter forest structural features, understanding their differential effects on different taxa remains a key research objective. Furthermore, the provision of ecosystem services and functions is under threat, which could lead to economic and environmental crises (Felipe-Lucia et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Malhi et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Millar and Stephenson, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), posing challenges to ecosystems and humanity (Cardinale et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Chapin III et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Sala et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, we explicitly distinguish between average forest structure in a plot (e.g. mean tree diameter at breast height (DBH) of trees on a plot) and small-scale heterogeneity of forests structures within a plot (e.g. variability in mean DBH of trees in a plot). The diversity of trees or other resources for organisms can also be viewed as a measure of heterogeneity. Both, mean conditions (mirrored by an average structure) as well as heterogeneity of the conditions (variation in structures, or diversity of resources) are known to shape the abundance, diversity and community composition of different taxa (Knuff et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Larrieu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Penone et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Important aspects of forest structure that are related to arthropods are mean canopy opening, microclimate, deadwood volume, tree size and tree identity (Doerfler et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Penone et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). An increased canopy opening leads to a warmer and drier microclimate, as well as increased light penetration on the forest ground (Thom et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Depending on their ecological characteristics and habitat preferences, arthropod communities react differently to those aspects (Gandhi et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Lettenmaier et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Perry et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Tree size and deadwood volume are two other important structural components. Whereas tree size had no consistent effect on beetle communities (positive: (Knuff et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), neutral: (Penone et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)), an increase in deadwood volume has consistently positive effects on the abundance and diversity of beetles (Doerfler et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Larrieu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Penone et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Rothacher et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, the proportion of non-native trees is an important structural element of forests and plays a crucial role in shaping the ecological dynamics of forest arthropod communities, particularly in terms of diversity, community composition and temporal changes (Penone et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effects of forest structural heterogeneity on arthropod communities, including vertical heterogeneity, deadwood diversity and tree diversity, have been investigated in fewer studies, with inconsistent results (Heidrich et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Knuff et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Larrieu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Increasing deadwood diversity positively affects saproxylic beetle diversity (Chamagne et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Heidrich et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), while higher tree diversity positively influences insect abundance trends over time (Staab et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Given the importance of arthropods in terms of biomass and diversity for the functioning of ecosystems (Buse and Entling, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lefcheck et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), it is crucial to identify the habitat characteristics that support arthropod communities in temperate forests. Much is known about insects that decompose deadwood, but little is known about dung-decomposing beetles' reactions to changes in forest structures and structural heterogeneity.\u003c/p\u003e \u003cp\u003eDung beetles (Coleoptera: Geotrupidae; Scarabaeidae) play an important role in ecosystem functioning because they can improve soil quality and nutrient cycling, thereby increasing plant growth (Anderson et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Nichols et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Slade et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In a full-factorial experiment, Staab et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found differences in dung beetle diversity, biomass, and dung removal rates between forest gaps and closed forests. This demonstrates that changes in structural features, such as the creation of forest gaps following total tree mortality or clear-cutting, are associated with a decrease in dung beetle biomass and, consequently, their functional role in ecosystems. This is comparable to changes in dung beetle biomass between old and young forests (H\u0026uuml;lsmann et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The key function of dung removal is mainly influenced by habitat type and dung beetle biomass (Buse and Entling, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Numerous studies have demonstrated that the species \u003cem\u003eAnoplotrupes stercorosus\u003c/em\u003e accounts for the greatest biomass and plays a pivotal role in dung decomposition in temperate European forests (Buse and Entling, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; H\u0026uuml;lsmann et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The harm caused to a pivotal species by changes in mean forest structure and structural heterogeneity highlights the need to analyse the responses of individual species, as well as those with similar morphological traits, which could fulfil its important functional role in forest ecosystems. This is particularly pertinent in forests where the structure and small-scale heterogeneity are currently changing due to increasing tree mortality.\u003c/p\u003e \u003cp\u003eIn this study, we examined a variety of forest plots that differed in terms of environmental characteristics such as tree size, canopy openness, proportion of non-native trees and forest ground cover. Some of the forest plots in our study area were severely damaged by heatwaves and drought in 2018 and 2019, and all plots have remained unmanaged since 2019. Our study examined the impact of variations in mean forest structure and structural heterogeneity between forest plots on dung beetle communities and dung removal. In doing so, we aimed to answer the following research questions:\u003c/p\u003e \u003cp\u003e(1) Does the strong variation in forest structure correspond to altered dung beetle biomass, diversity and community composition?\u003c/p\u003e \u003cp\u003e(2) Do effects correspond to average site conditions (mean structural parameters) or to their small-scale heterogeneity (variability of the structural parameters, tree diversity), or both?\u003c/p\u003e \u003cp\u003e(3) Do changes in the dung beetle community translate to altered dung decomposition rates?\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy site and forest characteristics\u003c/h2\u003e \u003cp\u003eThe study was carried out in two different regions (East and West orientation) of the municipal forest of Darmstadt (Hesse, Germany). The soil conditions differ between the regions, with nutrient-poor and water-deficient sandy soils dominating in the western part and water-retaining loamy soils in the eastern part (Wehner et al., unpubl.). The forest plots in the study area are characterised by different native and non-native main tree species. The native main tree species are beech (\u003cem\u003eFagus sylvatica\u003c/em\u003e), oak (\u003cem\u003eQuercus petraea/robur\u003c/em\u003e) and black alder (\u003cem\u003eAlnus glutinosa\u003c/em\u003e). In addition, planted pine (\u003cem\u003ePinus sylvestris\u003c/em\u003e), planted Norway spruce (\u003cem\u003ePicea abies\u003c/em\u003e) and self-seeding mountain black cherry trees (\u003cem\u003ePrunus serotina\u003c/em\u003e) dominate other plots. In the Darmstadt municipal forest, 320 inventory points (250 m apart) are inventoried annually according to the guidelines of the German National Forest Inventory (Meining, S., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). We established study plots of 30 x 30 m around 67 of those inventory points (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). On the plots we identified all living trees (\u0026gt;\u0026thinsp;7 cm in diameter) and measured their diameter at breast height (DBH) (~\u0026thinsp;1.3 m). These data were used to calculate mean DBH, coefficient of variance (CV) of DBH and total basal area (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sum\\:}_{i=\\:1}^{n}\\pi\\:*({\\frac{{DBH}_{i}}{2})}^{2},\\)\u003c/span\u003e\u003c/span\u003e in cm\u0026sup2;) per plot. Mean and CV of tree height per plot were estimated using stand height curves derived from measurements of selected trees per plot and tree species. Individual tree heights were measured using a laser distance meter (Bosch UniversalDistance40C). For each plot we also calculated tree species richness and tree diversity (e\u003csup\u003eH\u003c/sup\u003e) (Jost, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) based on the basal area of each tree species per plot. The proportion of non-native trees (\u003cem\u003ePinus strobus, Pinus sylvestris, Picea abies, Larix europeana, Prunus serotina, Quercus rubra, Robinia pseudoacacia, Alianthus altissima, Aesculus hippocastanum\u003c/em\u003e) was computed by dividing the sum of the basal area of the non-native tree species by the overall tree basal area. We considered Scots pine (\u003cem\u003ePinus sylvestris\u003c/em\u003e) and European spruce (\u003cem\u003ePicea abies\u003c/em\u003e) as non-native tree species because they would be very rare (Scots pine) or absent (European spruce) in the study region without human introduction. To calculate the volume of deadwood, we inventoried all standing dead trees on the plots with a DBH\u0026thinsp;\u0026gt;\u0026thinsp;7 cm by measuring DBH and height. For stumps and lying deadwood (\u0026gt;\u0026thinsp;25 cm in diameter) all pieces were measured by three diameters (beginning, mid, ending or top, middle, bottom) and height/length. Volume of smaller dead stumps and lying deadwood (7\u0026ndash;25 cm in diameter) was estimated using both diagonal lines from one corner of the plot to the other (~\u0026thinsp;42 m) following the line-intersect method of van Wagner (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Canopy openness was assessed by densiometer measurements (Forestry Suppliers, Inc, Jackson, Mississippi, USA.) at the SW corner, NE corner and centre of each plot. At each measurement point, three different people measured canopy openness for each of the four compass directions. Canopy openness per plot was then calculated as the mean of these 36 measurements. We also calculated the CV of canopy openness based on the 36 measurements. We used estimates of stand age and visible tree damage in the crown [%] (hereafter defoliation) for the eight biggest trees around the plot midpoint, as reported in the annual forest inventory report (Meining, S., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Defoliation values were estimated in 5% increments by visual inspection of the tree crown. Forest ground cover was inventoried in five 2 x 2 m squares, oriented on a diagonal line from the southeast to the northwest corner of the plots and approximately 10 m apart. In these squares we estimated the cover of moss, foliage, herbs, deadwood, small and large trees and bare ground and measured the height of the foliage. In order to obtain a value for all forest ground parameters per plot, we calculated a mean value for each cover parameter from the five squares per plot. Based on the mean cover values for each plot, we also calculated the evenness of the ground cover. All measurements of forest characteristics were taken in 2023 and 2024.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDung beetle and dung decomposition survey\u003c/h3\u003e\n\u003cp\u003eDung beetles were sampled in two surveys in June 2023 and June 2024 using baited pitfall traps. We placed one baited pitfall trap on each of the 67 plots. We used water with a drop of soap as the trapping fluid in these traps. The traps, with an opening of 9 cm in diameter and a volume of 400 ml, were filled with 250 ml of the trapping liquid. We used tea bags filled with cow dung as bait. The dung was filled into tea bags (~\u0026thinsp;30 g) and each tea bag was placed\u0026thinsp;~\u0026thinsp;5 cm above the trap by attaching the bag to a wooden stick with a rubber band. Prior to deployment, the filled tea bags were frozen at -18\u0026deg;C and removed approximately one hour before deployment. The traps were set out over two days. All dung beetles sampled were preserved in 70% ethanol and identified to species level.\u003c/p\u003e \u003cp\u003eThe protocols of Frank et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Staab et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) were used for the dung decomposition survey. We weighed 190 g of fresh cow dung (mean 189.07\u0026thinsp;\u0026plusmn;\u0026thinsp;6.37 g SD) in separate plastic bags. These bags were frozen at -18\u0026deg;C. On the plots, the cow dung from one plastic bag was placed on cellulose paper. After 48 h, the dung was collected and the attached debris was carefully removed. The dung was then oven-dried (60\u0026deg;C) and reweighed. To calculate the pre-exposure dry weight, we dried four additional dung samples and calculated their mean weight loss. This mean weight loss was used as a conversion factor from fresh to dry dung weight. Dung removal was calculated as the difference between the pre-exposure dry weight and the post-exposure dry weight divided by the pre-exposure dry weight. Removal was only calculated for samples with holes in the cellulose paper. If no holes were detected, dung removal was set to 0 but included in the analysis. Cow dung for the traps and the dung decomposition survey was provided by an organic farm (Hofgut Oberfeld, Darmstadt, Germany) where no vermicides are used and the cows are fed only grass and hay.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAnalyses were performed using R 4.3.1 (R Core Team, 2023). We computed two principal component analyses (PCAs): one PCA for the 16 mean structural parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), and one PCA for the 6 small-scale structural heterogeneity parameters (e.g. the spatial CV of DBH in a plot) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Before calculating the PCA, each parameter was scaled (mean\u0026thinsp;=\u0026thinsp;0, SD\u0026thinsp;=\u0026thinsp;1). We extracted the first two axes for each PCA for further analysis. The two PCA axes for the mean forest structure explained 46.23% of the variance (axis 1: 31.56%, axis 2: 14.67%) and the two PCA axes for the structural heterogeneity explained 59.8% (axis 1: 37.22%, axis 2: 22.58%). We assessed the significance and association with the PCA axes of the variables fitted to the PCA ordination space using a post-hoc permutation test (999 permutations) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe dry biomass in g for each dung beetle species was derived from mean species specific biomass calculations of Frank et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The total dry biomass of dung beetles [g] per plot was calculated by summing the products of the mean species specific biomass and the number of individuals of each species in each plot. The diversity of the dung beetle community was calculated as the exponential Shannon diversity (e\u003csup\u003eH\u003c/sup\u003e) (Jost, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). To test for differences in community composition, we calculated Bray-Curtis distance matrices on the basis of proportional abundance and on the basis of proportional biomass values (sqrt-transformed) per plot. Species abundances for \u003cem\u003eAnoplotrupes stercorosus\u003c/em\u003e, \u003cem\u003eTrypocopris vernalis\u003c/em\u003e and \u003cem\u003eVolinus sticticus\u003c/em\u003e were converted to presence-absence data due to a high proportion of zero counts, which limited the applicability of abundance-based models. We decided to keep \u003cem\u003eA. stercorosus\u003c/em\u003e and \u003cem\u003eT. vernalis\u003c/em\u003e in the analysis because large tunneling dung beetle species are the most effective group for dung removal in Central Europe (Buse and Entling, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Milotić et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In addition, we kept \u003cem\u003eV. sticticus\u003c/em\u003e as a small dung-dwelling and very abundant species in temperate European forests (Buse et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere were only moderate correlations (Pearson's r\u0026thinsp;\u0026lt;\u0026thinsp;0.4, Figure S2) between the four different PCA axes, none of which were significant based on the \u003cem\u003ecor.mtest\u003c/em\u003e function of the \u003cem\u003ecorrplot\u003c/em\u003e package (Wei et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) (Table S2). To account for the effects of the PCA axes on biomass and diversity per plot, we modelled their interrelationship using linear models with biomass (sqrt-transformed) or Shannon diversity (e\u003csup\u003eH\u003c/sup\u003e) as response, mean forest structure and structural heterogeneity PCA axes 1 and 2 as explanatory variables, and year as a random factor. To analyse the influence of the four PCA axes on the dung beetle community ordinations, we correlated the scores of the first two non-metric multidimensional scaling (NMDS) axes with the four environmental PCA axes in a post-hoc permutation test (999 permutations) using the \u003cem\u003evegan\u003c/em\u003e package (Oksanen et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We used generalized linear mixed models (\u003cem\u003eglmmTMB\u003c/em\u003e function from \u003cem\u003eglmmTMB\u003c/em\u003e package (Brooks et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)) with a binomial distribution and year as a random factor to test the effects of the four PCA axes on the occurrence of individual species on the plots. The effects of dung beetles and the environment on dung removal were analysed using linear models with dung beetle biomass (sqrt-transformed), Shannon diversity (e\u003csup\u003eH\u003c/sup\u003e) and the four PCA axes as explanatory variables. The correlation between the two dung beetle community ordinations and dung removal was tested using a post-hoc permutation test (999 permutations) with the \u003cem\u003evegan\u003c/em\u003e package (Oksanen et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As dung removal was only assessed in 2024, we only used the dung beetle community data from 2024 in this analysis. The analysis including both years was performed on 133 data points (67 plots in 2023 and 66 plots in 2024), but the analysis of dung removal in 2024 was only performed on 66 data points due to a trap failure in one plot. All model residuals were checked for normal distribution, heteroscedasticity and spatial autocorrelation, and the models themselves for overdispersion. Model assumptions were always met after transforming some of the variables and including region as a random factor in the model of \u003cem\u003eA. stercorosus\u003c/em\u003e occurrence due to prior spatial autocorrelation of the model residuals.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn both years together, we sampled 10743 dung beetle individuals of 15 species (3 Geotrupidae, 12 Scarabaeidae) with a total calculated dry biomass of 370.91 g. The most abundant species was the small scarabeid \u003cem\u003eVolinus sticticus\u003c/em\u003e (62.48% of all individuals), and the large geotrupid \u003cem\u003eAnoplotrupes stercorosus\u003c/em\u003e contributed 70.75% of the total dry biomass (Table S3). Total dry biomass of dung beetles was negatively related to mean forest structure PCA axis 1, i.e. dung beetle biomass decreased from native forests with taller trees, a larger tree basal area and a higher canopy cover to forests with lower trees, a higher proportion of non-native trees and a higher ground cover of herbs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table S4). Total dung beetle biomass also responded to changes in forest structural heterogeneity (forest structural heterogeneity PCA axis 2), because decreases in total dung beetle biomass were associated with a less diverse tree community, more heterogeneous ground cover and greater canopy diversification (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table S4). In contrast to the total dry biomass, Shannon diversity of dung beetles increased from native forests with taller trees, a larger tree basal area and a higher canopy cover to forests characterised by lower tree height, a higher proportion of non-native trees and a higher ground cover of herbs (mean forest structure PCA axis 1; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table S4). Those mean forest structures (mean forest structure PCA axis 1) and forest structural heterogeneity parameters (forest structural heterogeneity PCA axis 2) were also associated with changes in the dung beetle community calculated on the basis of biomass (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S5).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe two most abundant species (\u003cem\u003eA. stercorosus\u003c/em\u003e, \u003cem\u003eV. sticticus\u003c/em\u003e) and \u003cem\u003eTrypocopris vernalis\u003c/em\u003e as the functionally almost similar species to \u003cem\u003eA. stercorosus\u003c/em\u003e responded to changes in mean forest structure, but not to structural heterogeneity. The probability of occurrence of \u003cem\u003eA. stercorosus\u003c/em\u003e and \u003cem\u003eV. sticticus\u003c/em\u003e was high in forests with larger tree basal area, more native trees, taller trees, and higher canopy cover, and decreased in forests characterised by opposite structural conditions (mean forest structure PCA axis 1; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee, Table S6). Furthermore, the occurrence of \u003cem\u003eA. stercorosus\u003c/em\u003e and \u003cem\u003eV. sticticus\u003c/em\u003e was negatively associated with increasing tree defoliation and mean canopy openness (mean forest structure PCA axis 2; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef, Table S6). The responses of \u003cem\u003eT. vernalis\u003c/em\u003e were contrasting to responses of \u003cem\u003eA. stercorosus\u003c/em\u003e and \u003cem\u003eV. sticticus\u003c/em\u003e along both mean forest structure PCA axes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec-d, Table S6).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDung removal increased with higher dung beetle biomass, but was lower in forests characterised by a high proportion of non-native trees and high herb cover on the forest ground compared to forests characterised by tall and native trees, a large tree basal area and a high canopy cover (mean forest structure PCA axis 1; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table S7). Changes in dung beetle diversity and community composition did not correlate with dung removal rates (Table S8).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides insights into the response of dung beetles and dung removal to changes in forest characteristics, some of which are altered by tree mortality. Our results indicate that the biomass, diversity and community composition of dung beetles are related to changes in mean forest structure. Furthermore, shifts in the heterogeneity of canopy opening and ground cover, as well as variations in tree diversity, are linked to changes in dung beetle biomass and community composition. Individual dung beetle species responded differently to changes in mean forest structure, while changes in forest structural heterogeneity had no effect. Dung removal rates were higher in forests with high dung beetle biomass and in forests with taller trees, a higher proportion of native trees and a larger tree basal area.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEffects on dung beetle biomass, diversity and community composition\u003c/h2\u003e \u003cp\u003eIn forests with a more open canopy, a lower tree basal area, a higher proportion of non-native trees and a thinner litter layer, dung beetle biomass is lower compared to other forests in the study region. Additionally, our results show that a decrease in dung beetle biomass is associated with greater heterogeneity in canopy openness and forest ground cover, and lower tree diversity. Other studies have also found that recent forests and more open habitats have lower dung beetle biomass (Buse and Entling, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Frank et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; H\u0026uuml;lsmann et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As dung beetles are not directly dependent on trees, we expected only indirect effects of the proportion of non-native trees on dung beetles (e.g. through changes in canopy openness). In temperate European forests, dung beetle biomass is mostly driven by the forest specialist \u003cem\u003eAnoplotrupes stercorosus\u003c/em\u003e (Frank et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; H\u0026uuml;lsmann et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), as it is in this study. An important factor possibly driving the avoidance of more open and younger forests by dung beetles is predator avoidance (Go\u0026szlig;mann et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Using various techniques to prey on dung beetles in and on animal faeces, birds are probably the most efficient predators on dung beetles (Young, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and their efficiency may even increase in disturbed and more open forests. As predation risk increases with body size (Nakazawa et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Remmel and Tammaru, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), the large-bodied \u003cem\u003eA. stercorosus\u003c/em\u003e may avoid more open habitats with smaller trees and thinner litter layers because of the higher risk of predation. It is also possible that factors such as physiological constraints are driving the negative response of dung beetle biomass to younger, more open forests with higher herbaceous cover. In more open habitats with higher sunlight penetration, forest-adapted dung beetles show lower reproductive rates (Vessby, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) and probably cannot cope with the physiological challenges in such drier and lighter habitats (Nervo et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Verd\u0026uacute; et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast to the negative effects on overall dung beetle biomass, forests with a more open canopy, a lower tree basal area, a higher proportion of non-native trees and a thinner litter layer favour a higher diversity of dung beetles in the study region. Open forests are known to have a greater variety of dung beetles because species adapted to open habitats are recruited there (Ambrožov\u0026aacute; et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Such areas may resemble forest edges, which typically have greater taxonomic diversity due to the combination of open and forest habitat communities (Pinksen et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vanneste et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The diversity of dung beetles did however not consistently respond to changes in forest structural heterogeneity, although such effects have been shown for the diversity of other organisms such as bryophytes, vascular plants, other arthropods or birds (Heidrich et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hekkala et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Uhl et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile changes in forest structural heterogeneity from forests with a diverse tree community, homogeneous forest ground cover and canopy openness to forests with opposite forest conditions did not affect dung beetle diversity, they affected the community composition of dung beetles. In addition, our results show that the dung beetle community composition responds to changes in mean forest structures. These changes range from more closed, native forests with taller trees, a larger tree basal area, to more open forests with lower tree heights, a higher proportion of non-native trees, and higher herb cover on the forest ground.\u003c/p\u003e \u003cp\u003eThe occurrence of the species studied individually strongly responds to the mean structure of the forest plots but not to their structural heterogeneity. The occurrence of \u003cem\u003eTrypocopris vernalis\u003c/em\u003e is favoured by forests with lower tree height, lower tree basal area and higher proportion of non-native tree species, while the same forest characteristics lead to a decrease in the occurrence of \u003cem\u003eA. stercorosus\u003c/em\u003e (only marginally significant) and \u003cem\u003eVolinus sticticus\u003c/em\u003e. Our results provide new insights into the three species\u0026rsquo; preferences for forest structures, in addition to known positive dominance effects of \u003cem\u003eA. stercorosus\u003c/em\u003e over \u003cem\u003eT. vernalis\u003c/em\u003e with increasing forest stand age (Marczak, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In line with other studies, the probability of occurrence of the forest specialists \u003cem\u003eA. stercorosus\u003c/em\u003e and \u003cem\u003eV. sticticus\u003c/em\u003e decreases with increasing tree defoliation and canopy openness (Frank et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Koch, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; R\u0026ouml;ssner, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This is particularly important given the predicted increase in heat waves, droughts and associated tree mortality (Dai, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Senf et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Trenberth et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), as \u003cem\u003eA. stercorosus\u003c/em\u003e is the most common tunneling dung beetle species in Central Europe (Buse and Entling, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). \u003cem\u003eT. vernalis\u003c/em\u003e responds in the opposite way, showing a higher probability of occurrence on plots with increasing defoliation and canopy openness.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEffects on dung removal\u003c/h3\u003e\n\u003cp\u003eThe lower dung removal rate in more degraded forests correlates with a lower dung beetle biomass. Together with the aforementioned effects on dung beetle biomass, this finding is consistent with the results of other studies (Buse and Entling, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Staab et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). With lower tree height, a higher canopy openness, a lower tree basal area and a higher proportion of non-native tree species one can expect higher temperatures and dung removal rates (Ehbrecht et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Nervo et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, we did not observe an increase in dung removal with rising temperatures, instead we observed lower dung removal rates in degraded forests, likely due to lower densities of \u003cem\u003eA. stercorosus\u003c/em\u003e. This is probably because temperatures near the soil surface on the degraded plots sometimes exceed 40\u0026deg; C (personal observation), which is the temperature at which \u003cem\u003eA. stercorosus\u003c/em\u003e experiences complete paralysis (Nervo et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Even though the morphologically nearly identical \u003cem\u003eT. vernalis\u003c/em\u003e has a higher probability of occurrence in the degraded and more open forests it does not occur in the same densities as \u003cem\u003eA. stercorosus\u003c/em\u003e, probably due to the risk of predation and the ability of \u003cem\u003eA. stercorosus\u003c/em\u003e to switch to litter as an alternative food source to dung (Byk and Semkiw, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn temperate regions, habitat continuity is important for dung beetles (H\u0026uuml;lsmann et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and the colonisation of degraded forests by species adapted to open habitats that can subsidise \u003cem\u003eA. stercorosus\u003c/em\u003e could be hampered by the lack of habitat quantity and continuity in the surrounding area and the patchy and unpredictable availability of dung as a food source (Hanski and Cambefort, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Lighter and warmer conditions could also explain the negative effects on dung removal in forests with a more open canopy, lower tree height and a higher proportion of non-native trees. Dung beetles as important dung decomposers prefer a water content of more than 75% in their resource (Holter, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), but under higher solar radiation the water loss of dung could be too fast and dung beetles do not process the resource after shorter time periods.\u003c/p\u003e \u003cp\u003eChanges in total dung beetle biomass, diversity, and community composition are related to variations in forest characteristics following tree dieback in the study region. Dung beetle responses were more pronounced through shifts in mean forest structure than through small-scale structural heterogeneity. In summary, the lower biomass of dung beetles in younger and degraded forests may be due to a combination of factors, including higher predation risk, reduced continuity and availability of open habitats in the surrounding area, physiological constraints, and the need for faster decomposition due to accelerated water loss in dung. This highlights that changes in forest characteristics, particularly mean forest structures, lead to changes in the dung beetle community and subsequently affect dung decomposition rates. In addition to forest management, climate change is having an increasing impact on forest characteristics. Our results suggest that, if climate change continues to affect mean forest structures in the coming years, ecosystem functioning may be severely impaired.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank Andrea Hilpert, the ecology master courses of 2023 and 2024 at TU Darmstadt and all student helpers for their help with the work in the laboratory and in the field.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe work is supported by funds from the Federal Ministry of Agriculture, Food and Regional Identity by decision of the German Bundestag (2220NR244A).\u003c/p\u003e\n\u003ch2\u003eConflicts of interest\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003ch2\u003eEthics approval\u003c/h2\u003e\n\u003cp\u003eAll applicable institutional and/or national guidelines for the care and use of animals were followed.\u003c/p\u003e\n\u003ch2\u003eConsent to Participate\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and material\u003c/h2\u003e\n\u003cp\u003eUpon acceptance, all underlying data, derived data, and statistical code pertinent to the results will be made publicly available in https://zenodo.org/. Data for review is available using https://zenodo.org/records/15646611\u003c/p\u003e\n\u003ch2\u003eCode availability\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAuthors contribution\u003c/h2\u003e\n\u003cp\u003eJL, NB, MH, KW and NKS conceived the ideas and developed the methodology. JL, MT and KW conducted the fieldwork. JL analysed the data with the help of NB and NKS and wrote the manuscript. All authors provided editorial advice.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlbrich, K., Rammer, W., Seidl, R., 2020. Climate change causes critical transitions and irreversible alterations of mountain forests. Global Change Biology 26, 4013\u0026ndash;4027. https://doi.org/10.1111/gcb.15118\u003c/li\u003e\n \u003cli\u003eAllen, C.D., Macalady, A.K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D.D., Hogg, E.H. 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Transactions of the American Entomological Society 141, 111\u0026ndash;155. https://doi.org/10.3157/061.141.0110\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"dung decomposition, forest heterogeneity, forest structure, Geotrupidae, Scarabaeidae","lastPublishedDoi":"10.21203/rs.3.rs-6878459/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6878459/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eForest ecosystems are currently experiencing the consequences of climate change, particularly increasing tree damage and mortality due to higher temperatures and longer droughts. This leads to changes in forest structure, with consequences for the abundance, diversity, and composition of organisms, as well as their provision of ecosystem functions. However, relatively little is known about how dung beetles, which are important for decomposition, respond to recent changes in forest characteristics and tree dieback.\u003c/p\u003e \u003cp\u003eWe monitored dung beetles and dung decomposition in 67 forest plots in Darmstadt, Germany. The structure of these plots varied considerably due to tree mortality caused by several years of drought and heatwaves, as well as former forest management practices in the study region.\u003c/p\u003e \u003cp\u003eThe total biomass, diversity, and species composition of dung beetles were strongly related to changes in forest structure, such as mean canopy openness, mean diameter at breast height, and forest ground cover. However, they were less related to within-plot structural heterogeneity. Higher dung beetle biomass was related to a higher dung decomposition rate, but changes in dung beetle diversity and community composition did not correlate with dung decomposition.\u003c/p\u003e \u003cp\u003eOur results suggest that changes in forest structure result in changes in the biomass, diversity, and composition of dung beetle communities. The relationships between dung beetles and structural heterogeneity were not particularly pronounced. This indicates that the effects of tree mortality on dung beetles and subsequent changes in dung decomposition are mediated by directed shifts in mean forest structure rather than structural heterogeneity.\u003c/p\u003e","manuscriptTitle":"Forest structural changes after tree dieback affect dung beetle communities and dung removal rates","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 06:22:02","doi":"10.21203/rs.3.rs-6878459/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"857cdfea-61ec-4aa0-a680-3e2b2b2123ec","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-30T05:20:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-01 06:22:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6878459","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6878459","identity":"rs-6878459","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}