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Assessing the exposure of forest habitat types to projected climate change-implications for Bavarian protected areas
No full textAim: Due to their longevity and structure, forest ecosystems are particularly affected by climate change with consequences for their biodiversity, functioning, and services to mankind. In the European Union (EU), natural and seminatural forests are protected by the Habitats Directive and the Natura 2000 network. This study aimed to assess the exposure of three legally defined forest habitat types to climate change, namely (a) Tilio-Acerion forests of slopes, screes, and ravines (9180*), (b) bog woodlands (91D0*), and (c) alluvial forests with Alnus glutinosa and Fraxinus excelsior (91E0*). We analyzed possible changes in their Bavarian distribution, including their potential future coverage by Natura 2000 sites. We hypothesized that protected areas (PAs) with larger elevational ranges will remain suitable for the forests as they allow for altitudinal distribution shifts. Methods: To estimate changes in range size and coverage by PAs, we combined correlative species distribution models (SDMs) with spatial analyses. Ensembles of SDM algorithms were applied to two climate change scenarios (RCP4.5 and RCP8.5) of the HadGEM2-ES model for the period 2061-2080. Results: Our results revealed that bog woodlands experience the highest range losses (>2/3) and lowest PA coverage (max. 15% of sites with suitable conditions). Tilio-Acerion forests exhibit opposing trends depending on the scenario, while alluvial forests are less exposed to climatic changes. As expected, the impacts of climate change are more pronounced under the "business as usual" scenario (RCP8.5). Additionally, PAs in flat landscapes are more likely to lose environmental suitability for currently established forest habitat types. Main conclusions: Based on these findings, we advocate the expansion of the Natura 2000 network particularly in consideration of elevational gradients, connectivity, and projected climatic suitability. Nonclimatic stressors on forest ecosystems, especially bog woodlands, should be decreased and climate change mitigation efforts enhanced. We recommend transferring the approach to other habitat types and regions
Climatic and socioeconomic effects on land cover changes across Europe: Does protected area designation matter?
No full textLand cover change is a dynamic phenomenon driven by synergetic biophysical and socioeconomic effects. It involves massive transitions from natural to less natural habitats and thereby threatens ecosystems and the services they provide. To retain intact ecosystems and reduce land cover change to a minimum of natural transition processes, a dense network of protected areas has been established across Europe. However, even protected areas and in particular the zones around protected areas have been shown to undergo land cover changes. The aim of our study was to compare land cover changes in protected areas, non-protected areas, and 1 km buffer zones around protected areas and analyse their relationship to climatic and socioeconomic factors across Europe between 2000 and 2012 based on earth observation data. We investigated land cover flows describing major change processes: urbanisation, afforestation, deforestation, intensification of agriculture, extensification of agriculture, and formation of water bodies. Based on boosted regression trees, we modelled correlations between land cover flows and climatic and socioeconomic factors. The results show that land cover changes were most frequent in 1 km buffer zones around protected areas (3.0% of all buffer areas affected). Overall, land cover changes within protected areas were less frequent than outside, although they still amounted to 18,800 km2 (1.5% of all protected areas) from 2000 to 2012. In some parts of Europe, urbanisation and intensification of agriculture still accounted for up to 25% of land cover changes within protected areas. Modelling revealed meaningful relationships between land cover changes and a combination of influencing factors. Demographic factors (accessibility to cities and population density) were most important for coarse-scale patterns of land cover changes, whereas fine-scale patterns were most related to longitude (representing the general east/west economic gradient) and latitude (representing the north/south climatic gradient)
Predicting the effectiveness of protected areas of Natura 2000 under climate change
No full textBackground: Protected areas (PAs) are aimed to hold the environmental conditions that facilitate species and ecosystems to persist. PAs can become climatically unsuitable and unable to sustain their current number of species under climate change. The Natura 2000 (N2K) is the largest coordinated conservation tool assigned to maintain the long-term survival of Europe\u27s most significant species and habitats. In attempting to understand the effectiveness of PAs in the face of climate change scenarios, we tested two hypotheses: (1) PAs in the Alpine and the Boreal biogeographical regions will experience more newly emerged climate conditions (hotter and drier) compared to the climate representation of other biogeographical regions under future climate in Europe and (2) PAs in the Mediterranean and the Continental biogeographical regions will face more consistency in climate conditions due to less area of disappearing and novel climate in future. Methods: Current climate data (1960-1990) and projections for 2050 and 2070 of PAs of N2K were extracted from WorldClim global climate data. Principal components analysis (PCA) was performed to construct climate space for the PAs across the biogeographical regions based on 19 climatic variables assessed at 5-km resolution. ArcMap 10.1 was used to map the location of the novel and disappearing climates. Results: PAs in the Alpine region will experience more novel climate conditions in the future compared to other biogeographical regions. The future projections showed that 17.70% of the PAs in the Alpine region will experience novel climate by 2070. Considerable climate consistency was observed in the PAs in the Continental region compared to the other biogeographical regions. Our results showed that about 176 km2 of the selected PAs in the Continental region will face new emerging climate, while about 110 km2 will disappear under RCP 8.5 scenario. The prediction also revealed that in the Mediterranean region 08 PAs will experience novel climate and 786 km2 areas in these PAs will face disappearing climate by 2070. We found that fewer areas of PAs in the Boreal regions will experience disappearing climate in both the scenarios. Conclusions: The portion of novel climate conditions can be seen as a future opportunity to assign new reserves for the species. Our study highlights the importance of conservation planning to increase the connectivity between PAs, identifying novel conservation zones to maximize representation of habitats during the emerging climatic changes as well as designing strategies, management, and monitoring of the individual PAs
Effects of species traits and environmental predictors on performance and transferability of ecological niche models
No full textThe ability of ecological niche models (ENMs) to produce robust predictions for different time frames (i.e. temporal transferability) may be hindered by a lack of ecologically relevant predictors. Model performance may also be affected by species traits, which may reflect different responses to processes controlling species distribution. In this study, we tested four primary hypotheses involving the role of species traits and environmental predictors in ENM performance and transferability. We compared the predictive accuracy of ENMs based upon (1) climate, (2) land-use/cover (LULC) and (3) ecosystem functional attributes (EFAs), and (4) the combination of these factors for 27 bird species within and beyond the time frame of model calibration. The combination of these factors significantly increased both model performance and transferability, highlighting the need to integrate climate, LULC and EFAs to improve biodiversity projections. However, the overall model transferability was low (being only acceptable for less than 25% of species), even under a hierarchical modelling approach, which calls for great caution in the use of ENMs to predict bird distributions under global change scenarios. Our findings also indicate that positive effects of species traits on predictive accuracy within model calibration are not necessarily translated into higher temporal transferability
Butterfly distribution along altitudinal gradients: temporal changes over a short time period.
No full textMountain ecosystems are particularly sensitive to changes in climate and land cover, but at the same time, they can offer important refuges for species on the opposite of the more altered lowlands. To explore the potential role of mountain ecosystems in butterfly conservation and to assess the vulnerability of the alpine species, we analyzed the short-term changes (2006-2008 vs. 2012-2013) of butterflies\u27 distribution along altitudinal gradients in the NW Italian Alps. We sampled butterfly communities once a month (62 sampling stations, 3 seasonal replicates per year, from June to August) by semi-quantitative sampling techniques. The monitored gradient ranges from the montane to the alpine belt (600-2700 m a.s.l.) within three protected areas: Gran Paradiso National Park (LTER, Sitecode: LTER_EU_IT_109), Orsiera Rocciavr? Natural Park and Veglia Devero Natural Park. We investigated butterflies\u27 temporal changes in accordance with a hierarchical approach to assess potential relationships between species and community level. As a first step, we characterized each species in terms of habitat requirements, elevational range and temperature preferences and we compared plot occupancy and altitudinal range changes between time periods (2006-2008 vs. 2012-2013). Secondly, we focused on community level, analyzing species richness and community composition temporal changes. The species level analysis highlighted a general increase in mean occupancy level and significant changes at both altitudinal boundaries. Looking at the ecological groups, we observed an increase of generalist and highly mobile species at the expense of the specialist and less mobile ones. For the community level, we noticed a significant increase in species richness, in the community temperature index and a tendency towards homogenization within communities. Besides the short time period considered, butterflies species distribution and communities changed considerably. In light of these results, it is fundamental to continue monitoring activities to understand if we are facing transient changes or first signals of an imminent trend
Web of interactions among diversity approaches to identify ecosystem essential variables: Negev Highlands case study.
No full textThe concept of ecosystem diversity essential variables (EEVs) offers a foundation for ecosystem studies. Identification of EEVs continues to be a challenge in the field of ecology, due to the lack of a conceptual and applied framework. This paper develops a conceptual framework, offering theoretical foundation and a methodology for identifying EEVs, reflecting essential biodiversity and geodiversity variables. We start with a conceptual model of ecosystem essential variables linking biodiversity and geodiversity processes into ecosystem diversity as a web of interactions (WoI). The WoI components and interactions enable the identification of EEVs and their essentiality by relating interactions among diversities to variables that identify them. We tested our conceptual pass way by analyzing drivers and feedbacks of ecosystem processes in the Negev Highlands. Based on the general models and research of the Negev Highlands, we present four steps for EEVs: (1) developing a general conceptual model of the abiotic and biotic components of the ecosystem that links both biodiversity and geodiversity and their interactions; (2) testing the validity of the general model for a specific ecosystem to find out the hydro-?geo-?ecological drivers and feedbacks controlling ecosystem diversity; (3) constructing a WoI that adds to the regular analysis of an ecosystem as an interaction among geodiversity and biodiversity by breaking down the two components of diversities into subcomponent and their interactions; and (4) translating of the WoI components and interactions to EEVs. We suggest that EEVs should be related not only to the components but also to the interactions among diversities. These steps are essential for developing a scientific framework that allows for systematic identification of EEVs and justification regarding the final selection of the essential variables. We suggest that the approach can potentially be applied to all global terrestrial system
Identifying vegetation in arid regions using object-based image analysis with RGB-only aerial imagery.
No full textVegetation state is usually assessed by calculating vegetation indices (VIs) derived from remote sensing systems where the near infrared (NIR) band is used to enhance the vegetation signal. However VIs are pixel-based and require both visible and NIR bands. Yet, most archived photographs were obtained with cameras that record only the three visible bands. Attempts to construct VIs with the visible bands alone have shown only limited success, especially in drylands. The current study identifies vegetation patches in the hyperarid Israeli desert using only the visible bands from aerial photographs by adapting an alternative geospatial object-based image analysis (GEOBIA) routine, together with recent improvements in preprocessing. The preprocessing step selects a balanced threshold value for image segmentation using unsupervised parameter optimization. Then the images undergo two processes: segmentation and classification. After tallying modeled vegetation patches that overlap true tree locations, both true positive and false positive rates are obtained from the classification and receiver operating characteristic (ROC) curves are plotted. The results show successful identification of vegetation patches in multiple zones from each study area, with area under the ROC curve values between 0.72 and 0.8
Size dependency of patch departure behavior: evidence from granivorous rodents
No full textIndividual size is a major determinant of mobile organisms\u27 ecology and behavior. This study aims to explore whether allometric scaling principles can provide an underlying framework for general patterns of resource patch use. To this end, we used giving-up densities (GUDs), that is, the amount of resources remaining in a patch after a forager has quit feeding, as a comparative measure of the amount of resources exploited by a forager of any given size. We specifically tested the hypothesis that size-dependent responses to both internal (energy requirement) and external (risk management) forces may have an effect on GUDs. We addressed this topic by conducting an extensive meta-analysis of published data on granivorous rodents, including 292 GUD measurements reported in 25 papers. The data set includes data on 22 granivorous rodent species belonging to three taxonomic suborders (Castorimorpha, Myomorpha, and Sciuromorpha) and spans three habitat types (desert, grassland, and forest). The observations refer to both patches subject to predation risk and safe patches. Pooling all data, we observed positive allometric scaling of GUDs with average forager size (scaling exponent = 0.45), which explained 15% of overall variance in individual GUDs. Perceived predation risk during foraging led to an increase in GUDs independently of forager size and taxonomy and of habitat type, which explained an additional 12% of overall GUD variance. The size scaling exponent of GUDs is positive across habitat types and taxonomic suborders of rodents. Some variation was observed, however. The scaling coefficients in grassland and forest habitat types were significantly higher than in the desert habitat type. In addition, Sciuromorpha and Myomorpha exhibited a more pronounced size scaling of GUDs than Castorimorpha. This suggests that different adaptive behaviors may be used in different contexts and/or from different foragers. With body size being a fundamental ecological descriptor, research into size scaling of GUDs may help to place patch-use observations in a broader allometric framework
Reconstruction of long-distance bird migration routes using advanced machine learning techniques on geolocator data
No full textGeolocators are a well-established technology to reconstruct migration routes of animals that are too small to carry satellite tags (e.g. passerine birds). These devices record environmental light-level data that enable the reconstruction of daily positions from the time of twilight. However, all current methods for analysing geolocator data require manual pre-processing of raw records to eliminate twilight events showing unnatural variation in light levels, a step that is time-consuming and must be accomplished by a trained expert. Here, we propose and implement advanced machine learning techniques to automate this procedure and we apply them to 108 migration tracks of barn swallows (Hirundo rustica). We show that routes reconstructed from the automated pre-processing are comparable to those obtained from manual selection accomplished by a human expert. This raises the possibility of fully automating light-level geolocator data analysis and possibly analysing the large amount of data already collected on several species
A Bayesian approach to ecosystem service trade-off analysis utilizing expert knowledge
No full textThe concept of ecosystem services is gaining attention in the context of sustainable resource management. However, it is inherently difficult to account for tangible and intangible services in a combined model. The aim of this study is to extend the definition of ecosystem service trade-offs by using Bayesian Networks to capture the relationship between tangible and intangible ecosystem services. Tested is the potential of creating such a network based on existing literature and enhancement via expert elicitation. This study discusses the significance of expert elicitation to enhance the value of a Bayesian Network in data-restricted case studies, underlines the importance of inclusion of experts\u27 certainty, and demonstrates how multiple sources of knowledge can be combined into one model accounting for both tangible and intangible ecosystem services. Bayesian Networks appear to be a promising tool in this context, nevertheless, this approach is still in need of further refinement in structure and applicable guidelines for expert involvement and elicitation for a more unified methodology