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Large areas of Europe have been repeatedly affected by severe droughts. Stressed trees suffered from direct drought impacts such as water stress or heat and were also more susceptible to other biotic and abiotic stress agents and calamities. Monitoring such vulnerable forests area-wide is crucial to assess the highly dynamic climate change induced impacts not captured by traditional ground-based monitoring approaches. However, most remote sensing studies dealing with forest condition are either not species-specific, not accounting for morphological and climatic conditions across different regions, not considering natural variations in phenology or not including multiple disturbance agents. Here, we extract species-specific reflectance time series separately for seven natural regions covering Germany for 2016 to 2022. The seasonal evolution of these time series serves as reference for the detection of forest condition anomalies. We calculated a similarity metric – further called forest condition anomaly index (FCA) - between each single reflectance observation and the respective measurements within the reference time series, also considering the natural temporal deviations caused by phenology. Temporal aggregation of the FCA allows the generation of spatially comprehensive forest condition anomaly maps. We demonstrate that the FCA shows patterns related to fires, storms and insect infestations and found an overall agreement with state-of-the-art forest disturbance products using a threshold of FCA= -0.15 forest loss. Consequently, the FCA can be used to detect forest disturbances or linked with vegetation models to assess e.g. forest biomass or carbon flux.

Protected Areas contribute to the conservation of nature with associated cultural ecosystem services (CES) and values, such as recreational and educational opportunities, wildlife observation, scenic beauty, inspiration and sense of belonging. Informed management of Protected Areas needs to consider the distinct use and preferences for CES of different types of visitors to increase opportunities for nature experience while avoiding conflicts with biodiversity conservation. Therefore, it is important to understand the linkages between visitor characteristics and their demand for specific sets of CES, particularly in fragile mountain ecosystems. Here we do so by combining information from individual on-site surveys and participatory mapping of visitors in four European mountain Protected Areas. We analysed visitors’ frequency of use of eight CES and their socio-demographic information, identifying three clusters of visitors. We also assessed the spatial distribution of CES locations used by each visitor cluster. Our results highlight strong differences between clusters both in the most frequently experienced CES and in the spatial location where those CES were experienced. We suggest that a better understanding of visitors regarding the way they experience nature is relevant for the environmental management of mountain Protected Areas and their surroundings.

Alterations in the complement system have been reported in some people with psychotic disorder, including in pre-psychotic individuals, suggesting that complement pathway dysregulation may be a feature of the early psychosis phenotype. Measurement of complement protein expression in psychosis has been largely restricted to the blood from patients with established illness who were taking antipsychotic medication. The present study examined a range of complement proteins in blood and cerebrospinal fluid (CSF) derived from individuals at clinical high-risk for psychosis (CHR), antipsychotic-naïve first-episode psychosis (FEP) and healthy controls. A panel of complement proteins (C1q, C3, C3b/iC3b, C4, factor B and factor H) were quantified in serum and matched CSF in 72 participants [n = 23 individuals at CHR, n = 24 antipsychotic-naïve FEP, n = 25 healthy controls] using a multiplex immunoassay. Analysis of covariance was used to assess between-group differences in complement protein levels in serum and CSF. Pearson's correlation was used to assess the relationship between serum and CSF proteins, and between complement proteins and symptom severity. In serum, all proteins, except for C3, were significantly higher in FEP and CHR. While a trend was observed, protein levels in CSF did not statistically differ between groups and appeared to be impacted by BMI and sample storage time. Across the whole sample, serum and CSF protein levels were not correlated. In FEP, higher levels of serum classical and alternative grouped pathway components were correlated with symptom severity. Our exploratory study provides evidence for increased activity of the peripheral complement system in the psychosis spectrum, with such elevations varying with clinical severity. Further study of complement in CSF is warranted. Longitudinal investigations are required to elucidate whether complement proteins change peripherally and/or centrally with progression of psychotic illness.

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals’ 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AG

Assessing the environmental status of Protected Areas (PAs) is a challenging issue. To indicate that status, the identification of a common set of variables that are scientifically sound, and easy to assess and monitor by the PA practitioners, is particularly important. In this study, a set of 27 Essential Variables (EVs) for PA management was selected in a bottom-up process from 67 harmonised variables that describe the status of Ecosystem Functions and Structures, Ecosystem Services, and Threats in PAs. This bottom-up process involved 27 internationally recognised PAs, mostly European, with different level of protection, different extent, and a wide range of human-nature interactions. The EVs were selected by more than 120 practitioners, i.e. PA managers and rangers, as well as scientists, working in terrestrial and aquatic PAs. Across both terrestrial and aquatic PAs, scientists and practitioners largely identified the same variables as important. Data availability for these 27 EVs varied between PAs and averaged 67% across all studied PAs. As this set of EVs for PAs is defined through a bottom-up approach considering variables already in use both in management and research, it is more than for previous EVs likely to be adopted, applied and developed to record the status and changes in the ecological and socio-economic conditions of PAs and to forecast future changes. Thereby, the EVs for PAs present a common vocabulary and tool to enhance in a uniform way the (inter)national communication, exchange and comparison of information on the status of PAs between policy makers, scientists and PA managers. The perceived status of the EVs, on an average 3.6 on a scale to a maximum of 5, indicates the surveyed PAs are in a moderate to good environmental condition. Moreover, the EVs for PAs form a cost- and time-efficient tool for PA managers to monitor developments in essential elements of their PAs, including the potential for Societal Goods and Benefits (SG&B), and to (

17 juni 2022, Contains fulltext : 252380.pdf (Publisher’s version ) (Open Access), In our paper "Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data" (Global Ecology and Biogeography) we use GPS tracking data from 1,498 from 49 different species to evaluate the expert-based habitat suitability data from the International Union for Conservation of Nature (IUCN). Therefore, we used the GPS tracking data to estimate two measures of habitat suitability for each individual animal and habitat type: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN’s classification into suitable, marginal and unsuitable habitat types. Our results showed that IUCN habitat suitability data were in accordance with the GPS data (>95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a >50% probability of agreement based on proportional habitat use and selection ratios, respectively. These findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, our study shows that GPS tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data. In this dataset we provide the measures of habitat suitability for each individual and each habitat type, calculated using different methods. In addition, we provide data on the body mass and IUCN Red List category of the species, as well as whether the species can be considered a habitat specialist or habitat generalist.

Preliminary evidence indicates beneficial effects of omega-3 polyunsaturated fatty acids (PUFAs) in early psychosis. The present study investigates the molecular mechanism of omega-3 PUFA-associated therapeutic effects in clinical high-risk (CHR) participants. Plasma samples of 126 CHR psychosis participants at baseline and 6-months follow-up were included. Plasma protein levels were quantified using mass spectrometry and erythrocyte omega-3 PUFA levels were quantified using gas chromatography. We examined the relationship between change in polyunsaturated PUFAs (between baseline and 6-month follow-up) and follow-up plasma proteins. Using mediation analysis, we investigated whether plasma proteins mediated the relationship between change in omega-3 PUFAs and clinical outcomes. A 6-months change in omega-3 PUFAs was associated with 24 plasma proteins at follow-up. Pathway analysis revealed the complement and coagulation pathway as the main biological pathway to be associated with change in omega-3 PUFAs. Moreover, complement and coagulation pathway proteins significantly mediated the relationship between change in omega-3 PUFAs and clinical outcome at follow-up. The inflammatory protein complement C5 and protein S100A9 negatively mediated the relationship between change in omega-3 PUFAs and positive symptom severity, while C5 positively mediated the relationship between change in omega-3 and functional outcome. The relationship between change in omega-3 PUFAs and cognition was positively mediated through coagulation factor V and complement protein C1QB. Our findings provide evidence for a longitudinal association of omega-3 PUFAs with complement and coagulation protein changes in the blood. Further, the results suggest that an increase in omega-3 PUFAs decreases symptom severity and improves cognition in the CHR state through modulating effects of complement and coagulation proteins.

Reconciling conservation and socioeconomic development goals is key to sustainability but remains a source of fierce debate. Protected areas (PAs) are believed to play an essential role in achieving these seemingly conflicting goals. Yet, there is limited evidence as to whether PAs are actually achieving the two goals simultaneously.Here, we investigate when and to what extent synergies or trade-offs between biodiversity conservation and local socioeconomic development occur. To explore these relationships, we collected data across a wide range of socioeconomic settings through face-to-face survey with PA managers from 114 African and European PAs using structured questionnaire.We found synergies between biodiversity conservation and socioeconomic development for 62% of the PAs, albeit with significant differences between African (55%) and European PAs (75%). Moreover, the sustainability of PAs in conserving biodiversity was strongly correlated with the empowerment of the PA management and the involvement of local communities in PA planning and decision-making processes.Our results demonstrate that for PAs to promote synergies between biodiversity conservation and local socioeconomic development, and to enhance their long-term sustainability, they should invest in the empowerment of their respective management and involvement of local communities in their planning and management activities.

Protected area (PA) performance is thought to depend on effective conservation management and favourable socio-economic context. However, increasing evidence of continued biodiversity decline within PAs raises the question of whether fundamental ecological and socio-economic constraints might actually affect PA effectiveness. Here we quantify how threats to biodiversity, socio-economic context and conservation efforts play out across 114 PAs in 25 European and African countries. We found that even in the presence of highly favourable socio-economic context and conservation efforts, it is not possible to completely offset the intensity of threats and prevent biodiversity decline. Projections show that halting biodiversity decline across the studied PA network may require at least a 35% increase in conservation efforts over a decade. However, as PAs approach zero biodiversity loss, even greater efforts and resources would be needed because of the principle of diminishing marginal returns. Our findings point to limited effectiveness of PAs and their management that might not be possible to address by simply increasing resources. Additionally, the adoption of core design principles of sustainable systems that take into account the social–ecological contexts of PAs could help overcome the observed hurdles of limited effectiveness and thus better integrate PAs into sustainable development efforts.

Hunting and its impacts on wildlife are typically studied regionally, with a particular focus on the Global South. Hunting can, however, also undermine rewilding efforts or threaten wildlife in the Global North. Little is known about how hunting manifests under varying socioeconomic and ecological contexts across the Global South and North. Herein, we examined differences and commonalities in hunting characteristics across an exemplary Global South-North gradient approximated by the Human Development Index (HDI) using face-to-face interviews with 114 protected area (PA) managers in 25 African and European countries. Generally, we observed that hunting ranges from the illegal, economically motivated, and unsustainable hunting of herbivores in the South to the legal, socially and ecologically motivated hunting of ungulates within parks and the illegal hunting of mainly predators outside parks in the North. Commonalities across this Africa-Europe South-North gradient included increased conflict-related killings in human-dominated landscapes and decreased illegal hunting with beneficial community conditions, such as mutual trust resulting from community involvement in PA management. Nevertheless, local conditions cannot outweigh the strong effect of the HDI on unsustainable hunting. Our findings highlight regional challenges that require collaborative, integrative efforts in wildlife conservation across actors, while identified commonalities may outline universal mechanisms for achieving this goal.

Reconciling conservation and socioeconomic development goals is key to sustainability but remains a source of fierce debate. Protected areas (PAs) are believed to play an essential role in achieving these seemingly conflicting goals. Yet, there is limited evidence as to whether PAs are actually achieving the two goals simultaneously. Here, we investigate when and to what extent synergies or trade-offs between biodiversity conservation and local socioeconomic development occur. To explore these relationships, we collected data across a wide range of socioeconomic settings through face-to-face survey with PA managers from 114 African and European PAs using structured questionnaire. We found synergies between biodiversity conservation and socioeconomic development for 62% of the PAs, albeit with significant differences between African (55%) and European PAs (75%). Moreover, the sustainability of PAs in conserving biodiversity was strongly correlated with the empowerment of the PA management and the involvement of local communities in PA planning and decision-making processes. Our results demonstrate that for PAs to promote synergies between biodiversity conservation and local socioeconomic development, and to enhance their long-term sustainability, they should invest in the empowerment of their respective management and involvement of local communities in their planning and management activities.

Protected Area (PA) managers and policy makers need to determine and demonstrate the effectiveness of PA management and keep track of the conservation status in ways that are practical, scientifically sound and comparable among PAs in various terrestrial and aquatic environments. As most existing methods for measuring the managerial efficiency of PAs are restricted to specific elements of the management or a limited number of detailed environmental aspects, often without the participation of practitioners, we aim for a generally applicable method developed in close cooperation with PA managers; the Protection Level Index (PLI). PLI includes ecological, socio-economic, as well as managerial factors, and consists of twelve variables that together describe the state of a PA. Seven of those are derived from interviews with PA managers, and five of them are derived from GIS analyses. Data were obtained during face-to-face interviews with PA managers using a fixed protocol, thereby introducing a new way of incorporating the perception of the PA managers. PLI was tested in seven different PAs across Europe. The lowest final PLI score was for the Island Network of Protected Areas in La Palma and the highest final PLI score was for the Kalkalpen National Park. PLI is wider applicable than other related methods and more cost-effective. Therefore PLI can be used on a yearly basis to keep track of the progress of management activities and conservation status within and among (networks of) PAs.

IMPORTANCE: Biomarkers that are predictive of outcomes in individuals at risk of psychosis would facilitate individualized prognosis and stratification strategies. OBJECTIVE: To investigate whether proteomic biomarkers may aid prediction of transition to psychotic disorder in the clinical high-risk (CHR) state and adolescent psychotic experiences (PEs) in the general population. DESIGN, SETTING, AND PARTICIPANTS: This diagnostic study comprised 2 case-control studies nested within the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) and the Avon Longitudinal Study of Parents and Children (ALSPAC). EU-GEI is an international multisite prospective study of participants at CHR referred from local mental health services. ALSPAC is a United Kingdom-based general population birth cohort. Included were EU-GEI participants who met CHR criteria at baseline and ALSPAC participants who did not report PEs at age 12 years. Data were analyzed from September 2018 to April 2020. MAIN OUTCOMES AND MEASURES: In EU-GEI, transition status was assessed by the Comprehensive Assessment of At-Risk Mental States or contact with clinical services. In ALSPAC, PEs at age 18 years were assessed using the Psychosis-Like Symptoms Interview. Proteomic data were obtained from mass spectrometry of baseline plasma samples in EU-GEI and plasma samples at age 12 years in ALSPAC. Support vector machine learning algorithms were used to develop predictive models. RESULTS: The EU-GEI subsample (133 participants at CHR (mean [SD] age, 22.6 [4.5] years; 68 [51.1%] male) comprised 49 (36.8%) who developed psychosis and 84 (63.2%) who did not. A model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition outcome (area under the receiver operating characteristic curve [AUC], 0.95; positive predictive value [PPV], 75.0%; and negative predictive value [NPV], 98.6%). Functional analysis of differentially expr

Monitoring global biodiversity from space through remotely sensing geospatial patterns has high potential to add to our knowledge acquired by field observation. Although a framework of essential biodiversity variables (EBVs) is emerging for monitoring biodiversity, its poor alignment with remote sensing products hinders interpolation between field observations. This study compiles a comprehensive, prioritized list of remote sensing biodiversity products that can further improve the monitoring of geospatial biodiversity patterns, enhancing the EBV framework and its applicability. The ecosystem structure and ecosystem function EBV classes, which capture the biological effects of disturbance as well as habitat structure, are shown by an expert review process to be the most relevant, feasible, accurate and mature for direct monitoring of biodiversity from satellites. Biodiversity products that require satellite remote sensing of a finer resolution that is still under development are given lower priority (for example, for the EBV class species traits). Some EBVs are not directly measurable by remote sensing from space, specifically the EBV class genetic composition. Linking remote sensing products to EBVs will accelerate product generation, improving reporting on the state of biodiversity from local to global scales.

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.

Vegetation diversity and health is multidimensional and only partially understood due to its complexity. So far there is no single monitoring approach that can sufficiently assess and predict vegetation health and resilience. To gain a better understanding of the different remote sensing (RS) approaches that are available, this chapter reviews the range of Earth observation (EO) platforms, sensors, and techniques for assessing vegetation diversity. Platforms include close-range EO platforms, spectral laboratories, plant phenomics facilities, ecotrons, wireless sensor networks (WSNs), towers, air- and spaceborne EO platforms, and unmanned aerial systems (UAS). Sensors include spectrometers, optical imaging systems, Light Detection and Ranging (LiDAR), and radar. Applications and approaches to vegetation diversity modeling and mapping with air- and spaceborne EO data are also presented. The chapter concludes with recommendations for the future direction of monitoring vegetation diversity using RS.

The recolonization of wolves in European human-dominated landscapes poses a conservation challenge to protect this species and manage conflicts. The question of how humans can co-exist with large carnivores often triggers strong emotions. Here we provide an objective, science-based discussion on possible management approaches. Using existing knowledge on large carnivore management from Europe and other parts of the globe, we develop four potential wolf management scenarios; 1) population control, 2) protection and compensation, 3) fencing, 4) managing behaviour of wolf and man. For each scenario, we discuss its impact on wolf ecology, its prospects of reducing wolf-human conflicts and how it relates to current European legislation. Population control and fencing of local wolf populations are problematic because of their ecological impacts and conflicts with European legislation. In contrast, a no-interference approach does not have these problems but will likely increase human-wolf conflicts. Despite the large challenges in European, human-dominated landscapes, we argue that wolf management must focus on strengthening the separation between humans and wolves by influencing behaviour of wolves and humans on a fine spatio-temporal scale to prevent and reduce conflicts. As separation also demands a sufficiently large wild prey base, we urge restoring natural ungulate populations, to reduce human-wolf conflicts. Mutual avoidance provides the key to success, and is critical to avoid creating the conditions for reinstating wolf persecution as the default policy in Europe.

Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.

Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.