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opencc-zeroJan 2024View details →

Relative breeding timing and reproductive success of a resident montane bird species

The phenological match-mismatch hypothesis predicts that animals that better synchronize critical life history events with the peak availability of their primary food source should have higher fitness. If phenological match-mismatch determines breeding success, most individuals in a population may be expected to breed simultaneously within a given year because selection has favored mechanisms that allow for the tracking of optimal food abundance. Therefore, individuals that breed too early or too late relative to the bulk of the population ("peak" of breeding) should experience decreased fitness. Using 11 years of data, we investigated the effect of relative breeding timing on breeding success in resident mountain chickadees (Poecile gambeli) across two elevations in the Sierra Nevada mountains, USA. Chickadees that bred during the peak of nesting did not have the highest breeding success; instead, birds that bred earliest performed best at high elevation, while at low elevation early and peak nests performed similarly. Breeding success decreased linearly with relative timing at both high and low elevations, and the relationship between breeding success and timing differed among years. Our results suggest that phenological match-mismatch may not be the main driver of within-year variation in breeding success in animals residing in montane environments.

Figure 5 in Revised taxonomy of eastern North Pacific killer whales ( Orcinus orca ): Bigg's and resident ecotypes deserve species status

Figure 5. Global phylogenetic trees of killer whales based on (a) haplotypes from 452 mitogenomes and (b) 49 nuclear genome sequences. Reprinted with permission from Morin et al. [15] (figure 2; by permission from John Wiley & Sons, licence 5458310335802) and [9] (electronic supplementary material, figure S3b, by permission from Andrew D. Foote). Black branches in (a) lead to haplotypes that are from animals that have not been identified to ecotype (see electronic supplementary material, table S1 from [15]).

Figure 3 in Revised taxonomy of eastern North Pacific killer whales ( Orcinus orca ): Bigg's and resident ecotypes deserve species status

Figure 3. PCA plot of first two principal components based on (a) 88 SNPs: offshore (n = 3), resident (n = 11), Bigg's (n = 30) from data in Morin et al. [15]; (b) 26 microsatellites: offshore (n = 5), resident (n = 250), Bigg's (n = 116) (samples genotyped at ≥20 loci) [56]; unpublished); (c) 3678 RADseq SNPs: offshore (n = 7), resident (n = 52) and Bigg's (n = 37) populations [57,62]; (d) 1 00 000 (subset from 6 371 282) SNPs from 147 high-coverage genomes of offshore (n = 7), Bigg's (n = 14) and resident (n = 126) samples from multiple geographically and behaviourally defined subpopulations (Alaska, northern and southern resident populations) (based on subset of SNP genotype data from [113]. See Supplementary Materials for methods and data set information.

Figure 7 in Revised taxonomy of eastern North Pacific killer whales ( Orcinus orca ): Bigg's and resident ecotypes deserve species status

Figure 7. Photographs of neotype skulls for (a) Orcinus rectipinnus (USNM 594671) and (b) Orcinus ater (USNM 594672).

Figure 1 in Revised taxonomy of eastern North Pacific killer whales ( Orcinus orca ): Bigg's and resident ecotypes deserve species status

Figure 1. Expected range maps for (a) resident and (b) Bigg's killer whales, including locations of samples used for mitogenome analysis (figure 5a, resident n = 106, Bigg's n = 93) [15]. Distribution ranges have been inferred based on published identifications of individuals that are identified by ecotype [48–53]. Sample distributions cover the known ranges of both ecotypes, with the exception of residents of Oregon and northern California, and both ecotypes off northern Japan (Hokkaido) in the western Pacific [48,54]. Sample maps for microsatellite data are in electronic supplementary material, figure S2.

Figure 8 in Revised taxonomy of eastern North Pacific killer whales ( Orcinus orca ): Bigg's and resident ecotypes deserve species status

Figure 8. Vertical images of (a) an adult male Bigg's killer whale (BKW) from the West Coast Transient population of Bigg's killer whales and (b) an adult male resident killer whale (RKW) from the sympatric Southern Resident population of resident killer whales. Images are scaled to the estimated asymptotic lengths of 7.3 m [20] and 6.9 m [145], respectively. Vertical images were collected using an octocopter drone using methods described by Durban et al. [146], provided by John Durban and Holly Fearnbach.

Figure 6 in Revised taxonomy of eastern North Pacific killer whales ( Orcinus orca ): Bigg's and resident ecotypes deserve species status

Figure 6. Illustrations of (a) O. ater and (b) O. rectipinnus from Scammon [138,140]. These illustrations were likely made by Scammon, or made under his guidance from his field notes and sketches. Whether they represent renderings of specific specimens, or composite sketches, is unknown.

Figure 2. Canonical variate 1 and 2 in Revised taxonomy of eastern North Pacific killer whales ( Orcinus orca ): Bigg's and resident ecotypes deserve species status

Figure 2. Canonical variate 1 and 2 plots for cranial shape features that distinguish among ecotypes for (a) skull morphology (resident (n = 17), Bigg's (n = 13) and offshore (n = 6)) and (b) dentary bone morphology (resident (n = 21), Bigg's (n = 12) and offshore (n = 8) specimens) (reprinted from [103]).

Figure 4. Structure assignment probability plots for K in Revised taxonomy of eastern North Pacific killer whales ( Orcinus orca ): Bigg's and resident ecotypes deserve species status

Figure 4. Structure assignment probability plots for K = 3 groups from (a) 26 microsatellites: offshore (n = 5), resident (n = 250), Bigg's (n = 116) samples genotyped at ≥ 20 loci) (56; unpublished); (b) 3340 RADseq SNPs (polymorphic in sample set): offshore (n = 7), resident (n = 52) and Bigg's (n = 37) populations [57,62]. Vertical bars represent the individual assignment probability for each group inferred by Structure (groups identified by shading), with samples sorted by a priori ecotype assignment. See electronic supplementary material for methods and data set information.

opencc-zeroSep 2022View details →

Environmental DNA reveals fine-scale habitat associations for sedentary and resident marine species across a coastal mosaic of soft and hard-bottom habitats

Accurate knowledge on spatiotemporal distributions of marine species and their association with surrounding habitats is crucial to inform adaptive management actions responding to coastal degradation across the globe. Here, we investigate the potential use of environmental DNA (eDNA) to detect species-habitat associations in a patchy coastal area of the Baltic Sea. We directly compare species-specific qPCR analysis of eDNA with baited remote underwater video systems (BRUVS), two non-invasive methods widely used to monitor marine habitats. Four focal species (cod Gadus morhua, flounder Platichthys flesus, plaice Pleuronectes platessa and goldsinny wrasse Ctenolabrus rupestris) were selected based on contrasting habitat associations (reef- vs. sand-associated species), as well as differential levels of mobility and residency, to investigate whether these factors affected the detection of species-habitat associations from eDNA. To this end, a species-specific qPCR assay for goldsinny wrasse is developed and made available herein. In addition, potential correlations between eDNA signals and abundance counts (MaxN) from videos were assessed. Results from Bayesian multi-level models revealed strong evidence for a sand association for sedentary flounder (98% posterior probability) and a reef association for highly resident wrasse (99% posterior probability) using eDNA, in agreement with BRUVS. However, contrary to BRUVS, eDNA sampling did not detect habitat associations for cod or plaice. We found a positive correlation between eDNA detection and MaxN for wrasse (posterior probability 95%), but not for the remaining species and explanatory power of all relationships was generally limited. Our results indicate that eDNA sampling can detect species-habitat associations on a fine spatial scale, yet this ability likely depends on the mobility and residency of the target organism, with associations for sedentary or resident species most likely to be detected. Combined sampling with conventional non-invasive methods is advised to improve detection of habitat associations for mobile and transient species, or for species with low eDNA concentrations.

opencc-by-4.0Aug 2012View details →

Supplementary material 1 from: Dainese M, Poldini L (2012) Does residence time affect responses of alien species richness to environmental and spatial processes? NeoBiota 14: 47-66. https://doi.org/10.3897/neobiota.14.3273

Supplementary material 1 from: Dainese M, Poldini L (2012) Does residence time affect responses of alien species richness to environmental and spatial processes? NeoBiota 14: 47-66. https://doi.org/10.3897/neobiota.14.3273

publicSep 2022View details →

Environmental DNA reveals fine-scale habitat associations for sedentary and resident marine species across a coastal mosaic of soft and hard-bottom habitats

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publicFeb 2025View details →

Relative breeding timing and reproductive success of a resident montane bird species

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opencc-zeroDec 2020View details →

Dead litter of resident species first facilitates and then inhibits sequential life stages of range-expanding species

1. Resident species can facilitate invading species (biotic assistance) or inhibit their expansion (biotic resistance). Species interactions are often context-dependent and the relative importance of biotic assistance versus resistance could vary with abiotic conditions or the life stage of the invading species, as invader stress tolerances and resource requirements change with ontogeny. In northeast Florida salt marshes, the abundant dead litter (wrack) of the native marsh cordgrass, Spartina alterniflora, could influence the expansion success of the black mangrove, Avicennia germinans, a tropical species that is expanding its range northward. 2. We used two field experiments to examine how S. alterniflora wrack affects A. germinans success during 1) propagule establishment and 2) subsequent seedling survival. We also conducted laboratory feeding assays to identify propagule consumers and assess how wrack presence influences herbivory on mangrove propagules. 3. S. alterniflora wrack facilitated A. germinans establishment by promoting propagule recruitment, retention, and rooting; the tidal regime influenced the magnitude of these effects. However, over time S. alterniflora wrack inhibited A. germinans seedling success by smothering seedlings and attracting herbivore consumers. Feeding assays identified rodents – which seek refuge in wrack – as consumers of A. germinans propagules. 4. Synthesis: Our results suggest that the deleterious effects of S. alterniflora wrack on A. germinans seedling survival counterbalance the initial beneficial effects of wrack on A. germinans seed establishment. Such seed-seedling conflicts can arise when species stress tolerances and resource requirements change throughout development and vary with abiotic conditions. In concert with the tidal conditions, the relative importance of positive and negative interactions with wrack at each life stage can influence the rate of local and regional mangrove expansion. Because interaction strengths can change in direction and magnitude with ontogeny, it is essential to examine resident-invader interactions at multiple life stages and across environmental gradients to uncover the mechanisms of assistance and resistance during invasion.

opencc-zeroJun 2024View details →

Acoustic phenology of tropical resident birds differs between native forest species and parkland colonizer species

Most birds are characterized by a seasonal phenology closely adapted to local climatic conditions, even in tropical habitats where climatic seasonality is slight. In order to better understand the phenologies of resident tropical birds, and how phenology may differ among species at the same site, we used ~70,000 hours of audio recordings collected continuously for two years at four recording stations in Singapore and nine custom-made machine learning classifiers to determine the vocal phenology of a panel of nine resident bird species. We detected distinct seasonality in vocal activity in some species but not others. Native forest species sang seasonally. In contrast, species which have had breeding populations in Singapore only for the last few decades exhibited seemingly aseasonal or unpredictable song activity throughout the year. Urbanization and habitat modification over the last 100 years have altered the composition of species in Singapore, which appears to have influenced phenological dynamics in the avian community. It is unclear what is driving the differences in phenology between these two groups of species, but it may be due to either differences in seasonal availability of preferred foods, or newly established populations may require decades to adjust to local environmental conditions. Our results highlight the ways that anthropogenic habitat modification may disrupt phenological cycles in tropical regions in addition to altering the species community.

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Table 1 in Revised taxonomy of eastern North Pacific killer whales (Orcinus orca): Bigg's and resident ecotypes deserve species status

Table 1. Measures of differentiation, divergence and diagnosability based on nuclear microsatellite and SNP data. All frequency-based metrics (FST, F’ST, G’ST) were significantly different from zero at p <0.05.<table><tbody><tr><th>divergence metric</th><th></th><th>reference</th></tr></tbody><tbody><tr><th>dA (CR)</th><td>0.007 46a</td><td>[114]</td></tr><tr><th>dA (mitogenome)</th><td>0.003 91b</td><td>[114]</td></tr><tr><th>FST (microsatellite)</th><td>0.21–0.23</td><td>[56,85]</td></tr><tr><th>F’ST (microsatellite)</th><td>0.47</td><td>[56]</td></tr><tr><th>G’ST (microsatellite)</th><td>0.28</td><td>[56]</td></tr><tr><th>FST (SNP)</th><td>0.28</td><td>[15]</td></tr><tr><th>F(RADseq, neutral)c ST</th><td>0.27</td><td>[58]</td></tr><tr><th>F(RADseq, selected)c ST</th><td>0.67</td><td>[58]</td></tr><tr><th>FST (genomes)</th><td>0.32</td><td>[9] (electronic supplementary material, table S2)</td></tr><tr><th>diagnosability (CR)</th><td>100%</td><td>[114]</td></tr><tr><th>diagnosability (mitogenome)</th><td>100%</td><td>[114]</td></tr><tr><th>fixed differences (mitogenome)</th><td>57</td><td>[7]</td></tr><tr><th>fixed differences (3281 nuclear SNPs)</th><td>2–7</td><td>[58]</td></tr><tr><th>fixed differences (6 435 100 nuclear SNPs)</th><td>6361d</td><td>[113]</td></tr></tbody></table>a 95% confidence interval:0.00727–0.00772. b 95% confidence interval: 0.00388–0.00393. c Alaska transients (Bigg’s) versus Alaska residents. d Based on analysis of raw SNP data from Kardos et al. [113].

publicJan 2020View details →

Size-dependent costs of migration: migrant bird species are subordinate to residents, but only at small body sizes

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publicJun 2025View details →

Data from: Not in the countryside please! Investigating UK residents' perceptions of an introduced species, the ring-necked parakeet

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publicJun 2024View details →

Acoustic phenology of tropical resident birds differs between native forest species and parkland colonizer species

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