scholarly journals Food web networks shift across a precipitation gradient due to changes in community composition and species interactions

2018 ◽  
Author(s):  
Laura Melissa Guzman ◽  
Bram Vanschoenwinkel ◽  
Vinicius F. Farjalla ◽  
Anita Poon ◽  
Diane Srivastava
Keyword(s):  
Community Composition ◽  
Species Interactions ◽  
Environmental Gradients ◽  
Interaction Strength ◽  
Species Interaction ◽  
Ecological Networks ◽  
Water Volume ◽  
Brazilian Coast ◽  
Markov Network ◽  
Water Volumes

AbstractEcological networks change across spatial and environmental gradients due to (i) changes in species composition or (ii) changes in the frequency or strength of interactions. Here we use the communities of aquatic invertebrates inhabiting clusters of bromeliad phytotelms along the Brazilian coast as a model system for examining turnover in the properties of ecological networks. We first document the variation in the species pools of sites across a geographical climate gradient. Using the same sites, we also explored the geographic variation in species interaction strength using a newly developed Markov network approach. We found that community composition differed along a gradient of water volume within bromeliads due to the turnover of some species. From the Markov network analysis, we found that the top-down effects of certain predators differed geographically, which could also be explained by geographic differences in bromeliad water volumes. Overall, this study illustrates how a network can change across an environmental gradient through both changes in both species and their interactions.

scholarly journals Towards an Essential Biodiversity Variable for Species Interactions

2018 ◽  
Vol 2 ◽  
pp. e25409
Author(s):  
Quentin Groom ◽  
Robert Guralnick ◽  
W. Daniel Kissling
Keyword(s):  
Species Interactions ◽  
Interaction Strength ◽  
Species Traits ◽  
Species Interaction ◽  
Ecological Networks ◽  
Microbial Interactions ◽  
Ecosystem Structure ◽  
State Variables ◽  
Flower Visitation ◽  
Wide Range

Can Essential Biodiversity Variables (EBVs) be developed to monitor changes in species interactions? That was the difficult question asked at the GLOBIS-B workshop in February, 2017 in which >50 experts participated. EBVs can be defined as harmonized measurements that allow us to inform policy about essential changes in biodiversity. They can be seen as biological state variables from which more refined indicators may be derived. They have been presented as a means to monitor global biodiversity change and as a concept to drive the gathering, sharing, and standardisation of data on our biota (Geijzendorffer et al. 2015, Kissling et al. 2017, Pereira et al. 2013). There are different classes of EBVs that characterize, for example, the state of species populations, species traits and ecosystem structure and function. It has also been proposed that there should be EBVs related to species interactions. However, until now there has been little progress formulating what these should be, even though species interactions are central to ecology. Species interactions cover a wide range of important processes, from mutualisms, such as pollination, to different forms of heterotrophic nutrition, such as the predator-prey relationship. Indeed, ecological interactions are critical to understand why an ecosystem is more than the sum of its parts. Nevertheless, direct observation of species interactions is often difficult and time consuming work, which makes it difficult to monitor them in the long-term. For this reason the workshop focused on those species interactions that are feasible to study and are most relevant to policy. To bring focus to our discussions we concentrated on pollination, predation and microbial interactions. Taking pollination as an example, there was recognition of the importance of ecological networks and that network metrics may be a sensitive indicator of change. Potential EBVs might be the number of pairwise interactions between species or the modularity and interaction diversity of the whole network. This requires standardised data collection and reporting (e.g. standardization of measures of interaction strength or minimum data specifications for ecological networks) and sufficient data across time to regularly calculate these metrics. Other simpler surrogates for pollination might also prove useful, such as flower visitation rates or the proportion of fruit set. Finally, there was a recognition that we do not yet have enough tools to monitor some important interactions. Many interactions, particular among microbes, can currently only be inferred from the co-occurrence of taxa. However, technology is rapidly developing and it is possible to foresee a future where even these interactions can be monitored efficiently. Species interactions are essential to understanding ecology, but they are also difficult to monitor. Yet, delegates at the workshop left with a positive outlook that it is valuable to develop standardisation and harmonization of species interaction data to make them suitable for EBV production.

scholarly journals Bayesian characterization of uncertainty in species interaction strengths

2015 ◽  
Author(s):  
Christopher Wolf ◽  
Mark Novak ◽  
Alix I. Gitelman
Keyword(s):  
Species Interactions ◽  
Statistical Significance ◽  
Interaction Strength ◽  
Species Interaction ◽  
Superior Performance ◽  
Empirical Estimation ◽  
Statistical Significance Testing ◽  
Estimation Uncertainty ◽  
Point Estimates

Considerable effort has been devoted to the empirical estimation of species interaction strengths. This effort has focused primarily on statistical significance testing and on obtaining point estimates of parameters that contribute to interaction strength magnitude, leaving characterizations of estimation uncertainty and distinctions between the deterministic and stochastic contributions to variation largely unconsidered. Here we consider a means of quantifying interaction strength uncertainty by formulating an observational method for estimating per capita attack rates as a Bayesian statistical model. This formulation permits the explicit incorporation of multiple sources of uncertainty. In doing so we highlight the informative nature of several so-called non-informative prior choices in modeling the sparse data typical of predator feeding surveys and provide evidence for the superior performance of a new neutral prior choice. A case study application shows that while Bayesian point estimates may be made to correspond with those obtained by frequentist approaches, estimation uncertainty as described by the 95% intervals is more biologically realistic using the Bayesian method in that the lower bounds of the Bayesian posterior intervals for the attack rates do not include zero when the occurrence of a given predator-prey interaction is in fact observed. This contrasts with bootstrap confidence intervals that often do contain zero in such cases. The Bayesian approach provides a straightforward, probabilistic characterization of interaction strength uncertainty. In doing so it provides a framework for considering both the deterministic and stochastic drivers of species interactions and their impact on food web dynamics.

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

2021 ◽  
Vol 376 (1837) ◽  
pp. 20210063 ◽  
Author(s):  
Tanya Strydom ◽  
Michael D. Catchen ◽  
Francis Banville ◽  
Dominique Caron ◽  
Gabriel Dansereau ◽  
...  
Keyword(s):  
Species Interactions ◽  
False Negative ◽  
Research Programme ◽  
Species Interaction ◽  
Ecological Networks ◽  
Ecological Communities ◽  
True Negative ◽  
Structure Variation ◽  
Space And Time ◽  
Simple Neural Network

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’.

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 Dynamics of species interaction strength in space, time and with developmental stage

2010 ◽  
Vol 278 (1713) ◽  
pp. 1804-1813 ◽  
Author(s):  
Rebecca L. Kordas ◽  
Steve Dudgeon
Keyword(s):  
Species Interactions ◽  
Community Dynamics ◽  
Gulf Of Maine ◽  
Interaction Strength ◽  
Species Interaction ◽  
Priority Effects ◽  
Rocky Shores ◽  
Target Populations ◽  
Geographical Regions ◽  
Per Capita

Quantifying species interaction strengths enhances prediction of community dynamics, but variability in the strength of species interactions in space and time complicates accurate prediction. Interaction strengths can vary in response to density, indirect effects, priority effects or a changing environment, but the mechanism(s) causing direction and magnitudes of change are often unclear. We designed an experiment to characterize how environmental factors influence the direction and the strength of priority effects between sessile species. We estimated per capita non-trophic effects of barnacles ( Semibalanus balanoides ) on newly settled germlings of the fucoid, Ascophyllum nodosum , in the presence and absence of consumers in experiments on rocky shores throughout the Gulf of Maine, USA. Per capita effects on germlings varied among environments and barnacle life stages, and these interaction strengths were largely unaltered by changing consumer abundance. Whereas previous evidence shows adult barnacles facilitate fucoids, here, we show that recent settlers and established juveniles initially compete with germlings. As barnacles mature, they switch to become facilitators of fucoids. Consumers caused variable mortality of germlings through time comparable to that from competition. Temporally variable effects of interactors (e.g. S. balanoides ), or spatial variation in their population structure, in different regions differentially affect target populations (e.g. A. nodosum ). This may affect abundance of critical stages and the resilience of target species to environmental change in different geographical regions.

scholarly journals Bayesian characterization of uncertainty in species interaction strengths

2015 ◽  
Author(s):  
Christopher Wolf ◽  
Mark Novak ◽  
Alix I. Gitelman
Keyword(s):  
Species Interactions ◽  
Statistical Significance ◽  
Interaction Strength ◽  
Species Interaction ◽  
Superior Performance ◽  
Empirical Estimation ◽  
Statistical Significance Testing ◽  
Estimation Uncertainty ◽  
Point Estimates

Considerable effort has been devoted to the empirical estimation of species interaction strengths. This effort has focused primarily on statistical significance testing and on obtaining point estimates of parameters that contribute to interaction strength magnitude, leaving characterizations of estimation uncertainty and distinctions between the deterministic and stochastic contributions to variation largely unconsidered. Here we consider a means of quantifying interaction strength uncertainty by formulating an observational method for estimating per capita attack rates as a Bayesian statistical model. This formulation permits the explicit incorporation of multiple sources of uncertainty. In doing so we highlight the informative nature of several so-called non-informative prior choices in modeling the sparse data typical of predator feeding surveys and provide evidence for the superior performance of a new neutral prior choice. A case study application shows that while Bayesian point estimates may be made to correspond with those obtained by frequentist approaches, estimation uncertainty as described by the 95% intervals is more biologically realistic using the Bayesian method in that the lower bounds of the Bayesian posterior intervals for the attack rates do not include zero when the occurrence of a given predator-prey interaction is in fact observed. This contrasts with bootstrap confidence intervals that often do contain zero in such cases. The Bayesian approach provides a straightforward, probabilistic characterization of interaction strength uncertainty. In doing so it provides a framework for considering both the deterministic and stochastic drivers of species interactions and their impact on food web dynamics.

scholarly journals Network ecology in dynamic landscapes

2021 ◽  
Vol 288 (1949) ◽  
Author(s):  
Marie-Josée Fortin ◽  
Mark R. T. Dale ◽  
Chris Brimacombe
Keyword(s):  
Species Interactions ◽  
Environmental Changes ◽  
Complex Dynamics ◽  
Landscape Heterogeneity ◽  
Species Interaction ◽  
Ecological Networks ◽  
Species Dispersal ◽  
Trade Offs ◽  
Dynamic Landscapes ◽  
Network Topologies

Network ecology is an emerging field that allows researchers to conceptualize and analyse ecological networks and their dynamics. Here, we focus on the dynamics of ecological networks in response to environmental changes. Specifically, we formalize how network topologies constrain the dynamics of ecological systems into a unifying framework in network ecology that we refer to as the ‘ecological network dynamics framework’. This framework stresses that the interplay between species interaction networks and the spatial layout of habitat patches is key to identifying which network properties (number and weights of nodes and links) and trade-offs among them are needed to maintain species interactions in dynamic landscapes. We conclude that to be functional, ecological networks should be scaled according to species dispersal abilities in response to landscape heterogeneity. Determining how such effective ecological networks change through space and time can help reveal their complex dynamics in a changing world.

scholarly journals Specific non-monotonous interactions increase persistence of ecological networks

2014 ◽  
Vol 281 (1779) ◽  
pp. 20132797 ◽  
Author(s):  
Chuan Yan ◽  
Zhibin Zhang
Keyword(s):  
Population Density ◽  
Equilibrium Points ◽  
Interaction Strength ◽  
Species Interaction ◽  
Ecological Networks ◽  
High Population ◽  
Positive Interactions ◽  
High Population Density ◽  
Theoretical Predictions ◽  
The Relationship

The relationship between stability and biodiversity has long been debated in ecology due to opposing empirical observations and theoretical predictions. Species interaction strength is often assumed to be monotonically related to population density, but the effects on stability of ecological networks of non-monotonous interactions that change signs have not been investigated previously. We demonstrate that for four kinds of non-monotonous interactions, shifting signs to negative or neutral interactions at high population density increases persistence (a measure of stability) of ecological networks, while for the other two kinds of non-monotonous interactions shifting signs to positive interactions at high population density decreases persistence of networks. Our results reveal a novel mechanism of network stabilization caused by specific non-monotonous interaction types through either increasing stable equilibrium points or reducing unstable equilibrium points (or both). These specific non-monotonous interactions may be important in maintaining stable and complex ecological networks, as well as other networks such as genes, neurons, the internet and human societies.

Spray Volume, Canopy Density, and Other Factors Involved in Thinner Efficacy

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 553d-553
Author(s):  
C.R. Unrath
Keyword(s):  
Tree Height ◽  
Tree Canopy ◽  
Tree Size ◽  
Water Volume ◽  
Canopy Density ◽  
The North ◽  
Run Off ◽  
Tree Canopies ◽  
Average Water ◽  
Water Volumes

Historically, most airblast chemical applications to apple orchards used a single “average” water volume, resulting in variability of coverage with tree size and also the greatest variable in chemical thinning. This coverage variability can be eliminated by properly quantifying the tree canopy, as tree row volume (TRV), and relating that volume to airblast water rate for adequate coverge. Maximum typical tree height, cross-row limb spread, and between-row spacing are used to quantify the TRV. Further refinement is achieved by adjusting the water volume for tree canopy density. The North Carolina TRV model allows a density adjustment from 0.7 gal/1000 ft3 of TRV for young, very open tree canopies to 1.0 gal/1000 ft3 of TRV for large, thick tree canopies to deliver a full dilute application for maximum water application (to the point of run-off). Most dilute pesticide applications use 70% of full dilute to approach the point of drip (pesticide dilute) to not waste chemicals and reduce non-target environmental exposure. From the “chemical load” (i.e., lb/acre) calculated for the pesticide dilute application, the proper chemical load for lower (concentrate) water volumes can be accurately determined. Another significant source of variability is thinner application response is spray distribution to various areas of the tree. This variability is related to tree configuration, light, levels, fruit set, and natural thinning vs. the need for chemical thinning. Required water delivery patterns are a function of tree size, form, spacing, and density, as well as sprayer design (no. of nozzles and fan size). The TRV model, density adjustments, and nozzle patterns to effectively hit the target for uniform crop load will be addressed.

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