Florian Hartig

University of Regensburg | UR · Theoretical Ecology

Technological advances are enabling ecologists to conduct large‐scale and structured community surveys. However, it is unclear how best to extract information from these novel community data. We metabarcoded 48 vertebrate species from their eDNA in 320 ponds across England and applied the ‘internal structure' approach, which uses joint species dist...

Conspecific density dependence (CDD) in plant populations is widespread, most likely caused by local‐scale biotic interactions, and has potentially important implications for biodiversity, community composition, and ecosystem processes. However, progress in this important area of ecology has been hindered by differing viewpoints on CDD across subfi...

Deep neural networks (DNN) have become a central method in ecology. To build and train DNNs in deep learning (DL) applications, most users rely on one of the major deep learning frameworks, in particular PyTorch or TensorFlow. Using these frameworks, however, requires substantial experience and time. Here, we present ‘cito', a user‐friendly R packa...

Generating spatial predictions of species distribution is a central task for research and policy. Currently, correlative species distribution models (cSDMs) are among the most widely used tools for this purpose. However, a fundamental assumption of cSDMs, that species distributions are in equilibrium with their environment, is rarely fulfilled in r...

The regeneration niche of trees is governed by many processes and factors that are challenging to determine. Besides a species's geographic distribution, which determines if seeds are available, a myriad of local processes in forest ecosystems (e.g., competition and pathogens) exert influences on tree regeneration. Consequently, the representation...

Numerous studies have shown reduced performance in plants that are surrounded by neighbours of the same species1,2, a phenomenon known as conspecific negative density dependence (CNDD)³. A long-held ecological hypothesis posits that CNDD is more pronounced in tropical than in temperate forests4,5, which increases community stabilization, species co...

Metacommunity theory unites community and spatial ecology. Recent innovations in sequencing technology may now allow us, for the first time, to confront this theory with entire trophic community data at large scales. We metabarcoded vertebrate eDNA from 320 ponds in England. Using this "novel community data", we calculated the "internal structure"...

The regeneration niche of trees is governed by many processes and factors that are challenging to determine. Besides species distribution, which determine if seeds are available, complex local dynamics in forest ecosystems (e.g., competition, pathogens) exert fundamental influence on tree regeneration. Consequently, the representation of tree regen...

Supervised machine learning (ML) and deep learning (DL) algorithms excel at predictive tasks, but it is commonly assumed that they often do so by exploiting non-causal correlations, which may limit both interpretability and generalizability. Here, we show that this trade-off between explanation and prediction is not as deep and fundamental as expec...

Species respond to climate change with range and abundance dynamics. To better explain and predict them, we need a mechanistic understanding of how the underlying demographic processes are shaped by climatic conditions. Here, we aim to infer demography–climate relationships from distribution and abundance data. For this, we developed spatially expl...

Current approaches to project spatial biodiversity responses to climate change mainly focus on the direct effects of climate on species while regarding land use and land cover as constant or prescribed by global land‐use scenarios. However, local land‐use decisions are often affected by climate change and biodiversity on top of socioeconomic and po...

1. Deep neural networks (DNN) have become a central class of algorithms for regression and classification tasks. Although some packages exist that allow users to specify DNN in R, those are rather limited in their functionality. Most current deep learning applications therefore rely on one of the major deep learning frameworks, PyTorch or TensorFlo...

A bstract To infer the processes that gave rise to past speciation and extinction rates across taxa, space and time, we often formulate hypotheses in the form of stochastic diversification models and estimate their parameters from extant phylogenies using Maximum Likelihood or Bayesian inference. Unfortunately, however, likelihoods can easily becom...

Calibrating process‐based models using multiple constraints often improves the identifiability of model parameters, helps to avoid several errors compensating each other and produces model predictions that are more consistent with underlying processes. However, using multiple constraints can lead to predictions for some variables getting worse. Thi...

Understanding uncertainties and sensitivities of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyze sensitivities (change in model outputs per unit change in inputs) and uncertainties (changes in model outputs scaled to uncertainty in inputs) of vegetation dynamics un...

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest s...

The popularity of Machine learning (ML), Deep learning (DL), and Artificial intelligence (AI) has sharply risen in recent years. Despite their spike in popularity, the inner workings of ML and DL algorithms are perceived as opaque, and their relationship to classical data analysis tools remains debated. It is often assumed that ML and DL excel prim...

Ecologists have long sought to understand the controls of species’ geographic distributions. Two important hypotheses have been that range limits are determined 1) predominantly by climate or 2) by competition in addition to climate, with competitive interactions dominating where climate is benign. If the first hypothesis is correct, the effect of...

A lot of what we know about past speciation and extinction dynamics is based on statistically fitting birth–death processes to phylogenies of extant species. Despite their wide use, the reliability of these tools is regularly questioned. It was recently demonstrated that vast ‘congruent’ sets of alternative diversification histories cannot be disti...

Current modelling approaches to predict spatially explicit biodiversity responses to climate change mainly focus on the direct effects of climate on species. Integration of spatiotemporal land-cover scenarios is still limited. Current approaches either regard land cover as constant boundary conditions, or rely on general, typically globally defined...

Estimates of the percentage of species “committed to extinction” by climate change range from 15% to 37%. The question is whether factors other than climate need to be included in models predicting species’ range change. We created demographic range models that include climate vs. climate‐plus‐competition, evaluating their influence on the geograph...

Current analyses of metacommunity data largely focus on global attributes across the entire metacommunity, such as mean alpha, beta, and gamma diversity, as well as the partitioning of compositional variation into single estimates of contributions of space and environmental effects and, more recently, possible contributions of species interactions....

Joint species distribution models (JSDMs) explain spatial variation in community composition by contributions of the environment, biotic associations and possibly spatially structured residual covariance. They show great promise as a general analytical framework for community ecology and macroecology, but current JSDMs, even when approximated by la...

Understanding the origins of biodiversity has been an aspiration since the days of early naturalists. The immense complexity of ecological, evolutionary, and spatial processes, however, has made this goal elusive to this day. Computer models serve progress in many scientific fields, but in the fields of macroecology and macroevolution, eco-evolutio...

It has long been anticipated that relating functional traits to species demography would be a cornerstone for achieving large-scale predictability of ecological systems. If such a relationship existed, species demography could be modeled only by measuring functional traits, transforming our ability to predict states and dynamics of species-rich com...

Understanding the origins of biodiversity has been an aspiration since the days of early naturalists. The immense complexity of ecological, evolutionary and spatial processes, however, has made this goal elusive to this day. Computer models serve progress in many scientific fields, but in the fields of macroecology and macroevolution, eco-evolution...

Aim It is widely accepted that biodiversity is influenced by both niche‐related and spatial processes from local to global scales. Their relative importance, however, is still disputed, and empirical tests are surprisingly scarce at the global scale. Here, we compare the importance of area (as a proxy for pure spatial processes) and environmental h...

Half a century ago, Janzen and Connell hypothesized that the high tree species diversity in tropical forests is maintained by specialized natural enemies. Along with other mechanisms, these can cause conspecific negative density dependence (CNDD) and thus maintain species diversity. Numerous studies have measured proxies of CNDD worldwide, but doub...

Process‐based forest models (PBMs) are important tools for quantifying forest growth and vulnerability, particularly under climate change. The 3‐PG model (Physiological Processes Predicting Growth) is one of the most widely used forest growth simulators for this purpose worldwide. Here, we present r3PG , a new Fortran implementation of 3‐PG, wrappe...

Background Temperate forest understorey vegetation poses an excellent study system to investigate whether increases in resource availability lead to an increase in plant species richness. Most sunlight is absorbed by the species-poor tree canopy, making the much more species-rich understorey species inhabit a severely resource-limited habitat. Addi...

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests...

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long‐term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data i...

Climate change is expected to cause major changes in forest ecosystems during the 21 st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models. The combination of empirica...

Dynamic vegetation models (DVMs) are important tools to understand and predict the functioning and dynamics of terrestrial ecosystems under changing environmental conditions. In these models, uncertainty in the description of demographic processes, in particular tree mortality, is a persistent problem. Current mortality formulations lack realism an...

Plant trait variability, emerging from eco-evolutionary dynamics that range from alleles to macroecological scales, is one of the most elusive, but possibly most consequential, aspects of biodiversity. Plasticity, epigenetics, and genetic diversity are major determinants of how plants will respond to climate change, yet these processes are rarely r...

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data to calibrate and ev...

1. Ecologists have long suspected that species are more likely to interact if their traits match in a particular way. For example, a pollination interaction may be more likely if the proportions of a bee's tongue fit a plant's flower shape. Empirical estimates of the importance of trait-matching for determining species interactions, however, vary s...

The distribution and abundance of plants across the world depends in part on their ability to move, which is commonly characterized by a dispersal kernel. For seeds, the total dispersal kernel (TDK) describes the combined influence of all primary, secondary, and higher-order dispersal vectors on the overall dispersal kernel for a plant individual,...

Ecologists have long suspected that species are more likely to interact if their traits match in a particular way. For example, a pollination interaction may be particularly likely if the proportions of a bee's tongue match flower shape in a beneficial way. Empirical evidence for trait matching, however, varies significantly in strength among diffe...

Although dispersal is generally viewed as a crucial determinant for the fitness of any organism, our understanding of its role in the persistence and spread of plant populations remains incomplete. Generalizing and predicting dispersal processes are challenging due to context dependence of seed dispersal, environmental heterogeneity, and interdepen...

Recent studies have suggested that defaunation of large-bodied frugivores reduces above-ground carbon storage in tropical forests of South America and Africa, but not, or less so, in Southeast Asian tropical forests. Here we analyze the issue using the seed dispersal network (data of interaction between trees and animal seed dispersers) and forest...

Mediterranean riparian forests are comparably humid environments that provide shelter for several broadleaved deciduous tree species at their southernmost distribution margin. The stability of these communities, however, is threatened by climate change as well as invasive tree species, such as black locust (Robinia pseudoacacia L.). So far, black l...

The latitudinal diversity gradient (LDG) is one of Earth's most iconic biodiversity patterns and still one of the most debated. Explanations for the LDG are often categorized into three broad pathways in which the diversity gradient is created by (1) differential diversification rates, (2) differential carrying capacities (ecological limits), or (3...

Current process-based vegetation models are complex scientific tools that require proper evaluation of the different processes included in the models to prove that the models can be used to integrate our understanding of forest ecosystems and project climate change impacts on forests. The PROFOUND database (PROFOUND DB) described here aims to bring...

When climatic or environmental conditions change, plant populations must either adapt to these new conditions, or track their niche via seed dispersal. Adaptation of plants to different abiotic environments has mostly been discussed with respect to physiological and demographic parameters that allow local persistence. However, rapid modifications i...

When climatic or environmental conditions change, plant populations must either adapt to these new conditions, or track their niche via seed dispersal. Adaptation of plants to different abiotic environments has mostly been discussed with respect to physiological and demographic parameters that allow local persistence. However, rapid modifications i...

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to d...

Dynamic global vegetation models (DGVMs) are of crucial importance for understanding and predicting vegetation, carbon, nitrogen and water dynamics of ecosystems in response to climate change. Their complexity, however, creates challenges for model analysis and data integration. A solution is to interface DGVMs with established statistical computin...

With the maturation of methods for estimating aboveground forest biomass by remote sensing, researchers increasingly need test data, particularly ground reference data, that are large enough to fine-tune existing approaches and test their robustness under diverse conditions. In this context, realistic synthetic datasets present an interesting alter...

Assessing local population size is one of the most common tasks in biodiversity monitoring. Population size estimates are not only important for conservation management and population threat assessment; they also enter many other analyses in landscape ecology and conservation. It is therefore concerning that methods for estimating plant population...

LaManna et al. (Reports, 30 June 2017, p. 1389) claim that subadult trees are proportionally less common at high conspecific adult density (CNDD) and that this effect increases toward the tropics and for rare species. We show that the CNDD-abundance correlation may have arisen from a methodological artifact and that a range of processes can explain...

Aim -- Recent studies increasingly use statistical methods to infer biotic interactions from cooccurrence information at large spatial scale. However, disentangling biotic interactions from other factors that can affect co-occurrence patterns at the macro scale is a major challenge. -- Approach -- We present a set of questions that analysts and re...

In ecology, the true causal structure for a given problem is often not known, and several plausible models and thus model predictions exist. It has been claimed that using weighted averages of these models can reduce prediction error, as well as better reflect model selection uncertainty. These claims, however, are often demonstrated by isolated ex...

Ecological theories assume that ecological processes change during stand development. This change should be reflected in patterns of tree and crown allometries, stand demography and community composition. Empirical tests of these predictions have largely concentrated on temperate forests. Here, we ask whether these expectations also hold in tropica...

A moderate increase in temperature is going to favor the performance of black locust in SE Mediterranean riparian forests. A severe climate change may imply that both autochthonous and allochthonous tree species would worsen their performances.

To assess the long-term impacts of forest management interventions under climate change, process-based models, which allow to predict transient dynamics under environmental change, are arguably the most suitable tools available. A challenge for using these models for management decisions, however, is their higher parametric uncertainty, which propa...

With the rise of computers, simulation models have emerged beside the more traditional statistical and mathematical models as a third pillar for ecological analysis. Broadly speaking, a simulation model is an algorithm, typically implemented as a computer program, which propagates the states of a system forward. Unlike in a mathematical model, howe...

Climate change in the Mediterranean, associated with warmer temperatures and more frequent droughts, is expected to impact forest productivity and the functioning of forests ecosystems as carbon reservoirs in the region. Climate warming can positively affect forest growth by extending the growing season, whereas increasing summer drought generally...

Millions of animals are killed by vehicle collisions each year. As mitigation measures, wildlife warning reflectors have become increasingly popular, although clear evidence for their effectiveness is lacking. A reason for inconclusive results in the literature may be that most previous studies on the effectiveness of wildlife warning reflectors co...

Since peatlands store up to 30% of the global soil organic carbon, it is important to understand how these ecosystems will react to a change in climate and management. Process-based ecosystem models have emerged as important tools for predicting long-term peatland dynamics, but their application is often challenging because they require programming...

‘Bois noir’ is a phytoplasma-mediated grapevine yellows disease that causes great economic damage in European vineyards. Previous studies have examined habitat relationships on a regional scale, which help to better understand the large-scale epidemiology. Local drivers, such as micro-habitat preferences of the vector (Hyalesthes obsoletus, a cixii...

Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor p...

Macroecology and biogeography are concerned with understanding biodiversity patterns across space and time. In the past, the two disciplines have addressed this question mainly with correlative approaches, despite frequent calls for more mechanistic explanations. Recent advances in computational power, theoretical understanding, and statistical too...

Recent studies have shown that the diversity of flowering plants can enhance pollinator richness and visitation frequency and thereby increase the resilience of pollination. It is assumed that flower traits explain these effects, but it is still unclear which flower traits are responsible, and knowing that, if pollinator richness and visitation fre...

Droughts and their negative effects on forest ecosystems are projected to increase under climate change for many regions. It has been suggested that intensive thinning could reduce drought impacts on established forests in the short-term. Most previous studies on the effect of thinning on drought impacts, however, have been confined to single fores...

The challenges posed by complex stochastic models used in fields such as computational ecology, biology and genetics have stimulated the development of approximate approaches to statistical inference. Here we focus on Synthetic Likelihood, a procedure that reduces the observed and simulated data to a set of summary statistics, and quantifies the di...

The challenges posed by complex stochastic models used in computational ecology, biology and genetics have stimulated the development of approximate approaches to statistical inference. Here we focus on Synthetic Likelihood (SL), a procedure that reduces the observed and simulated data to a set of summary statistics, and quantifies the discrepancy...