scholarly journals Flexibility in Migratory Behaviour of a Flight Generalist: Migrate Day and Night, Sprinting Across Ecological Barriers 

Author(s):  
Lina Lopez-Ricaurte ◽  
Wouter Vansteelant ◽  
Jesús Hernández-Pliego ◽  
Daniel García-Silveira ◽  
Ana Bermejo ◽  
...  

Abstract Understanding what factors drive variation in movement patterns is a key challenge in current migration research. Environmental drivers such as landscape heterogeneity and weather strongly affect birds’ migration influencing daily travel schedules and flight speed. For strictly thermal-soaring migrants, typically large birds, weather explains most seasonal and regional differences in speed. In contrast, smaller-sized flight generalists, which alternate between soaring and flapping flight, may be less dependent on weather and thus more likely to be strongly influenced by landscape in daily travel schedules and internal drivers, such as sex. We GPS-tracked the migration performance of 70 lesser kestrels (Falco naumanni), to estimate the relative importance of environmental (wind and landscape), internal (e.g. sex) and seasonal drivers and to what extend do they explain variation in migratory performance, namely speed, distance, and travelling time. We found that tailwind strength explained most of the seasonal difference in migratory parameters. In both seasons lesser kestrels sprinted across ecological barriers and frequently extended migration into the night, while travelling at a slower pace and mainly during the day when not flying over barriers. Our results highlighted that environmental factors far outweighed internal and other seasonal drivers in explaining variation in migration performance of a flight generalist, despite the ability to switch between flight-modes.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lina Lopez-Ricaurte ◽  
Wouter M. G. Vansteelant ◽  
Jesús Hernández-Pliego ◽  
Daniel García-Silveira ◽  
Ana Bermejo-Bermejo ◽  
...  

AbstractExternal factors such as geography and weather strongly affect bird migration influencing daily travel schedules and flight speeds. For strictly thermal-soaring migrants, weather explains most seasonal and regional differences in speed. Flight generalists, which alternate between soaring and flapping flight, are expected to be less dependent on weather, and daily travel schedules are likely to be strongly influenced by geography and internal factors such as sex. We GPS-tracked the migration of 70 lesser kestrels (Falco naumanni) to estimate the relative importance of external factors (wind, geography), internal factors (sex) and season, and the extent to which they explain variation in travel speed, distance, and duration. Our results show that geography and tailwind are important factors in explaining variation in daily travel schedules and speeds. We found that wind explained most of the seasonal differences in travel speed. In both seasons, lesser kestrels sprinted across ecological barriers and frequently migrated during the day and night. Conversely, they travelled at a slower pace and mainly during the day over non-barriers. Our results highlighted that external factors far outweighed internal factors and season in explaining variation in migratory behaviour of a flight generalist, despite its ability to switch between flight modes.


2009 ◽  
Vol 67 (4) ◽  
pp. 787-795 ◽  
Author(s):  
Jason S. Link ◽  
Dawit Yemane ◽  
Lynne J. Shannon ◽  
Marta Coll ◽  
Yunne-Jai Shin ◽  
...  

Abstract Link, J. S., Yemane, D., Shannon, L. J., Coll, M., Shin, Y-J., Hill, L., and Borges, M. F. 2010. Relating marine ecosystem indicators to fishing and environmental drivers: an elucidation of contrasting responses. – ICES Journal of Marine Science, 67: 787–795. The usefulness of indicators in detecting ecosystem change depends on three main criteria: the availability of data to estimate the indicator (measurability), the ability to detect change in an ecosystem (sensitivity), and the ability to link the said change in an indicator as a response to a known intervention or pressure (specificity). Here, we specifically examine the third aspect of indicator change, with an emphasis on multiple methods to explore the “relativity” of major ecosystem drivers. We use a suite of multivariate methods to explore the relationships between a pre-established set of fisheries-orientated ecosystem status indicators and the key drivers for those ecosystems (particularly emphasizing proxy indicators for fishing and the environment). The results show the relative importance among fishing and environmental factors, which differed notably across the major types of ecosystems. Yet, they also demonstrated common patterns in which most ecosystems, and indicators of ecosystem dynamics are largely driven by fisheries (landings) or human (human development index) factors, and secondarily by environmental drivers (e.g. AMO, PDO, SST). How one might utilize this empirical evidence in future efforts for ecosystem approaches to fisheries is discussed, highlighting the need to manage fisheries in the context of environmental and other human (e.g. economic) drivers.


PLoS ONE ◽  
2013 ◽  
Vol 8 (8) ◽  
pp. e72348 ◽  
Author(s):  
Miguel A. Campo-Bescós ◽  
Rafael Muñoz-Carpena ◽  
David A. Kaplan ◽  
Jane Southworth ◽  
Likai Zhu ◽  
...  

2004 ◽  
Vol 94 (4) ◽  
pp. 297-306 ◽  
Author(s):  
S. Arthurs ◽  
K.M. Heinz ◽  
J.R. Prasifka

AbstractApplications of entomopathogenic nematodes in the families Steinernematidae and Heterorhabditidae have traditionally been targeted against soil insects. Nonetheless, research over the last two decades highlights the potential of such agents against above-ground pests under certain circumstances. A general linear model was used to test for patterns in efficacy among 136 published trials with Steinernema carpocapsae Weiser, the most common species applied against foliar and other above-ground pests. The focus was on field and greenhouse assessments, rather than laboratory assays where relevant ecological barriers to infection are typically removed. The model showed differences in nematode treatment efficacy depending on the pests’ target habitat (bore holes > cryptic foliage > exposed foliage) and trial location (greenhouse > field studies). Relative humidity and temperature during and up to 8 h post-application were also predicted to influence rates of nematode infection obtained. Conversely, spray adjuvants (both wetting agents and anti-desiccants) and nematode dosage applied (both concentration and use of consecutive applications 3–4 days apart) did not explain a significant amount of variance in nematode performance. With reference to case studies the model is used to discuss the relative importance of different factors on nematode efficacy and highlight priorities for workers considering using entomopathogenic nematodes to target pests in novel environments.


2020 ◽  
Vol 639 ◽  
pp. 73-89
Author(s):  
S Casabianca ◽  
S Capellacci ◽  
F Ricci ◽  
F Andreoni ◽  
T Russo ◽  
...  

Phytoplankton species can produce resting stages that persist in the sediment over long periods and accomplish important ecological functions. With the aim of investigating the phytoplankton assemblage structure in relation to environmental drivers and human pressures, we analyzed resting stages of diatoms and dinoflagellates, including harmful algal bloom taxa, in the surface sediments of 3 Mediterranean regional areas. Abundance of resting stages was determined by molecular quantitative polymerase chain reaction assay. Multivariate data analysis confirmed that the abundance of resting-stage assemblages seemed related to depth. Regional differences in the composition of the resting-stage assemblages were evident and environmental drivers were correlated with those regional differences. Three main groups of samples were defined according to SST and depth thresholds. Samples from the northern and central Adriatic Sea (average SST < 18°C) formed the richest assemblages, both in terms of abundance and species richness, while deep samples from all other basins (depth > 368 m) were poorer and less diverse than those from shallower sites (depth ≤ 368 m). Resting-stage taxa contributed differently to the 3 groups. Diatom spores and dinoflagellate cysts were the most abundant taxa, but Alexandrium minutum cysts and Ditylum brightwellii spores also accounted for a large share of the overall inter-group compositional distance. The structure of resting-stage assemblages can be regarded as a time- and space-integrated response of a subset of phytoplankton species to environmental conditions, including the physical oceanographic dynamics that favor or prevent sedimentation of resting stages.


Oecologia ◽  
2021 ◽  
Author(s):  
Juan Ernesto Guevara Andino ◽  
Nigel C. A. Pitman ◽  
Hans ter Steege ◽  
Manuel Peralvo ◽  
Carlos Cerón ◽  
...  

AbstractEnvironmental and dispersal filters are key determinants of species distributions of Amazonian tree communities. However, a comprehensive analysis of the role of environmental and dispersal filters is needed to understand the ecological and evolutionary processes that drive phylogenetic and taxonomic turnover of Amazonian tree communities. We compare measures of taxonomic and phylogenetic beta diversity in 41 one-hectare plots to test the relative importance of climate, soils, geology, geomorphology, pure spatial variables and the spatial variation of environmental drivers of phylogenetic and taxonomic turnover in Ecuadorian Amazon tree communities. We found low phylogenetic and high taxonomic turnover with respect to environmental and dispersal filters. In addition, our results suggest that climate is a significantly better predictor of phylogenetic turnover and taxonomic turnover than geomorphology and soils at all spatial scales. The influence of climate as a predictor of phylogenetic turnover was stronger at broader spatial scales (50 km2) whereas geomorphology and soils appear to be better predictors of taxonomic turnover at mid (5 km2) and fine spatial scales (0.5 km2) but a weak predictor of phylogenetic turnover at broad spatial scales. We also found that the combined effect of geomorphology and soils was significantly higher for taxonomic turnover at all spatial scales but not for phylogenetic turnover at large spatial scales. Geographic distances as proxy of dispersal limitation was a better predictor of phylogenetic turnover at distances of 50 < 500 km. Our findings suggest that climatic variation at regional scales can better predict phylogenetic and taxonomic turnover than geomorphology and soils.


PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2551 ◽  
Author(s):  
Laura M. Cisneros ◽  
Matthew E. Fagan ◽  
Michael R. Willig

BackgroundAssembly of species into communities following human disturbance (e.g., deforestation, fragmentation) may be governed by spatial (e.g., dispersal) or environmental (e.g., niche partitioning) mechanisms. Variation partitioning has been used to broadly disentangle spatial and environmental mechanisms, and approaches utilizing functional and phylogenetic characteristics of communities have been implemented to determine the relative importance of particular environmental (or niche-based) mechanisms. Nonetheless, few studies have integrated these quantitative approaches to comprehensively assess the relative importance of particular structuring processes.MethodsWe employed a novel variation partitioning approach to evaluate the relative importance of particular spatial and environmental drivers of taxonomic, functional, and phylogenetic aspects of bat communities in a human-modified landscape in Costa Rica. Specifically, we estimated the amount of variation in species composition (taxonomic structure) and in two aspects of functional and phylogenetic structure (i.e., composition and dispersion) along a forest loss and fragmentation gradient that are uniquely explained by landscape characteristics (i.e., environment) or space to assess the importance of competing mechanisms.ResultsThe unique effects of space on taxonomic, functional and phylogenetic structure were consistently small. In contrast, landscape characteristics (i.e., environment) played an appreciable role in structuring bat communities. Spatially-structured landscape characteristics explained 84% of the variation in functional or phylogenetic dispersion, and the unique effects of landscape characteristics significantly explained 14% of the variation in species composition. Furthermore, variation in bat community structure was primarily due to differences in dispersion of species within functional or phylogenetic space along the gradient, rather than due to differences in functional or phylogenetic composition.DiscussionVariation among bat communities was related to environmental mechanisms, especially niche-based (i.e., environmental) processes, rather than spatial mechanisms. High variation in functional or phylogenetic dispersion, as opposed to functional or phylogenetic composition, suggests that loss or gain of niche space is driving the progressive loss or gain of species with particular traits from communities along the human-modified gradient. Thus, environmental characteristics associated with landscape structure influence functional or phylogenetic aspects of bat communities by effectively altering the ways in which species partition niche space.


2012 ◽  
Vol 459 ◽  
pp. 169-184 ◽  
Author(s):  
C Fu ◽  
S Gaichas ◽  
JS Link ◽  
A Bundy ◽  
JL Boldt ◽  
...  

2021 ◽  
Vol 17 (4) ◽  
pp. e1008856
Author(s):  
Benjamin Deneu ◽  
Maximilien Servajean ◽  
Pierre Bonnet ◽  
Christophe Botella ◽  
François Munoz ◽  
...  

Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models (SDM) and in line with predictions of landscape ecology and island biogeography, CNN could grasp how local landscape structure affects prediction of species occurrence in SDMs. The prediction can thus reflect the signatures of entangled ecological processes. Although previous machine-learning based SDMs can learn complex influences of environmental predictors, they cannot acknowledge the influence of environmental structure in local landscapes (hence denoted “punctual models”). In this study, we applied CNNs to a large dataset of plant occurrences in France (GBIF), on a large taxonomical scale, to predict ranked relative probability of species (by joint learning) to any geographical position. We examined the way local environmental landscapes improve prediction by performing alternative CNN models deprived of information on landscape heterogeneity and structure (“ablation experiments”). We found that the landscape structure around location crucially contributed to improve predictive performance of CNN-SDMs. CNN models can classify the predicted distributions of many species, as other joint modelling approaches, but they further prove efficient in identifying the influence of local environmental landscapes. CNN can then represent signatures of spatially structured environmental drivers. The prediction gain is noticeable for rare species, which open promising perspectives for biodiversity monitoring and conservation strategies. Therefore, the approach is of both theoretical and practical interest. We discuss the way to test hypotheses on the patterns learnt by CNN, which should be essential for further interpretation of the ecological processes at play.


2020 ◽  
Author(s):  
Christian Torsten Seltmann ◽  
Jakob Wernicke ◽  
Rainer Petzold ◽  
Martin Baumann ◽  
Kristian Münder ◽  
...  

&lt;p&gt;In forest management and sience it is important to determine the drivers of tree growth and to quantify their relative importance with regard to forest site characteristics. The growth of individual trees depends on complex interactions between biotic and environmental drivers. Forest management can make use or buffer the effects of biotic drivers, e.&amp;#160;g. through thinning strategies. However, large uncertainties emerge from environmental drivers and its effects on tree growth.&lt;/p&gt;&lt;p&gt;The aim of this study is to quantify the relative importance of environmental drivers (climate, soil, and terrain attributes) on the growth of Norway spruce trees (&lt;em&gt;Picea abies&lt;/em&gt; (L.) Karst.). For that purpose we distinguished three common soil types of Saxony and Thuringia, Germany (Cambisols, Podzols and water-influenced soils, i.e. Gleysol, Planosol, Stagnosol). We used national forest inventory data, regionalized climate data and terrain inferred parameters with a Boosted Regression Tree (BRT) approach. The approach is particularly suitable, since BRT quantify the relative predictor importance, considering non-linearities and interactions among predictors.&lt;/p&gt;&lt;p&gt;The results of this study clearly demonstrate the importance of soil properties on the growth of Norway spruce trees. Terrain attributes and temperature are similarly important for Norway spruce growth on Cambisols and Podzols, whereas spruce growth is mainly influenced by the relative sand content of the soil, the available field capacity and terrain attributes on water-influenced soils. Interactions among environmental drivers are most relevant on Cambisols and Podzols but not on water-influenced soils. Thus, the implementation of the results in growth models of high spatial resolution will support decision making in forest management.&lt;/p&gt;


Sign in / Sign up

Export Citation Format

Share Document