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102 results for “abiotic factors”
Fig. 3 in Effect of vegetation and abiotic factors on the abundance and population structure of Crocodylus acutus (Cuvier, 1806) in coastal lagoons of Colima, Mexico
Fig. 3. Dendrogram considering the crocodiles observed, water salinity, temperature, depth, and the four vegetation types present. Acronym definitions and characteristics of the sites are given in Table 1.
Fig. 1 in Effect of vegetation and abiotic factors on the abundance and population structure of Crocodylus acutus (Cuvier, 1806) in coastal lagoons of Colima, Mexico
Fig. 1. Selected sites in the study area. Acronym definitions and characteristics of the sites are given in Table 1.
Fig. 2 in Effect of vegetation and abiotic factors on the abundance and population structure of Crocodylus acutus (Cuvier, 1806) in coastal lagoons of Colima, Mexico
Fig. 2. Non-metric Multidimensional Scaling (NMDS) analysis showing the formation of two groups, by taking into account the crocodiles observed, water salinity, temperature, depth, and the four vegetation types present. Acronym definitions and characteristics of the sites are given in Table 1.
Fig. 2 in Influence of biotic and abiotic factors on flea species population dynamics on Lasiopodomys brandtii
Fig. 2. Community structure of Lasiopodomys brandtii fleas by seasons. Three flea species were collected throughout the study meanwhile, Rhadinopsylla rothschildi was only detected in autumn. The top of each column indicates the number of samples for each season.
Fig. 6 in Fish larvae from the upper Paraná River: Do abiotic factors affect larval density?
Fig. 6. Conceptual model showing the relationships among abiotic factors, species larvae and areas (arrow directions on axis show increasing values of abiotic factors).
Fig. 3 in Fish larvae from the upper Paraná River: Do abiotic factors affect larval density?
Fig. 3. Mean scores (rectangles) and standard error (bars) (Axis 1=a and Axis 2=b of the Detrended Correspondence Analysis; DCA), derived from the larva density matrix for the different areas (AMA= Amambaí River, IVA= Ivaí River, PAR= Paraná River and RES= Itaipu Reservoir).
The interplay between abiotic and biotic factors on dispersal decisions: evidence and implications for metacommunities
<p>Suitable conditions for species to survive and reproduce constitute their ecological niche, which is built by abiotic conditions and interactions with conspecifics and heterospecifics. Organisms should ideally assess and use information about all these environmental dimensions to adjust their dispersal decisions depending on their own internal conditions. Dispersal plasticity is often considered through its dependence to abiotic conditions or conspecifics density, and to a lesser extent with the effects of interactions with heterospecifics, potentially leading to misinterpretation of dispersal drivers. Here, we first review the evidence for effects of, and the potential interplays between abiotic factors, biotic interactions with conspecifics and heterospecifics, and phenotype on dispersal decisions. We then present an experimental test of these potential interplays, testing the effects of density and interactions with conspecifics and heterospecifics on temperature-dependent dispersal in microcosms of <i>Tetrahymena </i>ciliates. We found significant differences in dispersal rates depending on temperature, density, and presence of another strain or species. However, the presence and density of conspecifics and heterospecifics had no effects on the thermal-dependency of dispersal. We discuss the causes and consequences of the (lack of) interplay between the different environmental dimensions and the phenotype for metacommunity assembly and dynamics.</p>
Abiotic factors modify ponderosa pine regeneration outcomes after high-severity fire
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Arbuscular mycorrhizal fungi in roots and soil respond differently to biotic and abiotic factors in the Serengeti
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Zooplankton recovery from a whole‐lake disturbance: Examining roles of abiotic factors, biotic interactions, and traits
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Impacts of abiotic and biotic factors on terrestrial leeches in
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Data from: Assessing the influence of biotic, abiotic, and social factors on the physiological stress of a large Neotropical primate in Atlantic Forest fragments
Wildlife physiological responses to environmental and human-related stressors provide useful clues on animal welfare. Non-invasive biomarkers, such as fecal glucocorticoid metabolites (fGCM), allow researchers to assess whether variations in habitat quality, behavior, and climate influence the animals' physiological stress. We examined the role of fragment size, ambient temperature, ripe fruit availability and consumption, percentage of records moving, sex, female reproductive state, and group composition as predictors of the level of fGCM in adult brown howler monkeys (Alouatta guariba clamitans) inhabiting three small (<10 ha) and three large (>90 ha) Atlantic Forest fragments in southern Brazil. We collected bimonthly behavioral data and fecal samples from adult individuals over three years, and used a multimodel inference framework to identify the main predictors of fGCM. We found that the mean (±SD) fGCM in the study groups ranged from 57 ± 49 ng/g to 93 ± 58 ng/g, which were within the known range for howler monkeys. We found 10 best models including five of the 17 tested variables. Sex and reproductive state were the only variables included in all these models. We found that fGCM was higher in nursing females (mean ± SD = 104 ± 73 ng/g) than in non-nursing females (64 ± 55 ng/g) and males (53 ± 40 ng/g, P < 0.05) and that it decreased with increasing ripe fruit consumption and minimum temperature. However, fragment size did not predict fGCM concentration (groups in small fragments = 71 ± 58 ng/g vs. groups in large fragments = 63 ± 54 ng/g, P > 0.05). We conclude that factors related to the energetic balance of individuals play major roles in modulating the physiological stress of brown howler monkeys. Future studies should investigate the consequences of higher levels of stress hormones on howler monkey health and demography.
Biotic and abiotic factors and the phylogenetic structure of extinction in the evolution of Tethysuchia
<p>Crocodylomorpha is a large and diverse clade with a long evolutionary history now restricted to modern crocodylians. Tethysuchia is a less-inclusive clade of semi-amphibious taxa that crossed two biological crises: the second Oceanic Anoxic Event (OAE 2) and the Cretaceous/Paleogene (K/Pg) Crisis. Numerous studies have sought to find the driving factors explaining crocodylomorph evolution producing contradictory conclusions. Studies of included groups may be useful. Here, we study factors driving tethysuchian evolution using phylogenetically informed statistical analyses. First, we tested the phylogenetic structure of tethysuchian extinction at the OAE 2 and K/Pg crises. We then used phylogenetic comparative methods to test the influence of intrinsic (body size, snout proportion) and extrinsic (temperature, paleolatitude) factors on the evolution of tethysuchian diversity at the OAE 2 and the K/Pg crises. Finally, we tested whether temperature influenced the evolution of body size. We conclude that (1) extinction was not random in regards to phylogeny for Tethysuchia at the OAE 2 and K/Pg crises; (2) while an important tethysuchian turnover follows OAE 2, the K/Pg crisis was followed by an explosion in diversity of tethysuchians, probably linked to the colonization of emptied ecological niches; (3) tethysuchians lived in warmer environments after the OAE 2 crisis, possibly because of both global warming and latitude distribution shifts; (4) there is a significant change of snout proportion after the OAE 2 and the K/Pg crises, likely caused by niche partitioning; and (5) there is a positive correlation between body size and temperature, possibly because of a longer growth season</p>
Meta-analysis of the effects of abiotic factors on plant microbes
<p>The abiotic environment exerts strong effects on plant-associated microbes, shaping their interactions with plants and resulting ecosystem processes. However, these abiotic effects on plant-microbe interactions are often highly specific and contingent on the abiotic driver or microbial group, requiring synthesis work describing general patterns and from this generate hypotheses and guide mechanistic work. To address this, we conducted a meta-analysis of the effects of climate change-related abiotic factors, namely warming, drought, and eCO<sub>2</sub>, on plant-associated microbes distinguishing by microbial taxonomic or biological group (bacteria, fungi or virus) and the plant part where microbes are found or associated with (phyllosphere or rhizosphere). We found abiotic driver-specific patterns, whereby drought significantly reduced microbial abundance, whereas warming and eCO<sub>2</sub> had no significant effects. In addition, these abiotic effects were contingent on the microbial taxonomic group, with fungi being negatively affected by drought but positively affected by warming (eCO<sub>2</sub> enrichment had no effect), whereas bacteria and viruses were not significantly affected by any factor. Likewise, rhizopheric microbes were negatively affected by drought but positively affected by warming (eCO<sub>2</sub> enrichment had no effect), whereas phyllospheric microbes were not significantly affected by any factor. Collectively, these findings point to important implications for global change research by highlighting contrasting effects of climate change-related abiotic drivers on plant-associated microbes and the contingency of such effects on microbe life histories and the nature of their interactions with plants.</p>
Abiotic stress and biotic factors mediate range dynamics on opposing edges
<p><strong><em>Aim:</em></strong> In the face of global change, understanding causes of range limits is one of the most pressing needs in biogeography and ecology. A prevailing hypothesis is that abiotic stress forms cold (upper latitude/altitude) limits whereas biotic interactions create warm (lower) limits. A new framework – Interactive Range-Limit Theory (iRLT) – asserts that positive biotic factors such as food availability can ameliorate abiotic stress along cold edges, whereas abiotic stress can have a positive effect and mediate biotic interactions (e.g., competition) along warm limits.</p> <p><strong><em>Location:</em></strong> Northeastern US</p> <p><strong><em>Taxon:</em></strong> Carnivora</p> <p><strong><em>Methods:</em></strong> We evaluated two hypotheses of iRLT using occupancy and structural equation modeling (SEM) frameworks based on data collected over a six-year period (2014–2019) of six carnivore species across a broad latitudinal (42.8–45.3°N) and altitudinal (3–1451 m) gradient.</p> <p><strong><em>Results:</em></strong> We found that snow directly limits populations, but prey or habitat availability can influence range dynamics along cold edges. For example, bobcats (<em>Lynx rufus</em>) and coyotes (<em>Canis latrans</em>) were limited by deep snow and long winters, but the availability of prey had a strong positive effect. Conversely, snow had a strong positive effect on the warm limits of Canada lynx (<em>Lynx canadensis</em>), countering the negative effect of competition with the phylogenetically-similar bobcat and with coyotes, highlighting how climate mediates competition between species.</p> <p><strong><em>Main conclusions:</em></strong> We used an integrated dataset that included competitors and prey species collected at the same spatial and temporal scale. As such, this design, along with a causal modeling framework (SEM), allowed us to evaluate community-wide hypotheses at macroecological scales and identify coarse-scale drivers of species' range limits. Our study supports iRLT and underscores the need to consider direct and indirect mechanisms for studying range dynamics and species' responses to global change.</p>
Figure 1 in Diurnal vertical distribution of zooplankton in a newly formed reservoir (Tahtalı Reservoir, Kocaeli): the role of abiotic factors and chlorophyll a
Figure 1. Study area and sampling station.
Fig. 1 in Biotic and abiotic factors influencing the prevalence, intensity and distribution of Eucoleus aerophilus and Crenosoma vulpis in red foxes, Vulpes vulpes from Romania
Fig. 1. Distribution of Crenosoma vulpis and Eucoleus aerophilus in Romania.
Fig. 1 in Influence of biotic and abiotic factors on flea species population dynamics on Lasiopodomys brandtii
Fig. 1. Map of the study area.
Do early-successional weeds facilitate or compete with seedlings in forest restoration? Disentangling abiotic vs. biotic factors
<p>Census data for seedlings part of a weed exclusion experiment at Sal del Rey, Texas within a larger field where ~100,000 seedlings were planted in October-November 2018. Records seedling height, vigor (0 - dead, > 0 - alive), branching, and animal damage for 158 individuals of eight species classified by growth habit (fast/slow) and distributed in control and exclusion (mowed) plots across seven censuses.</p>
Fig. 1 in Fish larvae from the upper Paraná River: Do abiotic factors affect larval density?
Fig. 1. Map of the upper Paraná River showing the location of the sampling stations.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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