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![A visual representation of the approach adopted in this study to investigate foraging habitat selection by nestling‐rearing snowfinches. [Colour figure can be viewed at wileyonlinelibrary.com]](publication/359895911/figure/fig1/AS:11431281180782918@1691707588511/A-visual-representation-of-the-approach-adopted-in-this-study-to-investigate-foraging.png)
A visual representation of the approach adopted in this study to investigate foraging habitat selection by nestling‐rearing snowfinches. [Colour figure can be viewed at wileyonlinelibrary.com]
Source publication
Fine‐scale habitat selection modelling can allow a mechanistic understanding of habitat selection processes, enabling better assessments of the effects of climate and habitat changes on biodiversity. Remotely sensed data provide an ever‐increasing amount of environmental and climatic variables at high spatio‐temporal resolutions, and a unique oppor...
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Human activities have caused a significant change in the function and services that ecosystems have provided to society since historical times. In mountainous landscapes, the regulation of services such as water quality or erosion control has been impacted by land use and land cover (LULC) changes, especially the loss and fragmentation of forest pa...
Citations
... In that sense, we observed a marked effect of the temperature-solar radiation interaction: snowfinches tend to forage in sunlit areas when ambient temperature is low, while with higher temperatures they prefer shady zones. This result confirms previous findings that relate foraging habitat use to the interaction between temperature and solar radiation in other alpine areas Alessandrini et al. 2022). Similar patterns have been reported for other alpine specialists like the Alpine marmot Marmota marmota (Ferrari et al. 2022) and the Alpine ibex Capra ibex (Aublet et al. 2009;Semenzato et al. 2021), raising further concern on the future of alpine species in relation to global warming. ...
In many mountain regions, tourism represents one of the main sources of income. Winter sports are often prevalent and, in the last decades, infrastructures linked to the ski industry have expanded worldwide in mountain ranges. Mountains are dramatically suffering the effects of climate change, many species are contracting or declining and ski‐pistes are predicted to shrink towards higher elevations. For high‐elevation ecosystems and species, the construction of ski‐pistes is a major issue, impacting on species such as alpine birds already threatened by climate change. Here, by assessing the ultimate drivers of habitat selection during the breeding season, we investigated the impacts of ski‐pistes in the Dolomites on the foraging behaviour of the white‐winged snowfinch Montifringilla nivalis, an iconic alpine bird highly threatened by climate change. Our results show that snowfinches, during the critical period of nestling rearing, prefer to forage on snow patches and short grass on medium slope, characteristics frequently found on the studied ski‐pistes. We also observed a marked effect of the temperature‐solar radiation interaction: snowfinches forage in sunlit areas when ambient temperature is low, while under higher temperatures they prefer shady zones, probably due to specific physiological/thermoregulatory requirements. Foraging snowfinches and ski‐pistes are associated with some shared environmental characteristics. This implies that the impact of ski‐pistes could be mitigated by adequate management targeted at maintaining short‐sward alpine grassland (e.g., through avoidance/reduction of machine grading and controlled grazing) and residual snow patches (preventing the complete levelling of the slope and maintaining shallow depressions in areas with lower solar radiation). Such strategies could contribute to reducing the ecological footprint of current and future ski resorts on alpine ecosystems.
... While not widely used in bird habitat studies, the NBR has been used to characterize vegetation regeneration due to its association with vegetation structure (White et al., 2017). TCT brightness, greenness and wetness variables describe the spectral characteristics of soil, vegetation, and soil/vegetation moisture (Crist & Cicone, 1984;Crist & Kauth, 1986) and have been used to model characteristics of forests (Healey et al., 2005;Stankova & Avetisyan, 2024), aspects of bird habitat (Alessandrini et al., 2022;Helmer et al., 2010;Moreira et al., 2022), and to predict ALS-derived structural attributes (e.g., Bolton et al., 2020). ...
... The high importance of FHD for Blue Tit only was surprising given that this attribute has a long history in bird habitat studies (e.g., since MacArthur & MacArthur, 1961) and has been found to be important in other studies, particularly studies of species diversity rather than single species occurrence (i.e., FHD was important to bird diversity in Melin et al., 2019). It was surprising that TCT variables were highly ranked given that these are not extensively used in previous bird habitat studies (with some exceptions, e.g., TCT variables have been found to be significant in Alessandrini et al., 2022;Moreira et al., 2022) but are more widely used in the remote sensing literature. ...
Remote sensing data capture ecologically important information that can be used to characterize, model and predict bird habitat. This study implements fusion techniques using Random Forests (RF) with spectral Landsat data and structural airborne laser scanning (ALS) data to scale habitat attributes through time and to characterize habitat for four bird species in dynamic young forest environments in the United Kingdom. We use multi-temporal (2000, 2005, 2012/13, 2015) multi-sensor (Landsat and ALS) data to (i) predict structural attributes via pixel-level fusion at 30 metre spatial resolution, (ii) model bird habitat via object-level fusion and compare with models based on ALS, Landsat and predicted structural attributes, and (iii) predict bird habitat through time (i.e., predict 2015 habitat based on 2000-2012 data). First, we found that models predicting mean height from spectral information had the highest accuracy, whilst maximum height, standard deviation of heights, foliage height diversity, canopy cover and canopy relief ratio had good accuracy, and entropy had low accuracy. The green band and the normalized burn ratio (NBR) were consistently important for prediction, with the red and shortwave infrared (SWIR) 1 bands also important. For all structural variables, high values were underpredicted and low values were overpredicted. Second, for Blue Tit ( Cyanistes caeruleus ) and Chaffinch ( Fringilla coelebs ), the most accurate model employed Landsat data, while object-level fusion performed best for Chiffchaff ( Phylloscopus collybita ) and Willow Warbler ( Phylloscopus trochilus ). ALS mean, maximum and standard deviation of heights and Landsat tasseled cap transformations (TCT) (i.e., wetness, greenness and brightness) were ranked as important to all species across various models. Third, we used our models to predict presence in 2015 and implemented a spatial intersection approach to assess the predictive accuracy for each species. Blue Tit and Willow Warbler presences were well predicted with the Landsat, ALS, and objectlevel fusion models. Chaffinch and Chiffchaff presences were best predicted with the ALS model. Predictions based on pixel-level predicted structure surfaces had low accuracy but were acceptable for Chaffinch and Willow Warbler. This study is significant as it provides guidance for Landsat and ALS data application and fusion in habitat modelling. Our results highlight the need to use appropriate remote sensing data for each study species based on their ecology. Object-level data fusion improved habitat characterization for all species relative to ALS, but not to Landsat for Blue Tit and Chaffinch. Pixel-level fusion for predicting structural attributes in years where ALS data are note available is increasingly being used in modelling but may not adequately represent within-patch wildlife habitat. Finally, incorporating predicted surfaces generated through pixel-level fusion in our habitat models yielded low accuracy.
Highlights
We used object- and pixel-level fusion with ALS and Landsat to examine bird habitat
Pixel-level fusion predicted surfaces yielded low accuracy in habitat models
Best models: Landsat (Blue Tit, Chaffinch); fusion (Chiffchaff, Willow Warbler)
Best prediction: ALS (Chaffinch, Chiffchaff)
Best prediction: ALS, Landsat, object-level fusion (Blue Tit, Willow Warbler)
Graphical abstract
... Moreover, in the case of range variation, we hypothesise that such changes could happen mainly by concentric retreats (i.e., abandoning peripheral areas) rather than by displacement (i.e., by colonising new areas in the future) (Hypothesis 2, "H2"); the prevalence of one of such patterns could be easily assessed by measuring the overlap between current and future suitable areas. A concentric retreat pattern could be expected because mountain orography and uneven distribution of cold microhabitat could limit dispersal (Ceresa et al., 2023), in particular when the species are habitat specialists (Alessandrini et al., 2022). Furthermore, by tracking their optimal thermal niche under a changing climate (Harvey et al., 2023), cold-adapted bumblebees should also undergo a strong upward shift in the average elevation of their occurrence sites and range (Hypothesis 3, "H3"). ...
... A crucial aspect of habitat selection is the utilisation of microhabitats, which refers to spatio-temporally discrete areas of varying spatial scales (in ornithological literature between 1 and 707 m 2 ; Morales et al. 2008;Patthey et al. 2012; see Alessandrini et al. 2022) that provide essential resources for various life-history functions (e.g., 4th order of habitat selection sensu Johnson 1980; Barbosa et al. 2010). Indeed, the use of the appropriate microhabitat influences individual fitness (Wagner and Fortin 2013;Bonner and Fritz 2015), both directly, by affecting species' survival and reproductive success (Wilson 1998;Jedlikowski and Brambilla 2017), and indirectly by improving foraging efficiency (Biscardi et al. 2007;Bowler et al. 2019), reducing costs of thermoregulation (du Plessis et al. 2012) and providing shelter from predators (Skelhorn and Ruxton 2013). ...
... Indeed, the use of the appropriate microhabitat influences individual fitness (Wagner and Fortin 2013;Bonner and Fritz 2015), both directly, by affecting species' survival and reproductive success (Wilson 1998;Jedlikowski and Brambilla 2017), and indirectly by improving foraging efficiency (Biscardi et al. 2007;Bowler et al. 2019), reducing costs of thermoregulation (du Plessis et al. 2012) and providing shelter from predators (Skelhorn and Ruxton 2013). Furthermore, studies investigating microhabitat use are becoming increasingly important in the context of climate change, as small-scale habitats can maximise the resilience and resistance of populations (i.e., refugia sites; Barbosa et al. 2010;Suggit et al. 2011, Frey et al. 2016Betts et al. 2017;Alessandrini et al. 2022). This may be pivotal in terms of biodiversity conservation, for example when the preservation of a species' entire geographic range is unfeasible, but the conservation of its habitats and microhabitats may be achievable. ...
... During the breeding period, snowfinches exhibit a well-established hierarchical pattern of microhabitat selection, with a preference for climate-sensitive microhabitats such as short-sward alpine grass and snow-grass margins Alessandrini et al. 2022). Our research not only confirmed this general trend but also highlighted the snowfinch remarkable capacity to fine-tune the relative use of different microhabitats in response to changes in prey availability. ...
Microhabitat utilisation holds a pivotal role in shaping a species’ ecological dynamics and stands as a crucial concern for effective conservation strategies. Despite its critical importance, microhabitat use has frequently been addressed as static, centering on microhabitat preference. Yet, a dynamic microhabitat use that allows individuals to adjust to fine-scale spatio-temporal prey fluctuations, becomes imperative for species thriving in challenging environments. High-elevation ecosystems, marked by brief growing seasons and distinct abiotic processes like snowmelt, winds, and solar radiation, feature an ephemeral distribution of key resources. To better understand species’ strategies in coping with these rapidly changing environments, we delved into the foraging behaviour of the white-winged snowfinch Montifringilla nivalis, an emblematic high-elevation passerine. Through studying microhabitat preferences during breeding while assessing invertebrate prey availability, we unveiled a highly flexible microhabitat use process. Notably, snowfinches exhibited specific microhabitat preferences, favoring grass and melting snow margins, while also responding to local invertebrate availability. This behaviour was particularly evident in snow-associated microhabitats and less pronounced amid tall grass. Moreover, our investigation underscored snowfinches’ fidelity to foraging sites, with over half located within 10 m of previous spots. This consistent use prevailed in snow-associated microhabitats and high-prey-density zones. These findings provide the first evidence of dynamic microhabitat use in high-elevation ecosystems and offer further insights into the crucial role of microhabitats for climate-sensitive species. They call for multi-faceted conservation strategies that go beyond identifying and protecting optimal thermal buffering areas in the face of global warming to also encompass locations hosting high invertebrate densities.
... This species is tightly connected to high mountain open areas above the treeline and its range includes some European mountain chains (Cantabrian mountains and Pyrenees, Alps, Apennines, mountains of Corsica and of the Balkan peninsula; Brambilla, Resano-Mayor, et al., 2020) and the main mountain systems of western and central Asia, up to Mongolia and western China (BirdLife International, 2022). Habitat needs during breeding are very specific, requiring both adequate nest sites like rock crevices or artificial structures and arthropod-rich foraging areas, represented by short grasslands and snow patches (Alessandrini et al., 2022;Brambilla et al., 2018;Resano-Mayor et al., 2019). The species is less specialized during the non-breeding period, though still associated with high mountain areas Resano-Mayor et al., 2017); during this period, the snowfinch usually performs erratic movements, often in large flocks, looking for food resources and some birds may also migrate over short distances (Resano-Mayor et al., 2017;. ...
Aim: High-elevation specialist species are threatened by climate change and habitat
loss, and their distributions are becoming increasingly reduced and fragmented. In such a context, dispersal ability is crucial to maintain gene flow among patches of suitable habitat. However, information about dispersal is often lacking for these species, especially for those taxa that are usually considered as good dispersers such as birds. We adopted a landscape genomics approach to investigate dispersal in a climate-sensitive high-elevation specialist bird. Our aims were to assess the levels of gene flow within a wide mountain area, and to assess the effects of geographic distance and landscape characteristics on dispersal, by testing the isolation by distance (IBD) hypothesis against the isolation by resistance (IBR) hypothesis.
Location: European Alps.
Taxon: Montifringilla nivalis.
Methods: We sampled individuals from several breeding areas and obtained single nucleotide polymorphism (SNP) data by ddRAD sequencing. We then calculated site-and individual level genetic distances and individual inbreeding coefficients. To test IBD versus IBR, we related genetic distances to both geographic distances and different measures of landscape resistance by using maximum likelihood population effects models.
Results: Gene flow among breeding areas was partly restricted, and we found support for IBD, indicating that geographic distance limits snowfinch dispersal. Spatial patterns of genetic distances suggested that philopatry strongly contributed to determine the observed IBD. High inbreeding coefficients in several individuals indicated frequent mating among relatives.
Main Conclusions: Restricted dispersal and frequent inbreeding within ‘sky island’
systems can also occur in highly mobile species, because their potential ability to
cover very large distances can be counteracted by high philopatry levels that are likely related to high dispersal costs. IBD and philopatry will increasingly hinder snowfinch dispersal among suitable areas within the future more restricted and fragmented breeding range, increasing the risks of local extinctions.
... The increasing availability of fine-scale environmental variables, made possible by for example progress in satellite imagery (Koma et al., 2022) and microclimate modeling (Klinges et al., 2022), will increase in turn the possibility of working out ecologically representative models at the territory/home-range scale, or at even finer grains, focusing on specific resources (Alessandrini et al., 2022). Fine-grain models may increase the possibility of effectively predicting the local abundance of more species and provide better tools for conservation and habitat management. ...
The use of species distribution models (SDMs) to predict local abundance has been often proposed and contested. We tested whether SDMs at different spatiotemporal resolutions may predict the local density of 14 bird species of open/semi‐open habitats. SDMs were built at 1 ha and 1 km, and with long‐term versus a mix of current and long‐term climatic variables. The estimated environmental suitability was used to predict local abundance obtained by means of 275 linear transects. We tested SDM ability to predict abundance for all sampled sites versus occurrence sites, using N‐mixture models to account for imperfect detection. Then, we related the R² of N‐mixture models to SDM traits. Fine‐grain SDMs appeared generally more robust than large‐grain ones. Considering the all‐transects models, for all species environmental suitability displayed a positive and highly significant effect at all the four combinations of spatial and temporal grains. When focusing only on occurrence transects, at the 1 km grain only one species showed a significant and positive effect. At the 1 ha grain, 62% of species models showed (over both climatic sets) a significant or nearly significant positive effect of environmental suitability on abundance. Grain was the only factor significantly affecting the model's explanatory power: 1 km grain led to lower amounts of variation explained by models. Our work re‐opens the debate about predicting abundance using SDM‐derived suitability, emphasizing the importance of grains and of spatiotemporal resolution more in general. The incorporation of local variables into SDMs at fine grains is key to predict local abundance. SDMs worked out at really fine grains, approaching the average size of territory or home range of target species, are needed to predict local abundance effectively. This may result from the fact that each single cell may represent a potential territory/home range, and hence a higher suitability over a given area means that more potential territories occur there.
... Moreover, in the case of range variation, we hypothesise that such changes could happen mainly by concentric retreats (i.e., abandoning peripheral areas) rather than by displacement (i.e., by colonising new areas in the future) (Hypothesis 2, "H2"). This pattern can be expected because mountain orography and uneven distribution of cold microhabitat could limit dispersal (Ceresa et al. 2023), in particular when the species are habitat specialists (Alessandrini et al. 2022). Furthermore, by tracking their optimal thermal niche under a changing climate (Harvey et al. 2023), cold-adapted bumblebees should also undergo a strong upward shift in the average elevation of their occurrence sites and range (Hypothesis 3, "H3"). ...
Cold-adapted species endangered by global change are crucial cases for understanding range dynamics and its interface with conservation. In view of climate change and their sensitivity, Alpine insects should modify their distribution by reducing ranges, while being unable of sufficient displacements and mostly moving uphill. To test these hypotheses, we targeted four threatened, high-altitude bumblebees differing in subgenera and elevation ranges, and covering the main central and south European mountains. We performed species distribution models including climate and habitat, and we described elevation uphill and the year of change with broken-line regressions. Results indicate that climate change will cause severe future range contractions across large areas, more in the Apennines (80% - 85% ca) than the Alps and Pyrenees (24 - 56% ca), with mostly concentric retreats as future extents will nearly entirely be included in the present ones. Remarkably, since the ‘80s elevation uplift has started by about 325 - 535 m, a period coinciding with the beginning of the main warming, and will continue. The size and distribution of climate refugia will challenge conservation: they will be small and context specific (2-60% of current areas), but while in the Apennines and Pyrenees they will be nearly entirely within Protected Areas, only a third will be so for the Alps. Such impressive distribution changes demonstrates that cold-adapted bumblebees can accurately track climate change and be precise sentinels of it, and these results link with the investigated species being specialists with specific habitat requirements of temperature and glacier presence. Overall, the distribution of cold specialist bumblebees driven by climate change demonstrates that conservation should act upon the dynamic realities of species ranges because their range reduction, the impossibility of finding new areas and the movement uphill emerge as consistent patterns.
... Fine-scaled models describing habitat use during the critical nestling-rearing phase have revealed an association with snow patches (Brambilla et al. 2017a(Brambilla et al. , 2019bResano-Mayor et al. 2019;Schano et al. 2021) and other climate-sensitive habitats, such as lowsward alpine grassland (Brambilla et al. 2018a, b). Microhabitat selection has also been shown to be affected by micro-climate, with foraging individuals adjusting habitat use according to air temperature (Alessandrini et al. 2022). All of these results have provided support for fine-scale associations with rather cold habitats which are perfectly mirrored at a larger scale by consistent effects of temperature on the broad species distribution: models developed at different spatial scales, from a 100 m radius to 2 x 2 km cells, have revealed a consistent link with low temperature (Brambilla et al. 2020c;de Gabriel-Hernando et al. 2021), which remained constant outside the areas used for model calibration (Brambilla et al. , 2017b, to the point that distribution models performed well even when projected to distant areas . ...
... Remote sensing has provided new environmental data (e.g., satellite images) that are helpful to distinguish new habitats (He et al. 2015;Randin et al. 2020), and to model the distributions of mountain birds (e.g., rock ptarmigan in Austria, Zohmann et al. 2013), down to very fine scales. As an example, Alessandrini et al. (2022) evaluated foraging habitat selection in white-winged snowfinches, highlighting a preference for intermediate vegetation cover, snow patches and higher heterogeneity, and an avoidance of extremely warm or cold micro-climates. Results matched previous knowledge based on accurate field measurements, and highlighted behavioural buffering against 'hot' conditions. ...
... Scales also matter: if micro-climate and microhabitats play a crucial role in driving distributions of mountain species (e.g., Frey et al. 2016b;Ceresa et al. 2020), fostering generalizable models at fine scales could promote conservation too, by allowing the identification of the characteristics (and their spatial arrangement) that make a site suitable for a species (e.g., Barras et al. 2020;Alessandrini et al. 2022). On the other hand, at the landscape level, potential climate refugia (Morelli et al. 2020), and the main 'corridors' connecting them from current to future occurrence sites (Brambilla et al. 2017b), represent key elements for conservation planning at this larger scale (Morelli et al. 2017). ...
Modelling distributions of species and communities is a key task for modern ecological research and conservation planning. Modelling mountain birds has specific challenges: mountain environments are characterized by steep gradients, where conditions in terms of climate, topography and habitat change markedly over relatively small scales. Moreover, mountain bird species are often less comprehensively monitored than lowland species, resulting in a general paucity of information for many species. We review the approaches to deal with these challenges in order to increase model accuracy to enhance ecological research and to improve conservation planning in mountain environments. We discuss how consistency between species occurrence and climate is tested, and what approaches help to assess distribution dynamics. We assess the current strategies to model microclimate and microhabitat, and how they could be incorporated in distribution modelling over increasingly larger extents. We discuss the pros and cons of (and the potential options for) modelling multiple species vs. community traits to get broad scale multi-species projections which are useful to evaluate the general persistence and resilience of mountain bird communities. Finally, the opportunities presented by Citizen Science data to contribute to monitoring and modelling mountain bird populations are assessed.
... Heterogenous landscapes increase resources available to birds (e.g., food, shelters) and may change their foraging behaviour (Schuldt et al., 2019) by influencing movement patterns (Jirinec et al., 2016) and species interactions (Seibold et al., 2013). In addition, landscape or habitat heterogeneity can also determine microclimatic conditions that could provide essential refugia in the face of climatic extremes, increasing habitat and bird resilience Virah-Sawmy et al., 2009), allowing e.g., alpine specialist species to avoid too warm microclimates (Alessandrini et al., 2022). The loss of heterogeneity is likely one of the main drivers of the farmland birds crisis (Benton et al., 2003), especially in intensive agricultural landscapes (Bat ary et al., 2011), which are currently undergoing major land use and land cover changes in many parts of Europe, including the Alps. ...
Understanding the main drivers of biodiversity loss in Europe's agricultural landscapes has been a research priority in the last decades. One of the most important factors promoting biodiversity in farmed landscapes is habitat heterogeneity, which has often proved crucial for avian species and communities. Birds are highly sensitive to environmental changes and make use of a broad range of ecological niches, thus being exceptionally sensitive to the loss of habitat heterogeneity. Remote sensing data are particularly suited to quantify habitat heterogeneity at fine scales over relatively large extents, allowing to consider how different measures of heterogeneity may affect biotic communities at a regional scale. Here, we used airborne LiDAR (Light Detection And Ranging) and satellite multispectral data to derive vegetation canopy height and primary productivity for 118 sites in complex agricultural landscapes in a region in the Central Alps. We computed different bird diversity indices and classified bird species into guilds according to specific traits to analyse the relationship between avian communities and different facets of habitat heterogeneity. Results confirmed that habitat heterogeneity is essential in shaping rich and diverse bird communities, and it is particularly important for several farmland birds. By comparing the effects of canopy height, primary productivity, and specific vegetation features (e.g., cover of grassland, shrub, and tree layers), we showed how different habitat characteristics as well as landscape heterogeneity affected bird richness, diversity, functional entropy, and trait patterns. Landscape and height heterogeneity, estimated by NDVI and LiDAR Rao's Q indices, strongly influenced all response variables, for example, high NDVI values promoted species diversity and ground-understory nesters, and shrub layer was important for ground-understory nesters and forest specialists. Finally, we provide recommendations for conservation practices and mitigation measures to improve bird diversity in agricultural landscapes.
... To characterize the winter microhabitat preferences of hazel grouse, we collected detailed microhabitat data from late December to early March 2017-2018 at occurrence points (location of hazel grouse faeces) and for an equal number of random locations (pseudo-absences) representative of the local environmental conditions (see Sect. 2.5.1 for more details) which were collected in order to create a perfectly balanced, matched design of 'cases' (droppings) and 'controls' (random location) for conditional logistic regression modelling, a technique commonly used in other studies (e.g. Brambilla et al. 2018;Alessandrini et al. 2022). At each site (i.e. ...
In contrast to old-growth forests, early-successional stands remain understudied despite potentially harbouring species of conservation interest. With this work, focused on hazel grouse Tetrastes bonasia , a cryptic and indicator species known to select for close-to-natural forests, we evaluated winter densities, home range, microhabitat selection and diet, combining DNA-based mark-recapture and metabarcoding from faecal samples. In total, 216 droppings, collected over 2 years along forest transects in the Italian Alps, were successfully genotyped and 43 individuals were identified. Density estimates were similar to values reported by other studies in the Alps with an average of 4.5 and 2.4 individuals/km ² in the first and second study year, respectively, and mean home ranges estimated at 0.95 km ² . According to habitat selection models and eDNA-based diet analysis, hazel grouse selected early-succession secondary-growth forests formed after the abandonment of traditional agropastoral activities. These forests, mostly composed of hazel Corylus avellana, Norway spruce Picea abies and Sorbus spp., provided winter food resources and shelter. The diet analysis also highlighted forest arthropods as a non-negligible source of food. Birds avoided areas subject to intensive browsing by ungulates; small forest roads seasonally closed to traffic had positive influence on hazel grouse (i.e. higher abundance of droppings), while roads open to traffic had no effect. Importantly, despite the high coverage of mature forest habitats of Community Interest (53% of our study area), droppings were more abundant in non-listed early-succession secondary forests with similar plant composition. Our results suggest that forest succession after agropastoral abandonment may be beneficial for some forest birds of conservation interest, while acknowledging its negative effects on the previous grassland biodiversity.
Graphical abstract
