105 research outputs found
Balancing conservation with national development: a socio-economic case study of the alternatives to the Serengeti Road
Developing countries often have rich natural resources but poor infrastructure to capitalize on them, which leads to significant challenges in terms of balancing poverty alleviation with conservation. The underlying premise in development strategies is to increase the socio-economic welfare of the people while simultaneously ensuring environmental sustainability, however these objectives are often in direct conflict. National progress is dependent on developing infrastructure such as effective transportation networks, however roads can be ecologically catastrophic in terms of disrupting habitat connectivity and facilitating illegal activity. How can national development and conservation be balanced? The proposed Serengeti road epitomizes the conflict between poverty alleviation on one hand, and the conservation of a critical ecosystem on the other. We use the Serengeti as an exemplar case-study in which the relative economic and social benefits of a road can be assessed against the ecological impacts. Specifically, we compare three possible transportation routes and ask which route maximizes the socio-economic returns for the people while minimizing the ecological costs. The findings suggest that one route in particular that circumnavigates the Serengeti links the greatest number of small and medium sized entrepreneurial businesses to the largest labour force in the region. Furthermore, this route connects the most children to schools, provisions the greatest access to hospitals, and opens the most fertile crop and livestock production areas, and does not compromise the ecology and tourism revenue of the Serengeti. This route would improve Tanzaniaâs food security and self-reliance and would facilitate future infrastructure development which would not be possible if the road were to pass through the Serengeti. This case study provides a compelling example of how a detailed spatial analysis can balance the national objectives of poverty alleviation while maintaining ecological integrity
Human-wildlife conflict, benefit sharing and the survival of lions in pastoralist community-based conservancies
No abstract available
From single steps to mass migration: the problem of scale in the movement ecology of the Serengeti wildebeest
A central question in ecology is how to link processes that occur over
different scales. The daily interactions of individual organisms ultimately
determine community dynamics, population fluctuations and the functioning
of entire ecosystems. Observations of these multiscale ecological
processes are constrained by various technological, biological or logistical
issues, and there are often vast discrepancies between the scale at which
observation is possible and the scale of the question of interest. Animal
movement is characterized by processes that act over multiple spatial and
temporal scales. Second-by-second decisions accumulate to produce
annual movement patterns. Individuals influence, and are influenced by,
collective movement decisions, which then govern the spatial distribution
of populations and the connectivity of meta-populations. While the
field of movement ecology is experiencing unprecedented growth in the
availability of movement data, there remain challenges in integrating
observations with questions of ecological interest. In this article, we present
the major challenges of addressing these issues within the context of the
Serengeti wildebeest migration, a keystone ecological phenomena that
crosses multiple scales of space, time and biological complexity.
This article is part of the theme issue âCollective movement ecologyâ
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Assessing rotation-invariant feature classification for automated wildebeest population counts
Accurate and on-demand animal population counts are the holy grail for wildlife conservation organizations throughout the world because they enable fast and responsive adaptive management policies. While the collection of image data from camera traps, satellites, and manned or unmanned aircraft has advanced significantly, the detection and identification of animals within images remains a major bottleneck since counting is primarily conducted by dedicated enumerators or citizen scientists. Recent developments in the field of computer vision suggest a potential resolution to this issue through the use of rotation-invariant object descriptors combined with machine learning algorithms. Here we implement an algorithm to detect and count wildebeest from aerial images collected in the Serengeti National Park in 2009 as part of the biennial wildebeest count. We find that the per image error rates are greater than, but comparable to, two separate human counts. For the total count, the algorithm is more accurate than both manual counts, suggesting that human counters have a tendency to systematically over or under count images. While the accuracy of the algorithm is not yet at an acceptable level for fully automatic counts, our results show this method is a promising avenue for further research and we highlight specific areas where future research should focus in order to develop fast and accurate enumeration of aerial count data. If combined with a bespoke image collection protocol, this approach may yield a fully automated wildebeest count in the near future
Automated and repeated aerial observations of GPSâcollared animals using UAVs and openâsource electronics
Telemetry has enabled ecologists to link animal movement trajectories and environmental features at a fine spatiotemporal resolution; however, the effects of social interactions on individual choice within large mobile groups remain largely unknown. Estimating the effect of social interaction in the wild remains challenging because existing longâterm tracking tools such as GPS collars focus on the movements of a single individual and cannot observe the behavior of other individuals within the group. The progression of socially informed movement models requires measuring simultaneous trajectories of many individuals at once, as well as the instantaneous social cues to which individuals may be responding. The availability of lowâflying unmanned aerial vehicles (UAVs) and lowâcost openâsource electronics presents a promising opportunity to collect fineâscale data on social interactions in order to advance our understanding of collective behavior. Here, we present a tracking system that enables the repeated localization and observation of a collared individual and its near neighbors using nadir video footage collected from a commercial UAV. We make use of openâsource electronics combined with the UAV's inâbuilt functionality that allows it to follow a stream of GPS locations to create an automated system that can follow a specific individual without user control. We demonstrate the tracking systems' performance by studying the group movements of a herd of Exmoor ponies (Equus ferus caballus), and as a proof of concept, we examine the position of the focal individual (collared animal) in relation to the center of the video frame. We also collect information about the focal individual's nearest neighbors. The automated animal observation tool is effective at consistently keeping the focal individual close to the center of the video frame, offering a new dimension to existing remote telemetry tools. For instance, the repeated observation of the same individual in different physiological states, seasons, and demographic groups potentially opens new avenues in collective movement ecology research. By making our design, software, and firmware freely available, we aim to encourage continuous improvements to collective behavior research and to facilitate replicable approaches across other species and ecosystems
Competition, predation, and migration: individual choice patterns of Serengeti migrants captured by hierarchical models
Large-herbivore migrations occur across gradients of food quality or food abundance that are generally determined by underlying geographic patterns in rainfall, elevation, or latitude, in turn causing variation in the degree of interspecific competition and the exposure to predators. However, the role of top-down effects of predation as opposed to the bottom-up effects of competition for resources in shaping migrations is not well understood. We studied 30 GPS radio-collared wildebeest and zebra migrating seasonally in the Serengeti-Mara ecosystem to ask how predation and food availability differentially affect the individual movement patterns of these co-migrating species. A hierarchical analysis of movement trajectories (directions and distances) in relation to grass biomass, high-quality food patches, and predation risk show that wildebeest tend to move in response to food quality, with little attention to predation risk. In contrast, individual zebra movements reflect a balance between the risk of predation and the access to high-quality food of sufficient biomass. Our analysis shows how two migratory species move in response to different attributes of the same landscape. Counterintuitively and in contrast to most other animal movement studies, we find that both species move farther each day when resources are locally abundant than when they are scarce. During the wet season when the quality of grazing is at its peak, both wildebeest and zebra move the greatest distances and do not settle in localized areas to graze for extended periods. We propose that this punctuated movement in highquality patches is explained by density dependency, whereby large groups of competing individuals (up to 1.65 million grazers) rapidly deplete the localized grazing opportunities. These findings capture the roles of predation and competition in shaping animal migrations, which are often claimed but rarely measured
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Conservation and economic benefits of a road around the Serengeti
No abstract available
Fence management and time since pack formation influence African wild dog escapes from protected areas in South Africa
In human-dominated and highly fragmented landscapes, keeping wildlife within reserve boundaries is vital for conservation success. In South Africa, fences are a widely employed conservation management tool for protected areas and are successful in mitigating human-wildlife conflict. However, fences are permeable, and predators are able to cross through reserve fences. African wild dogs (Lycaon pictus) often leave fenced boundaries, resulting in high capture and translocation costs. Moreover, when wild dog packs (up to 30 individuals) leave fenced reserves they enter human-dominated landscapes where they face strong persecution and livestock predation incurs high costs. The factors driving packs to leave managed reserves are poorly understood, thus, to effectively manage wild dogs in fenced systems, it is important to understand why they leave reserve boundaries. There are several hypotheses as to why wild dogs cross through reserve fences, including inter- and intra-specific competition, social behaviour, management, prey density and environmental variability. Using a long-term dataset comprising 32 resident packs across five reserves, we investigated the relative strength of these hypotheses on the probability of wild dogs exiting a fenced reserve. During the 14-year study period, we recorded 154 exit events. We found that the interaction of fence integrity and time since pack formation were the primary factors affecting the probability of a pack leaving a reserve. When fence integrity was poor, escape probability decreased with pack age likely due to the exploratory behaviour of new packs. When fence integrity was average, escape probability increased with pack age likely due to the fitness benefits of holding larger and more exclusive territories as packs age. When fence integrity was good, the probability of a pack escaping was very low (only 1% occurrence). The implications of this research suggest that the primary management consideration for reducing wild dog escapes from fenced reserves should be maintaining adequate reserve-wide fence integrity, rather than focusing on social structure or drivers of inter- and intra-specific competition
Using sulfur stable isotope ratios (δ34S) for animal geolocation: estimating the delay mechanisms between diet ingestion and isotope incorporation in tail hair.
Rationale:
Metabolism and diet quality play an important role in determining delay mechanisms between an animal ingesting an element and depositing the associated isotope signal in tissue. While many isotope mixing models assume instantaneous reflection of diet in an animalâ tissue, this is rarely the case. Here we use data from wildebeest to measure the lag time between ingestion of 34S and its detection in tail hair.
Methods:
We use time-lagged regression analysis of δ34S data from GPS-collared blue wildebeest from the Serengeti ecosystem in combination with δ34S isoscape data to estimate the lag time between an animal ingesting and depositing 34S in tail hair.
Results:
The best fitting regression model of δ34S in tail hair and an individualâ position on the δ34S isoscape is generated assuming an average time delay of 78âdays between ingestion and detection in tail hair. This suggests that sulfur may undergo multiple metabolic transitions before being deposited in tissue.
Conclusion:
Our findings help to unravel the underlying complexities associated with sulfur metabolism and are broadly consistent with results from other species. These findings will help to inform research aiming to apply the variation of δ34S in inert biological material for geolocation or understanding dietary changes, especially for fast moving migratory ungulates such as wildebeest
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