Beröring och begränsning

Touch and Restriction: On the Human-Animal Interface Climate crisis and mass extinction show the need to reshape our understanding of human culture in relation to non-human lifeforms. The article considers touch as a point where the border between humans and other species may be renegotiated. Three supplementary modes of human thought, which combine explanation, speculation, and imagination, are interrogated in terms of how they each deal with the tactility of cross-species interaction: philosophy, mythical representations in literature and art, and documentary film. Interface is used as a common concept for how bodies remain distinct from each other while also being able to connect with each other. First, I present how the interface is conceptualized in general by philosophers like Derrida, Nancy and Harman, and between humans and animals in particulars by thinkers like Wood and Michaux. Then, I relate the discussion to how two mythical motifs, focusing on instances of erotic touch across species lines, have been represented in literature and visual art: Leda and the swan, and Pasiphaë and the bull. Finally, I move on to two documentary films: Robinson Devor’s Zoo (2007) and Nikolaus Geyrhalter’s Unser täglich Brot (2005). The idea of zoosexual intercourse is contrasted to the distanced violence of the industrial keeping of animals. I suggest how touch show the possibility of a cross-species communion otherwise negated by late-modern industrial capitalism.

Modelling the disappearance of coarse woody debris, following a land clearing event

Background Land clearing generates coarse woody debris (CWD), much of which ultimately becomes atmospheric CO2. Schemes for greenhouse gas accounting must consider the contribution from land clearing, but the timing of the contribution will have large uncertainty, due to a paucity of knowledge about the rate of CWD disappearance. To better understand above-ground CWD disappearance following a land clearing event—through the actions of microorganisms, invertebrates, wildfire, or deliberate burning—we combined statistical modelling with an archive of semi-quantitative observations (units of CWD %), made within Queensland, Australia. Results Using a generalised additive mixed-effects model (median absolute error = 14.7%), we found that CWD disappearance was strongly influenced by the: (i) number of years elapsed since clearing; (ii) clearing method; (iii) bioregion (effectively a climate-by-tree species interaction); and (iv) the number of times burned. Years-since-clearing had a strongly non-linear effect on the rate of CWD disappearance. The data suggested that disappearance was reverse-sigmoidal, with little change in CWD apparent for the first three years after clearing. In typical conditions for Queensland, the model predicted that it will take 38 years for 95% of CWD to disappear, following a land clearing event; however, accounting for uncertainty in the data and model, this value could be as few as 5 years, or > 100 years. In contrast, due to an assumption about the propensity of land managers to burn CWD, the official method used to assess Australia’s greenhouse gas emissions predicted that 95% of CWD will disappear in < 1 year. Conclusions In Queensland, the CWD generated by land clearing typically takes 38 years to disappear. This ultimately implies that a key assumption of Australia’s official greenhouse gas reporting—i.e. that 98% of CWD is burned soon after a clearing event—does not adequately account for delayed CO2 emissions.

Landscape and microhabitat features determine small mammal abundance in forest patches in agricultural landscapes

Intensification of agricultural landscapes represent a major threat for biodiversity conservation also affecting several ecosystem services. The natural and semi-natural remnants, available in the agricultural matrix, represent important sites for small mammals and rodents, which are fundamental for sustaining various ecosystem functions and trophic chains. We studied the populations of two small mammals (Apodemus agrarius, A. sylvaticus) to evaluate the effects of landscape and habitat features on species abundance along a gradient of agricultural landscape intensification. The study was performed in Friuli Venezia Giulia (north-eastern Italy) during 19 months, in 19 wood remnants. Species abundance was determined using Capture-Mark-Recapture (CMR) techniques. In the same plots, main ecological parameters of the habitat (at microhabitat and patch scale) and landscape were considered. Abundance of A. agrarius increased in landscapes with high extent of permanent crops (i.e., orchards and poplar plantations) and low content of undecomposed litter in the wood understory. Instead, A. sylvaticus, a more generalist species, showed an opposite, albeit less strong, relationship with the same variables. Both species were not affected by any landscape structural feature (e.g., patch shape, isolation). Our findings showed that microhabitat features and landscape composition rather than wood and landscape structure affect populations’ abundance and species interaction. The opposite response of the two study species was probably because of their specific ecological requirements. In this light, conservation management of agricultural landscapes should consider the ecological needs of species at both landscape and habitat levels, by rebalancing composition patterns in the context of ecological intensification, and promoting a sustainable forest patch management.

Visual Signalling in Plant-Animal Interactions

<p>The process of visual signalling between plant and animals is often a combination of exciting discoveries and more often than not; highly controversial hypotheses. Plants and animals interact mutualistically and antagonistically creating a complex network of species relations to some extent suggesting a co evolutionary network. In this study, I investigate two basic research questions: the first is how plants utilize aposematic and cryptic colours? The second is how animals are affected by the colour signals broadcasted by plants? By using the avian eye model, I discover how visual signals/colours from plants are actually perceived, and the effects of these signals on birds (not human) perception. Aposematism and crypsis are common strategies utilized by animals, yet little evidence is known of such occurrences in plants. Aposematic and cryptic colours were evaluated by studying different colouration strategy through the ontogeny of two native heteroblastic New Zealand plants: Pseudopanax crassifolius and Elaeocarpus hookerianus. To determine the potential effect of colour signals on animals, I investigated an evolutionary theory of leaf colours constraining the conspicuousness of their fruit colour counterparts. Based on the available data, I also conducted a community level analysis about the effects of fruit colours and specific avian frugivores that might be attracted to them. Finally, I examined the fruit colour selection by a frugivorous seed dispersing insect; the Wellington Tree Weta (Hemideina crassidens). My result shows that aposematic and cryptic colours are successfully applied by plants to either warn or remain inconspicuous from browsing herbivores. The evidence I presented lends support to the Moa browsing hypothesis in relation to constraining the conspicuousness of their fruit colour counterparts. Based on the cryptic plant colourations. However, the same level of selective interaction could not be inferred for frugivore fruit colour selection based on avian vision. I demonstrated that leaf reflectance does not constrain/influence the conspicuousness of fruit colours. There was also no fruit colour diversity based on geographical location. Fruit colour alone is not sufficient to influence a specific frugivore assemblage. Other environmental factors and species interaction must be taken into account. Weta proved to possess colour vision capable of colour perception even in low light conditions. Weta also consistently selected naturally blue streaked and manipulated blue coloured fruits of Coprosma acerosa in a binary test. This supports the idea of weta co- evolving with fruit colours of certain divaricating plants in New Zealand. I suggest that the fruit colours of New Zealand are shaped by the combined selection pressure from birds, lizards/geckos and weta.</p>

Visual Signalling in Plant-Animal Interactions

<p>The process of visual signalling between plant and animals is often a combination of exciting discoveries and more often than not; highly controversial hypotheses. Plants and animals interact mutualistically and antagonistically creating a complex network of species relations to some extent suggesting a co evolutionary network. In this study, I investigate two basic research questions: the first is how plants utilize aposematic and cryptic colours? The second is how animals are affected by the colour signals broadcasted by plants? By using the avian eye model, I discover how visual signals/colours from plants are actually perceived, and the effects of these signals on birds (not human) perception. Aposematism and crypsis are common strategies utilized by animals, yet little evidence is known of such occurrences in plants. Aposematic and cryptic colours were evaluated by studying different colouration strategy through the ontogeny of two native heteroblastic New Zealand plants: Pseudopanax crassifolius and Elaeocarpus hookerianus. To determine the potential effect of colour signals on animals, I investigated an evolutionary theory of leaf colours constraining the conspicuousness of their fruit colour counterparts. Based on the available data, I also conducted a community level analysis about the effects of fruit colours and specific avian frugivores that might be attracted to them. Finally, I examined the fruit colour selection by a frugivorous seed dispersing insect; the Wellington Tree Weta (Hemideina crassidens). My result shows that aposematic and cryptic colours are successfully applied by plants to either warn or remain inconspicuous from browsing herbivores. The evidence I presented lends support to the Moa browsing hypothesis in relation to constraining the conspicuousness of their fruit colour counterparts. Based on the cryptic plant colourations. However, the same level of selective interaction could not be inferred for frugivore fruit colour selection based on avian vision. I demonstrated that leaf reflectance does not constrain/influence the conspicuousness of fruit colours. There was also no fruit colour diversity based on geographical location. Fruit colour alone is not sufficient to influence a specific frugivore assemblage. Other environmental factors and species interaction must be taken into account. Weta proved to possess colour vision capable of colour perception even in low light conditions. Weta also consistently selected naturally blue streaked and manipulated blue coloured fruits of Coprosma acerosa in a binary test. This supports the idea of weta co- evolving with fruit colours of certain divaricating plants in New Zealand. I suggest that the fruit colours of New Zealand are shaped by the combined selection pressure from birds, lizards/geckos and weta.</p>

Evolution of phenotypic fluctuation under host-parasite interactions

Robustness and plasticity are essential features that allow biological systems to cope with complex and variable environments. In a constant environment, robustness, i.e., insensitivity of phenotypes, is expected to increase, whereas plasticity, i.e., the changeability of phenotypes, tends to diminish. Under a variable environment, existence of plasticity will be relevant. The robustness and plasticity, on the other hand, are related to phenotypic variances. As phenotypic variances decrease with the increase in robustness to perturbations, they are expected to decrease through the evolution. However, in nature, phenotypic fluctuation is preserved to a certain degree. One possible cause for this is environmental variation, where one of the most important “environmental” factors will be inter-species interactions. As a first step toward investigating phenotypic fluctuation in response to an inter-species interaction, we present the study of a simple two-species system that comprises hosts and parasites. Hosts are expected to evolve to achieve a phenotype that optimizes fitness. Then, the robustness of the corresponding phenotype will be increased by reducing phenotypic fluctuations. Conversely, plasticity tends to evolve to avoid certain phenotypes that are attacked by parasites. By using a dynamic model of gene expression for the host, we investigate the evolution of the genotype-phenotype map and of phenotypic variances. If the host–parasite interaction is weak, the fittest phenotype of the host evolves to reduce phenotypic variances. In contrast, if there exists a sufficient degree of interaction, the phenotypic variances of hosts increase to escape parasite attacks. For the latter case, we found two strategies: if the noise in the stochastic gene expression is below a certain threshold, the phenotypic variance increases via genetic diversification, whereas above this threshold, it is increased mediated by noise-induced phenotypic fluctuation. We examine how the increase in the phenotypic variances caused by parasite interactions influences the growth rate of a single host, and observed a trade-off between the two. Our results help elucidate the roles played by noise and genetic mutations in the evolution of phenotypic fluctuation and robustness in response to host–parasite interactions.

Bird-plant interaction networks in native forests and eucalyptus plantations within a protected area

Frugivory is a plant-animal mutualistic interaction carried out mostly by birds. It consists in the bird consumption of fruits with later dispersion of the plants' seeds, helping in the vegetation regeneration. Frugivory can be affected by the habitat fragmentation and introduction of exotic species, which may alter the species interaction by extinction or competitor introduction. This study aimed to compare the structure of the network of frugivorous interactions between birds and plants in native forest and eucalyptus plantation. Birds were captured by mist nets and had their feces collected. Later, the seeds were identified in laboratory. The records of fruit consumption by birds in the zoochoric plant species present in the study area were also conducted. The data collected was used to build a network of interactions and identify the most important network metrics, species, and ecological functional groups in the studied environments. The results showed that the species composition, the connectivity of the relationships, the importance of the species for the interaction networks and the number of subgroups within the networks were highly similar between the native forest and the eucalyptus plantation. This could be explained by the favorable conditions that the studied eucalyptus plantations presented, such as the lack of anthropogenic activities, well-developed understory, and the presence of native surrounding vegetation, allowing practically the same seed dispersal capacity in both types of environments.

A roadmap towards predicting species interaction networks (across space and time)

Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species—and to describe the structure, variation, and change of the ecological networks they form—we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.

Classification of Biological Interactions: Challenges in the field and in analysis

Within biological communities, species interact in a wide variety of ways. Species interactions have always been noted and classified by naturalists in describing living organisms and their ways. Moreover, they are essential to characterize ecological communities as functioning entities. Biodiversity databases, as a rule, are comprised of species records in certain localities and times. Many, if not most, originated as databases of museum specimens and/or published records. As such, they provide data on species occurrences and distribution, with little functional information. Currently, online databases for species interaction data are being formed or proposed. Usually, these databases set out to compile data from actual field studies, and their design reflects the singularities of particular studies that seed their development. In two online databases: the Web of Life (2021) and the Interaction Web DataBase (2020) (IWDB), the categories of interactions are quite heterogeneous (Table 1). For instance, they may refer explicitly to certain taxonomic groups (e.g., anemone-fish), or do so implicitly (host-parasitoid; parasitoids are all holometabolous insects with arthropod hosts); conversely, they may encompass almost any taxon (food webs). In another example, the Global Biotic Interactions database (Poelen et al. 2014) (GloBI) offers a choice of relational attributes when entering data, ranging from undefined to quite restricted (Table 2). Here we intend to contribute to the development of interaction databases, from two different points of view. First, what categories can be effectively applied to field observations of biotic interactions? Second, what theoretical and applied questions do we expect to address with interaction databases? These should be equally applicable to comparisons of studies of the same kind or mode of interaction, and to contrasts between interactions in multimodal studies.