Land use gradients drive spatial variation in Lassa fever host communities in Eastern Sierra Leone.
The natal multimammate mouse (Mastomys natalensis) is the primary reservoir species of the zoonotic infectious disease, Lassa fever (Lassa mammarenavirus). This disease is endemic to Sierra Leone with the highest incidence of human infection reported from the Eastern Province. The spatial occurrence and abundance of this rodent species is regulated by the human environment and biotic interactions within small mammal communities, little is known about these effects even in highly endemic areas of Lassa fever. We conducted a rodent trapping study at four village study sites between 2020-2023, comprising 40,152 trap nights to understand how M. natalensis is distributed across a gradient of landuse types and how this may be influenced by the broad small mammal community structure. We conducted a Bayesian multiple species occupancy model, accounting for imperfect detection, to test the hypothesis that M. natalensis were more likely to occur within human dominated landuse types. We found that M. natalensis occurrence increased from less to more human dominated landscapes. We further found that this effect was not replicated across scales as the probability of occurrence in peri-urban settings was lower than in rural settings. Interactions within the small mammal community appeared to moderate the occurrence of M. natalensis, with the presence of Mus musculus, but not Rattus rattus reducing the probability of occurrence of M. natalensis. This finding may explain prior observations of lower-than-expected human cases of Lassa Fever fever from urban settings in endemic regions. Our findings highlight the spatially heterogeneous distribution of rodent species across landuse gradients with implications for the hazard of Lassa fever outbreaks.
This work is currently in preparation with additional data expected
Motivation
This study was designed to investigate the effect of changes in landuse on the occurrence of different rodent species in a Lassa fever endemic region of Eastern Sierra Leone. While habitat preferences of Mastomys natalensis have been well studied in West Africa to better understand the risk to human populations from Lassa mammarenavirus spillover (Fichet‐Calvet et al. 2010), there is limited understanding of the wider rodent species communities. Biotic interactions between different species will drive occurrence and abundance in different habitats and this study was designed to understand how these species co-exist in these habitats.
We conducted repeated, systematic, rodent trapping in the Eastern province of Sierra Leone, along a landuse gradient to model the association of landuse and occurrence of M. natalensis and more generally small mammal communities. We aimed to investigate the following questions. First, what is the diversity of rodent communities in varied landuse types in Eastern Sierra Leone? Second, how do patterns of landuse affect the occupancy of M. natalensis and other sympatric rodents? Finally, is there evidence that the local spatial distribution of M. natalensis is regulated by biotic interactions with co-occurring species? We expect these analyses to further our understanding of rodent community structures that may explain observed patterns of Lassa fever spillover.
Method
A protocol was developed prior to a pilot trapping session in November 2020. This protocol is archived on the Open Science Framework. All field data is collected using the Open Data Kit (ODK).
Rodent sampling
We conducted rodent trapping surveys between October 2020-February 2023 within and around four village study sites (Baiama; latitude = 7.8375, longitude = -11.2683, Lalehun; latitude = 8.1973, longitude = -11.0803, Lambayama; latitude = 7.8505, longitude = -11.1969, and Seilama; latitude = 8.1224, longitude = -11.1936) in the Lassa fever endemic zone of the Eastern Province of Sierra Leone (Figure 1A.). Surveys were conducted within trapping grids along a landuse gradient of anthropogenic disturbance comprising, forest, agriculture (including fallow and currently in-use areas), and villages (within and outside of permanent structures) (See Supplementary Material 1 for images representative of trapping grid locations). Trapping grids were designated during the initial trapping survey session, one grid was deployed in forest land use, three to four grids were deployed in agricultural land with two grids deployed in village land use. For one village study site, Lambayama, there were no local forest areas, so this landuse type was omitted (Figure 1B-E). Trapping survey sessions within each village occurred four times annually with two trapping surveys in each of the rainy and dry seasons (May to November and December to April, respectively), giving a total of 9 trapping sessions over the study period.
Species classification
Taxonomic identification was performed in the field based on external characteristics using a taxonomic key, including external morphological measurements and characteristics, developed from Kingdon and Monadjem (Kingdon and Happold 2013; Monadjem et al. 2015). Morphological identification alone is unable to distinguish some small-mammal species within the study area at species level. Therefore, molecular identification was performed on whole blood, tissue or dried blood spots. Samples were stored at -20°C until processing, genomic DNA was extracted using QIAGEN DNAeasy kits as per the manufacturers instructions (Supplementary Material 2) (QIAGEN 2023). DNA extracts were amplified using platinum Taq polymerase (Invitrogen) and cytochrome B primers (Bangura et al. 2021). DNA amplification was assessed through gel electrophoreisis with successful amplification products undergoing Sanger sequencing. Attribution of obtained sequences to rodent species was through the BLAST programme comparing NCBI species records for rodent cytochrome B to our sample sequences (Altschul et al. 1990).
Description of rodent detection and species community structure
Adequacy of sampling effort was assessed using species accumulation curves produced for each village study site and each land use type within a village study site, suggesting sufficient effort to detect the expected rodent species within these categories. We constructed detection/non-detection histories for each grid cell and rodent species, assigning “1” when the species was detected and “0” otherwise. We describe species communities at multiple spatial scales. First, all species identified across all village sites and land use types. Second, all species identified within a village study site. Third, all species identified within a single land use type within a single village study site. We report species richness and Shannon diversity at these different spatial scales.
Estimating the effect of land use on species occurrence and richness
To adjust for differential probabilities of detection that may be driven by environmental conditions and trapping effort during the trapping study and between species, we use a Bayesian spatial latent factor multi-species occupancy model that incorporates residual species correlations, imperfect detection and spatial autocorrelation. Variable selection was informed by a pre-specified conceptual model. Models were defined using the sfMsPGOcc function in the spOccupancy package in the R statistical computing language (Doser et al. 2022).
Results
Rodent detection and species community structure
During the study period 530 individuals were detected from 30,364 trap-nights across the four village study sites (1.7% trap-success (TS)). The greatest number of individuals, highest species richness and Shannon diversity values were obtained in the agricultural landuse type, meanwhile, TS was greatest within village landuse settings (i.e., within and outside of permanent structures) (Table 1). The village study site of Seilama had the highest overall TS, species’ richness and Shannon diversity and unlike the three other village study sites had the greatest TS in agricultural landuse. Species richness in Seilama was twice that of the peri-urban village study site (Lambayama) with relatively high Shannon diversity across all landuse types. The sole peri-urban village study site (Lambayama) located within the expanding boundaries of Kenema city, had the lowest species’ richness and Shannon diversity with the majority of rodents detected within the village landuse type.
The most commonly detected rodent species across all village study sites and land use types was M. natalensis (N = 99, 18.7%), followed by Praomys spp. (N = 81, 15.2%), R. rattus (N = 71, 13.3%), M. musculus (N = 57, 10.7%) and Lophuromys sikapusi (N = 47, 8.8%). Mastomys natalensis and R. rattus were detected at all village study sites, although M. natalensis was not detected in forest landuse types (Figure 2.). Conversely, Hybomys planifrons and Gerbilliscus kempii were only detected in a single village study site, with H. planifrons detected in forest landuse and G. kempii in agricultural landuse types. The invasive rodent species M. musculus was only detected in the Lambayama and Seilama village study sites within village landuse types. The detection rate (the number of individuals detected per 1000 TN) varied by species, landuse type and village study site. The greatest rate of detection was for M. musculus in the Lambayama village study site, with the other commensal species M. natalensis and R. rattus having high detection rates across multiple village study sites within village landuse types. Praomys spp. had the highest detection rates in forest and agricultural landuse types.
Estimating the effect of land use on species occurrence and richness
We drew posterior samples from the most parsimonious Bayesian occupancy model incorporating spatial autocorrelation to estimate the probability of occurrence of a species within a trapping grid cell (see Supplementary Material 8. for model selection). Occurrence terms included landuse type, village study site and scaled terms for distance to the nearest permanent structure and elevation. Detection terms included scaled precipitation and trapping effort (TN) and the fraction of a full moon. We found three patterns of probability of occurrence (\(\psi\)) within a trapping grid cell for the seven included species (Figure 3.), marginal effects of the remaining parameters are shown in Supplementary Material 9. First, M. natalensis, R. rattus and M. musculus had greatest probabilities of occurrence in village landuse types with lower occurrence probabilities in agricultural and forest landuse types. Mastomys natalensis differed from the two commensal, invasive species (R rattus and M musculus) as their probability of occurrence in agricultural settings was generally high. Second, Praomys spp. had high probability of occurrence in forest landuse types with lower probabilities in agricultural and village landuse types. Finally, Crocidura spp, Lophuromys spp and Mus minutoides had their highest probabilities of occurrence in agricultural land use with lower probabilities of occurrence in forest and village landuse. No species showed high probability of occurrence across all land use types, consistent with species being adapted to distinct ecological niches.
The probability of occurrence within a trapping grid cell of some species within the same landuse types showed wide variability for some species. To further explore this we stratified village study sites by human population density into rural and peri-urban (rural <= 500 individuals per 1km2). The probability of occurrence of M natalensis was importantly different, with high probability of occurrence in both agricultural and village landuse settings in rural areas but substantially lower probability in peri-urban village study sites. The same pattern was observed for R. rattus. For the rodent species predicted to have lower probability of occurrence in village landuse settings, namely, Praomys spp, Lophuromys sikapusi and M. minutoides probabilities of occurrence were greater in all landuse types in rural areas compared to peri-urban areas. Shrew species were predicted to have similar probabilities of occurrence in rural and peri-urban areas. In contrast, M. musculus was predicted to have a low probability of occurrence in all landuse types in rural areas, with high values only for village landuse settings in peri-urban areas. The occurrence probabilities for the three commensal species (M. natalensis, R. rattus and M. musculus) suggest that competition may be reducing the occurrence of M. natalensis and R. rattus in the presence of M. musculus as in it’s absence these two species have high occurrence probabilities in village landuse types.
Co-occurrence of species
We hypothesised that the local spatial distribution of M. natalensis is regulated by biotic interactions with co-occurring species. Our tests for species correlations supported this for M. natalensis and other species’ of the rodent communities (Figure 5.). We observed that in landuse types where both M. natalensis and M. musculus co-occurred the presence of one species led to a reduction in the probability of occurrence at a grid cell level of the other with a statistically significant very weak negative correlation observed (Spearman’s \(\rho\) = -0.15, p < 0.001). This negative relationship was not observed between M. natalensis and the other commensal, invasive rodent R. rattus, where a strong positive correlation between probabilities of occurrences in both agricultural (\(\rho\) = 0.86, p < 0.001) and village (\(\rho\) = 0.84, p < 0.001) landuse settings was observed. Generally, within village landuse types, high probabilities for the presence of M. musculus was associated with lower probabilities for all other rodent species. This was not replicated for M. natalensis and R. rattus, which did not have a similar effect on the presence of the native rodent species Praomys spp and L. sikapusi. Within agricultural landuse types the probability for co-occurrence between rodent species were high. Generally, across all landuse types, the presence of shrew species’ had a negative correlation with the presence of rodent species’.
Data availability and draft manuscript
Data are available in the project’s GitHub repository. The most recent version of the draft currently being shared with co-authors is V3.
Additional discussion
An interactive report has been produced for collaborators, it may take some time to load.
I presented data from the first year of trapping at the 2022 Ecology and Evolution of Infectious Diseases conference, the slides are available and the talk is embedded below.
References
Citation
@online{simons2022,
author = {Simons, David},
title = {Land Use Gradients Drive Spatial Variation in {Lassa} Fever
Host Communities in {Eastern} {Sierra} {Leone.}},
date = {2022-11-02},
url = {https://www.dsimons.org/lassa/rodent_trapping.html},
langid = {en},
abstract = {The natal multimammate mouse (*Mastomys natalensis*) is
the primary reservoir species of the zoonotic infectious disease,
Lassa fever (*Lassa mammarenavirus*). This disease is endemic to
Sierra Leone with the highest incidence of human infection reported
from the Eastern Province. The spatial occurrence and abundance of
this rodent species is regulated by the human environment and biotic
interactions within small mammal communities, little is known about
these effects even in highly endemic areas of Lassa fever. We
conducted a rodent trapping study at four village study sites
between 2020-2023, comprising 40,152 trap nights to understand how
*M. natalensis* is distributed across a gradient of landuse types
and how this may be influenced by the broad small mammal community
structure. We conducted a Bayesian multiple species occupancy model,
accounting for imperfect detection, to test the hypothesis that *M.
natalensis* were more likely to occur within human dominated landuse
types. We found that *M. natalensis* occurrence increased from less
to more human dominated landscapes. We further found that this
effect was not replicated across scales as the probability of
occurrence in peri-urban settings was lower than in rural settings.
Interactions within the small mammal community appeared to moderate
the occurrence of *M. natalensis*, with the presence of *Mus
musculus*, but not *Rattus rattus* reducing the probability of
occurrence of *M. natalensis*. This finding may explain prior
observations of lower-than-expected human cases of Lassa Fever fever
from urban settings in endemic regions. Our findings highlight the
spatially heterogeneous distribution of rodent species across
landuse gradients with implications for the hazard of Lassa fever
outbreaks.}
}