The next generation of site-based long-term ecological monitoring: Linking essential biodiversity variables and ecosystem integrity

The added value of the long-term ecological research network to upscale restoration in Europe

Achieving global restoration targets poses challenges including the need for long-term research and effective monitoring of success, fostering collaborations across diverse fields and actors, ensuring the availability of suitable reference ecosystems, and securing sustained funding. Yet, these conditions are often lacking, limiting the effectiveness of restoration. We provide an overview of ecological restoration practices in the pan-European region of the Long-term Ecological Research Network (eLTER) and demonstrate the importance of eLTER and its potential contributions to support the implementation of the EU Nature Restoration Law. We developed an online questionnaire to collect information on eLTER restoration experts and restoration projects details including the use of eLTER contributions (e.g. infrastructure, data and knowledge), between November 2021 and March 2022. We identified 62 restoration experts and 42 restoration projects from 18 countries. Our results show that eLTER restoration expertise covers most of the European habitats, diverse degradation states and restoration techniques. Most restoration projects (78%) involved long-term monitoring exceeding the average project lifespan, which has proven necessary to achieve restoration success. No common protocol was used for monitoring and evaluation or cost-benefit estimates, but respondents reported effective projects, mostly financed from national funds, and benefits in five ecosystem services on average covered per project. Key eLTER contributions included providing reference ecosystems, biotic and abiotic background data, and interdisciplinary discussion or stakeholder management. Ecological restoration is time intensive and requires long-term research and monitoring standardization to fully understand the restoration process and to ensure comparability across ecosystems. The eLTER network can help address these challenges providing added-value contributions through its infrastructure, long-term datasets, diversity of expertise and strategies that can help identify best restoration practices and support the EU Nature Restoration Law. Finally, additional and long-term funding from the EU and the private sector is needed to achieve global larger-scale restoration targets.

Variation in ecological scorecards and their potential for wider use

Ecological monitoring is a vital tool to help us assess habitat condition and understand the mechanism(s) for habitat change. Yet many countries struggle to meet their monitoring requirements in part due to the high assessment workload. Rapid ecological assessment methods may have an important role to play in this regard. Following their success within several European habitats (e.g., semi-natural grasslands), they are now being developed for additional habitats such as heathlands, peatlands, and other agri-associated areas. Whilst some rapid assessments using ecological scorecards have been shown to be accurate compared to traditional ecological monitoring, less is known about the functionality of these scorecards in heterogenous landscapes. In this study, we selected four existing scorecards to test alongside a prototype. We assessed how these different scorecards measured habitat condition on the same heathland sites. We found that the choice of metrics, their score weighting, and the thresholds used for categorical scores cause scorecards to assess the same site with substantial variation (37%). Vegetation metrics were the primary cause of score variation, with vegetation structure and positive indicator species being the leading causes. Our study indicates that whilst current scorecards may be representative of project-specific goals, they may not be suitable for wider monitoring uses in their current form. Ecological scorecards have great potential to drastically increase the extent of monitoring, but caution is needed before adapting existing scorecards beyond the purposes from which they were designed.

Stream macroinvertebrate communities in restored and impacted catchments respond differently to climate, land-use, and runoff over a decade

Identifying which environmental drivers underlie degradation and improvements of ecological communities is a fundamental goal of ecology. Achieving this goal is a challenge due to diverse trends in both environmental conditions and ecological communities across regions, and it is constrained by the lack of long-term parallel monitoring of environmental and community data needed to study causal relationships. Here, we identify key environmental drivers using a high-resolution environmental - ecological dataset, an ensemble of the Soil and Water Assessment Tool (SWAT+) model, and ecological models to investigate effects of climate, land-use, and runoff on the decadal trend (2012-2021) of stream macroinvertebrate communities in a restored urban catchment and an impacted catchment with mixed land-uses in Germany. The decadal trends showed decreased precipitation, increased temperature, and reduced anthropogenic land-uses, which led to opposing runoff trends - with decreased runoff in the restored catchment and increased runoff in the impacted catchment. The two catchments also varied in decadal trends of taxonomic and trait composition and metrics. The most significant improvements over time were recorded in communities of the restored catchment sites, which have become wastewater free since 2007 to 2009. Within the restored catchment sites, community metric trends were primarily explained by land-use and evaporation trends, while community composition trends were mostly associated with precipitation and runoff trends. Meanwhile, the communities in the impacted catchment did not undergo significant changes between 2012 and 2021, likely influenced by the effects of prolonged droughts following floods after 2018. The results of our study confirm the significance of restoration and land-use management in fostering long-term improvements in stream communities, while climate change remains a prodigious threat. The coupling of long-term biodiversity monitoring with concurrent sampling of relevant environmental drivers is critical for preventative and restorative management in ecology.

Quantifying multi-dimensional services of water ecosystems and breakpoint-based spatial radiation of typical regulating services considering the hierarchical clustering-based classification

This study proposes a set of water ecosystem services (WES) research system, including classification, benefit quantification and spatial radiation effect, with the goal of promoting harmonious coexistence between humans and nature, as well as providing a theoretical foundation for optimizing water resources management. Hierarchical cluster analysis was applied to categorize WES taking in to account the four nature constraints of product nature, energy flow relationships, circularity, and human social utility. A multi-dimensional benefit quantification methodology system for WES was constructed by combining the emergy theory with multidisciplinary methods of ecology, economics, and sociology. Based on the theories of spatial autocorrelation and breaking point, we investigated the spatial radiation effects of typical services in the cyclic regulation category. The proposed methodology has been applied to Luoyang, China. The results show that the Resource Provisioning (RP) and Cultural Addition (CA) services change greatly over time, and drive the overall WES to increase and then decrease. The spatial and temporal distribution of water resources is uneven, with WES being slightly better in the southern region than the northern region. Additionally, spatial radiation effects of typical regulating services are most prominent in S County. This finding suggests the establishment of scientific and rational intra-basin or inter-basin water management systems to expand the beneficial impacts of water-rich areas on neighboring regions.

Vertical distribution rules and factors influencing phytoplankton in front of a drinking water reservoir outlet

The phenomenon of algal blooms caused by the excessive proliferation of phytoplankton in drinking water reservoirs is becoming increasingly frequent, seriously endangering water quality, ecosystems, water safety, and people's health. Thus, there is urgent need to conduct research on the distribution rules and factors influencing phytoplankton in drinking water reservoirs. Given that the outflows from reservoirs usually come from the middle and lower layers of the water column and the current studies on phytoplankton in drinking water reservoirs are usually carried out on the surface, an 8-month monitoring of vertical phytoplankton and the corresponding influencing factors in front of the outlet in a drinking water reservoir was conducted. Based on the monitoring results, the distribution rules of phytoplankton and the associated factors were analyzed. The results showed that phytoplankton biomass significantly decreased with increasing water depth, but the biomass near the outlet (40 m depth) still reached the WHO level 2 warning threshold for algal blooms multiple times. During the monitoring period, Cyanophyta, Chlorophyta and Bacillariophyta dominated. The selected multisource environmental factors explained 60.5 % of the spatiotemporal changes in phytoplankton, with thermal intensity (water temperature and thermal stratification intensity) being the driving factor. Meanwhile, excessive TN and TP provided necessary conditions for the growth of phytoplankton. Based on influencing factors, reducing upstream nutrient inflows and thermal stratification intensity are recommended as measures to prevent and control algal blooms. This study provides insights into the vertical distribution rules and factors influencing phytoplankton in a drinking water reservoir, which can provide a reference for the management of drinking water reservoirs and the prevention and control of algal blooms.

The recovery of European freshwater biodiversity has come to a halt

Owing to a long history of anthropogenic pressures, freshwater ecosystems are among the most vulnerable to biodiversity loss1. Mitigation measures, including wastewater treatment and hydromorphological restoration, have aimed to improve environmental quality and foster the recovery of freshwater biodiversity2. Here, using 1,816 time series of freshwater invertebrate communities collected across 22 European countries between 1968 and 2020, we quantified temporal trends in taxonomic and functional diversity and their responses to environmental pressures and gradients. We observed overall increases in taxon richness (0.73% per year), functional richness (2.4% per year) and abundance (1.17% per year). However, these increases primarily occurred before the 2010s, and have since plateaued. Freshwater communities downstream of dams, urban areas and cropland were less likely to experience recovery. Communities at sites with faster rates of warming had fewer gains in taxon richness, functional richness and abundance. Although biodiversity gains in the 1990s and 2000s probably reflect the effectiveness of water-quality improvements and restoration projects, the decelerating trajectory in the 2010s suggests that the current measures offer diminishing returns. Given new and persistent pressures on freshwater ecosystems, including emerging pollutants, climate change and the spread of invasive species, we call for additional mitigation to revive the recovery of freshwater biodiversity.

Chilean long-term Socio-Ecological Research Network: progresses and challenges towards improving stewardship of unique ecosystems

Ecosystems provide a variety of benefits to human society and humanity’s utilization of ecosystems affects their composition, structure, and functions. Global change drivers demand us to study the interactions between ecological and social systems, and advise strategies to protect the large fraction of Chilean unique ecosystems. Long-term research and monitoring are vital for meaningful understanding of human impacts and socio-ecological feedback, which occur over multiple spatial and time-scales and can be invisible to traditional grant-sponsored short-term studies.

Despite the large fraction of unique ecosystems, Chilean government agencies have not established long-term monitoring programs to inform and guide management decisions for use, conservation, and adaptation to climate change. Responding to this void, the Chilean Long-Term Socio-Ecological Research Network (LTSER-Chile) was created, comprising nine study sites funded by a variety of private and public institutions, that broadly seeks to understand how global change is altering biodiversity and ecosystem functions. The LTSER-Chile is currently in a phase of institutional consolidation to achieve its objectives of alignment with international efforts, fill the need for high-quality, long-term data on social, biological and physical components of Chilean ecosystems, and develop itself as an open research platform for the world. Despite the wide diversity of ecosystems ecncompased by LTSER-Chile sites, several common variables are monitored, especially climatic and hydrographic variables and many ecological indicator variables that consider temporal fluctuations, population and community dynamics.

The main challenges currently facing the LTSER-Chile are to secure funding to maintain existing long-term monitoring programs, to persuade public and private decision-makers about its central role in informing and anticipating socio-ecological problems, and to achieve greater ecosystem representation by integrating new long-term study sites. This will require a more decisive political commitment of the State, to improve the stewardship of our unique terrestrial and marine ecosystems, and the realization that sound ecologically-sustainable policies will never be possible without a national monitoring network. We argue that the State should build on LTSER and several other private and university initiatives to provide the country with a monitoring network. In the absence of this commitment, the LTSER system is subject to discontinuity and frequent interruptions, which jeopardizes the long-term effort to understand the functioning of nature and its biodiversity.

Freshwater trophic status mediates microbial community assembly and interdomain network complexity

Freshwater microorganisms and their interactions are important drivers of nutrient cycling that are in turn affected by nutrient status, causing shifts in microbial community diversity, composition, and interactions. However, the impact of water trophic status on bacterial-archaeal interdomain interactions remains poorly understood. This study focused on the impact of trophic status, as characterized by trophic state index (TSI), on the interdomain interactions of freshwater microbial communities from 45 ponds in Hangzhou. Our results showed that the mesotrophic wetland bordering on lightly eutrophic (Hemu: TSI of 49; lightly eutrophic is defined as 50 ≤ TSI <60) harbored a much more complex bacterial-archaeal interdomain network, which showed significantly (P < 0.05) higher connectivity than the wetlands with lower (TSI of 38) or higher (TSI of 57) trophic levels. Notably, light eutrophication strengthened the network modules' negative associations with organic carbon through some network hubs, which could trigger carbon loss in wetlands. We also detected a non-linear response of interdomain network complexity to the increasing of nutrients with a turning point of approximately TSI 50. Quantitative estimates of community assembly processes and structural equation modelling analysis indicated that chlorophyll-a, total nitrogen, and total phosphorus could regulate interdomain network complexity (50% of the variation explanation rate) by driving microbial community assembly. This study demonstrates that microbial interdomain network complexity could be used as a bioindicator for ecological changes, which would helpful for improving ecological assessment of the freshwater eutrophication.

Improvement of ecosystem quality in National Key Ecological Function Zones in China during 2000-2015

Improving ecosystem quality is the ultimate goal of ecological restoration projects and sustainable ecosystem management. However, previous results of ecosystem quality lack comparability among different regions when assessing the effectiveness of ecological restoration projects on the regional or national scales, due to the influence of geographical and climatic background conditions. Here we proposed a new index, ecosystem quality ratio (EQR), by integrating the status of landscape structure, ecosystem services, ecosystem stability, and human disturbance relative to their reference conditions, and assessed the EQR changes in China's counties and National Key Ecological Function Zones (NKEFZs) from 1990 to 2015. The results showed that the average ecosystem quality of China's counties deviated from the reference condition by 28%. EQR decreased by 1.2% during 1990-2000 but increased by 3.7% during 2000-2015. Those counties with increasing EQR in 2000-2015 occupy 64.7%, with obviously increasing counties mainly located in the water conservation, biodiversity maintenance, and water and soil conservation types of NKEFZs. The EQR increase in counties within NKEFZs was 3.65 times that outside of NKEFZs. Remarkable improvement of ecosystem quality occurred in the forest region in Changbai Mountain, biodiversity and soil conservation region in Wuling Mountains, and hilly and gully region of Loess Plateau, where EQR increases mainly resulted from the conversion of farmland to forest or grassland and consequent increases in ecosystem services and stability. The magnitude of EQR enhancement showed a positive relationship with the increase in forest and grassland coverage in NKEFZs. Our results highlight the important role of ecological restoration projects in improving ecosystem quality in China, and demonstrate the feasibility of the new index (EQR) for the assessment of ecosystem quality in terms of ecosystem management and restoration.

Long-term monitoring projects of Brazilian marine and coastal ecosystems

Biodiversity assessment is a mandatory task for sustainable and adaptive management for the next decade, and long-term ecological monitoring programs are a cornerstone for understanding changes in ecosystems. The Brazilian Long-Term Ecological Research Program (PELD) is an integrated effort model supported by public funds that finance ecological studies at 34 locations. By interviewing and compiling data from project coordinators, we assessed monitoring efforts, targeting biological groups and scientific production from nine PELD projects encompassing coastal lagoons to mesophotic reefs and oceanic islands. Reef environments and fish groups were the most often studied within the long-term projects. PELD projects covered priority areas for conservation but missed sensitive areas close to large cities, as well as underrepresenting ecosystems on the North and Northeast Brazilian coast. Long-term monitoring projects in marine and coastal environments in Brazil are recent (<5 years), not yet integrated as a network, but scientifically productive with considerable relevance for academic and human resources training. Scientific production increased exponentially with project age, despite interruption and shortage of funding during their history. From our diagnosis, we recommend some actions to fill in observed gaps, such as: enhancing projects' collaboration and integration; focusing on priority regions for new projects; broadening the scope of monitored variables; and, maintenance of funding for existing projects.

Decomposing predictability to identify dominant causal drivers in complex ecosystems

Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of different levels of stochasticity and nonlinearity, handling these data is a challenge for existing methods of time series-based causal inferences. Here, we show that, by harnessing contemporary machine learning approaches, the concept of Granger causality can be effectively extended to the analysis of complex ecosystem time series and bridge the gap between dynamical and statistical approaches. The central idea is to use an ensemble of fast and highly predictive artificial neural networks to select a minimal set of variables that maximizes the prediction of a given variable. It enables decomposition of the relationship among variables through quantifying the contribution of an individual variable to the overall predictive performance. We show how our approach, EcohNet, can improve interaction network inference for a mesocosm experiment and simulated ecosystems. The application of the method to a long-term lake monitoring dataset yielded interpretable results on the drivers causing cyanobacteria blooms, which is a serious threat to ecological integrity and ecosystem services. Since performance of EcohNet is enhanced by its predictive capabilities, it also provides an optimized forecasting of overall components in ecosystems. EcohNet could be used to analyze complex and hybrid multivariate time series in many scientific areas not limited to ecosystems.

Disentangling the ecosystem service 'flood regulation': Mechanisms and relevant ecosystem condition characteristics

Riverine floods cause increasingly severe damages to human settlements and infrastructure. Ecosystems have a natural capacity to decrease both severity and frequency of floods. Natural flood regulation processes along freshwaters can be attributed to two different mechanisms: flood prevention that takes place in the whole catchment and flood mitigation once the water has accumulated in the stream. These flood regulating mechanisms are not consistently recognized in major ecosystem service (ES) classifications. For a balanced landscape management, it is important to assess the ES flood regulation so that it can account for the different processes at the relevant sites. We reviewed literature, classified them according to these mechanisms, and analysed the influencing ecosystem characteristics. For prevention, vegetation biomass and forest extent were predominant, while for mitigation, the available space for water was decisive. We add some aspects on assessing flood regulation as ES, and suggest also to include flood hazard into calculations.

Dryland mechanisms could widely control ecosystem functioning in a drier and warmer world

Responses of terrestrial ecosystems to climate change have been explored in many regions worldwide. While continued drying and warming may alter process rates and deteriorate the state and performance of ecosystems, it could also lead to more fundamental changes in the mechanisms governing ecosystem functioning. Here we argue that climate change will induce unprecedented shifts in these mechanisms in historically wetter climatic zones, towards mechanisms currently prevalent in dry regions, which we refer to as 'dryland mechanisms'. We discuss 12 dryland mechanisms affecting multiple processes of ecosystem functioning, including vegetation development, water flow, energy budget, carbon and nutrient cycling, plant production and organic matter decomposition. We then examine mostly rare examples of the operation of these mechanisms in non-dryland regions where they have been considered irrelevant at present. Current and future climate trends could force microclimatic conditions across thresholds and lead to the emergence of dryland mechanisms and their increasing control over ecosystem functioning in many biomes on Earth.

Integrating design and ecological theory to achieve adaptive diverse pastures

Increasing plant diversity is often suggested as a way of overcoming some of the challenges faced by managers of intensive pasture systems, but it is unclear how to design the most suitable plant mixtures. Using innovative design theory, we identify two conceptual shifts that foster potentially beneficial design approaches. Firstly, reframing the goal of mixture design to supporting ecological integrity, rather than delivering lists of desired outcomes, leads to flexible design approaches that support context-specific solutions that should operate within identifiable ecological limits. Secondly, embracing, rather than minimising uncertainty in performance leads to adaptive approaches that could enhance current and future benefits of diversifying pasture. These two fundamental shifts could therefore accelerate the successful redesign of intensive pastures.

Habitat Protection Approaches Facilitate Conservation of Overlooked Fungal Diversity - A Case Study From the Norwegian Coastal Heathland System

European coastal heathlands are distinct ecosystems shaped by land use tradition and they have experienced an 80% area reduction from their historical maximum. These mosaics of mires and wind exposed patches have ericaceous shrub dominated vegetation, and soils within coastal heathlands are characterized by low pH and high levels of recalcitrant debris. Using a culture-based approach with molecular identification of isolates, we characterized root-associated fungal communities of six ericaceous species in eight heathland localities along Norway's western coast. Site-level alpha diversity ranged from 21-38 OTUs, while the total estimated gamma diversity for culturable heathland root fungi was 190-231 OTUs. Most species recovered are previously reported at low abundance in Norway, suggesting the biodiversity in this community is underreported, rather than novel for science. The fungi recovered were primarily Ascomycota, specifically endophytic Phialocephala, and Pezicula, and no host specificity was observed in the communities. The fungal communities exhibited high turnover and low nestedness, both between ericaceous hosts and across heathland sites. We observed no spatial patterns in fungal betadiversity, and this heterogeneity may be a product of the unique historic land use practices at each locality creating a distinct mycofloral "fingerprint". Robust diversity estimates will be key for managing fungal biodiversity in coastal heathlands. Our results indicate that sampling schemes that maximize the number of host plants sampled per site, rather than the number of cultures per plant yield improved alpha diversity estimates. Similarly, gamma diversity estimates are improved by maximizing the total number of localities sampled, rather than increasing the number of plants sampled per locality. We argue that while the current protected status of coastal heathland habitats and restoration efforts have knock-on effects for the conservation of fungal biodiversity, fungi have a vital functional role in the ecosystem and holistic conservation plans that consider fungal biodiversity would be beneficial.

Remote Sensing of Geomorphodiversity Linked to Biodiversity—Part III: Traits, Processes and Remote Sensing Characteristics

Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well as the constraints of monitoring the diversity of geomorphology using RS, are discussed. RS-aided techniques that can be used for monitoring geomorphodiversity in regimes with changing land-use intensity are presented. Further, new approaches of geomorphic traits that enable the monitoring of geomorphodiversity through the valorisation of RS data from multiple missions are discussed as well as the ecosystem integrity approach. Likewise, the approach of monitoring the five characteristics of geomorphodiversity recording with RS is discussed, as are existing approaches for recording spectral geomorhic traits/ trait variation approach and indicators, along with approaches for assessing geomorphodiversity. It is shown that there is no comparable approach with which to define and record the five characteristics of geomorphodiversity using only RS data in the literature. Finally, the importance of the digitization process and the use of data science for research in the field of geomorphology in the 21st century is elucidated and discussed.

A comparative mapping of plant species diversity using ensemble learning algorithms combined with high accuracy surface modeling

Plant species diversity (PSD) has always been an essential component of biodiversity and plays an important role in ecosystem functions and services. However, it is still a huge challenge to simulate the spatial distribution of PSD due to the difficulties of data acquisition and unsatisfactory performance of predicting algorithms over large areas. A surge in the number of remote sensing imagery, along with the great success of machine learning, opens new opportunities for the mapping of PSD. Therefore, different machine learning algorithms combined with high-accuracy surface modeling (HASM) were firstly proposed to predict the PSD in the Xinghai, northeastern Qinghai-Tibetan Plateau, China. Spectral reflectance and vegetation indices, generated from Landsat 8 images, and environmental variables were taken as the potential explanatory factors of machine learning models including least absolute shrinkage and selection operator (Lasso), ridge regression (Ridge), eXtreme Gradient Boosting (XGBoost), and Random Forest (RF). The prediction generated from these machine learning methods and in situ observation data were integrated by using HASM for the high-accuracy mapping of PSD including three species diversity indices. The results showed that PSD was closely associated with vegetation indices, followed by spectral reflectance and environmental factors. XGBoost combined with HASM (HASM-XGBoost) showed the best performance with the lowest MAE and RMSE. Our results suggested that the fusion of heterogeneous data and the ensemble of heterogeneous models may revolutionize our ability to predict the PSD over large areas, especially in some places limited by sparse field samples.

Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro

The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.

Applying conservation reserve design strategies to define ecosystem monitoring priorities

In an era of unprecedented ecological upheaval, monitoring ecosystem change at large spatial scales and over long-time frames is an essential endeavor of effective environmental management and conservation. However, economic limitations often preclude revisiting entire monitoring networks at high frequency. We aimed here to develop a prioritization strategy for monitoring networks to select a subset of existing sites that meets the principles of complementarity and representativeness of the whole ecological reality, and maximizes ecological complementarity (species accumulation) and the spatial and environmental representativeness. We applied two well-known approaches for conservation design, the "minimum set" and the "maximal coverage" problems, using a suite of alpha and beta biodiversity metrics. We created a novel function for the R environment that performs biodiversity metric comparisons and site prioritization on a plot-by-plot basis. We tested our procedures using plot data provided by the Terrestrial Ecosystem Research Network (TERN) AusPlots, an Australian long-term monitoring network of 774 vegetation and soil monitoring plots. We selected 250 plots and 80% of the total species recorded as targets for the maximal coverage and minimum set problems, respectively. We compared the subsets selected by the different biodiversity metrics in terms of complementarity and spatial and environmental representativeness. We found that prioritization based on species turnover (i.e., iterative selection of the most dissimilar plot to a cumulative sample in terms of species replacement) maximized ecological complementarity and spatial representativeness, while also providing high environmental coverage. Species richness was an unreliable metric for spatial representation. Selection based on range-rarity-richness was balanced in terms of complementarity and representativeness, whereas its richness-corrected implementation failed to capture ecological and environmental variation. Prioritization based on species turnover is desirable to cover the maximum variability of the whole network. Synthesis and applications: Our results inform monitoring design and conservation priorities, which can benefit by considering the turnover component of beta diversity in addition to univariate metrics. Our tool is computationally efficient, free, and can be readily applied to any species versus sites dataset, facilitating rapid decision-making.

Multidecadal changes in functional diversity lag behind the recovery of taxonomic diversity

While there has been increasing interest in how taxonomic diversity is changing over time, less is known about how long-term taxonomic changes may affect ecosystem functioning and resilience. Exploring long-term patterns of functional diversity can provide key insights into the capacity of a community to carry out ecological processes and the redundancy of species' roles. We focus on a protected freshwater system located in a national park in southeast Germany. We use a high-resolution benthic macroinvertebrate dataset spanning 32 years (1983-2014) and test whether changes in functional diversity are reflected in taxonomic diversity using a multidimensional trait-based approach and regression analyses. Specifically, we asked: (i) How has functional diversity changed over time? (ii) How functionally distinct are the community's taxa? (iii) Are changes in functional diversity concurrent with taxonomic diversity? And (iv) what is the extent of community functional redundancy? Resultant from acidification mitigation, macroinvertebrate taxonomic diversity increased over the study period. Recovery of functional diversity was less pronounced, lagging behind responses of taxonomic diversity. Over multidecadal timescales, the macroinvertebrate community has become more homogenous with a high degree of functional redundancy, despite being isolated from direct anthropogenic activity. While taxonomic diversity increased over time, functional diversity has yet to catch up. These results demonstrate that anthropogenic pressures can remain a threat to biotic communities even in protected areas. The differences in taxonomic and functional recovery processes highlight the need to incorporate functional traits in assessments of biodiversity responses to global change.

Mountain Watch: How LT(S)ER Is Safeguarding Southern Africa’s People and Biodiversity for a Sustainable Mountain Future

Southern Africa is an exceptionally diverse region with an ancient geologic and climatic history. Its mountains are located in the Southern Hemisphere mid-latitudes at a tropical–temperate interface, offering a rare opportunity to contextualise and frame our research from an austral perspective to balance the global narrative around sustainable mountain futures for people and biodiversity. Limited Long-Term Ecological Research (LTER) was initiated more than a century ago in South Africa to optimise catchment management through sound water policy. The South African Environmental Observation Network (SAEON) has resurrected many government LTER programmes and added observatories representative of the country’s heterogeneous zonobiomes, including its mountain regions. LTER in other Southern African mountains is largely absent. The current rollout of the Expanded Freshwater and Terrestrial Environmental Observation Network (EFTEON) and the Southern African chapters of international programmes such as the Global Observation Research Initiative in Alpine Environments (GLORIA), RangeX, and the Global Soil Biodiversity Observation Network (Soil BON), as well as the expansion of the Mountain Invasion Research Network (MIREN), is ushering in a renaissance period of global change research in the region, which takes greater cognisance of its social context. This diversity of initiatives will generate a more robust knowledge base from which to draw conclusions about how to better safeguard the well-being of people and biodiversity in the region and help balance livelihoods and environmental sustainability in our complex, third-world socio-ecological mountain systems.

Diagnostic Species Diversity Pattern Can Provide Key Information on Vegetation Change: An Insight into High Mountain Habitats in Central Apennines

High mountain ecosystems are hotspots of biodiversity that are highly vulnerable to climate warming and land use change. In Europe, high mountain habitats are included in the EC Directive 92/43/EEC (Habitats Directive) and the identification of practices facilitating effective monitoring is crucial for meeting HD goals. We analyzed the temporal changes in species composition and diversity on high mountain EU habitats and explored if the subgroup of diagnostic species was able to summarize the comprehensive information on plant community variations. We performed a re-visitation study, using a set of 30 georeferenced historical plots newly collected after 20 years on two EU habitats (Galium magellense community growing on screes (8120 EU) and Trifolium thalii community of snowbeds (6170 EU)) in the Maiella National Park (MNP), which is one of the most threatened Mediterranean mountains in Europe. The presence of several endangered species and the availability of a botanical garden, a seed bank, and a nursery, make the MNP an excellent training ground to explore in situ and ex situ conservation strategies. We compared overall and diagnostic species richness patterns over time by rarefaction curves and described the singular aspects of species diversity (e.g., richness, Shannon index, Simpson index, and Berger–Parker index), by Rènyi’s diversity profiles. Diversity values consistently varied over time and across EU habitat types, with increasing values on scree communities and decreasing values on snowbeds. These changes could be associated with both land use change, through the increase of grazing pressure of Apennine chamois (Rupicapra pyrenaica ornata), which determined a rise of nitrophilous species in the scree community, and an increase of grasses at the expense of forbs in snowbeds, and to climate change, which promoted a general expansion of thermophilous species. Despite the two opposite, ongoing processes on the two plant communities studied, our results evidenced that diagnostic species and overall species followed the same trend of variation, demonstrating the potential of diagnostics for EU habitat monitoring. Our observations suggested that the re-visitation of historical plots and the implementation of frequent monitoring campaigns on diagnostic species can provide important data on species abundance and distribution patterns in these vulnerable ecosystems, supporting optimized in situ and ex situ conservation actions.

Long-term data reveal unimodal responses of ground beetle abundance to precipitation and land use but no changes in taxonomic and functional diversity

While much of global biodiversity is undoubtedly under threat, the responses of ecological communities to changing climate, land use intensification, and long-term changes in both taxonomic and functional diversity over time, has still not been fully explored for many taxonomic groups, especially invertebrates. We compiled time series of ground beetles covering the past two decades from 40 sites located in five regions across Germany. We calculated site-based trends for 21 community metrics representing taxonomic and functional diversity of ground beetles, activity density (a proxy for abundance), and activity densities of functional groups. We assessed both overall and regional temporal trends and the influence of the global change drivers of temperature, precipitation, and land use on ground beetle communities. While we did not detect overall temporal changes in ground beetle taxonomic and functional diversity, taxonomic turnover changed within two regions, illustrating that community change at the local scale does not always correspond to patterns at broader spatial scales. Additionally, ground beetle activity density had a unimodal response to both annual precipitation and land use. Limited temporal change in ground beetle communities may indicate a shifting baseline, where community degradation was reached prior to the start of our observation in 1999. In addition, nonlinear responses of animal communities to environmental change present a challenge when quantifying temporal trends.

Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics

Most metabarcoding protocols for invertebrate bulk samples start with sample homogenisation, followed by DNA extraction, amplification of a specific marker region, and sequencing. Many of the above-mentioned laboratory steps have been verified thoroughly and best practice strategies exist, yet, no clear recommendation for the basis of almost all metabarcoding studies exists: the homogenisation of samples itself. Two different categories of devices are typically used for homogenisation: bead mills or blenders. Both have upsides and downsides. Bead mills rely on single-use plastics and therefore produce a lot of waste and are expensive. In addition to that, processing times can go up to 30 minutes making them unsuitable for large-scale studies. Blenders can handle larger sample volumes in a shorter time, and be cleaned – yet suffer from an increased risk of cross-contamination. We aimed to develop a fast, robust, cheap, and reliable sample homogenisation protocol that overcomes limitations of both approaches, i.e. does not produce difficult to discard waste and avoid single-use plastics while reducing overall costs. We tested the performance of the new protocol using six size-sorted Malaise trap samples and six unsorted stream macroinvertebrate kick-net samples. We used 14 replicates per sample and included many negative controls at different steps of the protocol to quantify the impacts of i) insufficient homogenisation and ii) cross-contamination. Our results show that 3-min homogenisation is sufficient to recover about 80% of OTUs per sample in each replicate and that a non-hazardous DIY cleaning solution provides an effective and efficient way of cleaning. The improvements of the protocol in terms of speed, ease of handling, an overall reduction of costs as well as the documented reliability and robustness make it an important candidate for sample homogenisation after sampling in particular for large-scale and regulatory metabarcoding but also metagenomics biodiversity assessments and monitoring.

Abundance and demography of common bottlenose dolphins (Tursiops truncatus truncatus) in the Indian River Lagoon, Florida: A robust design capture-recapture analysis

Common bottlenose dolphins (Tursiops truncatus truncatus) inhabiting the Indian River Lagoon (IRL) estuarine system along the east coast of Florida are impacted by anthropogenic activities and have had multiple unexplained mortality events. Given this, managers need precise estimates of demographic and abundance parameters. Mark-recapture photo-identification boat-based surveys following a Robust Design were used to estimate abundance, adult survival, and temporary emigration for the IRL estuarine system stock of bottlenose dolphins. Models allowed for temporary emigration and included a parameter (time since first capture) to assess evidence for transient individuals. Surveys (n = 135) were conducted along predetermined contour and transect lines throughout the entire IRL (2016-2017). The best fitting model allowed survival to differ for residents and transients and to vary by primary period, detection to vary by secondary session, and did not include temporary emigration. Dolphin abundance was estimated from 981 (95% CI: 882-1,090) in winter to 1,078 (95% CI: 968-1,201) in summer with a mean of 1,032 (95% CI: 969-1,098). Model averaged seasonal survival rate for marked residents was 0.85-1.00. Capture probability was 0.20 to 0.42 during secondary sessions and the transient rate was estimated as 0.06 to 0.07. This study is the first Robust Design mark-recapture survey to estimate abundance for IRL dolphins and provides population estimates to improve future survey design, as well as an example of data simulation to validate and optimize sampling design. Transients likely included individuals with home ranges extending north of the IRL requiring further assessment of stock delineation. Results were similar to prior abundance estimates from line-transect aerial surveys suggesting population stability over the last decade. These results will enable managers to evaluate the impact of fisheries-related takes and provide baseline demographic parameters for the IRL dolphin population which contends with anthropogenic impacts and repeated mortality events.

Recovery from air pollution and subsequent acidification masks the effects of climate change on a freshwater macroinvertebrate community

Freshwater ecosystems are dynamic, complex systems with a multitude of physical and ecological processes and stressors which drive fluctuations on the community-level. Disentangling the effects of different processes and stressors is challenging due to their interconnected nature. However, as protected areas (i.e. national parks) are less anthropogenically impacted, they are ideal for investigating single stressors. We focus on the Bavarian Forest National Park, a Long-Term Ecological Research (LTER) site in Germany, where the major stressors are climate warming, air pollution (i.e. acidification) and bark beetle infestations. We investigated the effects of these stressors on freshwater macroinvertebrates using comprehensive long-term (1983-2014) datasets comprising high-resolution macroinvertebrate and physico-chemical data from a near-natural stream. Macroinvertebrate communities have undergone substantial changes over the past 32 years, highlighted by increases in overall community abundance (+173%) and richness (+51.6%) as well as taxonomic restructuring driven by a disproportional increase of dipterans. Prior to the year 2000, regression analyses revealed a decline in sulphate deposition and subsequent recovery from historical acidification as potential drivers of the increases in abundance and richness rather than to increases in water temperature (1.5 °C overall increase). Post 2000, however, alterations to nutrient cycling caused by bark beetle infestations coupled with warming temperatures were correlated to taxonomic restructuring and disproportional increases of dipterans at the expense of sensitive taxa such as plecopterans and trichopterans. Our results highlight the challenges when investigating the effects of climate change within a multi-stressor context. Even in conservation areas, recovery from previous disturbance might mask the effects of ongoing disturbances like climate change. Overall, we observed strong community restructuring, demonstrating that stenothermal headwater communities face additional stress due to emerging competition with tolerant taxa. Conservation efforts should consider the temporal variability of communities and their recovery from disturbances to adequately identify species vulnerable to local or widespread extinction.

Marine health of the Arabian Gulf: Drivers of pollution and assessment approaches focusing on desalination activities

The Arabian Gulf is one of the most adversely affected marine environments worldwide, which results from combined pollution drivers including climate change, oil and gas activities, and coastal anthropogenic disturbances. Desalination activities are one of the major marine pollution drivers regionally and internationally. Arabian Gulf countries represent a hotspot of desalination activities as they are responsible for nearly 50% of the global desalination capacity. Building desalination plants, up-taking seawater, and discharging untreated brine back into the sea adversely affects the biodiversity of the marine ecosystems. The present review attempted to reveal the potential negative effects of desalination plants on the Gulf's marine environments. We emphasised different conventional and innovative assessment tools used to assess the health of marine environments and evaluate the damage exerted by desalination activity in the Gulf. Finally, we suggested effective management approaches to tackle the issue including the significance of national regulations and regional cooperation.

Two centuries for an almost complete community turnover from native to non-native species in a riverine ecosystem

Non-native species introductions affect freshwater communities by changing community compositions, functional roles, trait occurrences and ecological niche spaces. Reconstructing such changes over long periods is difficult due to limited data availability. We collected information spanning 215 years on fish and selected macroinvertebrate groups (Mollusca and Crustacea) in the inner-Florentine stretch of the Arno River (Italy) and associated water grid, to investigate temporal changes. We identified an almost complete turnover from native to non-native fish (1800: 92% native; 2015: 94% non-native species) and macroinvertebrate species (1800: 100% native; 2015: 70% non-native species). Non-native fish species were observed ~50 years earlier compared to macroinvertebrate species, indicating phased invasion processes. In contrast, α-diversity of both communities increased significantly following a linear pattern. Separate analyses of changes in α-diversities for native and non-native species of both fish and macroinvertebrates were nonlinear. Functional richness and divergence of fish and macroinvertebrate communities decreased non-significantly, as the loss of native species was compensated by non-native species. Introductions of non-native fish and macroinvertebrate species occurred outside the niche space of native species. Native and non-native fish species exhibited greater overlap in niche space over time (62%-68%) and non-native species eventually replaced native species. Native and non-native macroinvertebrate niches overlapped to a lesser extent (15%-30%), with non-natives occupying mostly unoccupied niche space. These temporal changes in niche spaces of both biotic groups are a direct response to the observed changes in α-diversity and species turnover. These changes are potentially driven by deteriorations in hydromorphology as indicated by alterations in trait modalities. Additionally, we identified that angling played a considerable role for fish introductions. Our results support previous findings that the community turnover from native to non-native species can be facilitated by, for example, deteriorating environmental conditions and that variations in communities are multifaceted requiring more indicators than single metrics.

A common typology for ecosystem characteristics and ecosystem condition variables

The UN System of Environmental-Economic Accounting Experimental Ecosystem Accounting (SEEA EEA) aims at regular and standardised stocktaking on the extent of ecosystems, their condition and the services they provide to society. Recording the condition of ecosystems is one of the most complex pieces in this exercise, needing to be supported by robust and consistent guidelines. SEEA EEA defines the condition of an ecosystem as its overall quality, measured in terms of quantitative metrics describing both abiotic and biotic characteristics. The main objective of this paper is to propose a simple universal classification (typology) for these ecosystem condition characteristics and metrics, based on long standing ecological concepts and traditions.

The proposed SEEA EEA Ecosystem Condition Typology (SEEA ECT) is a hierarchical classification consisting of six classes grouped into three main groups (abiotic, biotic and landscape-level ecosystem characteristics). In order to facilitate practical applications, SEEA ECT is cross-linked to the most relevant existing typologies for ecosystem characteristics currently used for other purposes. To ensure clarity and practicality, we identified potential overlaps between classes and also identified the most important groups of ‘ancillary data’ that should not be considered as ecosystem condition characteristics. We consider that this new typology for ecosystem condition will create a meaningful reporting structure for ecosystem condition accounts, thus facilitating its standardisation and broad application.

Novel Insights to Be Gained From Applying Metacommunity Theory to Long-Term, Spatially Replicated Biodiversity Data

Global loss of biodiversity and its associated ecosystem services is occurring at an alarming rate and is predicted to accelerate in the future. Metacommunity theory provides a framework to investigate multi-scale processes that drive change in biodiversity across space and time. Short-term ecological studies across space have progressed our understanding of biodiversity through a metacommunity lens, however, such snapshots in time have been limited in their ability to explain which processes, at which scales, generate observed spatial patterns. Temporal dynamics of metacommunities have been understudied, and large gaps in theory and empirical data have hindered progress in our understanding of underlying metacommunity processes that give rise to biodiversity patterns. Fortunately, we are at an important point in the history of ecology, where long-term studies with cross-scale spatial replication provide a means to gain a deeper understanding of the multiscale processes driving biodiversity patterns in time and space to inform metacommunity theory. The maturation of coordinated research and observation networks, such as the United States Long Term Ecological Research (LTER) program, provides an opportunity to advance explanation and prediction of biodiversity change with observational and experimental data at spatial and temporal scales greater than any single research group could accomplish. Synthesis of LTER network community datasets illustrates that long-term studies with spatial replication present an under-utilized resource for advancing spatio-temporal metacommunity research. We identify challenges towards synthesizing these data and present recommendations for addressing these challenges. We conclude with insights about how future monitoring efforts by coordinated research and observation networks could further the development of metacommunity theory and its applications aimed at improving conservation efforts.

Effective ecosystem monitoring requires a multi-scaled approach

Ecosystem monitoring is fundamental to our understanding of how ecosystem change is impacting our natural resources and is vital for developing evidence-based policy and management. However, the different types of ecosystem monitoring, along with their recommended applications, are often poorly understood and contentious. Varying definitions and strict adherence to a specific monitoring type can inhibit effective ecosystem monitoring, leading to poor program development, implementation and outcomes. In an effort to develop a more consistent and clear understanding of ecosystem monitoring programs, we here review the main types of monitoring and recommend the widespread adoption of three classifications of monitoring, namely, targeted, surveillance and landscape monitoring. Landscape monitoring is conducted over large areas, provides spatial data, and enables questions relating to where and when ecosystem change is occurring to be addressed. Surveillance monitoring uses standardised field methods to inform on what is changing in our environments and the direction and magnitude of that change, whilst targeted monitoring is designed around testable hypotheses over defined areas and is the best approach for determining the causes of ecosystem change. The classification system is flexible and can incorporate different interests, objectives, targets and characteristics as well as different spatial scales and temporal frequencies, while also providing valuable structure and consistency across distinct ecosystem monitoring programs. To support our argument, we examine the ability of each monitoring type to inform on six key types of questions that are routinely posed for ecosystem monitoring programs, such as where and when change is occurring, what is the magnitude of change, and how can the change be managed? As we demonstrate, each type of ecosystem monitoring has its own strengths and weaknesses, which should be carefully considered relative to the desired results. Using this scheme, scientists and land managers can design programs best suited to their needs. Finally, we assert that for our most serious environmental challenges, it is essential that we include information from each of these monitoring scales to inform on all facets of ecosystem change, and this is best achieved through close collaboration between the scales. With a renewed understanding of the importance of each monitoring type, along with greater commitment to monitor cooperatively, we will be well placed to address some of our greatest environmental challenges.

Quality Assessment of Photogrammetric Methods—A Workflow for Reproducible UAS Orthomosaics

Unmanned aerial systems (UAS) are cost-effective, flexible and offer a wide range of applications. If equipped with optical sensors, orthophotos with very high spatial resolution can be retrieved using photogrammetric processing. The use of these images in multi-temporal analysis and the combination with spatial data imposes high demands on their spatial accuracy. This georeferencing accuracy of UAS orthomosaics is generally expressed as the checkpoint error. However, the checkpoint error alone gives no information about the reproducibility of the photogrammetrical compilation of orthomosaics. This study optimizes the geolocation of UAS orthomosaics time series and evaluates their reproducibility. A correlation analysis of repeatedly computed orthomosaics with identical parameters revealed a reproducibility of 99% in a grassland and 75% in a forest area. Between time steps, the corresponding positional errors of digitized objects lie between 0.07 m in the grassland and 0.3 m in the forest canopy. The novel methods were integrated into a processing workflow to enhance the traceability and increase the quality of UAS remote sensing.

Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

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.

A conceptual framework and practical structure for implementing ecosystem condition accounts

Ecosystem condition is a fundamental component in the ecosystem accounting framework as part of the System of Environmental-Economic Accounting Experimental Ecosystem Accounting (SEEA EEA). Here, we develop a conceptual framework and present a practical structure for implementing ecosystem condition accounts to contribute to the revision process of the SEEA EEA, focussing on six core elements: (1) developing a common definition of ecosystem condition, (2) establishing a conceptual framing for ecosystem condition, (3) portraying the role of condition within the SEEA EEA accounting system, (4) deriving an inclusive multi-purpose approach, (5) describing the components of condition accounts and (6) developing a three-stage structure for reporting accounts. We develop a conceptual framework for an inclusive condition account, building on an ecological understanding of ecosystems upon which definitions, concepts, classifications and reporting structures were based. The framework encompasses the dual perspectives of first, the interdependencies of ecosystem composition, structure and function in maintaining ecosystem integrity and second, the capacity of ecosystems to supply services as benefits for humans. The following components of ecosystem condition accounts are recommended to provide comprehensive, consistent, repeatable and transparent accounts: (1) intrinsic and instrumental values, together with ecocentric and anthropocentric worldviews; (2) a formal typology or classification of characteristics, variables and indicators, based on selection criteria; (3) a reference condition used both to compare past, current and future levels of indicators of condition and as a basis for aggregation of indicators; and (4) a three-stage approach to compiling accounts with increasing levels of information and complexity that are appropriate for different purposes and applications. The recommended broad and inclusive scope of ecosystem condition and the demonstrated practical methods for implementation of accounts will enhance the ecosystem accounting framework and thus support a wider range of current and potential applications and users.

A Multi-Disciplinary Approach to Understand Hydrologic and Geochemical Processes at Koiliaris Critical Zone Observatory

Koiliaris CZO is a European Critical Zone Observatory (CZO) typical of the Mediterranean karstic geomorphology, which represents watersheds affected by humans over the centuries. This study aims to provide information that underpins the hydrologic and geochemical processes functioning at Koiliaris CZO. Linking geomorphologic and tectonic analysis improved the delineation of a karstic area which extends outside of the Koiliaris watershed and identified how structural elements influence the regional hydrology. The fluctuation in the river flow represents processes occurring in the karst and the periodic signal is related to Earth tide stressing of the karstic reservoirs. The conceptualization of a two-reservoir, well-mixed karstic system is confirmed by both the geomorphologic and tidal analysis. The hydrologic response is fast and it is manifested especially during extreme events where 70% of the precipitation becomes surface runoff, creating major flood events. The different sampling sites in the Koiliaris CZO were geochemically clustered and the quantification of the weathering fluxes showed that 25 mm/1000 years and 39 mm/1000 years of carbonate were removed by chemical weathering for the Keramianos ephemeral river and the springs, respectively. These studies illustrate the importance of critical zone science and transdisciplinary studies on water and soil management.

Meta-analysis of multidecadal biodiversity trends in Europe

Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15-91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.

Changing environmental conditions underpin long-term patterns of phytoplankton in a freshwater reservoir

Environmental changes can exert strong pressure on freshwater biota and lead to unwanted alterations of local communities and deterioration of ecosystem services. Disentangling the links between environmental and community changes is, therefore, essential to understand and predict the impact of human activities on freshwater ecosystems. This is particularly relevant for man-made freshwater reservoirs that represent a nexus between anthropogenic, environmental, and biotic effects. Reservoir food webs depend strongly on phytoplankton dynamics, which are affected by abiotic conditions, nutrient availability and grazing pressure by zooplankton. We studied the effects of relevant environmental drivers (hydrochemistry, hydrodynamics and zooplankton) on the composition, diversity and community stability of main morpho-functional phytoplankton groups over 32 years in the Římov Reservoir (Czech Republic). Environmental conditions in the reservoir are characterised by three distinct periods (1983-89, 1990-99, and 2000-14) defined by shifts and breakpoints in temporal trends in reservoir hydrochemistry and hydraulic conditions, and we examined if and how phytoplankton responded to these abrupt changes. We found significant differences in phytoplankton composition among the three periods. Phytoplankton underwent a substantial compositional shift towards a dominance of pennate diatoms. Time-lag analysis of dissimilarity in phytoplankton composition revealed higher and stochastic annual variations until 1999, followed by a lower variability and divergence in phytoplankton composition in subsequent years. Changes in overall phytoplankton assemblage and most abundant morpho-functional phytoplankton groups were driven mainly by hydrochemical (total nitrogen) and hydrodynamic variables (inflow rate, surface level and mixing depth) and less by zooplankton dynamics. These results suggest that phytoplankton are driven primarily by nutrient input and water regime, both of which can be appropriately managed to support valuable ecosystem services provided by phytoplankton in freshwater reservoirs.

Collaboration across Time and Space in the LTER Network

The scale of ecological research is getting larger and larger. At such scales, collaboration is indispensable, but there is little consensus on what factors enable collaboration. In the present article, we investigated the temporal and spatial pattern of institutional collaboration within the US Long Term Ecological Research (LTER) Network on the basis of the bibliographic database. Social network analysis and the Monte Carlo method were applied to identify the characteristics of papers published by LTER researchers within a baseline of papers from 158 leading ecological journals. Long-term and long-distance collaboration were more frequent in the LTER Network, and we investigate and discuss the underlying mechanisms. We suggest that the maturing infrastructure and environment for collaboration within the LTER Network could encourage scientists to make large-scale hypotheses and to ask big questions in ecology.

Research questions to facilitate the future development of European long-term ecosystem research infrastructures: A horizon scanning exercise

Distributed environmental research infrastructures are important to support assessments of the effects of global change on landscapes, ecosystems and society. These infrastructures need to provide continuity to address long-term change, yet be flexible enough to respond to rapid societal and technological developments that modify research priorities. We used a horizon scanning exercise to identify and prioritize emerging research questions for the future development of ecosystem and socio-ecological research infrastructures in Europe. Twenty research questions covered topics related to (i) ecosystem structures and processes, (ii) the impacts of anthropogenic drivers on ecosystems, (iii) ecosystem services and socio-ecological systems and (iv), methods and research infrastructures. Several key priorities for the development of research infrastructures emerged. Addressing complex environmental issues requires the adoption of a whole-system approach, achieved through integration of biotic, abiotic and socio-economic measurements. Interoperability among different research infrastructures needs to be improved by developing standard measurements, harmonizing methods, and establishing capacities and tools for data integration, processing, storage and analysis. Future research infrastructures should support a range of methodological approaches including observation, experiments and modelling. They should also have flexibility to respond to new requirements, for example by adjusting the spatio-temporal design of measurements. When new methods are introduced, compatibility with important long-term data series must be ensured. Finally, indicators, tools, and transdisciplinary approaches to identify, quantify and value ecosystem services across spatial scales and domains need to be advanced.