scholarly journals The Biodiversity of Ecological Interactions: Challenges for recording and documenting the Web of Life

2021 ◽  
Vol 5 ◽  
Author(s):  
Pedro Jordano
Keyword(s):  
Species Interactions ◽  
Camera Traps ◽  
Individual Species ◽  
Ecological Interactions ◽  
Interaction Type ◽  
Ecological Interaction ◽  
Daunting Task ◽  
Biodiversity Inventories ◽  
Main Components ◽  
Earth’S System

Biodiversity is more than a collection of individual species. It is the combination of biological entities and processes supporting life on Earth: no single species persists without interacting with other species. A full account of biodiversity on Earth needs to document the essential ecological interactions that support Earth’s system through their functional outcomes. Quantifying biodiversity’s interactome (the whole suite of interactions among biotic organisms) is challenging not just because of the daunting task of describing ecosystem complexity, it’s also limited by the need to define and establish a proper grammar to record and catalog species interactions. Actually, a record of a pairwise interaction between two species can be identified as a "tetranomial species", with just a concatenation of the two Latin binomials. Thus sampling interactions requires solving exactly the same constraints and problems we face when sampling biodiversity. In real interaction webs, the number of actual pairwise interactions among species in local assemblages scales exponentially with species richness. I discuss the main components of these interactions and those that are key to properly sample and document them. Interactions take the form of predation, competition, commensalism, amensalism, mutualism, symbiosis, and parasitism and, in all cases, involve reciprocal effects for the interacting species and build into highly complex networks (Fig. 1). The type of metadata required to document ecological interactions between partner species depends on interaction type; yet a fraction of these metadata is shared with those of the partner species. The interaction type sets limits to between-species encounters (actually, encounters between individuals of the partner species) and, more importantly, sets the type of outcome emerging from the interactions. There is a broad range of information that can eventually be acquired when recording an ecological interaction: from its simple presence (the interaction exists, it's been just recorded) to an estimate of its frequency, to obtaining data about its outcome or per-interaction effect (e.g., number of flowers pollinated in a visit by a pollinator to a plant). In addition, the types of interaction data can be quite diverse, reflecting the variety of sampling methods: interaction records from direct observation in the field; camera-traps; DNA-barcoding; bibliographic sources; surveys of image databases, etc. Interaction biodiversity inventories may require merging information coming from these distinct data sources. All these components need to be properly defined in order to build informative metadata and to document ecological interaction records. We are just starting to delineate the main components needed to catalog and inventory ecological interactions as a part of biodiversity inventories.

scholarly journals Inhibition or Facilitation? Contrasted Inter-Specific Interactions in Sphagnum under Laboratory and Field Conditions

Plants ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1554
Author(s):  
Chao Liu ◽  
Zhao-Jun Bu ◽  
Azim Mallik ◽  
Yong-Da Chen ◽  
Xue-Feng Hu ◽  
...  
Keyword(s):  
Field Experiment ◽  
Species Interactions ◽  
Laboratory Experiments ◽  
Resource Competition ◽  
Specific Interactions ◽  
Interaction Type ◽  
Negative Effects ◽  
Experiment Data ◽  
The Stability ◽  
Positive Effect

In a natural environment, plants usually interact with their neighbors predominantly through resource competition, allelopathy, and facilitation. The occurrence of the positive effect of allelopathy between peat mosses (Sphagnum L.) is rare, but it has been observed in a field experiment. It is unclear whether the stability of the water table level in peat induces positive vs. negative effects of allelopathy and how that is related to phenolic allelochemical production in Sphagnum. Based on field experiment data, we established a laboratory experiment with three neighborhood treatments to measure inter-specific interactions between Sphagnum angustifolium (Russ.) C. Jens and Sphagnum magellanicum Brid. We found that the two species were strongly suppressed by the allelopathic effects of each other. S. magellanicum allelopathically facilitated S. angustifolium in the field but inhibited it in the laboratory, and relative allelopathy intensity appeared to be positively related to the content of released phenolics. We conclude that the interaction type and intensity between plants are dependent on environmental conditions. The concentration of phenolics alone may not explain the type and relative intensity of allelopathy. Carefully designed combined field and laboratory experiments are necessary to reveal the mechanism of species interactions in natural communities.

scholarly journals An equation-free method reveals the ecological interaction networks within complex microbial ecosystems

2016 ◽  
Author(s):  
Kenta Suzuki ◽  
Katsuhiko Yoshida ◽  
Yumiko Nakanishi ◽  
Shinji Fukuda
Keyword(s):  
Time Series ◽  
Microbial Communities ◽  
Microbial Processes ◽  
Interaction Networks ◽  
List Type ◽  
Metagenomic Sequencing ◽  
Ecological Interactions ◽  
Microbial Interaction ◽  
Ecological Interaction ◽  
Dataset Size

AbstractMapping the network of ecological interactions is key to understanding the composition, stability, function and dynamics of microbial communities. In recent years various approaches have been used to reveal microbial interaction networks from metagenomic sequencing data, such as time-series analysis, machine learning and statistical techniques. Despite these efforts it is still not possible to capture details of the ecological interactions behind complex microbial dynamics.We developed the sparse S-map method (SSM), which generates a sparse interaction network from a multivariate ecological time-series without presuming any mathematical formulation for the underlying microbial processes. The advantage of the SSM over alternative methodologies is that it fully utilizes the observed data using a framework of empirical dynamic modelling. This makes the SSM robust to non-equilibrium dynamics and underlying complexity (nonlinearity) in microbial processes.We showed that an increase in dataset size or a decrease in observational error improved the accuracy of SSM whereas, the accuracy of a comparative equation-based method was almost unchanged for both cases and equivalent to the SSM at best. Hence, the SSM outperformed a comparative equation-based method when datasets were large and the magnitude of observational errors were small. The results were robust to the magnitude of process noise and the functional forms of inter-specific interactions that we tested. We applied the method to a microbiome data of six mice and found that there were different microbial interaction regimes between young to middle age (4-40 week-old) and middle to old age (36-72 week-old) mice.The complexity of microbial relationships impedes detailed equation-based modeling. Our method provides a powerful alternative framework to infer ecological interaction networks of microbial communities in various environments and will be improved by further developments in metagenomics sequencing technologies leading to increased dataset size and improved accuracy and precision.

scholarly journals Species interactions in three Lemnaceae species growing along a gradient of zinc pollution

2021 ◽  
Author(s):  
Lorena Lanthemann ◽  
Sofia van Moorsel
Keyword(s):  
Growth Rates ◽  
Species Interactions ◽  
Metal Removal ◽  
Lemna Minor ◽  
Polluted Water ◽  
Future Research ◽  
Individual Species ◽  
High Tolerance ◽  
Species Mixture ◽  
The Individual

Duckweeds (Lemnaceae) are increasingly studied for their potential for phytoremediation of heavy-metal polluted water bodies. A prerequisite for metal removal, however, is the tolerance of the organism to the pollutant, e.g., the metal zinc (Zn). Duckweeds have been shown to differ in their tolerances to Zn, however, despite them most commonly co-occurring with other species, there is a lack of research concerning the effect of species interactions on Zn tolerance. Here we tested whether the presence of a second species influenced the growth rate of the three duckweed species Lemna minor, Lemna gibba, and Lemna turionifera. We used four different Zn concentrations in a replicated microcosm experiment under sterile conditions, either growing the species in isolation or in a 2-species mixture. The response to Zn differed between species, but all three species showed a high tolerance to Zn, with low levels of Zn even increasing the growth rates. The growth rates of the individual species were influenced by the identity of the competing species, but this was independent of the Zn concentration. Our results suggest that species interactions should be considered in future research with duckweeds and that several duckweed species have high tolerance to metal pollution, making them candidates for phytoremediation efforts.

scholarly journals A sparse observation model to quantify species interactions in time and space

2019 ◽  
Author(s):  
Sadoune Ait Kaci Azzou ◽  
Liam Singer ◽  
Thierry Aebischer ◽  
Madleina Caduff ◽  
Beat Wolf ◽  
...  
Keyword(s):  
Species Interactions ◽  
Activity Patterns ◽  
Niche Partitioning ◽  
Camera Trap ◽  
Camera Traps ◽  
Observation Model ◽  
Occupancy Models ◽  
Time And Space ◽  
Imperfect Detection ◽  
Mobile Species

SummaryCamera traps and acoustic recording devices are essential tools to quantify the distribution, abundance and behavior of mobile species. Varying detection probabilities among device locations must be accounted for when analyzing such data, which is generally done using occupancy models. We introduce a Bayesian Time-dependent Observation Model for Camera Trap data (Tomcat), suited to estimate relative event densities in space and time. Tomcat allows to learn about the environmental requirements and daily activity patterns of species while accounting for imperfect detection. It further implements a sparse model that deals well will a large number of potentially highly correlated environmental variables. By integrating both spatial and temporal information, we extend the notation of overlap coefficient between species to time and space to study niche partitioning. We illustrate the power of Tomcat through an application to camera trap data of eight sympatrically occurring duiker Cephalophinae species in the savanna - rainforest ecotone in the Central African Republic and show that most species pairs show little overlap. Exceptions are those for which one species is very rare, likely as a result of direct competition.

scholarly journals Ecological Interactions and the Netflix Problem

2016 ◽  
Author(s):  
Philippe Desjardins-Proulx ◽  
Idaline Laigle ◽  
Timothée Poisot ◽  
Dominique Gravel
Keyword(s):  
Machine Learning ◽  
Supervised Learning ◽  
Random Forests ◽  
Species Interactions ◽  
Similarity Measures ◽  
Theoretical Models ◽  
Machine Learning Techniques ◽  
Nearest Neighbour ◽  
Ecological Interactions ◽  
Learning Techniques

0AbstractSpecies interactions are a key component of ecosystems but we generally have an incomplete picture of who-eats-who in a given community. Different techniques have been devised to predict species interactions using theoretical models or abundances. Here, we explore the K nearest neighbour approach, with a special emphasis on recommendation, along with other machine learning techniques. Recommenders are algorithms developed for companies like Netflix to predict if a customer would like a product given the preferences of similar customers. These machine learning techniques are well-suited to study binary ecological interactions since they focus on positive-only data. We also explore how the K nearest neighbour approach can be used with both positive and negative information, in which case the goal of the algorithm is to fill missing entries from a matrix (imputation). By removing a prey from a predator, we find that recommenders can guess the missing prey around 50% of the times on the first try, with up to 881 possibilities. Traits do not improve significantly the results for the K nearest neighbour, although a simple test with a supervised learning approach (random forests) show we can predict interactions with high accuracy using only three traits per species. This result shows that binary interactions can be predicted without regard to the ecological community given only three variables: body mass and two variables for the species’ phylogeny. These techniques are complementary, as recommenders can predict interactions in the absence of traits, using only information about other species’ interactions, while supervised learning algorithms such as random forests base their predictions on traits only but do not exploit other species’ interactions. Further work should focus on developing custom similarity measures specialized to ecology to improve the KNN algorithms and using richer data to capture indirect relationships between species.

scholarly journals Differential arthropod responses to warming are altering the structure of Arctic communities

2018 ◽  
Vol 5 (4) ◽  
pp. 171503 ◽  
Author(s):  
Amanda M. Koltz ◽  
Niels M. Schmidt ◽  
Toke T. Høye
Keyword(s):  
Community Composition ◽  
Primary Productivity ◽  
Species Interactions ◽  
Ecosystem Processes ◽  
The Arctic ◽  
Individual Species ◽  
Freeze Thaw ◽  
Compositional Changes ◽  
Arctic Communities

The Arctic is experiencing some of the fastest rates of warming on the planet. Although many studies have documented responses to such warming by individual species, the idiosyncratic nature of these findings has prevented us from extrapolating them to community-level predictions. Here, we leverage the availability of a long-term dataset from Zackenberg, Greenland (593 700 specimens collected between 1996 and 2014), to investigate how climate parameters influence the abundance of different arthropod groups and overall community composition. We find that variation in mean seasonal temperatures, winter duration and winter freeze–thaw events is correlated with taxon-specific and habitat-dependent changes in arthropod abundances. In addition, we find that arthropod communities have exhibited compositional changes consistent with the expected effects of recent shifts towards warmer active seasons and fewer freeze–thaw events in NE Greenland. Changes in community composition are up to five times more extreme in drier than wet habitats, with herbivores and parasitoids generally increasing in abundance, while the opposite is true for surface detritivores. These results suggest that species interactions and food web dynamics are changing in the Arctic, with potential implications for key ecosystem processes such as decomposition, nutrient cycling and primary productivity.

Zooming in on mechanistic predator–prey ecology: Integrating camera traps with experimental methods to reveal the drivers of ecological interactions

2020 ◽  
Vol 89 (9) ◽  
pp. 1997-2012 ◽  
Author(s):  
Justine A. Smith ◽  
Justin P. Suraci ◽  
Jennifer S. Hunter ◽  
Kaitlyn M. Gaynor ◽  
Carson B. Keller ◽  
...  
Keyword(s):  
Experimental Methods ◽  
Camera Traps ◽  
Ecological Interactions ◽  
Predator Prey

Effects of different attractants and human scent on mesocarnivore detection at camera traps

2020 ◽  
Vol 47 (4) ◽  
pp. 338
Author(s):  
Bracy W. Heinlein ◽  
Rachael E. Urbanek ◽  
Colleen Olfenbuttel ◽  
Casey G. Dukes
Keyword(s):  
Fatty Acid ◽  
Castor Oil ◽  
Camera Trap ◽  
Camera Traps ◽  
Individual Species ◽  
Detection Rates ◽  
Capture Success ◽  
Affect Detection ◽  
Species Specific

Abstract ContextCamera traps paired with baits and scented lures can be used to monitor mesocarnivore populations, but not all attractants are equally effective. Several studies have investigated the efficacy of different attractants on the success of luring mesocarnivores to camera traps; fewer studies have examined the effect of human scent at camera traps. AimsWe sought to determine the effects of human scent, four attractants and the interaction between attractants and human scent in luring mesocarnivores to camera traps. Methods We compared the success of synthetic fermented egg (SFE), fatty acid scent (FAS) tablets, castor oil, and sardines against a control of no attractant in luring mesocarnivores to camera traps. We deployed each attractant and the control with either no regard to masking human scent or attempting to restrict human scent for a total of 10 treatments, and replicated treatments eight to nine times in two different phases. We investigated whether: (1) any attractants increased the probability of capturing a mesocarnivore at a camera trap; (2) not masking human scent affected the probability of capturing a mesocarnivore at a camera trap; and (3) any attractants increased the probability of repeat detections at a given camera trap. We also analysed the behaviour (i.e. speed and distance to attractant) of each mesocarnivore in relation to the attractants. Key resultsSardines improved capture success compared with the control treatments, whereas SFE, castor oil, and FAS tablets had no effect when all mesocarnivores were included in the analyses. Masking human scent did not affect detection rates in the multispecies analyses. Individually, the detection of some species depended on the interactions between masking (or not masking) human scent and some attractants. ConclusionsSardines were the most effective as a broad-based attractant for mesocarnivores. Mesocarnivores approached traps baited with sardines at slower rates, which allows for a higher success of capturing an image of the animal. ImplicationsHuman scent may not need to be masked when deploying camera traps for multispecies mesocarnivore studies, but researchers should be aware that individual species respond differently to attractants and may have higher capture success with species-specific attractants.

Ecological Interactions and Macroevolution: A New Field with Old Roots

2020 ◽  
Vol 51 (1) ◽  
pp. 215-243 ◽  
Author(s):  
David H. Hembry ◽  
Marjorie G. Weber
Keyword(s):  
Species Interactions ◽  
Interspecific Interactions ◽  
Biotic Interactions ◽  
Evolutionary Change ◽  
Future Research ◽  
Ecological Interactions ◽  
Open Questions ◽  
Work Done ◽  
Lineage Diversification

Linking interspecific interactions (e.g., mutualism, competition, predation, parasitism) to macroevolution (evolutionary change on deep timescales) is a key goal in biology. The role of species interactions in shaping macroevolutionary trajectories has been studied for centuries and remains a cutting-edge topic of current research. However, despite its deep historical roots, classic and current approaches to this topic are highly diverse. Here, we combine historical and contemporary perspectives on the study of ecological interactions in macroevolution, synthesizing ideas across eras to build a zoomed-out picture of the big questions at the nexus of ecology and macroevolution. We discuss the trajectory of this important and challenging field, dividing research into work done before the 1970s, research between 1970 and 2005, and work done since 2005. We argue that in response to long-standing questions in paleobiology, evidence accumulated to date has demonstrated that biotic interactions (including mutualism) can influence lineage diversification and trait evolution over macroevolutionary timescales, and we outline major open questions for future research in the field.

scholarly journals Multiple methods increase detection of large and medium-sized mammals: working with volunteers in south-eastern Oman

Oryx ◽  
2016 ◽  
Vol 51 (2) ◽  
pp. 290-297 ◽  
Author(s):  
Marcelo Mazzolli ◽  
Taiana Haag ◽  
Beatriz G. Lippert ◽  
Eduardo Eizirik ◽  
Matthias L.A. Hammer ◽  
...  
Keyword(s):  
Camera Traps ◽  
Individual Species ◽  
Grid Cells ◽  
Multiple Methods ◽  
Mammal Species ◽  
Wild Mammals ◽  
Molecular Scatology ◽  
Sign Surveys ◽  
Procavia Capensis ◽  
Hyaena Hyaena

AbstractWe compared the effectiveness of various methods for surveying medium and large wild mammals in southern Oman. Working with volunteers recruited by Biosphere Expeditions, wildlife professionals and local rangers, we used direct observation, camera traps, sign surveys (tracks and/or dung) and molecular scatology to study 66 sampling units of 2 × 2 km (grid cells) in an area of 32 × 36 km during a 4-week period in February–March 2011. Sixteen mammal species were recorded, and the largest numbers of species were recorded by sign surveys and camera traps (both n = 9); sign surveys, direct sightings and DNA scatology recorded species across the largest number of grid cells. For species with a sample size large enough for comparison (i.e. detected in ≥ 8 grid cells), DNA scatology proved most effective for detecting caracal Caracal caracal, signs for hyaena Hyaena hyaena, ibex Capra nubiana, porcupine Hystrix indica and hyrax Procavia capensis, and signs and direct sightings for mountain gazelle Gazella gazella. Clustering, in which records from multiple methods are either adjacent or overlapping, was highest (≥ 76%) for the wolf Canis lupus, porcupine, ibex and gazelle. Our results indicate the best methods to detect and record the distributions of individual species in the study area, and demonstrate the advantage of using multiple methods to reduce the risk of false absences or partial detections. Our findings also highlight the potential of clustering as a means of cross-checking results of observations that are skill-dependent, which is particularly useful when employing a large workforce.

Sign in / Sign up

Export Citation Format

Share Document