The concerted emergence of well-known spatial and temporal ecological patterns in an evolutionary food web model in space

Ecological systems show a variety of characteristic patterns of biodiversity in space and time. It is a challenge for theory to find models that can reproduce and explain the observed patterns. Since the advent of island biogeography these models revolve around speciation, dispersal, and extinction, but they usually neglect trophic structure. Here, we propose and study a spatially extended evolutionary food web model that allows us to study large spatial systems with several trophic layers. Our computer simulations show that the model gives rise simultaneously to several biodiversity patterns in space and time, from species abundance distributions to the waxing and waning of geographic ranges. We find that trophic position in the network plays a crucial role when it comes to the time evolution of range sizes, because the trophic context restricts the occurrence and survival of species especially on higher trophic levels

On the Emergence of Macroecological Patterns in Meta-Community Models

A recurring question in ecology is how species diversity arises and persists. Theoretical ecology tries to find underlying principles that explain spatial and temporal species diversity. Models are a valuable tool for this endeavour as they allow to study systems in well-known settings and pin down decisive processes that shape diversity. Consensus on the core mechanisms that shape diversity is achieved, namely an interplay of evolutionary and spatial processes, but many aspects still need to be included in an overarching theory. One aspect often neglected in models for the sake of simplicity is spatial heterogeneity even though heterogeneity is considered a main driver for species diversity. A similar problem exists for trophic structure. Food web theory has successfully reduced the high dimensional complexity of an ecosystem to predator-prey interactions and proven to capture essential features of empirical food webs like fraction of basal, intermediate and top species. Still many models that try to answer which processes shape diversity neglect food web structure. This work incorporates both aspects, food web structure and spatial heterogeneity, into the model-based examination of species diversity. Two different food web models considering different scales of space and time are studied: First, a meta-food web model on smaller spatial scales with classical population dynamics to examine diversity patterns found in heterogeneous landscapes and particularly at ecotones. The model suggests that the coupling strength between habitats is crucial for the final outcome of species diversity. A hump-shaped diversity-dispersal relation is observed which is enhanced compared to former studies in homogeneous spatial settings. Second, a new evolutionary food web model developed in this work which is employed to study species diversity on large spatial and temporal scales first in homogeneous and then in heterogeneous landscapes. In both settings the model reproduces a set of well-known empirical diversity patterns, namely species-area relationship, range size distribution, similarity decay of diversity with distance as well as lifetime distributions and evolution of species range sizes, but the exact shape of the relations depends on the spatial setting. Trophic levels have major impacts on the dynamics of species in both settings. Basal species have larger ranges and longer lifetimes than species on higher trophic levels. The most striking difference occurs in geographic range size evolution curves. Homogeneous spatial settings lead to symmetric curves for basal species, whilst in heterogeneous systems these curves become asymmetric. This work demonstrates that heterogeneity and complex trophic structure must not be neglected and can easily extend existing ecological models. This enhances the usability of such tools in tackling the questions related to the emergence of biodiversity in space and time. The good agreement with many results found in real systems indicates that the models presented here, despite their simplicity, capture the essence of the processes at work in reality. Consequently such models can guide future research direction and help specify empirical testable hypotheses

Anxious Temperament Predicts Poor Acceptance of Self and Life in Bipolar Disorder during the COVID-19 Pandemic

The coronavirus disease (COVID-19) pandemic and the social distancing resulting thereof are having a great impact on psychological well-being. Studies investigating resilience found that it impacts mental health during crises. This study aimed to evaluate the influence of pre-crisis temperament on resilience in individuals with bipolar disorder during the COVID-19 pandemic. An online survey was conducted in Austria between April and June 2020, including 36 individuals with bipolar disorder and 39 healthy controls. Resilience was assessed with the 13-item resilience scale, and temperament was measured with the Temperament Evaluation of Memphis, Pisa, Paris and San Diego-autoquestionnaire (TEMPS-A). The bipolar disorder group showed lower resilience than the control group, and scored higher on the TEMPS-A for depressive, cyclothymic, and anxious temperaments. Resilience could be predicted by anxious temperament in individuals with bipolar disorder, and correlated negatively with depressive symptoms in both groups. The results suggest that anxious temperament influences the resilience of individuals with bipolar disorder, likely more than temporary hardships, such as the first months of the COVID-19 crisis. It is therefore important to improve the resilience of individuals with bipolar disorder not only by short-term interventions, but by strengthening resilience and reducing anxious temperament in the long term