Andreas H. Schweiger

Ecological and evolutionary legacy of megafauna extinctions

For hundreds of millions of years, large vertebrates (megafauna) have inhabited most of the ecosystems on our planet. During the late Quaternary, notably during the Late Pleistocene and the early Holocene, Earth experienced a rapid extinction of large, terrestrial vertebrates. While much attention has been paid to understanding the causes of this massive megafauna extinction, less attention has been given to understanding the impacts of loss of megafauna on other organisms with whom they interacted. In this review, we discuss how the loss of megafauna disrupted and reshaped ecological interactions, and explore the ecological consequences of the ongoing decline of large vertebrates. Numerous late Quaternary extinct species of predators, parasites, commensals and mutualistic partners were associated with megafauna and were probably lost due to their strict dependence upon them (co‐extinctions). Moreover, many extant species have megafauna‐adapted traits that provided evolutionary benefits under past megafauna‐rich conditions, but are now of no or limited use (anachronisms). Morphological evolution and behavioural changes allowed some of these species partially to overcome the absence of megafauna. Although the extinction of megafauna led to a number of co‐extinction events, several species that likely co‐evolved with megafauna established new interactions with humans and their domestic animals. Species that were highly specialized in interactions with megafauna, such as large predators, specialized parasites, and large commensalists (e.g. scavengers, dung beetles), and could not adapt to new hosts or prey were more likely to die out. Partners that were less megafauna dependent persisted because of behavioural plasticity or by shifting their dependency to humans via domestication, facilitation or pathogen spill‐over, or through interactions with domestic megafauna. We argue that the ongoing extinction of the extant megafauna in the Anthropocene will catalyse another wave of co‐extinctions due to the enormous diversity of key ecological interactions and functional roles provided by the megafauna.

Optimizing sampling approaches along ecological gradients

Summary Natural scientists and especially ecologists use manipulative experiments or field observations along gradients to differentiate patterns driven by processes from those caused by random noise. A well-conceived sampling design is essential for identifying, analysing and reporting underlying patterns in a statistically solid and reproducible manner, given the normal restrictions in labour, time and money. However, a technical guideline about an adequate sampling design to maximize prediction success under restricted resources is lacking. This study aims at developing such a solid and reproducible guideline for sampling along gradients in all fields of ecology and science in general. We conducted simulations with artificial data for five common response types known in ecology, each represented by a simple function (no response, linear, exponential, symmetric unimodal and asymmetric unimodal). In the simulations, we accounted for different levels of random and systematic error, the two sources of noise in ecological data. We quantified prediction success for varying total sample size, number of locations sampled along a spatial/temporal gradient and number of replicates per sampled location. The number of replicates becomes more important with increasing random error, whereas replicates become less relevant for a systematic error bigger than 20% of total variation. Thus, if high levels of systematic error are indicated or expected (e.g. in field studies with spatial autocorrelation, unaccountable additional environmental drivers or population clustering), continuous sampling with little to no replication is recommended. In contrast, sampling designs with replications are recommended in studies that can control for systematic errors. In a setting that is characteristic for ecological experiments and field studies strictly controlling for undeterminable systematic error (random error ≥10% and systematic error ≤10% of total variation), prediction success was best for an intermediate number of sampled locations along the gradient (10–15) and a low number of replicates per location (3). Our findings from reproducible, statistical simulations will help design appropriate and efficient sampling approaches and avoid erroneous conclusions based on studies with flawed sampling design, which is currently one of the main targets of public criticism against science.

Salt in the wound : the interfering effect of road salt on acidified forest catchments

Atmospheric acidic depositions have strongly altered the functioning and biodiversity of Central European forest ecosystems. Most impacts occurred until the end of the 20(th) century but the situation substantially improved thereafter caused by legal regulations in the late 1980s to reduce acidifying atmospheric pollution. Since then slow recovery from acidification has been observed in forested catchments and adjacent waters. However, trends of recovery are inconsistent and underlying mechanisms diminishing recovery are still poorly understood. We propose that the input of road salt can significantly affect acidity regime and acidification recovery of forest ecosystems. By comparing the discharge hydro-chemistry and plant community composition of springs fed by forested catchments with and without high levels of salt input over two decades we observed a significant suppression of recovery and elevated levels of nutrient leaching (K(+), Ca(2+) and Mg(2+)) in highly salt contaminated catchments. We show that the pollution of near-surface groundwater (interflow) by road salt application can have lasting effects on ecosystem processes over distances of several hundred metres apart from the salt emitting road.

The Afro-alpine dwarf shrub Helichrysum citrispinum favours understorey plants through microclimate amelioration

Background: Positive plant–plant interactions similar to specialised plant growth forms are potential strategies to overcome the environmental harshness of Afro-alpine ecosystems. However, knowledge about plant–plant interactions is limited for African alpine regions. Aims: We investigated the ameliorative effect of the densely leaved dwarf shrub Helichrysum citrispinum on two frequently co-occurring herbaceous plant species in the alpine zone of Mt. Kilimanjaro. Methods: We recorded microclimatic conditions, plant water potentials and gross primary production (GPP) for plants of the low-growing perennial Alchemilla johnstonii and the tussock grass Festuca abyssinica and compared these parameters between open sites and under H. citrispinum shrubs between July and August 2012. Results: Shrubs significantly buffered daily variation and extreme values of irradiation, air-, plant surface- and soil-temperatures as well as vapour pressure deficit. We found enhanced plant water potentials and gross primary production for shaded plants of both species investigated; ameliorative effects were higher for A. johnstonii than for F. abyssinica. Conclusions: Habitat amelioration of H. citrispinum significantly improves the productivity of plant species that grow under the shrub, although the net outcome may be affected by interspecific growth form differences. Future studies on positive plant–plant interactions should more strongly focus on the ecophysiological consequences of habitat amelioration.

The importance of ecological memory for trophic rewilding as an ecosystem restoration approach: Ecological memory and trophic rewilding

Increasing human pressure on strongly defaunated ecosystems is characteristic of the Anthropocene and calls for proactive restoration approaches that promote self‐sustaining, functioning ecosystems. However, the suitability of novel restoration concepts such as trophic rewilding is still under discussion given fragmentary empirical data and limited theory development. Here, we develop a theoretical framework that integrates the concept of ‘ecological memory’ into trophic rewilding. The ecological memory of an ecosystem is defined as an ecosystems accumulated abiotic and biotic material and information legacies from past dynamics. By summarising existing knowledge about the ecological effects of megafauna extinction and rewilding across a large range of spatial and temporal scales, we identify two key drivers of ecosystem responses to trophic rewilding: (i) impact potential of (re)introduced megafauna, and (ii) ecological memory characterising the focal ecosystem. The impact potential of (re)introduced megafauna species can be estimated from species properties such as lifetime per capita engineering capacity, population density, home range size and niche overlap with resident species. The importance of ecological memory characterising the focal ecosystem depends on (i) the absolute time since megafauna loss, (ii) the speed of abiotic and biotic turnover, (iii) the strength of species interactions characterising the focal ecosystem, and (iv) the compensatory capacity of surrounding source ecosystems. These properties related to the focal and surrounding ecosystems mediate material and information legacies (its ecological memory) and modulate the net ecosystem impact of (re)introduced megafauna species. We provide practical advice about how to quantify all these properties while highlighting the strong link between ecological memory and historically contingent ecosystem trajectories. With this newly established ecological memory–rewilding framework, we hope to guide future empirical studies that investigate the ecological effects of trophic rewilding and other ecosystem‐restoration approaches. The proposed integrated conceptual framework should also assist managers and decision makers to anticipate the possible trajectories of ecosystem dynamics after restoration actions and to weigh plausible alternatives. This will help practitioners to develop adaptive management strategies for trophic rewilding that could facilitate sustainable management of functioning ecosystems in an increasingly human‐dominated world.

The complex adaptive character of spring fens as model ecosystems

Predicting the ecological effects of environmental perturbations remains challenging due to complex interactions between species and the environment, which constantly adapt the ecological memory and, thus, the future response of ecosystems. General theoretical frameworks like the Complex Adaptive Systems (CAS) theory might provide a solution. Here I discuss the applicability of the CAS theory for ecosystems by examining its three major principles (interaction, adaptation and scale dependence) for spring fens. For these ecosystems, adaptation of plant communities to historical environmental stressors (acidification) affecting the resilience to subsequent perturbations (climatic extremes) is empirically shown. Alternative stable states in community composition initiated by acidification turned out to be stabilized by abiotic-biotic feedbacks. Furthermore, ecological response of species to temperature showed high cross-scale similarity. I argue that the exceptional environmental character of spring fens qualifies these ecosystems as ideal model systems to test and further develop CAS theory for ecology and biogeography.

To replicate, or not to replicate – that is the question: how to tackle nonlinear responses in ecological experiments

A fundamental challenge in experimental ecology is to capture nonlinearities of ecological responses to interacting environmental drivers. Here, we demonstrate that gradient designs outperform replicated designs for detecting and quantifying nonlinear responses. We report the results of (1) multiple computer simulations and (2) two purpose-designed empirical experiments. The findings consistently revealed that unreplicated sampling at a maximum number of sampling locations maximised prediction success (i.e. the R² to the known truth) irrespective of the amount of stochasticity and the underlying response surfaces, including combinations of two linear, unimodal or saturating drivers. For the two empirical experiments, the same pattern was found, with gradient designs outperforming replicated designs in revealing the response surfaces of underlying drivers. Our findings suggest that a move to gradient designs in ecological experiments could be a major step towards unravelling underlying response patterns to continuous and interacting environmental drivers in a feasible and statistically powerful way.

Biogeography, Patterns in

Biogeographic patterns result from environmental influences interacting with historic legacies and biotic characteristics. The emergence of biogeographic patterns is often scale dependent and the identification of causal processes is difficult due to complex cross-scale interactions. Prominent biogeographic patterns emerge particularly along strong environmental gradients such as latitude and elevation (species richness, range size, body size, coloration) or under isolated conditions like on islands (island gigantism/dwarfism, island woodiness, and dispersal loss). Historic legacies (such as colonization progression rules) or repeated evolutionary patterns (taxon cycle) may influence current distribution patterns. Yet, global patterns in species traits or growth forms can be clearly associated with specific environmental conditions (e.g., giant rosette plants, trait variability in Solanum ).