Long-term ecological changes influence herbivore diversity and abundance inside a protected area in the Mara-Serengeti ecosystem

Rethinking livestock encroachment at a protected area boundary

The presence of livestock inside protected areas, or "livestock encroachment," is a global conservation concern because livestock is broadly thought to negatively affect wildlife. The Maasai Mara National Reserve (MMNR), Kenya, exemplifies this tension as livestock is believed to have resulted in the declining wildlife populations, contributing to the strict and sometimes violent exclusion measures targeting Maasai pastoralists. However, research embedded in the real-world setting that draws insights from the social-ecological contexts is lacking. In this study, we conducted 19 mo of ecological monitoring covering 60 sites in MMNR and found that cattle presence inside the reserve did not significantly impact most co-occurring wild herbivores at the current intensity. Using the Hierarchical Modeling of Species Communities and Gaussian copula graphic models, we showed that cattle had no direct associations-neither negative nor positive-with nearly all wild herbivores despite frequently sharing the same space. Moreover, we did not detect resource degradation correlated with cattle presence near the MMNR boundary. Given the colonial legacy and land use history of Mara, entering MMNR becomes the only viable option for many herders. These results corroborate the emerging perspective that the ecological impacts of extensively herded livestock on wildlife might be more nuanced than previously thought. To effectively balance the needs of people, livestock, and wildlife, the current rigid livestock exclusion measures need to be reassessed to holistically consider herbivore ecology, local land use history, and modern politics of protected area management.

A multispecies hierarchical model to integrate count and distance-sampling data

Integrated community models-an emerging framework in which multiple data sources for multiple species are analyzed simultaneously-offer opportunities to expand inferences beyond the single-species and single-data-source approaches common in ecology. We developed a novel integrated community model that combines distance sampling and single-visit count data; within the model, information is shared among data sources (via a joint likelihood) and species (via a random-effects structure) to estimate abundance patterns across a community. Parameters relating to abundance are shared between data sources, and the model can specify either shared or separate observation processes for each data source. Simulations demonstrated that the model provided unbiased estimates of abundance and detection parameters even when detection probabilities varied between the data types. The integrated community model also provided more accurate and more precise parameter estimates than alternative single-species and single-data-source models in many instances. We applied the model to a community of 11 herbivore species in the Masai Mara National Reserve, Kenya, and found considerable interspecific variation in response to local wildlife management practices: Five species showed higher abundances in a region with passive conservation enforcement (median across species: 4.5× higher), three species showed higher abundances in a region with active conservation enforcement (median: 3.9× higher), and the remaining three species showed no abundance differences between the two regions. Furthermore, the community average of abundance was slightly higher in the region with active conservation enforcement but not definitively so (posterior mean: higher by 0.20 animals; 95% credible interval: 1.43 fewer animals, 1.86 more animals). Our integrated community modeling framework has the potential to expand the scope of inference over space, time, and levels of biological organization, but practitioners should carefully evaluate whether model assumptions are met in their systems and whether data integration is valuable for their applications.

Taxonomic, Genomic, and Functional Variation in the Gut Microbiomes of Wild Spotted Hyenas Across 2 Decades of Study

The gut microbiome provides vital functions for mammalian hosts, yet research on its variability and function across adult life spans and multiple generations is limited in large mammalian carnivores. Here, we used 16S rRNA gene and metagenomic high-throughput sequencing to profile the bacterial taxonomic composition, genomic diversity, and metabolic function of fecal samples collected from 12 wild spotted hyenas (Crocuta crocuta) residing in the Masai Mara National Reserve, Kenya, over a 23-year period spanning three generations. The metagenomic data came from four of these hyenas and spanned two 2-year periods. With these data, we determined the extent to which host factors predicted variation in the gut microbiome and identified the core microbes present in the guts of hyenas. We also investigated novel genomic diversity in the mammalian gut by reporting the first metagenome-assembled genomes (MAGs) for hyenas. We found that gut microbiome taxonomic composition varied temporally, but despite this, a core set of 14 bacterial genera were identified. The strongest predictors of the microbiome were host identity and age, suggesting that hyenas possess individualized microbiomes and that these may change with age during adulthood. The gut microbiome functional profiles of the four adult hyenas were also individual specific and were associated with prey abundance, indicating that the functions of the gut microbiome vary with host diet. We recovered 149 high-quality MAGs from the hyenas' guts; some MAGs were classified as taxa previously reported for other carnivores, but many were novel and lacked species-level matches to genomes in existing reference databases. IMPORTANCE There is a gap in knowledge regarding the genomic diversity and variation of the gut microbiome across a host's life span and across multiple generations of hosts in wild mammals. Using two types of sequencing approaches, we found that although gut microbiomes were individualized and temporally variable among hyenas, they correlated similarly to large-scale changes in the ecological conditions experienced by their hosts. We also recovered 149 high-quality MAGs from the hyena gut, greatly expanding the microbial genome repertoire known for hyenas, carnivores, and wild mammals in general. Some MAGs came from genera abundant in the gastrointestinal tracts of canid species and other carnivores, but over 80% of MAGs were novel and from species not previously represented in genome databases. Collectively, our novel body of work illustrates the importance of surveying the gut microbiome of nonmodel wild hosts, using multiple sequencing methods and computational approaches and at distinct scales of analysis.

Place-Based Bias in Environmental Scholarship Derived from Social-Ecological Landscapes of Fear

Historical perspectives (e.g., moments of social, political, and economic significance) are increasingly relevant for developing insights into landscape change and ecosystem degradation. However, the question of how to incorporate historical events into ecological inquiry is still under development, owing to the evolving paradigm of transdisciplinary thinking between natural science and the humanities. In the present article, we call for the inclusion of negative human histories (e.g., evictions of communities and environmental injustices) as important factors that drive landscape change and shape research questions relevant to environmental conservation. We outline the detrimental effects of conservationists not addressing negative human histories by likening this social phenomenon to the ecological concept of landscapes of fear, which describes how not acknowledging these histories produces a landscape that constrains where and how research is conducted by scientists. Finally, we provide three positive recommendations for scholars or practitioners to address the manifestation of historic place-based bias in ecological research. What we call the social-ecological landscapes of fear provides a conceptual framework for more inclusive practices in ecology to increase the success of environmental and conservation goals.

Spatio-Temporal Dynamics and Sensitive Distance Identification of Light Pollution in Protected Areas Based on Muti-Source Data: A Case Study of Guangdong Province, China

Ecosystems in protected areas (PAs) are facing new challenges from light pollution. Timely assessment of light pollution in protected areas and exploration of its characteristics are positively valuable for biodiversity conservation and sustainable development. As the province with the largest number of nature reserves and the richest biodiversity in China, Guangdong's protected areas have faced more severe light pollution threats in recent years along with rapid urbanization. Hence, in this study, the temporal trends and spatial distribution of light pollution changes, the correlation between light pollution and human activities, and the sensitive distance induced by light pollution in PAs of Guangdong Province from 2000 to 2018 were analyzed based on nighttime light (NTL) remote sensing data, land-use data, and POI data. The results show that: (1) Overall, the light pollution within the PAs increased significantly in these years, with the mean value of NTL (MNTL) increasing from 8.04 to 15.21 nanoWatt/cm²/sr. The number of PAs affected by light pollution was 900 in 2018, accounting for 83% of the total. (2) From the perspective of spatial distribution, the PAs in the Pearl River Delta suffered from the highest intensity of light pollution. Specifically, the MNTL of PAs within the Pearl River Delta was 5.8 times and 2.8 times higher than that in northern Guangdong in 2000 and 2018, respectively. (3) There is a significant correlation between human activities and NTL in PAs within 100 km, and the most sensitive distance is within 40 km, especially the sensitivity within 20 km is much higher than that between 30-40 km. The findings of this study will provide a reference for the implementation of external lighting control and guidance measures to mitigate light pollution in protected areas in Guangdong Province.

Evidence of co-exposure with Brucella spp, Coxiella burnetii, and Rift Valley fever virus among various species of wildlife in Kenya

Background

Co-infection, especially with pathogens of dissimilar genetic makeup, may result in a more devastating impact on the host. Investigations on co-infection with neglected zoonotic pathogens in wildlife are necessary to inform appropriate prevention and control strategies to reduce disease burden in wildlife and the potential transmission of these pathogens between wildlife, livestock and humans. This study assessed co-exposure of various Kenyan wildflife species with Brucella spp, Coxiella burnetii and Rift Valley fever virus (RVFV).

Methodology

A total of 363 sera from 16 different wildlife species, most of them (92.6%) herbivores, were analysed by Enzyme-linked immunosorbent assay (ELISA) for IgG antibodies against Brucella spp, C. burnetii and RVFV. Further, 280 of these were tested by PCR to identify Brucella species.

Results

Of the 16 wildlife species tested, 15 (93.8%) were seropositive for at least one of the pathogens. Mean seropositivities were 18.9% (95% CI: 15.0–23.3) for RVFV, 13.7% (95% CI: 10.3–17.7) for Brucella spp and 9.1% (95% CI: 6.3–12.5) for C. burnetii. Buffaloes (n = 269) had higher seropositivity for Brucella spp. (17.1%, 95% CI: 13.0–21.7%) and RVFV (23.4%, 95% CI: 18.6–28.6%), while giraffes (n = 36) had the highest seropositivity for C. burnetii (44.4%, 95% CI: 27.9–61.9%). Importantly, 23 of the 93 (24.7%) animals positive for at least one pathogen were co-exposed, with 25.4% (18/71) of the positive buffaloes positive for brucellosis and RVFV. On molecular analysis, Brucella DNA was detected in 46 (19.5%, CI: 14.9–24.7) samples, with 4 (8.6%, 95% CI: 2.2–15.8) being identified as B. melitensis. The Fisher’s Exact test indicated that seropositivity varied significantly within the different animal families, with Brucella (p = 0.013), C. burnetii (p = <0.001) and RVFV (p = 0.007). Location was also significantly associated (p = <0.001) with Brucella spp. and C. burnetii seropositivities.

Conclusion

Of ~20% of Kenyan wildlife that are seropositive for Brucella spp, C. burnetii and RVFV, almost 25% indicate co-infections with the three pathogens, particularly with Brucella spp and RVFV.

Infection of an animal with more than one pathogen may result into a more devastating impact. Only few studies have investigated co-infection with multiple pathogens in wildlife, despite their key role as reservoirs of zoonotic diseases. Therefore, there is need for investigations on co-infection with neglected zoonotic pathogens in wildlife to inform prevention and control approaches and reduce disease impact in wildlife and potential transmission of these pathogens between wildlife, livestock, and humans. This study assessed co-exposure of various Kenyan wildlife species with three zoonotic pathogens, including Brucella spp, Coxiella burnetii and Rift Valley fever virus (RVFV). Results from this study revealed widespread, but varied exposure levels to the three individual pathogens within the several wildlife species. Likewise, the study also found the presence of co-exposure with the three pathogens. The findings from this study points to the need for establishment of surveillance and control programmes that target multiple pathogens in the wildlife populations to reduce the risk of transmission of infectious pathogens in wildlife and their zoonotic transmission.

Spatial and seasonal group size variation of wild mammalian herbivores in multiple use landscapes of the Ngorongoro Conservation Area, Tanzania

Group sizes of wild herbivores can be indicators of ecosystem health and proxies for individual and population fitness, particularly in areas where human activities have become increasingly common. We recorded 176 single- and multi-species groups of wild herbivores in human-dominated landscapes of the Ngorongoro Conservation Area (NCA) during dry and wet seasons. We analyzed how wild herbivore group sizes were affected by: (1) season, (2) distance to fully protected area (NCA crater) and to streams, (3) distance to human settlements, and (4) numbers of livestock. Group sizes were generally larger during the wet season than during the dry season and varied seasonally with distance to NCA crater, streams, and human settlements. During the wet season, larger groups were observed further away from the NCA crater whereas the opposite pattern was apparent during the dry season. Average wild herbivore group sizes increased by about three-fold with increasing distance from the streams during the dry season but were invariant to streams during the wet season. Furthermore, during the dry season, group sizes were larger close to settlements but varied little with distance to settlements during the wet season. While livestock presence did not directly affect wild herbivore group size, distance to settlements, streams and distance to the Ngorongoro crater in interaction with rainfall seasonality did. We conclude that the NCA crater functions as a key resource area for wild herbivores such as wildebeest (Connochaetes taurinus) and zebra (Equus quagga burchelli) during the dry season, highlighting the need for its full protection status in this Man and Biosphere reserve.

Reproduction Within a Hierarchical Society from a Female's Perspective

The reproductive biology of many female mammals is affected by their social environment and their interactions with conspecifics. In mammalian societies structured by linear dominance hierarchies, such as that of the spotted hyena (Crocuta crocuta), a female's social rank can have profound effects on both her reproductive success and her longevity. In this species, social rank determines priority of access to food, which is the resource limiting reproduction. Due largely to rank-related variation in access to food, reproduction from the perspective of a female spotted hyena can only be understood in the context of her position in the social hierarchy. In this review, we examine the effects of rank on the various phases of reproduction, from mating to weaning. Summed over many individual reproductive lifespans, the effect of rank at these different reproductive phases leads to dramatic rank-related variation in fitness among females and their lineages. Finally, we ask why females reproduce socially despite these apparent costs of group living to low-ranking females. Gregariousness enhances the fitness of females regardless of their positions in the social hierarchy, and females attempting to survive and reproduce without clanmates lose all their offspring. The positive effects of gregariousness appear to result from having female allies, both kin and non-kin, who cooperate to advertise and defend a shared territory, acquire, and defend food resources, maintain the status quo, and occasionally also to rise in social rank.

Host phylogeny and host ecology structure the mammalian gut microbiota at different taxonomic scales

The gut microbiota is critical for host function. Among mammals, host phylogenetic relatedness and diet are strong drivers of gut microbiota structure, but one factor may be more influential than the other. Here, we used 16S rRNA gene sequencing to determine the relative contributions of host phylogeny and host diet in structuring the gut microbiotas of 11 herbivore species from 5 families living sympatrically in southwest Kenya. Herbivore species were classified as grazers, browsers, or mixed-feeders and dietary data (% C4 grasses in diet) were compiled from previously published sources. We found that herbivore gut microbiotas were highly species-specific, and that host taxonomy accounted for more variation in the gut microbiota (30%) than did host dietary guild (10%) or sample month (8%). Overall, similarity in the gut microbiota increased with host phylogenetic relatedness (r = 0.74) across the 11 species of herbivores, but among 7 closely related Bovid species, dietary %C4 grass values more strongly predicted gut microbiota structure (r = 0.64). Additionally, within bovids, host dietary guild explained more of the variation in the gut microbiota (17%) than did host species (12%). Lastly, while we found that the gut microbiotas of herbivores residing in southwest Kenya converge with those of distinct populations of conspecifics from central Kenya, fine-scale differences in the abundances of bacterial amplicon sequence variants (ASVs) between individuals from the two regions were also observed. Overall, our findings suggest that host phylogeny and taxonomy strongly structure the gut microbiota across broad host taxonomic scales, but these gut microbiotas can be further modified by host ecology (i.e., diet, geography), especially among closely related host species.

Partnerships and Stakeholder Participation in the Management of National Parks: Experiences of the Gonarezhou National Park in Zimbabwe

National parks play an important role in maintaining natural ecosystems which are important sources of income and livelihood sustenance. Most national parks in Southern Africa are managed by their states. Before 2007, Gonarezhou National Park was managed by the Zimbabwe Parks Management and Wildlife Authority, which faced challenges in maintaining its biodiversity, community relations and infrastructure. However, in 2017 the Frankfurt Zoological Society and the Zimbabwe Parks Management and Wildlife Authority formed an innovative partnership under the Gonarezhou Conservation Trust (GCT). This study examines the relationship between GCT management, Gonarezhou National Park stakeholders and communities as well as the impact of the relationship on biodiversity and ecosystems. The study also highlights challenges faced and lessons learned in managing Gonarezhou as a protected area. To obtain the information, key informant interviews, Landsat satellite imagery, secondary data from previous studies and government sources were utilized. The results indicate that the concerted efforts of the Gonarezhou Conservation Trust to manage the park are starting to bear fruit in improving biodiversity conservation, ecosystem management and engaging communities. However, challenges such as governance obstacles, problematic stakeholder management, maintaining trust in community relations, ensuring sustainability, managing the adverse impacts of climate change and human-wildlife conflicts must still be navigated to ensure the park’s sustainable management. Notwithstanding challenges, we argue that a partnership arrangement such as the Gonarezhou Conservation Trust is a desirable model that can be applied in national parks in Zimbabwe and Africa for better biodiversity management and tourism.

Integrating distance sampling and presence-only data to estimate species abundance

Integrated models combine multiple data types within a unified analysis to estimate species abundance and covariate effects. By sharing biological parameters, integrated models improve the accuracy and precision of estimates compared to separate analyses of individual data sets. We developed an integrated point process model to combine presence-only and distance sampling data for estimation of spatially explicit abundance patterns. Simulations across a range of parameter values demonstrate that our model can recover estimates of biological covariates, but parameter accuracy and precision varied with the quantity of each data type. We applied our model to a case study of black-backed jackals in the Masai Mara National Reserve, Kenya, to examine effects of spatially varying covariates on jackal abundance patterns. The model revealed that jackals were positively affected by anthropogenic disturbance on the landscape, with highest abundance estimated along the Reserve border near human activity. We found minimal effects of landscape cover, lion density, and distance to water source, suggesting that human use of the Reserve may be the biggest driver of jackal abundance patterns. Our integrated model expands the scope of ecological inference by taking advantage of widely available presence-only data, while simultaneously leveraging richer, but typically limited, distance sampling data.

Local Community Perceptions on Landscape Change, Ecosystem Services, Climate Change, and Livelihoods in Gonarezhou National Park, Zimbabwe

Understanding humanity’s relationship with nature is crucial for the well-being and sustainable development of mankind in the face of global environmental change. Communities depend on landscapes for survival and landscapes determine if sustainable development is to be achieved. The links between landscapes, ecosystem services, livelihoods, and climate change are often complex, misunderstood, and barely studied in rural areas of Africa, where communities live side-by-side with conservation areas. Our study surveyed the perception of the nexus of landscape change, climate change, ecosystem services, and livelihoods in Gonarezhou, a national park in southeastern Zimbabwe. We also used Landsat satellite imagery to map the landscape change over 20 years to validate and to correlate with the survey data. The survey results indicated that people relied on rainfed agriculture as a means of livelihood, but droughts as a result of climate change force communities to engage in other means of livelihoods such as small-scale poaching of small game such as impala and harvesting of natural resources such as edible shrubs. Crops and livestock as provisional ecosystem services have been negatively affected by climate change and landscape change. Landsat data confirmed that there was a negative transformation of the landscape as a result of agriculture, growth in settlements, and large herbivores. However, there was also a positive landscape transformation resulting from the conservation efforts by the Gonarezhou Conservation Trust (GCT). Cultural services about education and awareness of the environment and provisional services such as wild fruits are booming. Challenges such as soil erosion, human–wildlife conflict, and minimal community benefits from conservation efforts hindered sustainable development in the study area. While changes in landscape, climate, livelihoods, and ecosystem services happened at a local scale, the underlying drivers such as politics and the economy were also identified as drivers of landscape change.

Mapping Kenyan Grassland Heights Across Large Spatial Scales with Combined Optical and Radar Satellite Imagery

Grassland monitoring can be challenging because it is time-consuming and expensive to measure grass condition at large spatial scales. Remote sensing offers a time- and cost-effective method for mapping and monitoring grassland condition at both large spatial extents and fine temporal resolutions. Combinations of remotely sensed optical and radar imagery are particularly promising because together they can measure differences in moisture, structure, and reflectance among land cover types. We combined multi-date radar (PALSAR-2 and Sentinel-1) and optical (Sentinel-2) imagery with field data and visual interpretation of aerial imagery to classify land cover in the Masai Mara National Reserve, Kenya using machine learning (Random Forests). This study area comprises a diverse array of land cover types and changes over time due to seasonal changes in precipitation, seasonal movements of large herds of resident and migratory ungulates, fires, and livestock grazing. We classified twelve land cover types with user’s and producer’s accuracies ranging from 66%–100% and an overall accuracy of 86%. These methods were able to distinguish among short, medium, and tall grass cover at user’s accuracies of 83%, 82%, and 85%, respectively. By yielding a highly accurate, fine-resolution map that distinguishes among grasses of different heights, this work not only outlines a viable method for future grassland mapping efforts but also will help inform local management decisions and research in the Masai Mara National Reserve.

Pastoralist activities affect the movement patterns of a large African carnivore, the spotted hyena (Crocuta crocuta)

Populations of large carnivores are declining in many parts of the world due to anthropogenic activity. Some species of large carnivores, however, are able to coexist with people by altering their behavior. Altered behaviors may be challenging to identify in large carnivores because these animals are typically cryptic, nocturnal, live at low densities, and because changes in their behavior may be subtle or emerge slowly over many years. We studied the effects of livestock presence on the movements of one large carnivore, the spotted hyena (Crocuta crocuta). We fit 22 adult female spotted hyenas with GPS collars to quantify their movements in areas with and without livestock or herders present, in and around a protected area in southwestern Kenya. We investigated anthropogenic, social, and ecological effects on the speed of movement, distances traveled, long-distance movements, and extraterritorial excursions by spotted hyenas. Hyenas living primarily within the protected area, but in the presence of livestock and herders, moved faster, traveled over longer distances, and were more likely to be within their territories than did conspecifics living in areas without livestock and herders. Hyenas of low social rank were more likely than hyenas of high social rank to engage in long-distance travel events, and these were more likely to occur when prey were scarce. The movement patterns of this large African carnivore indicate a flexibility that may allow them to persist in landscapes that are becoming increasingly defined by people.