The Scale-Dependent Role of Biological Traits in Landscape Ecology: A Review

2018 ◽  
Vol 3 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Andrés Felipe Suárez-Castro ◽  
Jeremy S. Simmonds ◽  
Matthew G. E. Mitchell ◽  
Martine Maron ◽  
Jonathan R. Rhodes
Keyword(s):  
Landscape Ecology ◽  
Biological Traits

Unified Framework II Ecosystem Processes: A Link Between Species and Landscape Diversity

2005 ◽  
Author(s):  
Robert Waide ◽  
Peter M. Groffman
Keyword(s):  
Landscape Ecology ◽  
Nutrient Cycling ◽  
Community Ecology ◽  
Energy Flow ◽  
Ecosystem Processes ◽  
Landscape Diversity ◽  
Ecosystem Ecology ◽  
Unified Framework ◽  
Ecosystem Diversity

The discipline of ecology can be subdivided into several subdisciplines, including community, ecosystem, and landscape ecology. While all the subdisciplines are important to the study of biodiversity, there is great variation in the extent to which their contributions have been analyzed. For example, the role of community ecology in biodiversity studies is well established. In community ecology, the entities of study are species that differ in their properties and generate a web of interactions that, in turn, organize the species into a community. Similar to community ecology, the contribution of landscape ecology to biodiversity is apparent. The entities of study, definable “patches,” are tangible. They differ in their properties and generate a web of interactions that organize the patches into a landscape mosaic. In contrast to community and landscape ecology, the role of ecosystem ecology in biodiversity is less apparent. In ecosystem ecology, it often is not clear what the entities are, and how they are organized. To the extent that ecosystem ecology focuses on energy flow and nutrient cycling, we can define fundamental entities as compartments and vectors in models that depict the flows of water, energy, and nutrients through communities. If we apply diversity criteria to these entities, we can use the term ecosystem diversity to refer to the number of compartments and vectors, the differences among them in type and size, and their organization in promoting energy flow or nutrient cycling. To our knowledge, ecosystem scientists have not yet developed criteria for ecosystem diversity similar to those used for species and landscape diversity. There has been some use of the term “ecosystem diversity” to refer to a diversity of ecosystems, implying a variety of habitats, landscapes, or biomes. As discussed above, we suggest that to define the role of ecosystem ecology in biodiversity studies, the approach should be to study the relationships among species, landscape, and ecosystem diversities (chapters 1 and 13). However, since the concept of ecosystem diversity awaits further development, we adopt a different approach for understanding the role of ecosystem science in biodiversity studies. In this chapter, we examine relationships among ecosystem processes, species diversity, and landscape diversity.

scholarly journals How to consider history in landscape ecology: patterns, processes, and pathways

2020 ◽  
Author(s):  
Ulrike Tappeiner ◽  
Georg Leitinger ◽  
Anita Zariņa ◽  
Matthias Bürgi
Keyword(s):  
Landscape Ecology ◽  
Landscape Change ◽  
Path Dependence ◽  
Complete Analysis ◽  
The Past ◽  
Natural Landscapes ◽  
Patterns And Processes ◽  
Event Chains ◽  
Over Time

Abstract Context Landscape ecology early on developed the awareness that central objects of investigation are not stable over time and therefore the historical dimension must be included, or at least considered. Objectives This paper considers the importance of history in landscape ecology in terms of its impact on patterns and processes and proposes to complement these with the notion of pathways in order to provide a comprehensive analysis of landscape change. Methods We develop a conceptual framework distinguishing between legacy effects, which include pattern and processes, and path dependence, with a focus of development pathways and we illustrate these perspectives by empirical examples. Results Combined short- to long-lasting imprints and legacies of historical patterns and processes reveal how present patterns and processes are in various ways influenced by legacies of the past. The focus on inherent dynamics of development pathways sheds light on the process of change itself, and its trajectories, and reveals the role of event chains and institutional reproduction. Conclusions Understanding patterns, processes, and pathways over time, allows a more complete analysis of landscape change, and forms the base to preserve vital ecosystem services of both human-made and natural landscapes for the future.

scholarly journals Environmental Factors Are Stronger Predictors of Primate Species’ Distributions Than Basic Biological Traits

2021 ◽  
Author(s):  
Katherine A. Williams ◽  
Helen D. Slater ◽  
Phillipa Gillingham ◽  
Amanda H. Korstjens
Keyword(s):  
Environmental Conditions ◽  
Environmental Variables ◽  
Large Scale ◽  
Species Distributions ◽  
Sub Saharan Africa ◽  
Primate Species ◽  
Biological Traits ◽  
Data Set ◽  
Environmental Processes

AbstractUnderstanding the neutral, biological, and environmental processes driving species distributions is valuable in informing conservation efforts because it will help us predict how species will respond to changes in environmental conditions. Environmental processes affect species differently according to their biological traits, which determine how they interact with their environment. Therefore, functional, trait-based modeling approaches are considered important for predicting distributions and species responses to change but even for data-rich primate communities our understanding of the relationships between traits and environmental conditions is limited. Here we use a large-scale, high-resolution data set of African diurnal primate distributions, biological traits, and environmental conditions to investigate the role of biological traits and environmental trait filtering in primate distributions. We collected data from published sources for 354 sites and 14 genera with 57 species across sub-Saharan Africa. We then combined a three-table ordination method, RLQ, with the fourth-corner approach to test relationships between environmental variables and biological traits and used a mapping approach to visually assess patterning in primate genus and species’ distributions. We found no significant relationships between any groups of environmental variables and biological traits, despite a clear role of environmental filtering in driving genus and species’ distributions. The most important environmental driver of species distributions was temperature seasonality, followed by rainfall. We conclude that the relative flexibility of many primate genera means that not any one particular set of traits drives their species–environment associations, despite the clear role of such associations in their distribution patterns.

scholarly journals Early biomarkers of psychosis

2005 ◽  
Vol 7 (1) ◽  
pp. 17-29
Keyword(s):  
Nicotinic Receptor ◽  
Predictive Power ◽  
Genetic Research ◽  
Chromosome 15 ◽  
Biological Traits ◽  
Prevention Strategies ◽  
Genetic Transmission ◽  
Early Biomarkers ◽  
Its Gene

Biological traits that are predictive of the later development of psychosis have not yet been identified. The complex, multidetermined nature of schizophrenia and other psychoses makes it unlikely that any single biomarker will be both sensitive and specific enough to unambiguously identify individuals who will later become psychotic. However, current genetic research has begun to identify genes associated with schizophrenia, some of which have phenotypes that appear early in life. While these phenotypes have low predictive power for identifying individuals who will become psychotic, they do serve as biomarkers for pathophysiological processes that can become the targets of prevention strategies. Examples are given from work on the role of the alpha(T)nicotinic receptor and its gene CHRNA7 on chromosome 15 in the neurobiology and genetic transmission of schizophrenia.

scholarly journals Biological and environmental drivers of deep-sea benthic ecosystem functioning in Canada’s Laurentian Channel Area of Interest (AOI)

2018 ◽  
Author(s):  
Marta Miatta ◽  
Paul V Snelgrove
Keyword(s):  
Deep Sea ◽  
Ecosystem Functioning ◽  
Environmental Variables ◽  
Environmental Changes ◽  
Marine Ecosystem ◽  
Environmental Drivers ◽  
Biological Traits ◽  
Area Of Interest ◽  
Prokaryotic Abundance

Ongoing environmental changes and accelerating biodiversity loss raise concern and interest about the role of environmental factors and biodiversity in determining marine ecosystem functioning. This study aims to identify the main drivers of benthic ecosystem functioning in deep-sea sedimentary habitats in the Laurentian Channel Area of Interest (AOI), and in particular the role of sea pens (Pennatulacea) as potential keystone species in the area. Using the ROV ROPOS we collected sediment cores and measured environmental variables from 6 stations inside the AOI (depths 348–445m) in September 2017. Through 48-hours incubations and flux measurements (oxygen, inorganic nutrients), we estimated organic matter remineralization, a key benthic function. Preliminary analyses show no significant variation in fluxes among stations, despite significant differences in environmental variables However, the presence/absence of Pennatulacea inside the cores indicated some capability to enhance remineralization and particularly nitrification. Ongoing analyses will address sediment properties, macrofaunal biodiversity, prokaryotic abundance, and biological traits as drivers of remineralization. Shedding new light on the primary drivers of ecosystem functioning in the area will inform the design or monitoring strategies proposed for this AOI and offer new perspectives and tools for MPA design.

scholarly journals Semalytics: a semantic analytics platform for the exploration of distributed and heterogeneous cancer data in translational research

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Andrea Mignone ◽  
Alberto Grand ◽  
Alessandro Fiori ◽  
Enzo Medico ◽  
Andrea Bertotti
Keyword(s):  
Large Scale ◽  
Clinical Care ◽  
Predictive Biomarkers ◽  
Molecular Profile ◽  
Biological Traits ◽  
Semantic Web Technologies ◽  
Cancer Data ◽  
Molecular Features ◽  
Data Framework

Abstract Each cancer is a complex system with unique molecular features determining its dynamics, such as its prognosis and response to therapies. Understanding the role of these biological traits is fundamental in order to personalize cancer clinical care according to the characteristics of each patient’s disease. To achieve this, translational researchers propagate patients’ samples through in vivo and in vitro cultures to test different therapies on the same tumor and to compare their outcomes with the molecular profile of the disease. This in turn generates information that can be subsequently translated into the development of predictive biomarkers for clinical use. These large-scale experiments generate huge collections of hierarchical data (i.e. experimental trees) with relative annotations that are extremely difficult to analyze. To address such issues in data analyses, we came up with the Semalytics data framework, the core of an analytical platform that processes experimental information through Semantic Web technologies. Semalytics allows (i) the efficient exploration of experimental trees with irregular structures together with their annotations. Moreover, (ii) the platform links its data to a wider open knowledge base (i.e. Wikidata) to add an extended knowledge layer without the need to manage and curate those data locally. Altogether, Semalytics provides augmented perspectives on experimental data, allowing the generation of new hypotheses, which were not anticipated by the user a priori. In this work, we present the data core we created for Semalytics, focusing on its semantic nucleus and on how it exploits semantic reasoning and data integration to tackle issues of this kind of analyses. Finally, we describe a proof-of-concept study based on the examination of several dozen cases of metastatic colorectal cancer in order to illustrate how Semalytics can help researchers generate hypotheses about the role of genes alterations in causing resistance or sensitivity of cancer cells to specific drugs.

The distribution of South American galaxiid fishes: the role of biological traits and post-glacial history

2003 ◽  
Vol 31 (1) ◽  
pp. 103-121 ◽  
Author(s):  
Víctor Cussac ◽  
Silvia Ortubay ◽  
Gustavo Iglesias ◽  
Daniela Milano ◽  
María E. Lattuca ◽  
...  
Keyword(s):  
Biological Traits ◽  
South American ◽  
Glacial History

scholarly journals Biological and environmental drivers of deep-sea benthic ecosystem functioning in Canada’s Laurentian Channel Area of Interest (AOI)

2018 ◽  
Author(s):  
Marta Miatta ◽  
Paul V Snelgrove
Keyword(s):  
Deep Sea ◽  
Ecosystem Functioning ◽  
Environmental Variables ◽  
Environmental Changes ◽  
Marine Ecosystem ◽  
Environmental Drivers ◽  
Biological Traits ◽  
Area Of Interest ◽  
Prokaryotic Abundance

Ongoing environmental changes and accelerating biodiversity loss raise concern and interest about the role of environmental factors and biodiversity in determining marine ecosystem functioning. This study aims to identify the main drivers of benthic ecosystem functioning in deep-sea sedimentary habitats in the Laurentian Channel Area of Interest (AOI), and in particular the role of sea pens (Pennatulacea) as potential keystone species in the area. Using the ROV ROPOS we collected sediment cores and measured environmental variables from 6 stations inside the AOI (depths 348–445m) in September 2017. Through 48-hours incubations and flux measurements (oxygen, inorganic nutrients), we estimated organic matter remineralization, a key benthic function. Preliminary analyses show no significant variation in fluxes among stations, despite significant differences in environmental variables However, the presence/absence of Pennatulacea inside the cores indicated some capability to enhance remineralization and particularly nitrification. Ongoing analyses will address sediment properties, macrofaunal biodiversity, prokaryotic abundance, and biological traits as drivers of remineralization. Shedding new light on the primary drivers of ecosystem functioning in the area will inform the design or monitoring strategies proposed for this AOI and offer new perspectives and tools for MPA design.

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