scholarly journals A common framework for identifying linkage rules across different types of interactions

2015 ◽  
Author(s):  
Ignasi Bartomeus ◽  
Dominique Gravel ◽  
Jason Tylianakis ◽  
Marcelo Aizen ◽  
Ian Dickie ◽  
...  
Keyword(s):  
Ecosystem Functioning ◽  
Species Interactions ◽  
Community Dynamics ◽  
Developmental Stages ◽  
Environmental Gradients ◽  
Interspecific Interactions ◽  
General Structure ◽  
Species Traits ◽  
Ecological Processes ◽  
Wrong Reason

Species interactions, ranging from antagonisms to mutualisms, form the architecture of biodiversity and determine ecosystem functioning. Understanding the rules responsible for who interacts with whom, as well as the functional consequences of these interspecific interactions, is central to predicting community dynamics and stability. Species traitssensu latomay affect different ecological processes determining species interactions through a two-step process. First, ecological and life-history traits govern species distributions and abundance, and hence determine species co-occurrence, which is a prerequisite for them to interact. Second, morphological traits between co-occurring potential interaction partners should match for the realization of an interaction. Moreover, inferring functioning from a network of interactions may require the incorporation of interaction efficiency. This efficiency may be also trait-mediated, and can depend on the extent of matching, or on morphological, physiological or behavioural traits. It has been shown that both neutral and trait-based models can predict the general structure of networks, but they rarely accurately predict individual interactions, suggesting that these models may be predicting the right structure for the wrong reason. We propose to move away from testing null models with a framework that explicitly models the probability of interaction among individuals given their traits. The proposed models integrate both neutral and trait-matching constraints while using only information about known interactions, thereby overcoming problems originating from under-sampling of rare interactions (i.e. missing links). They can easily accommodate qualitative or quantitative data, and can incorporate trait variation within species, such as values that vary along developmental stages or environmental gradients. We use three case studies to show that they can detect strong trait matching (e.g. predator-prey system), relaxed trait matching (e.g. herbivore-plant system) and barrier trait matching (e.g. plant-pollinator systems). Only by elucidating which species traits are important in each process, i.e. in determining interaction establishment, frequency, and efficiency, can we advance in explaining how species interact and the consequences for ecosystem functioning.

scholarly journals A remote sensing-based dataset to characterize the ecosystem functioning and functional diversity of a Biosphere Reserve: Sierra Nevada (SE Spain)

2020 ◽  
Author(s):  
Beatriz P. Cazorla ◽  
Javier Cabello ◽  
Andrés Reyes ◽  
Emilio Guirado ◽  
Julio Peñas ◽  
...  
Keyword(s):  
Functional Diversity ◽  
Sierra Nevada ◽  
Ecosystem Functioning ◽  
Vegetation Index ◽  
Management Practices ◽  
Environmental Gradients ◽  
Environmental Data ◽  
Data Availability ◽  
Ecological Processes

Abstract. Conservation Biology faces the challenge of safeguarding the ecological processes that sustain biodiversity. Characterization and evaluation of these processes can be carried out through attributes or functional traits related to the exchanges of matter and energy between vegetation and the atmosphere. Nowadays, the use of satellite imagery provides useful methods to produce a spatially continuous characterization of ecosystem functioning and processes at regional scales. Our dataset characterizes the patterns of ecosystem functioning in Sierra Nevada (Spain) from the vegetation greenness dynamics captured through the spectral vegetation index EVI (Enhanced Vegetation Index) since 2001 to 2018 (product MOD13Q1.006 from MODIS sensor). First, we provided three Ecosystem Functional Attributes (EFAs) (i.e., descriptors of annual primary production, seasonality, and phenology of carbon gains), as well as their integration into a synthetic mapping of Ecosystem Functional Types (EFTs). Second, we provided two measures of functional diversity: EFT richness and EFT rarity. Finally, in addition to the yearly maps, we calculated interannual summaries, i.e., means and inter-annual variabilities. Examples of research and management applications of these data sets are also included to highlight the value of EFAs and EFTs to improve the understanding and monitoring ecosystem processes across environmental gradients. The datasets are available in two open-source sites (PANGAEA: https://doi.pangaea.de/10.1594/PANGAEA.904575 (Cazorla et al. 2019) and http://obsnev.es/apps/efts_SN.html), and bring to scientists, managers and the general public valuable information on the first characterization of the functional diversity at ecosystem level developed in a Mediterranean hotspot. Sierra Nevada represents an exceptional ecology laboratory of field conditions, where a long-term monitoring (LTER) program was established 10 years ago. The data availability on biodiversity, climate, ecosystem services, hydrology, land-use changes and management practices from Sierra Nevada, will allow to explore the relationships between these other environmental data and ecosystem functional data that we provide in this work.

scholarly journals A Holling Functional Response Model for Mapping QTLs Governing Interspecific Interactions

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiao-Yu Zhang ◽  
Huiying Gong ◽  
Qing Fang ◽  
Xuli Zhu ◽  
Libo Jiang ◽  
...  
Keyword(s):  
Functional Response ◽  
Species Interactions ◽  
Community Dynamics ◽  
Interspecific Interactions ◽  
Microbial Interactions ◽  
Ecological Communities ◽  
Response Model ◽  
Ecological Interactions ◽  
Dynamic Complexity ◽  
Genome Level

Genes play an important role in community ecology and evolution, but how to identify the genes that affect community dynamics at the whole genome level is very challenging. Here, we develop a Holling type II functional response model for mapping quantitative trait loci (QTLs) that govern interspecific interactions. The model, integrated with generalized Lotka-Volterra differential dynamic equations, shows a better capacity to reveal the dynamic complexity of inter-species interactions than classic competition models. By applying the new model to a published mapping data from a competition experiment of two microbial species, we identify a set of previously uncharacterized QTLs that are specifically responsible for microbial cooperation and competition. The model can not only characterize how these QTLs affect microbial interactions, but also address how change in ecological interactions activates the genetic effects of the QTLs. This model provides a quantitative means of predicting the genetic architecture that shapes the dynamic behavior of ecological communities.

scholarly journals Novel communities from climate change

2012 ◽  
Vol 367 (1605) ◽  
pp. 2913-2922 ◽  
Author(s):  
Miguel Lurgi ◽  
Bernat C. López ◽  
José M. Montoya
Keyword(s):  
Climate Change ◽  
Species Interactions ◽  
Community Dynamics ◽  
Size Structure ◽  
Species Traits ◽  
Ecological Specialization ◽  
Community Size ◽  
Interacting Species ◽  
Distribution Ranges ◽  
Body Sizes

Climate change is generating novel communities composed of new combinations of species. These result from different degrees of species adaptations to changing biotic and abiotic conditions, and from differential range shifts of species. To determine whether the responses of organisms are determined by particular species traits and how species interactions and community dynamics are likely to be disrupted is a challenge. Here, we focus on two key traits: body size and ecological specialization. We present theoretical expectations and empirical evidence on how climate change affects these traits within communities. We then explore how these traits predispose species to shift or expand their distribution ranges, and associated changes on community size structure, food web organization and dynamics. We identify three major broad changes: (i) Shift in the distribution of body sizes towards smaller sizes, (ii) dominance of generalized interactions and the loss of specialized interactions, and (iii) changes in the balance of strong and weak interaction strengths in the short term. We finally identify two major uncertainties: (i) whether large-bodied species tend to preferentially shift their ranges more than small-bodied ones, and (ii) how interaction strengths will change in the long term and in the case of newly interacting species.

scholarly journals A hitchhiker guide to manta rays: Patterns of association between Mobula alfredi, M. birostris, their symbionts, and other fishes in the Maldives

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253704
Author(s):  
Aimee E. Nicholson-Jack ◽  
Joanna L. Harris ◽  
Kirsty Ballard ◽  
Katy M. E. Turner ◽  
Guy M. W. Stevens
Keyword(s):  
Species Interactions ◽  
Community Dynamics ◽  
Spatial And Temporal Variation ◽  
Ecological Processes ◽  
Individual Level ◽  
Near Term ◽  
Complex Relationships ◽  
The Individual ◽  
Future Work ◽  
First Time

Despite being among the largest and most charismatic species in the marine environment, considerable gaps remain in our understanding of the behavioural ecology of manta rays (Mobula alfredi, M. birostris). Manta rays are often sighted in association with an array of smaller hitchhiker fish species, which utilise their hosts as a sanctuary for shelter, protection, and the sustenance they provide. Species interactions, rather than the species at the individual level, determine the ecological processes that drive community dynamics, support biodiversity and ecosystem health. Thus, understanding the associations within marine communities is critical to implementing effective conservation and management. However, the underlying patterns between manta rays, their symbionts, and other hitchhiker species remain elusive. Here, we explore the spatial and temporal variation in hitchhiker presence with M. alfredi and M. birostris throughout the Maldives and investigate the factors which may influence association using generalised linear mixed effects models (GLMM). For the first time, associations between M. alfredi and M. birostris with hitchhiker species other than those belonging to the family Echeneidae are described. A variation in the species of hitchhiker associated with M. alfredi and M. birostris was identified, with sharksucker remora (Echeneis naucrates) and giant remora (Remora remora) being the most common, respectively. Spatiotemporal variation in the presence of manta rays was identified as a driver for the occurrence of ephemeral hitchhiker associations. Near-term pregnant female M. alfredi, and M. alfredi at cleaning stations, had the highest likelihood of an association with adult E. naucrates. Juvenile E. naucrates were more likely to be associated with juvenile M. alfredi, and a seasonal trend in E. naucrates host association was identified. Remora were most likely to be present with female M. birostris, and a mean number of 1.5 ± 0.5 R. remora were observed per M. birostris. It is hoped these initial findings will serve as the basis for future work into the complex relationships between manta rays and their hitchhikers.

Disease Ecology

Ecology ◽  
2015 ◽  
Author(s):  
Richard S. Ostfeld
Keyword(s):  
Infectious Disease ◽  
Population Dynamics ◽  
Species Interactions ◽  
Disease Ecology ◽  
Molecular Mechanisms ◽  
Community Dynamics ◽  
Interspecific Interactions ◽  
Biological Organization ◽  
Late 20Th Century ◽  
Individual Organism

Disease ecology is a rapidly developing subdiscipline of ecology concerned with how species interactions and abiotic components of the environment affect patterns and processes of disease. To date, disease ecology has focused largely on infectious disease. The scientific study of infectious disease has a long history dominated by specialists on the taxa of infectious agents (e.g., bacteriologists, virologists), mechanisms of host defense (e.g., immunologists), effects of infection on individual hosts (e.g., pathologists), effects on host populations (epidemiologists), and treatment (e.g., practicing physicians and veterinarians). Disease ecology arose as scientists increasingly recognized that the interactions between pathogen and host could be conceptually united with other interspecific interactions, such as those between predator and prey, competitors, or mutualists. At its simplest, an infectious disease consists of an interaction between one species of pathogen and one species of host. The evolution of disease ecology since the late 20th century has incorporated additional layers of complexity, including recognition that most pathogens infect multiple species of host, that hosts are infected with multiple pathogens, and that abiotic conditions (e.g., temperature, moisture) interact with biotic conditions to affect transmission and disease. As a consequence, a framework broader than the simplest host-pathogen system is often required to understand disease dynamics. Disease ecologists are interested both in the ecological causes of disease patterns (for instance, how the population density of a host influences transmission rates), and the ecological consequences of disease (for instance, how the population dynamics of a host species change as an epidemic progresses). Consequently, disease ecology today often integrates across several levels of biological organization, from molecular mechanisms of pathology and immunity; to individual-organism changes in health, survival, and reproduction; to population dynamics of hosts and pathogens; to community dynamics of hosts and pathogens; to impacts of disease on ecosystem processes; to ecosystem-level effects of climate change and landscape change on disease.

scholarly journals Ecological limits to evolutionary rescue

2020 ◽  
Vol 375 (1814) ◽  
pp. 20190453 ◽  
Author(s):  
Christopher A. Klausmeier ◽  
Matthew M. Osmond ◽  
Colin T. Kremer ◽  
Elena Litchman
Keyword(s):  
Species Interactions ◽  
Interspecific Interactions ◽  
Research Programme ◽  
Species Traits ◽  
Marine Conservation ◽  
Fundamental Limits ◽  
Fitness Functions ◽  
Changing Environments ◽  
Research Perspectives ◽  
Evolutionary Rescue

Environments change, for both natural and anthropogenic reasons, which can threaten species persistence. Evolutionary adaptation is a potentially powerful mechanism to allow species to persist in these changing environments. To determine the conditions under which adaptation will prevent extinction (evolutionary rescue), classic quantitative genetics models have assumed a constantly changing environment. They predict that species traits will track a moving environmental optimum with a lag that approaches a constant. If fitness is negative at this lag, the species will go extinct. There have been many elaborations of these models incorporating increased genetic realism. Here, we review and explore the consequences of four ecological complications: non-quadratic fitness functions, interacting density- and trait-dependence, species interactions and fundamental limits to adaptation. We show that non-quadratic fitness functions can result in evolutionary tipping points and existential crises, as can the interaction between density- and trait-dependent mortality. We then review the literature on how interspecific interactions affect adaptation and persistence. Finally, we suggest an alternative theoretical framework that considers bounded environmental change and fundamental limits to adaptation. A research programme that combines theory and experiments and integrates across organizational scales will be needed to predict whether adaptation will prevent species extinction in changing environments. This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.

scholarly journals Environment affects specialisation of plants and pollinators

2019 ◽  
Author(s):  
E. Fernando Cagua ◽  
Audrey Lustig ◽  
Jason M. Tylianakis ◽  
Daniel B. Stouffer
Keyword(s):  
Environmental Stress ◽  
Community Composition ◽  
Environmental Conditions ◽  
Species Interactions ◽  
Evolutionary History ◽  
Environmental Gradients ◽  
Species Traits ◽  
Environmental Variable ◽  
Species Level ◽  
Plant Pollinator

AbstractWhat determines whether or not a species is a generalist or a specialist? Evidence that the environment can influence species interactions is rapidly accumulating. However, a systematic link between environment and the number of partners a species interacts with has been elusive so far. Presumably, because environmental gradients appear to have contrasting effects on species depending on the environmental variable. Here, we test for a relationship between the stresses imposed by the environment, instead of environmental gradients directly, and species specialisation using a global dataset of plant-pollinator interactions. We found that the environment can play a significant effect on specialisation, even when accounting for community composition, likely by interacting with species’ traits and evolutionary history. Species that have a large number of interactions are more likely to focus on a smaller number of, presumably higher-quality, interactions under stressful environmental conditions. Contrastingly, the specialists present in multiple locations are more likely to broaden their niche, presumably engaging in opportunistic interactions to cope with increased environmental stress. Indeed, many apparent specialists effectively behave as facultative generalists. Overall, many of the species we analysed are not inherently generalist or specialist. Instead, species’ level of specialisation should be considered on a relative scale depending on where they are found and the environmental conditions at that location.

scholarly journals Plant-pollinator Vocabulary - a Contribution to Interaction Data Standardization

2021 ◽  
Vol 5 ◽  
Author(s):  
José Augusto Salim ◽  
Paula Zermoglio ◽  
Debora Drucker ◽  
Filipi Soares ◽  
Antonio Saraiva ◽  
...  
Keyword(s):  
Ecosystem Functioning ◽  
Species Interactions ◽  
Interspecific Interactions ◽  
Data Representation ◽  
Data Availability ◽  
Primary Data ◽  
Great Effort ◽  
Interaction Data ◽  
Data Repositories ◽  
Plant Pollinator

Human demands on resources such as food and energy are increasing through time while global challenges such as climate change and biodiversity loss are becoming more complex to overcome, as well as more widely acknowledged by societies and governments. Reports from initiatives like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) have demanded quick and reliable access to high-quality spatial and temporal data of species occurrences, their interspecific relations and the effects of the environment on biotic interactions. Mapping species interactions is crucial to understanding and conserving ecosystem functioning and all the services it can provide (Tylianakis et al. 2010, Slade et al. 2017). Detailed data has the potential to improve our knowledge about ecological and evolutionary processes guided by interspecific interactions, as well as to assist in planning and decision making for biodiversity conservation and restoration (Menz et al. 2011). Although a great effort has been made to successfully standardize and aggregate species occurrence data, a formal standard to support biotic interaction data sharing and interoperability is still lacking. There are different biological interactions that can be studied, such as predator-prey, host-parasite and pollinator-plant and there is a variety of data practices and data representation procedures that can be used. Plant-pollinator interactions are recognized in many sources from the scientific literature (Abrol 2012, Ollerton 2021) for the importance of ecosystem functioning and sustainable agriculture. Primary data about pollination are becoming increasingly available online and can be accessed from a great number of data repositories. While a vast quantity of data on interactions, and on pollination in particular, is available, data are not integrated among sources, largely because of a lack of appropriate standards. We present a vocabulary of terms for sharing plant-pollinator interactions using one of the existing extensions to the Darwin Core standard (Wieczorek et al. 2012). In particular, the vocabulary is meant to be used for the term measurementType of the Extended Measurement Or Facts extension. The vocabulary was developed by a community of specialists in pollination biology and information science, including members of the TDWG Biological Interaction Data Interest Group, during almost four years of collaborative work. The vocabulary introduces 40 new terms, comprising many aspects of plant-pollinator interactions, and can be used to capture information produced by studies with different approaches and scales. The plant-pollinator interactions vocabulary is mainly a set of terms that can be both understood by people or interpreted by machines. The plant-pollinator vocabulary is composed of a defining a set of terms and descriptive documents explaining how the vocabulary is to be used. The terms in the vocabulary are divided into six categories: Animal, Plants, Flower, Interaction, Reproductive Success and Nectar Dynamics. The categories are not formally part of the vocabulary, they are used only to organize the vocabulary and to facilitate understanding by humans. We expect that the plant-pollinator vocabulary will contribute to data aggregation from a variety of sources worldwide at higher levels than we have experienced, significantly amplify plant-pollinator data availability for global synthesis, and contribute to knowledge in conservation and sustainable use of biodiversity.

scholarly journals Stochastic processes dominate community assembly in cichlid communities in Lake Tanganyika

2016 ◽  
Author(s):  
Thijs Janzen ◽  
Adriana Alzate ◽  
Moritz Muschick ◽  
Fons van der Plas ◽  
Rampal S. Etienne
Keyword(s):  
Stochastic Processes ◽  
Community Assembly ◽  
Environmental Conditions ◽  
Lake Tanganyika ◽  
Environmental Gradients ◽  
Cichlid Fish ◽  
Species Traits ◽  
Ecological Processes ◽  
African Great Lakes ◽  
Community Dissimilarity

ABSTRACTThe African Great Lakes are characterized by an extraordinary diversity of endemic cichlid fish species. The cause of this diversity is still largely unknown. Most studies have tried to solve this question by focusing on macro-evolutionary processes, such as speciation. However, the ecological processes determining local cichlid diversity have so far been understudied, even though knowledge on these might be crucial for understanding larger scale biodiversity patterns.Using trait, environmental and abundance data of cichlid fishes along 36 transects, we have studied how differences in local environmental conditions influence cichlid community assembly in the littoral of Lake Tanganyika, Zambia. We investigated changes in average trait values and in trait-based community assembly processes along three key environmental gradients.Species diversity and local abundance decreased with increasing sand cover and diet-associated traits changed with depth. Analyses on within-community trait diversity patterns indicated that cichlid community assembly was mainly driven by stochastic processes, to a smaller extent by processes that limit the similarity among co-existing species and least by filtering processes that limit the range of species traits occurring in an environment. Despite, the low impact of habitat filtering processes, we find community dissimilarity to increase with increasing environmental difference.Our results suggest that local environmental conditions determine cichlid abundance, while the predominance of stochastic community assembly across all environments explains why the communities with the highest abundances contain most species.

scholarly journals Seasonal food webs with migrations: multi-season models reveal indirect species interactions in the Canadian Arctic tundra

2020 ◽  
Vol 378 (2181) ◽  
pp. 20190354 ◽  
Author(s):  
Chantal Hutchison ◽  
Frédéric Guichard ◽  
Pierre Legagneux ◽  
Gilles Gauthier ◽  
Joël Bêty ◽  
...  
Keyword(s):  
Food Web ◽  
Food Webs ◽  
Ecosystem Functioning ◽  
Species Interactions ◽  
Multiple Equilibria ◽  
Community Dynamics ◽  
Static Model ◽  
Predator Prey ◽  
Summer Time ◽  
The Impact

Models incorporating seasonality are necessary to fully assess the impact of global warming on Arctic communities. Seasonal migrations are a key component of Arctic food webs that still elude current theories predicting a single community equilibrium. We develop a multi-season model of predator–prey dynamics using a hybrid dynamical systems framework applied to a simplified tundra food web (lemming–fox–goose–owl). Hybrid systems models can accommodate multiple equilibria, which is a basic requirement for modelling food webs whose topology changes with season. We demonstrate that our model can generate multi-annual cycling in lemming dynamics, solely from a combined effect of seasonality and state-dependent behaviour. We compare our multi-season model to a static model of the predator–prey community dynamics and study the interactions between species. Interestingly, including seasonality reveals indirect interactions between migrants and residents not captured by the static model. Further, we find that the direction and magnitude of interactions between two species are not necessarily accurate using only summer time-series. Our study demonstrates the need for the development of multi-season models and provides the tools to analyse them. Integrating seasonality in food web modelling is a vital step to improve predictions about the impacts of climate change on ecosystem functioning. This article is part of the theme issue ‘The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning’.

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