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opencc-zeroJul 2021View details →

Single species acute lethal toxicity tests are not predictive of relative population, community and ecosystem effects of two salinity types

Human mediated salinity increases are occurring in freshwaters globally, with consequent negative effects on freshwater biodiversity. Salinity comprises multiple anions and cations. While total concentrations are typically used to infer effects, individual ion concentrations and ion ratios are critical in determining effects. Moreover, estimates of toxicity from single species laboratory tests, may not accurately predict relative effects on populations, communities and ecosystems. Here we compare salinity increases from synthetic marine salts (SMS) and sodium bicarbonate (NaHCO3) in an outdoor mesocosm experiment in south-eastern Australia. We found different effects of salt types on stream macroinvertebrates at the population, community, and ecosystem function levels, where similar effects were predicted from single species laboratory tests. Our results caution against the use of single species laboratory derived toxicological data to predict both environmentally safe salinity levels and the relative effects of different salt sources on freshwater biodiversity.

opencc-by-4.0Apr 2015View details →

Figure 15. Type locality for Trichonotuloides aphoderrans n in Trichonotuloides aphoderrans, n.sp. (Coleoptera: Scarabaeidae: Aphodiinae), a new genus and species for the United States

Figure 15. Type locality for Trichonotuloides aphoderrans n. sp.

opencc-by-4.0Sep 2009View details →

Figure 2 in Taxonomic overview of the greater fritillary genus Speyeria Scudder and the atlantis - hesperis species complexes, with species accounts, type images, and relevant literature (Lepidoptera: Nymphalidae)

Figure 2. Original description and colored illustrations for 'Idalia' reproduced from Drury 1773.

FIGURE 7 in Rediscovery and redescription of the type species of Myrmozercon, Myrmozercon brevipes Berlese, 1902 (Acari: Mesostigmata: Laelapidae)

FIGURE 7: Myrmozercon brevipes Berlese 1902, male: A – Venter; extensive setation of opisthogaster partially illustrated; B – Chelicerae; C – Ventral gnathosoma (c = corniculus; im = internal malae; lb = labrum).

FIGURE 6 in Rediscovery and redescription of the type species of Myrmozercon, Myrmozercon brevipes Berlese, 1902 (Acari: Mesostigmata: Laelapidae)

FIGURE 6: Myrmozercon brevipes Berlese 1902, female: A – Tarsus I (circle = blunt-tipped, ribbed seta; diamond = minute seta; x = abruptly tapering seta); B – Leg I, coxa to tibia; C – Leg II, coxa to tarsus; D – Leg III, trochanter to tarsus; E – Leg IV, trochanter to tarsus;

FIGURE 3 in Rediscovery and redescription of the type species of Myrmozercon, Myrmozercon brevipes Berlese, 1902 (Acari: Mesostigmata: Laelapidae)

FIGURE 3: Myrmozercon brevipes Berlese 1902, female: A – Venter; extensive setation of opisthogaster partially illustrated (mp = metapo-

FIGURE 2 in Rediscovery and redescription of the type species of Myrmozercon, Myrmozercon brevipes Berlese, 1902 (Acari: Mesostigmata: Laelapidae)

FIGURE 2: Scanning electron micrographs of Myrmozercon brevipes Berlese 1902, female: A – Dorsum; B – Venter; C – Ventral gnathosoma.

FIGURE 1 in Rediscovery and redescription of the type species of Myrmozercon, Myrmozercon brevipes Berlese, 1902 (Acari: Mesostigmata: Laelapidae)

FIGURE 1: Myrmozercon brevipes Berlese 1902, female: Dorsal shield. Lyrifissures, pores and sigillae are shown on the right-hand side.

FIGURE 5 in Rediscovery and redescription of the type species of Myrmozercon, Myrmozercon brevipes Berlese, 1902 (Acari: Mesostigmata: Laelapidae)

FIGURE 5: Myrmozercon brevipes Berlese 1902, female, chelicerae from three different specimens, with two interpretations of cheliceral morphology labelled (see Remarks). cs = vestigial cheliceral seta; dps = distal pseudosegment of second cheliceral digit; ly = lyrifissure; md = movable digit; pps = proximal pseudosegment of second cheliceral digit;? = novel structure.

FIGURE 4 in Rediscovery and redescription of the type species of Myrmozercon, Myrmozercon brevipes Berlese, 1902 (Acari: Mesostigmata: Laelapidae)

FIGURE 4: Myrmozercon brevipes Berlese 1902, female: A – Subcapitulum (c = corniculus; lb = labrum); B – Gnathotectum (ch = chelicera; gt = gnathotectum; p = palp); C – Palp (x = tarsal seta; blunt-tipped sensory setae are coloured black); D – Detail of palp apotele (ap) (different specimen).

opencc-by-4.0Nov 2005View details →

Figure 1 in The species of Papilionidae and Pieridae (Lepidoptera) described by Cramer and Stoll and their putative type material in the Natural History Museum in London

Figure 1. De Uitlandsche Kapellen (title page).

opencc-by-4.0Nov 2005View details →

Figure 2 in The species of Papilionidae and Pieridae (Lepidoptera) described by Cramer and Stoll and their putative type material in the Natural History Museum in London

Figure 2. De Uitlandsche Kapellen (dedication to Cornelis van Lennep).

opencc-by-4.0Jul 2021View details →

Dominant plant species in different growth form categories in various ecosystem types

The table contains a list of vegetation parameter values of dominant plant species in different growth form categories in various ecosystem types based on their importance value indices (IVI) (max. IVI for tree and pole category = 300; max. IVI for sapling and seedling category = 200) in Bantimurung Bulusaraung National Park (BBNP) and Hasanuddin University Educational Forest (HUEF), South Sulawesi.

opencc-by-4.0Jul 2021View details →

Dominant plant species in different growth form categories in various ecosystem types

opencc-zeroApr 2023View details →

Local habitat type influences bumble bee pathogen loads and bee species distribution

Bumble bees (Bombus spp.) perform important ecological services in both managed and natural ecosystems. Anthropogenically-induced change, however, has altered the availability of floral resources, climatic suitability, and exposure to insecticides, factors that impact overall health and disease levels in these bees. Habitat management presents a solution for improving bee health and biodiversity, but this requires better understanding of how different pathogens and bee species respond to habitat conditions. Herein, we take advantage of the washboard of repeated ridges (forested) and valleys (mostly unforested and developed) in central Pennsylvania to examine whether local variation in habitat type and other landscape factors influence bumble bee community composition and the levels of four leading pathogens in the common eastern bumble bee, Bombus impatiens. Loads of viral pathogens (deformed wing virus and black queen cell virus) were found to be lowest in forest habitats, whereas loads of a gut parasite, Crithidia bombi, were highest in forests. Ridgetop forests hosted the most diverse bumble bee communities, including several habitat specialists. B. impatiens was most abundant in valleys, and showed higher incidence in areas of greater disturbance, including more developed, unforested, and lower floral resource sites, a pattern that mirrors its success in the face of anthropogenic change. Additionally, DNA barcoding revealed that B. sandersoni is much more common than is apparent from databases, likely due to misidentification as mimics B. perplexus and B. vagans. Our results provide evidence that habitat type can play a large role in pathogen load dynamics, but in ways that differ by pathogen type, and point to a need for consideration of habitat at both macro-ecological and local spatial scale

opencc-by-4.0Dec 2012View details →

Fig. 2. Tritogenia howickiana Kinberg, 1867 in The megadrile fauna (Annelida: Oligochaeta) of Queen Elizabeth Park, South Africa: species composition and distribution within different vegetation types

Fig. 2. Tritogenia howickiana Kinberg, 1867, the whole body of the lectotype. Scale bar = 5 mm.

opencc-by-4.0Dec 2012View details →

Fig. 5 in The megadrile fauna (Annelida: Oligochaeta) of Queen Elizabeth Park, South Africa: species composition and distribution within different vegetation types

Fig. 5. Tritogenia howickiana, position of the spermathecae (Sp) in segments 12 and 13.

opencc-by-4.0Dec 2012View details →

Fig. 1. A in The megadrile fauna (Annelida: Oligochaeta) of Queen Elizabeth Park, South Africa: species composition and distribution within different vegetation types

Fig. 1. A map of Queen Elizabeth Park, showing the different vegetation types.

opencc-zeroMay 2023View details →

Data from: Integrating multiple sign types to improve occupancy estimation for inconspicuous species

Standard occupancy models enable unbiased estimation of occupancy by accounting for observation errors such as missed detections (false negatives) and, less commonly, incorrect detections (false positives). Occupancy models are fitted to data from repeated site visits in which surveyors record evidence of species presence. Use of indirect sign (e.g., scat, tracks) as evidence of presence can vastly improve survey efficiency for inconspicuous species but can also introduce additional sources of error. We developed a "multi‐sign" occupancy approach to model the detection process separately for unique sign types and used this method to improve estimates of occupancy dynamics for an inconspicuous species, the American pika (Ochotona princeps). We investigated how estimates of pika occupancy and environmental drivers differed under four increasingly realistic representations of the observation process: (1) perfect detection (commonly assumed for modeling pika occupancy), (2) standard occupancy model (single observation process without possibility of false detection), (3) multi‐sign with no false detections (non‐false positive model), and (4) multi‐sign with false detections (full model). For the multi‐sign occupancy models, we modeled the detection of each sign type (fresh scat, fresh haypiles, pika calls, and pika sightings) separately as a function of climatic and environmental covariates. Estimates of occupancy processes and inferences about environmental drivers were sensitive to different detection models. Simplified representations of the detection processes generally resulted in higher occupancy estimates and higher turnover rates than the full multi‐sign model. Environmental drivers also varied in their influence on occupancy models, where (e.g.) forb cover was estimated to more strongly influence occupancy in the full multi‐sign model than the simpler models. As has been reported previously in other contexts, unmodeled heterogeneity in the observation process can lead to biases in occupancy processes and uncertainty in the relationships between occupancy and environmental covariates. Overall, our multi‐sign approach to dynamic occupancy modeling, which accounts for spatiotemporal variation in reliability among sign types, has strong potential to generate more realistic estimates of occupancy dynamics for inconspicuous species.