Trade-offs in community ecology: linking spatial scales and species coexistence

2004 ◽  
Vol 7 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Jamie M. Kneitel ◽  
Jonathan M. Chase
2021 ◽  
Vol 13 (5) ◽  
pp. 2468
Author(s):  
Nguyen Hong Hai ◽  
Yousef Erfanifard ◽  
Van Bac Bui ◽  
Trinh Hien Mai ◽  
Any Mary Petritan ◽  
...  

Studying spatial patterns and habitat association of plant communities may provide understanding of the ecological mechanisms and processes that maintain species coexistence. To conduct assessments of correlation between community compositions and habitat association, we used data from two topographically different plots with 2 ha area in tropical evergreen forests with the variables recorded via grid systems of 10 × 10 m subplots in Northern-Central Vietnam. First, we tested the relationship between community composition and species diversity indices considering the topographical variables. We then assessed the interspecific interactions of 20 dominant plant species using the nearest-neighbor distribution function, Dij(r), and Ripley’s K-function, Kij(r). Based on the significant spatial association of species pairs, indices of interspecific interaction were calculated by the quantitative amounts of the summary statistics. The results showed that (i) community compositions were significantly influenced by the topographic variables and (ii) almost 50% significant pairs of species interactions were increased with increasing spatial scales up to 10–15 m, then declined and disappeared at scales of 30–40 m. Segregation and partial overlap were the dominant association types and disappeared at larger spatial scales. Spatial segregation, mixing, and partial overlap revealed the important species interactions in maintaining species coexistence under habitat heterogeneity in diverse forest communities.


2016 ◽  
Vol 122 ◽  
pp. 111-120 ◽  
Author(s):  
Stephan Klasen ◽  
Katrin M. Meyer ◽  
Claudia Dislich ◽  
Michael Euler ◽  
Heiko Faust ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Charlotte Marcinko ◽  
Robert Nicholls ◽  
Tim Daw ◽  
Sugata Hazra ◽  
Craig Hutton ◽  
...  

<p>The United Nations Sustainable Development Goals (SDGs) and their corresponding targets are significantly interconnected, with many interactions, synergies and trade-offs between individual goals across multiple temporal and spatial scales.  We propose a framework for the Integrated Assessment Modelling (IAM) of a complex deltaic socio-ecological system in order to analyse such SDG interactions. We focus on the Sundarbans Biosphere Reserve (SBR), India within the Ganges-Brahmaputra-Meghna Delta. It is densely populated with 4.4 million people (2011), high levels of poverty and a strong dependence on rural livelihoods. It is only 50 km from the growing megacity of Kolkata (about 15 million people in 2020). The area also includes the Indian portion of the world’s largest mangrove forest – the Sundarbans – hosting the iconic Bengal Tiger. Like all deltaic systems, this area is subject to multiple drivers of environmental change operating across different scales. The IAM framework is designed to investigate current and future trends in socio-environmental change and explore associated policy impacts, considering a broad range of sub-thematic SDG indicators. Integration is achieved through the soft coupling of multiple sub-models, knowledge and data of relevant environmental and socio-economic processes.  The following elements are explicitly considered: (1) agriculture; (2) aquaculture; (3) mangroves; (4) fisheries; and (5) multidimensional poverty. Key questions that can be addressed include the implications of changing monsoon patterns, trade-offs between agriculture and aquaculture, or the future of the Sundarbans mangroves under sea-level rise and different management strategies, including trade-offs with land use to the north.  The novel high-resolution analysis of SDG interactions allowed by the IAM will provide stakeholders and policy makers the opportunity to prioritize and explore the SDG targets that are most relevant to the SBR and provide a foundation for further integrated analysis.</p>


2018 ◽  
Vol 115 (47) ◽  
pp. 12069-12074 ◽  
Author(s):  
Samuel G. Roy ◽  
Emi Uchida ◽  
Simone P. de Souza ◽  
Ben Blachly ◽  
Emma Fox ◽  
...  

Aging infrastructure and growing interests in river restoration have led to a substantial rise in dam removals in the United States. However, the decision to remove a dam involves many complex trade-offs. The benefits of dam removal for hazard reduction and ecological restoration are potentially offset by the loss of hydroelectricity production, water supply, and other important services. We use a multiobjective approach to examine a wide array of trade-offs and synergies involved with strategic dam removal at three spatial scales in New England. We find that increasing the scale of decision-making improves the efficiency of trade-offs among ecosystem services, river safety, and economic costs resulting from dam removal, but this may lead to heterogeneous and less equitable local-scale outcomes. Our model may help facilitate multilateral funding, policy, and stakeholder agreements by analyzing the trade-offs of coordinated dam decisions, including net benefit alternatives to dam removal, at scales that satisfy these agreements.


2021 ◽  
Vol 9 ◽  
Author(s):  
Eliezer Gurarie ◽  
Sriya Potluri ◽  
George Christopher Cosner ◽  
Robert Stephen Cantrell ◽  
William F. Fagan

Seasonal migrations are a widespread and broadly successful strategy for animals to exploit periodic and localized resources over large spatial scales. It remains an open and largely case-specific question whether long-distance migrations are resilient to environmental disruptions. High levels of mobility suggest an ability to shift ranges that can confer resilience. On the other hand, a conservative, hard-wired commitment to a risky behavior can be costly if conditions change. Mechanisms that contribute to migration include identification and responsiveness to resources, sociality, and cognitive processes such as spatial memory and learning. Our goal was to explore the extent to which these factors interact not only to maintain a migratory behavior but also to provide resilience against environmental changes. We develop a diffusion-advection model of animal movement in which an endogenous migratory behavior is modified by recent experiences via a memory process, and animals have a social swarming-like behavior over a range of spatial scales. We found that this relatively simple framework was able to adapt to a stable, seasonal resource dynamic under a broad range of parameter values. Furthermore, the model was able to acquire an adaptive migration behavior with time. However, the resilience of the process depended on all the parameters under consideration, with many complex trade-offs. For example, the spatial scale of sociality needed to be large enough to capture changes in the resource, but not so large that the acquired collective information was overly diluted. A long-term reference memory was important for hedging against a highly stochastic process, but a higher weighting of more recent memory was needed for adapting to directional changes in resource phenology. Our model provides a general and versatile framework for exploring the interaction of memory, movement, social and resource dynamics, even as environmental conditions globally are undergoing rapid change.


<em>Abstract</em>.—Stream fishes carry out their life histories across broad spatial and temporal scales, leading to spatially structured populations. Therefore, incorporating metapopulation dynamics into models of stream fish populations may improve our ability to understand mechanisms regulating them. First, we reviewed empirical research on metapopulation dynamics in the stream fish ecology literature and found 31 papers that used the metapopulation framework. The majority of papers applied no specific metapopulation model, or included space only implicitly. Although parameterization of spatially realistic models is challenging, we suggest that stream fish ecologists should incorporate space into models and recognize that metapopulation types may change across scales. Second, we considered metacommunity theory, which addresses how trade-offs among dispersal, environmental heterogeneity, and biotic interactions structure communities across spatial scales. There are no explicit tests of metacommunity theory using stream fishes to date, so we used data from our research in a Great Plains stream to test the utility of these paradigms. We found that this plains fish metacommunity was structured mainly by spatial factors related to dispersal opportunity and, to a lesser extent, by environmental heterogeneity. Currently, metacommunity models are more heuristic than predictive. Therefore, we propose that future stream fish metacommunity research should focus on developing testable hypotheses that incorporate stream fish life history attributes, and seasonal environmental variability, across spatial scales. This emerging body of research is likely to be valuable not only for basic stream fish ecological research, but also multispecies conservation and management.


Land ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 422
Author(s):  
Ramon Felipe Bicudo da Silva ◽  
Mateus Batistella ◽  
James D. A. Millington ◽  
Emilio Moran ◽  
Luiz A. Martinelli ◽  
...  

Agricultural systems are heterogeneous across temporal and spatial scales. Although much research has investigated farm size and economic output, the synergies and trade-offs across various agricultural and socioeconomic variables are unclear. This study applies a GIS-based approach to official Brazilian census data (Agricultural Censuses of 1995, 2006, and 2017) and surveys at the municipality level to (i) evaluate changes in the average soybean farm size across the country and (ii) compare agricultural and socioeconomic outcomes (i.e., soybean yield, agricultural production value, crop production diversity, and rural labor employment) relative to the average soybean farm size. Statistical tests (e.g., Kruskal–Wallis tests and Spearman’s correlation) were used to analyze variable outcomes in different classes of farm sizes and respective Agricultural Censuses. We found that agricultural and socioeconomic outcomes are spatially correlated with soybean farm size class. Therefore, based on the concepts of trade-offs and synergies, we show that municipalities with large soybean farm sizes had larger trade-offs (e.g., larger farm size was associated with lower crop diversity), while small and medium ones manifest greater synergies. These patterns are particularly strong for analysis using the Agricultural Census of 2017. Trade-off/synergy analysis across space and time is key for supporting long-term strategies aiming at alleviating unemployment and providing sustainable food production, essential to achieve the UN Sustainable Development Goals.


2018 ◽  
Vol 75 (6) ◽  
pp. 1849-1863 ◽  
Author(s):  
Thomas Kiørboe ◽  
André Visser ◽  
Ken H Andersen

Abstract Trait-based ecology merges evolutionary with classical population and community ecology and is a rapidly developing branch of ecology. It describes ecosystems as consisting of individuals rather than species, and characterizes individuals by few key traits that are interrelated through trade-offs. The fundamental rationale is that the spatio-temporal distribution of organisms and their functional role in ecosystems depend on their traits rather than on their taxonomical affiliation. The approach respects that interactions are between individuals, not between species or populations, and in trait-based models ecosystem structure emerges as a result of interactions between individuals and with the environments, rather than being prescribed. It offers an alternative to classical species-centric approaches and has the potential to describe complex ecosystems in simple ways and to assess the effects of environmental change on ecosystem structure and function. Here, we describe the components of the trait-based approach and apply it to describe and model marine ecosystems. Our description is illustrated with multiple examples of life in the ocean from unicellular plankton to fish.


2019 ◽  
Vol 4 (5) ◽  
pp. 846-853 ◽  
Author(s):  
Daniel S. Maynard ◽  
Mark A. Bradford ◽  
Kristofer R. Covey ◽  
Daniel Lindner ◽  
Jessie Glaeser ◽  
...  
Keyword(s):  

2017 ◽  
Vol 1 (8) ◽  
pp. 1066-1073 ◽  
Author(s):  
Simon P. Hart ◽  
Jacob Usinowicz ◽  
Jonathan M. Levine

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