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Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.
Epigenetic modifications, of which DNA methylation is the best studied one, can convey environmental information through generations via parental germ lines. Past studies have focused on the maternal transmission of epigenetic information to the offspring of isogenic mice and rats in response to external changes, whereas heterogeneous wild mammals as well as paternal epigenetic effects have been widely neglected. In most wild mammal species, males are the dispersing sex and have to cope with differing habitats and thermal changes. As temperature is a major environmental factor we investigated if genetically heterogeneous Wild guinea pig (Cavia aperea) males can adapt epigenetically to an increase in temperature and if that response will be transmitted to the next generation(s). Five adult male guinea pigs (F0) were exposed to an increased ambient temperature for 2 months, i.e. the duration of spermatogenesis. We studied the liver (as the main thermoregulatory organ) of F0 fathers and F1 sons, and testes of F1 sons for paternal transmission of epigenetic modifications across generation(s). Reduced representation bisulphite sequencing revealed shared differentially methylated regions in annotated areas between F0 livers before and after heat treatment, and their sons’ livers and testes, which indicated a general response with ecological relevance. Thus, paternal exposure to a temporally limited increased ambient temperature led to an ‘immediate’ and ‘heritable’ epigenetic response that may even be transmitted to the F2 generation. In the context of globally rising temperatures epigenetic mechanisms may become increasingly relevant for the survival of species.
It has been proposed that growth and reproduction of animals is frequently limited by multiple nutrients simultaneously. To improve our understanding of the consequences of multiple nutrient limitations (i.e. co-limitation) for the performance of animals, we conducted standardized population growth experiments using an important aquatic consumer, the rotifer Brachionus calyciflorus. We compared nutrient profiles (sterols, fatty acids and amino acids) of rotifers and their diets to reveal consumerdiet imbalances and thus potentially limiting nutrients. In concomitant growth experiments, we directly supplemented potentially limiting substances (sterols, fatty acids, amino acids) to a nutrient-deficient diet, the cyanobacterium Synechococcus elongatus, and recorded population growth rates. The results from the supplementation experiments corroborated the nutrient limitations predicted by assessing consumerdiet imbalances, but provided more detailed information on co-limiting nutrients. While the fatty acid deficiency of the cyanobacterium appeared to be of minor importance, the addition of both cholesterol and certain amino acids (leucine and isoleucine) improved population growth rates of rotifers, indicating a simultaneous limitation by sterols and amino acids. Our results add to growing evidence that consumers frequently face multiple nutrient limitations and suggest that the concept of co-limitation has to be considered in studies assessing nutrient-limited growth responses of consumers.
Aim: Across the planet, grass-dominated biomes are experiencing shrub encroachment driven by atmospheric CO2 enrichment and land-use change. By altering resource structure and availability, shrub encroachment may have important impacts on vertebrate communities. We sought to determine the magnitude and variability of these effects across climatic gradients, continents, and taxa, and to learn whether shrub thinning restores the structure of vertebrate communities. Location: Worldwide. Time period: Contemporary. Major taxa studied: Terrestrial vertebrates. Methods: We estimated relationships between percentage shrub cover and the structure of terrestrial vertebrate communities (species richness, Shannon diversity and community abundance) in experimentally thinned and unmanipulated shrub-encroached grass-dominated biomes using systematic review and meta-analyses of 43 studies published from 1978 to 2016. We modelled the effects of continent, biome, mean annual precipitation, net primary productivity and the normalized difference vegetation index (NDVI) on the relationship between shrub cover and vertebrate community structure. Results: Species richness, Shannon diversity and total abundance had no consistent relationship with shrub encroachment and experimental thinning did not reverse encroachment effects on vertebrate communities. However, some effects of shrub encroachment on vertebrate communities differed with net primary productivity, amongst vertebrate groups, and across continents. Encroachment had negative effects on vertebrate diversity at low net primary productivity. Mammalian and herpetofaunal diversity decreased with shrub encroachment. Shrub encroachment also had negative effects on species richness and total abundance in Africa but positive effects in North America. Main conclusions: Biodiversity conservation and mitigation efforts responding to shrub encroachment should focus on low-productivity locations, on mammals and herpetofauna, and in Africa. However, targeted research in neglected regions such as central Asia and India will be needed to fill important gaps in our knowledge of shrub encroachment effects on vertebrates. Additionally, our findings provide an impetus for determining the mechanisms associated with changes in vertebrate diversity and abundance in shrub-encroached grass-dominated biomes.
Aim To understand the role and significance of the reindeer, Rangifer tarandus (Linnaeus, 1758), as a specific indicator in terms of late Quaternary biogeography and to determine the effects of global climate change on its range and local extinction dynamics at the end of the Ice Age.
Location Late Pleistocene/early Holocene range of reindeer over all of central and western Europe, including southern Scandinavia and northern Iberia, but excluding Russia, Belarus and the Ukraine.
Methods Radiocarbon-dated subfossil records of R. tarandus from both archaeological and natural deposits younger than 25,000 years were assembled in a database. The distribution area was divided into six representative regions. The C-14 dates were calibrated and plotted chronologically in maps in order to compare presence and absence and regional extinction patterns from one region to another.
Main conclusions The late Quaternary record for reindeer in Europe during the last 25 kyr shows a climate-driven dispersal and retreat in response to climate change, with regional variations. The collapse of the mammoth steppe biome did not lead to the local extinction in Europe, as in the case of other megafaunal species. Rangifer tarandus co-existed for about 3000 years during the Late Glacial and early Holocene with typical temperate species such as red deer and roe deer in non-analogue faunal communities. The regional extinction at the end of the Pleistocene coincides with the transition from light open birch/pine forests to pine/deciduous forests.
Recent research has shown that many cold-adapted species survived the last glacial maximum (LGM) in northern refugia. Whether this evolutionary history has had consequences for their genetic diversity and adaptive potential remains unknown. We sampled 14 populations of Carex limosa, a sedge specialized to bog ecosystems, along a latitudinal gradient from its Scandinavian core to the southern lowland range-margin in Germany. Using microsatellite and experimental common-garden data, we evaluated the impacts of global climate change along this gradient and assessed the conservation status of the southern marginal populations. Microsatellite data revealed two highly distinct genetic groups and hybrid individuals. In our common-garden experiment, the two groups showed divergent responses to increased nitrogen/phosphorus (N/P) availability, suggesting ecotypic differentiation. Each group formed genetically uniform populations at both northern and southern sampling areas. Mixed populations occurred throughout our sampling area, an area that was entirely glaciated during the LGM. The fragmented distribution implies allopatric divergence at geographically separated refugia that putatively differed in N/P availability. Molecular data and an observed low hybrid fecundity indicate the importance of clonal reproduction for hybrid populations. At the southern range-margin, however, all populations showed effects of clonality, lowered fecundity and low competitiveness, suggesting abiotic and biotic constraints to population persistence.
Specialisation and diversity of multiple trophic groups are promoted by different forest features
(2019)
While forest management strongly influences biodiversity, it remains unclear how the structural and compositional changes caused by management affect different community dimensions (e.g. richness, specialisation, abundance or completeness) and how this differs between taxa. We assessed the effects of nine forest features (representing stand structure, heterogeneity and tree composition) on thirteen above- and belowground trophic groups of plants, animals, fungi and bacteria in 150 temperate forest plots differing in their management type. Canopy cover decreased light resources, which increased community specialisation but reduced overall diversity and abundance. Features increasing resource types and diversifying microhabitats (admixing of oaks and conifers) were important and mostly affected richness. Belowground groups responded differently to those aboveground and had weaker responses to most forest features. Our results show that we need to consider forest features rather than broad management types and highlight the importance of considering several groups and community dimensions to better inform conservation.
Aim The study and prediction of speciesenvironment relationships is currently mainly based on species distribution models. These purely correlative models neglect spatial population dynamics and assume that species distributions are in equilibrium with their environment. This causes biased estimates of species niches and handicaps forecasts of range dynamics under environmental change. Here we aim to develop an approach that statistically estimates process-based models of range dynamics from data on species distributions and permits a more comprehensive quantification of forecast uncertainties.
Innovation We present an approach for the statistical estimation of process-based dynamic range models (DRMs) that integrate Hutchinson's niche concept with spatial population dynamics. In a hierarchical Bayesian framework the environmental response of demographic rates, local population dynamics and dispersal are estimated conditional upon each other while accounting for various sources of uncertainty. The method thus: (1) jointly infers species niches and spatiotemporal population dynamics from occurrence and abundance data, and (2) provides fully probabilistic forecasts of future range dynamics under environmental change. In a simulation study, we investigate the performance of DRMs for a variety of scenarios that differ in both ecological dynamics and the data used for model estimation.
Main conclusions Our results demonstrate the importance of considering dynamic aspects in the collection and analysis of biodiversity data. In combination with informative data, the presented framework has the potential to markedly improve the quantification of ecological niches, the process-based understanding of range dynamics and the forecasting of species responses to environmental change. It thereby strengthens links between biogeography, population biology and theoretical and applied ecology.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
The spatial distribution of a species is determined by dynamic processes such as reproduction, mortality and dispersal. Conventional static species distribution models (SDMs) do not incorporate these processes explicitly. This limits their applicability, particularly for non-equilibrium situations such as invasions or climate change. In this paper we show how dynamic SDMs can be formulated and fitted to data within a Bayesian framework. Our focus is on discrete state-space Markov process models which provide a flexible framework to account for stochasticity in key demographic processes, including dispersal, growth and competition. We show how to construct likelihood functions for such models (both discrete and continuous time versions) and how these can be combined with suitable observation models to conduct Bayesian parameter inference using computational techniques such as Markov chain Monte Carlo. We illustrate the current state-of-the-art with three contrasting examples using both simulated and empirical data. The use of simulated data allows the robustness of the methods to be tested with respect to deficiencies in both data and model. These examples show how mechanistic understanding of the processes that determine distribution and abundance can be combined with different sources of information at a range of spatial and temporal scales. Application of such techniques will enable more reliable inference and projections, e.g. under future climate change scenarios than is possible with purely correlative approaches. Conversely, confronting such process-oriented niche models with abundance and distribution data will test current understanding and may ultimately feedback to improve underlying ecological theory.