Ecology and Dynamics of Human Influenced Systems

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.

Microclimate research gained renewed interest over the last decade and its importance for many ecological processes is increasingly being recognized. Consequently, the call for high-resolution microclimatic temperature grids across broad spatial extents is becoming more pressing to improve ecological models. Here, we provide a new set of open-access bioclimatic variables for microclimate temperatures of European forests at 25 × 25 m2 resolution.

Abstract Forest biodiversity and ecosystem services have been predominantly quantified in forest interiors, well away from edge influences. However, edges represent a significant portion of the forest cover in many regions world-wide. We quantified a broad set of plant biodiversity and ecosystem service indicators in 225 plots along forest edge-to-interior transects across Europe. We found strong trade-offs: while phylogenetic diversity (evolutionary measure of biodiversity), the proportion of forest specialists, nutrient cycling and heatwave buffering increased towards the forest interior, species richness (taxonomic measure of biodiversity), nectar production potential, stemwood biomass and overall tree regeneration were promoted towards the forest edge. These trade-offs were mainly driven by forest structural complexity differences from edge to interior. As fragmentation continues, forest edges increasingly reshape biodiversity and ecosystem service provisioning, which is yet to be integrated in forest management and policy to ensure sustainability in ecosystem services delivery.

Abstract AimDark diversity refers to the set of species that are not observed in an area but could potentially occur based on suitable local environmental conditions. In this paper, we applied both niche-based and co-occurrence-based methods to estimate the dark diversity of vascular plant species in the subarctic tundra. We then aimed to unravel the drivers explaining (1) why some locations were missing relatively more suitable species than others, and (2) why certain plant species were more often absent from suitable locations than others.LocationThe Scandinavian tundra around Abisko, northern Sweden.MethodsWe calculated the dark diversity in 107 plots spread out across four mountain trails using four different methods. Two niche-based (Beals’ index and hypergeometric method) and two co-occurrences-based (climatic niche model and climatic niche model followed by species-specific threshold) methods. This was then followed by multiple generalized linear mixed models and general linear models to determine which habitat characteristics and species traits contributed most to the dark diversity.ResultsThe study showed a notable divergence in the predicted drivers of dark diversity depending on the method used. Nevertheless, we can conclude that plot-level dark diversity was generally 18% higher in areas at low elevations and 30% and 10% higher in areas with a low species richness or low levels of habitat disturbance, respectively.ConclusionOur findings call for caution when interpreting statistical findings of dark diversity estimates. Even so, all analyses point towards an important role for natural processes such as competitive dominance as main driver of the spatial patterns found in dark diversity in the northern Scandes.

High-elevation ecosystems are among the few ecosystems worldwide that are not yet heavily invaded by non-native plants. This is expected to change as species expand their range limits upwards to fill their climatic niches and respond to ongoing anthropogenic disturbances. Yet, whether and how quickly these changes are happening has only been assessed in a few isolated cases. Starting in 2007, we conducted repeated surveys of non-native plant distributions along mountain roads in 11 regions from 5 continents. We show that over a 5- to 10-year period, the number of non-native species increased on average by approximately 16% per decade across regions. The direction and magnitude of upper range limit shifts depended on elevation across all regions. Supported by a null-model approach accounting for range changes expected by chance alone, we found greater than expected upward shifts at lower/mid elevations in at least seven regions. After accounting for elevation dependence, significant average upward shifts were detected in a further three regions (revealing evidence for upward shifts in 10 of 11 regions). Together, our results show that mountain environments are becoming increasingly exposed to biological invasions, emphasizing the need to monitor and prevent potential biosecurity issues emerging in high-elevation ecosystems.

Abstract AimsEllenberg‐type indicator values are expert‐based rankings of plant species according to their ecological optima on main environmental gradients. Here we extend the indicator‐value system proposed by Heinz Ellenberg and co‐authors for Central Europe by incorporating other systems of Ellenberg‐type indicator values (i.e., those using scales compatible with Ellenberg values) developed for other European regions. Our aim is to create a harmonized data set of Ellenberg‐type indicator values applicable at the European scale.MethodsWe collected European data sets of indicator values for vascular plants and selected 13 data sets that used the nine‐, ten‐ or twelve‐degree scales defined by Ellenberg for light, temperature, moisture, reaction, nutrients and salinity. We compared these values with the original Ellenberg values and used those that showed consistent trends in regression slope and coefficient of determination. We calculated the average value for each combination of species and indicator values from these data sets. Based on species’ co‐occurrences in European vegetation plots, we also calculated new values for species that were not assigned an indicator value.ResultsWe provide a new data set of Ellenberg‐type indicator values for 8908 European vascular plant species (8168 for light, 7400 for temperature, 8030 for moisture, 7282 for reaction, 7193 for nutrients, and 7507 for salinity), of which 398 species have been newly assigned to at least one indicator value.ConclusionsThe newly introduced indicator values are compatible with the original Ellenberg values. They can be used for large‐scale studies of the European flora and vegetation or for gap‐filling in regional data sets. The European indicator values and the original and taxonomically harmonized regional data sets of Ellenberg‐type indicator values are available in the Supporting Information and the Zenodo repository.

Abstract Riparian zones are the paragon of transitional ecosystems, providing critical habitat and ecosystem services that are especially threatened by global change. Following consultation with experts, 10 key challenges were identified to be addressed for riparian vegetation science and management improvement: (1) Create a distinct scientific community by establishing stronger bridges between disciplines; (2) Make riparian vegetation more visible and appreciated in society and policies; (3) Improve knowledge regarding biodiversity—ecosystem functioning links; (4) Manage spatial scale and context‐based issues; (5) Improve knowledge on social dimensions of riparian vegetation; (6) Anticipate responses to emergent issues and future trajectories; (7) Enhance tools to quantify and prioritize ecosystem services; (8) Improve numerical modeling and simulation tools; (9) Calibrate methods and increase data availability for better indicators and monitoring practices and transferability; and (10) Undertake scientific validation of best management practices. These challenges are discussed and critiqued here, to guide future research into riparian vegetation.This article is categorized under: Water and Life > Nature of Freshwater Ecosystems Water and Life > Stresses and Pressures on Ecosystems Water and Life > Conservation, Management, and Awareness

The TV landscape went through significant changes during the past decades. The traditional broadcast switched from analog to digital thanks to new modulation, transport and coding systems. In the meantime, internet brought new ways of experiencing TV services with more customization by creating the need of on-demand features, paving the way to the streaming world we know today. These ecosystems grown separately, with MPEG-TS centric broadcast application being developed by DVB/ATSC and broadband streaming applications being developed by GAFAM based on IP-protocols from IETF. This created a fragmentation in the audience in terms of usage (linear, on-demand), access-network (IPTV, broadcast, OTT & 4G-Lte/5G) and devices (TV, set-top-boxes, mobiles). Broadcasters and operators addressed this fragmentation by declining services in many flavors, leveraging various and non-homogeneous technologies which led to a complex video delivery infrastructure having a lot of redundancies. This increases the delivery cost significantly and represent an energetic waste in networks and datacenters. In this paper, a solution for universal TV service delivery is proposed, based on recently standardized DVB-I, and addressing OTT, IPTV and 4G-Lte/5G mobile networks.

Forests harbour large spatiotemporal heterogeneity in canopy structure. This variation drives the microclimate and light availability at the forest floor. So far, we do not know how light availability and sub-canopy temperature interactively mediate the impact of macroclimate warming on understorey communities. We therefore assessed the functional response of understorey plant communities to warming and light addition in a full factorial experiment installed in temperate deciduous forests across Europe along natural microclimate, light and macroclimate gradients. Furthermore, we related these functional responses to the species' life-history syndromes and thermal niches. We found no significant community responses to the warming treatment. The light treatment, however, had a stronger impact on communities, mainly due to responses by fast-colonizing generalists and not by slow-colonizing forest specialists. The forest structure strongly mediated the response to light addition and also had a clear impact on functional traits and total plant cover. The effects of short-term experimental warming were small and suggest a time-lag in the response of understorey species to climate change. Canopy disturbance, for instance due to drought, pests or logging, has a strong and immediate impact and particularly favours generalists in the understorey in structurally complex forests.

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow.In this paper, we present a new R package—rasterdiv—to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns.The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open‐source algorithms.