scholarly journals Community structure and ecological specialization in plant–ant interactions

2015 ◽  
Vol 31 (4) ◽  
pp. 325-334 ◽  
Author(s):  
Paola A. Barriga ◽  
Carsten F. Dormann ◽  
Edward E. Gbur ◽  
Cynthia L Sagers
Keyword(s):  
Network Structure ◽  
Species Interactions ◽  
Null Model ◽  
Interaction Networks ◽  
Host Specialization ◽  
Random Networks ◽  
Ecological Specialization ◽  
Study Sites ◽  
Plant Extinction

Abstract:Environmental effects on species interactions can be studied by comparative analyses of network structure. For example, comparison of interaction networks among study sites can provide clues to geographic variation of host breadth. Obligate plant–ant interactions are ideal systems to explore these phenomena because they are long term and can be accurately sampled in the field. We tested two hypotheses: (1) network structure and host specialization do not vary among communities, and (2) the effects of plant extinction do not vary among communities. We sampled 10 or more plants for each of the 30 ant–plant species found in three Neotropical locations. We found that network specialization,H2′, was significantly higher than expected in random networks. The ant or plant specialization index,d′, distribution did not vary among localities, neither varied in link or asymmetry distribution. Plant extinction simulations showed that these interactions are vulnerable to plant loss, and the null model was more robust than the observed networks. This study provides a foundation on which plant and ant phylogenies can be added to explore compartment evolution.

scholarly journals When is a network complex? Connectance drives degree distribution and emerging network properties

2013 ◽  
Author(s):  
Timothée Poisot ◽  
Dominique Gravel
Keyword(s):  
Network Structure ◽  
Degree Distribution ◽  
Null Model ◽  
Ecological Networks ◽  
Random Networks ◽  
Ecosystem Properties ◽  
Network Properties ◽  
Statistical Argument ◽  
Simple Network ◽  
Network Complex

Connectance and degree distributions are important components of the structure of ecological networks. In this contribution, we use a statistical argument and simple network generating models to show that properties of the degree distribution are driven by network connectance. We discuss the consequences of this finding for (1) the generation of random networks in null-model analyses, and (2) the interpretation of network structure and ecosystem properties in relationship with degree distribution.

scholarly journals When is a network complex? Connectance drives degree distribution and emerging network properties

2013 ◽  
Author(s):  
Timothée Poisot ◽  
Dominique Gravel
Keyword(s):  
Network Structure ◽  
Degree Distribution ◽  
Null Model ◽  
Ecological Networks ◽  
Random Networks ◽  
Ecosystem Properties ◽  
Network Properties ◽  
Statistical Argument ◽  
Simple Network ◽  
Network Complex

Connectance and degree distributions are important components of the structure of ecological networks. In this contribution, we use a statistical argument and simple network generating models to show that properties of the degree distribution are driven by network connectance. We discuss the consequences of this finding for (1) the generation of random networks in null-model analyses, and (2) the interpretation of network structure and ecosystem properties in relationship with degree distribution.

scholarly journals When is an ecological network complex? Connectance drives degree distribution and emerging network properties

2013 ◽  
Author(s):  
Timothée Poisot ◽  
Dominique Gravel
Keyword(s):  
Network Structure ◽  
Degree Distribution ◽  
Null Model ◽  
Random Networks ◽  
Ecological Network ◽  
Ecosystem Properties ◽  
Network Properties ◽  
Statistical Argument ◽  
Simple Network ◽  
Network Complex

Connectance and degree distributions are important components of the structure of ecological networks. In this contribution, we use a statistical argument and simple network generating models to show that properties of the degree distribution are driven by network connectance. We discuss the consequences of this finding for (1) the generation of random networks in null-model analyses, and (2) the interpretation of network structure and ecosystem properties in relationship with degree distribution.

scholarly journals When is a network complex? Connectance drives degree distribution and emerging network properties

2013 ◽  
Author(s):  
Timothée Poisot ◽  
Dominique Gravel
Keyword(s):  
Network Structure ◽  
Degree Distribution ◽  
Null Model ◽  
Ecological Networks ◽  
Random Networks ◽  
Ecosystem Properties ◽  
Network Properties ◽  
Statistical Argument ◽  
Simple Network ◽  
Network Complex

Connectance and degree distributions are important components of the structure of ecological networks. In this contribution, we use a statistical argument and simple network generating models to show that properties of the degree distribution are driven by network connectance. We discuss the consequences of this finding for (1) the generation of random networks in null-model analyses, and (2) the interpretation of network structure and ecosystem properties in relationship with degree distribution.

scholarly journals When is an ecological network complex? Connectance drives degree distribution and emerging network properties

2013 ◽  
Author(s):  
Timothée Poisot ◽  
Dominique Gravel
Keyword(s):  
Network Structure ◽  
Degree Distribution ◽  
Null Model ◽  
Random Networks ◽  
Ecological Network ◽  
Ecosystem Properties ◽  
Network Properties ◽  
Statistical Argument ◽  
Simple Network ◽  
Network Complex

Connectance and degree distributions are important components of the structure of ecological networks. In this contribution, we use a statistical argument and simple network generating models to show that properties of the degree distribution are driven by network connectance. We discuss the consequences of this finding for (1) the generation of random networks in null-model analyses, and (2) the interpretation of network structure and ecosystem properties in relationship with degree distribution.

Nest cameras do not affect nest survival in a meadow-nesting shorebird

2020 ◽  
pp. 1-10
Author(s):  
VOLKER SALEWSKI ◽  
LUIS SCHMIDT
Keyword(s):  
Nest Survival ◽  
Bird Species ◽  
Conservation Strategies ◽  
Survival Models ◽  
Northern Germany ◽  
Term Study ◽  
Long Term Study ◽  
Limosa Limosa ◽  
Study Sites

Summary Identifying the fate of birds’ nests and the causes of breeding failure is often crucial for the development of conservation strategies for threatened species. However, collecting these data by repeatedly visiting nests might itself contribute to nest failure or bias. To solve this dilemma, automatic cameras have increasingly been used as a time-efficient means for nest monitoring. Here, we consider whether the use of cameras itself may influence hatching success of nests of the Black-tailed Godwit Limosa limosa at two long-term study sites in northern Germany. Annually between 2013 and 2019, cameras were used to monitor godwit nests. In 2014 and 2019, nests were randomly equipped with cameras or not, and nest survival checked independently of the cameras. Nest-survival models indicated that survival probabilities varied between years, sites and with time of the season, but were unaffected by the presence of cameras. Even though predation is the main cause of hatching failure in our study system, we conclude that predators did not learn to associate cameras with food either when the cameras were initially installed or after they had been used for several years. Cameras were thus an effective and non-deleterious tool to collect data for conservation in this case. As other bird species may react differently to cameras at their nests, and as other sets of predators may differ in their ability to associate cameras with food, the effect of cameras on breeding success should be carefully monitored when they are used in a new study system.

scholarly journals Territorial governance of managed retreat in Sweden: addressing challenges

2021 ◽  
Author(s):  
Gunnel Göransson ◽  
Lisa Van Well ◽  
David Bendz ◽  
Per Danielsson ◽  
Jim Hedfors
Keyword(s):  
Climate Adaptation ◽  
Governance Framework ◽  
Case Study Site ◽  
Feasible Option ◽  
Flexible Planning ◽  
Barriers And Opportunities ◽  
Study Sites ◽  
Inland Flooding

AbstractMany climate adaptation options currently being discussed in Sweden to meet the challenge of surging seas and inland flooding advocate holding the line through various hard and soft measures to stabilize the shoreline, while managed retreat is neither considered as feasible option nor has it been explicitly researched in Sweden. However, failure to consider future flooding from climate change in municipal planning may have dangerous and costly consequences when the water does come. We suggest that managed retreat practices are challenging in Sweden, not only due to public opinions but also because of a deficit of uptake of territorial knowledge by decision-makers and difficulties in realizing flexible planning options of the shoreline. A territorial governance framework was used as a heuristic to explore the challenges to managed retreat in four urban case studies (three municipalities and one county) representing different territorial, hydrological and oceanographic environments. This was done through a series of participatory stakeholder workshops. The analysis using a territorial governance framework based on dimensions of coordination, integration, mobilization, adaptation and realization presents variations in how managed retreat barriers and opportunities are perceived among case study sites, mainly due to the differing territorial or place-based challenges. The results also indicate common challenges regardless of the case study site, including coordination challenges and unclear responsibility, the need for integrated means of addressing goal conflicts and being able to adapt flexibly to existing regulations and plans. Yet rethinking how managed retreat could boost community resilience and help to implement long-term visions was seen as a way to deal with some of the territorial challenges.

scholarly journals A method for simulating risk profiles of wheat yield in data-sparse conditions

2021 ◽  
pp. 1-12
Author(s):  
G. Bracho-Mujica ◽  
P.T. Hayman ◽  
V.O. Sadras ◽  
B. Ostendorf
Keyword(s):  
Reference Site ◽  
Climate Impacts ◽  
Weather Data ◽  
Climate Data ◽  
High Quality ◽  
Risk Profiles ◽  
Record Length ◽  
Daily Weather Data ◽  
Study Sites

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.

scholarly journals Worldwide variations in artificial skyglow

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Christopher C. M. Kyba ◽  
Kai Pong Tong ◽  
Jonathan Bennie ◽  
Ignacio Birriel ◽  
Jennifer J. Birriel ◽  
...  
Keyword(s):  
Monitoring Program ◽  
Artificial Light ◽  
Clear Sky ◽  
International Monitoring ◽  
Sky Brightness ◽  
Ground Truthing ◽  
Study Sites ◽  
Night Sky Brightness ◽  
Key Questions

Abstract Despite constituting a widespread and significant environmental change, understanding of artificial nighttime skyglow is extremely limited. Until now, published monitoring studies have been local or regional in scope and typically of short duration. In this first major international compilation of monitoring data we answer several key questions about skyglow properties. Skyglow is observed to vary over four orders of magnitude, a range hundreds of times larger than was the case before artificial light. Nearly all of the study sites were polluted by artificial light. A non-linear relationship is observed between the sky brightness on clear and overcast nights, with a change in behavior near the rural to urban landuse transition. Overcast skies ranged from a third darker to almost 18 times brighter than clear. Clear sky radiances estimated by the World Atlas of Artificial Night Sky Brightness were found to be overestimated by ~25%; our dataset will play an important role in the calibration and ground truthing of future skyglow models. Most of the brightly lit sites darkened as the night progressed, typically by ~5% per hour. The great variation in skyglow radiance observed from site-to-site and with changing meteorological conditions underlines the need for a long-term international monitoring program.

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