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Fig. 7 in The biology of an isolated Mashona mole-rat population from southern Malawi, with implications for the diversity and biogeography of the genus Fukomys

Fig. 7 Violin plots showing the distribution of growth parameters (A, K, I, and maximum growth rate) calculated separately for 73 individuals of Fukomys darlingi from the Nsanje population

Fig. 6 in The biology of an isolated Mashona mole-rat population from southern Malawi, with implications for the diversity and biogeography of the genus Fukomys

Fig. 6 Growth in captive Fukomys darlingi from the Nsanje population. Mean body mass (g) calculated weekly for individuals belonging to one of four groups based on sex and breeding status (non-breeding female NB, n = 27; breeding female B, n = 13; non-breeding male NB, n = 19; breeding male B, n = 13) over a period of 10 years. Gompertz growth parameters have been estimated for each individual separately, and thereafter, mean values have been calculated for each group. These parameters have been used for modelling the solid lines

Fig. 8 in The biology of an isolated Mashona mole-rat population from southern Malawi, with implications for the diversity and biogeography of the genus Fukomys

Fig. 8 Adult body mass distribution of Fukomys darlingi from Zimbabwe (nominate form, n =18) and southern Malawi (Nsanje form, n =96). Note the larger body mass and greater sexual dimorphism in animals from Nsanje. Data on F. darlingi individuals from Goromonzi were compiled from Bennett et al. (1994), Gabathuler et al. (1996), and Herbst and Bennett (2001); animals were deemed adult when identified as breeders or when being heavier as the same-sex breeder in the respective family. Nsanje mole-rats were classified as adults at an age of 18 months

Fig. 5 in The biology of an isolated Mashona mole-rat population from southern Malawi, with implications for the diversity and biogeography of the genus Fukomys

Fig. 5 Nuclear phylogeny of Fukomys mole-rats. MCC tree estimated from nuclear datasets of five genes. Tip labels are colour-matched with those shown in the range map and the mitochondrial tree (Figs. 1 and 4). Each tip name contains the sample ID, the name of the respective CYTB lineage, and in the case of samples from F. darlingi clade also the name of the collection locality

opencc-by-4.0Dec 2017View details →

Dataset for RANAS and water quality survey in Malawi

Data outlines behaviour factors and water quality results used in the co-design and development of educational materials for Malawi WaterSPOUTT prototype

opencc-by-4.0Dec 2018View details →

Spatial partial identity model for spatial capture-recapture analysis of large carnivores in Kasungu National Park, Malawi

Overview: Decline in global carnivore populations has led to increased demand for assessment of carnivore densities in understudied habitats. Spatial capture-recapture is used increasingly to estimate species densities, where individuals are often identified from their unique pelage patterns. However, uncertainty in bilateral individual identification can lead to the omission of capture data and reduce the precision of results. The recent development of the two-flank spatial partial identity model (SPIM), offers a cost-effective approach which can reduce uncertainty in individual identity assignment and provide robust density estimates. We conducted camera trap surveys annually between 2016 and 2018 in Kasungu National Park, Malawi, a primary miombo woodland and a habitat lacking baseline data on carnivore densities. We used SPIM to estimate density for leopard (Panthera pardus) and spotted hyaena (Crocuta crocuta), and report on the status of other large carnivores. Usage notes: These data are to estimate density for leopard and spotted hyaena in KNP, Malawi. They are provided as an example for using the spatial partial identity model for spatial capture-recapture analysis in populations where individuals are partially identified. Methods: Individual leopards and spotted hyaena were identified from photographs using their unique pelage patterns (Henschel & Ray, 2003). A database was maintained of identified individuals, with partial (single flank) or complete (two flank) identities, to build capture histories for SCR analysis. We identified individuals from left flank captures for both species, due to higher numbers of identified left flank individuals recorded during preliminary surveys. Complete identities were added where flanks were certain to come from the same individual (from baited stations outside of survey time, live captures, dual camera trap stations and multiple passes of a single camera trap). Leopards were sexed by visual determination of external genitalia, presence of the dewlap, frontal bossing and overall body size (Henschel & Ray, 2003; Devens et al. 2018). Sexing was not possible for spotted hyaena due to difficulties in determining sex from external genitalia and body size. Capture histories were developed for spatial captures and trap effort, with each day (24 hours) treated as a separate sampling occasion (Goldberg et al. 2015). Trap effort was measured through a binary matrix of active-inactive days, to improve estimates of detection probability, and included the spatial location of each camera location. Density was modelled using the package SPIM (Augustine, 2018) in R v.3.5.2 (R Development Core Team, 2018) to resolve the complete identity of individuals from single-flank samples probabilistically (see Augustine et al. 2018 for complete description of spatial partial identity model), and a Bernoulli observation model fitted, whereby an individual may be captured in each trap only once during each sampling occasion (Royle et al. 2013; Augustine et al. 2018). For Markov Chain Monte Carlo simulations, a single chain of 50,000 iterations per single session analysis was undertaken, with a burn-in of 500 iterations and data augmentation of 100-130 individuals for leopard and 125-250 for spotted hyaena. Analysis was conducted with an increasing buffer width from 10,000 to 25,000 metres (leopard) and 10,000 to 40,000 metres (spotted hyaena), using 5,000 metre increments, until density estimates stabilised (Chase-Grey et al. 2013; Devens et al. 2018).

opencc-by-4.0Jan 2022View details →

Figures 4–10 in Papillocepheus banari sp. nov. (Acari, Oribatida, Otocepheidae) from Malawi

Figures 4–10. Papillocepheus banari sp. nov., adult: 4—subcapitulum, ventral view; 5—palp, right, antiaxial view; 6—chelicera, right, antiaxial view; 7—leg I, right, antiaxial view; 8—leg II (tarsus omitted), right, antiaxial view; 9— leg III (tarsus omitted), left, antiaxial view; 10—leg IV, left, antiaxial view. Scale bars 50 μm (4, 6–10), 20 μm (5).

Figure 2 in The structure and composition of the woody plant communities of Majete Wildlife Reserve, Malawi

Figure 2. Typical examples of the plant communities in Majete Wildlife Reserve; A, riparian woodland (Rw); B, grassland (Gr); C–D, shrublands and woodlands (SW); E, transitional woodland (Tw); and F, miombo (M). Photo credits: W.A. Nieman.

Figure 1 in The structure and composition of the woody plant communities of Majete Wildlife Reserve, Malawi

Figure 1. Dendrogram of species composition for different woody plant communities based on the Jaccard similarity index.

Figure 4 in The structure and composition of the woody plant communities of Majete Wildlife Reserve, Malawi

Figure 4. The comparative performance of six incidence-based species richness estimators (Chao 2, Chao 2-bc, iChao 2, Jack 1, Jack 2 and ICE) for all woody plant species recorded in Majete Wildlife Reserve (n = 118). The observed species accumulation curve (Sobs) with 95% confidence intervals, as well as the cumulative number of singletons (the number of species recorded only once during the survey) and doubletons (the number of species recorded only twice during the survey), were also plotted. Estimated woody species richness values are indicated in brackets.

Figure 3 in The structure and composition of the woody plant communities of Majete Wildlife Reserve, Malawi

Figure 3. Distribution of woody plant communities in Majete Wildlife Reserve (MWR). The inset shows the location of the MWR in Malawi.

opencc-by-4.0Jul 2020View details →

Figure 4 in Distribution of Mimosa diplotricha in eastern and southern Africa and its socio- ecological impacts in northern Malawi

Figure 4: Mimosa diplotricha invasions in southern Tanzania (top row), northern Malawi (middle row), and western Ethiopia (bottom row).

opencc-by-4.0Jul 2020View details →

Figure 3 in Distribution of Mimosa diplotricha in eastern and southern Africa and its socio- ecological impacts in northern Malawi

Figure 3: Map showing the location of Malawi in Africa (inset) and Karonga District in Malawi where the socio-economic surveys were undertaken.

opencc-by-4.0Jul 2020View details →

Figure 2 in Distribution of Mimosa diplotricha in eastern and southern Africa and its socio- ecological impacts in northern Malawi

Figure 2: Map showing the current known distribution of Mimosa diplotricha in eastern and southern Africa (~55 km × 55 km/ half degree grid cells) using data collected in this study and other sources of information. Grey grid cells show areas surveyed; red grid cells indicate areas where Mimosa diplotricha was found to be invasive (widespread and/or abundant); orange cells where it was present and/or naturalised; and yellow cells where it was recorded with no other information.

opencc-by-4.0Apr 2024View details →

Fig. 1 in An alien intermediate snail host in Malawi - Orientogalba viridis (Quoy and Gaimard, 1832) - A new concern for schistosomiasis transmission in Africa?

Fig. 1. Site photo of the location where O. viridis was first encountered. Numerous snails were found on mud within the rice paddy [large inset] and, of particular note, a single schistosome cercaria of S. haematobium was observed upon microscopy and photographed [small inset] and confirmed by DNA barcoding. This rice paddy was immediately adjacent to a small oxbow lake, where children were seen swimming and numerous Bulinus were found but these snails were not observed to shed schistosome cercariae at the time of first survey in May 2023.

opencc-by-4.0Apr 2024View details →

Fig. 2. A in An alien intermediate snail host in Malawi - Orientogalba viridis (Quoy and Gaimard, 1832) - A new concern for schistosomiasis transmission in Africa?

Fig. 2. A) Shell, scale bar: 3 mm; B) mantle pigmentation, scale bar: 3 mm; C) bursa copulatrix, scale bar: 2 mm; D) penis, ratio of penis sheath (ps)/preputium (pp) ~1, overall length 0.5 cm; E) radula, scale bar: 10 μm; F) experimental infection with S. haematobium with miracidia highlighted within red elipses with unaltered swimming around the snail's body. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Linked collectors and determiners for: ABC Useful Plants of Malawi: Economical & Commercial.

Natural history specimen data linked to collectors and determiners held within, "ABC Useful Plants of Malawi: Economical & Commercial". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/da39fadf-94c9-4d9d-ba65-64750b58cfe7">https://bionomia.net/dataset/da39fadf-94c9-4d9d-ba65-64750b58cfe7</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/da39fadf-94c9-4d9d-ba65-64750b58cfe7">https://gbif.org/dataset/da39fadf-94c9-4d9d-ba65-64750b58cfe7</a>. Formatted as a Frictionless Data package.

Linked collectors and determiners for: malawi-scarabaeoidea-biodiversity-data.

Natural history specimen data linked to collectors and determiners held within, "malawi-scarabaeoidea-biodiversity-data". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/7f1dc982-02f3-4ae7-8fe8-d2cf6d079ccd">https://bionomia.net/dataset/7f1dc982-02f3-4ae7-8fe8-d2cf6d079ccd</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/7f1dc982-02f3-4ae7-8fe8-d2cf6d079ccd">https://gbif.org/dataset/7f1dc982-02f3-4ae7-8fe8-d2cf6d079ccd</a>. Formatted as a Frictionless Data package.

Linked collectors and determiners for: ABC_Useful plants of Malawi; medicinal plants used in maternal and child health care.

Natural history specimen data linked to collectors and determiners held within, "ABC_Useful plants of Malawi; medicinal plants used in maternal and child health care". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/789e1248-c737-4d6a-bcec-e4b92775becc">https://bionomia.net/dataset/789e1248-c737-4d6a-bcec-e4b92775becc</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/789e1248-c737-4d6a-bcec-e4b92775becc">https://gbif.org/dataset/789e1248-c737-4d6a-bcec-e4b92775becc</a>. Formatted as a Frictionless Data package.

Linked collectors and determiners for: Invasive Alien plant species of Malawi.

Natural history specimen data linked to collectors and determiners held within, "Invasive Alien plant species of Malawi". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/6183f1f7-0513-4587-bee6-cad11e23002d">https://bionomia.net/dataset/6183f1f7-0513-4587-bee6-cad11e23002d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/6183f1f7-0513-4587-bee6-cad11e23002d">https://gbif.org/dataset/6183f1f7-0513-4587-bee6-cad11e23002d</a>. Formatted as a Frictionless Data package.