Serengeti Ecosystem

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Plant Species Composition and Distribution in Relation to Land Use Patterns in Serengeti Ecosystem Tanzania

Plant Species Composition and Distribution in Relation to Land Use Patterns in Serengeti Ecosystem Tanzania

Although the unprotected areas were vulnerable to anthropogenic disturbance, they had high species richness and this portrayed that species composition changed along a coenocline as pointed out by Okland (1990). Ex- ploitation and other forms of disturbance may result into habitat heterogeneity that provides a nurse effect for the establishment of diverse plant types and hence high species diversity and richness in unprotected areas. The sample sites from protected area were positioned between sites from the unprotected areas (Figure 3). Some plant species present in the protected area were absent in unprotected areas and some species were common among sample clusters from both types of management regimes within Serengeti ecosystem. Whilst the wood- lands of the unprotected area were represented by Olea europaea, Acacia tortilis, Acokanthera oppositifolia, Acacia robusta and Euclea divinorum especially in Ololosokwani and Kibeyo study sites, the savanna wood- lands, grasslands with patches of woody stands or scattered trees were common in the protected area. The Mdito site is part of unprotected area with a mixture of livestock grazing and crop cultivation; however it was largely dominated by the undisturbed Commiphora woodland. An extensive woodland cover with a pristine condition from an anthropogenic disturbance point of view indicates the importance of ecosystem services (pollinators) rendered by the woodland to the crop yield. Also, the pristine condition may be because of a great support on biodiversity conservation rendered by the local community causing little disturbance regardless of being part of the unprotected areas of Serengeti ecosystem. Because of large part being relatively undisturbed, the agricultural activities in these areas were regarded as an encroachment into the pristine habitat of the unprotected areas. Li- mited anthropogenic activities in the aforementioned site favoured the performance of plant communities with diverse life forms, including the lichens which are bio-indicator species of a pristine or less disturbed habitat conditions. The conserved trees in this area have become potential hosts of epiphytic orchids i.e. Acampe pa- chyglosa and Aerangis kirkii that have survived because of lower anthropogenic activities in Ololosokwani and Mdito than in the more degraded parts (Plate 1). From an ecological point of view, this part of Serengeti eco- system contains plant communities that are at the reaction stage of succession towards climax status.
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Isolation and Potential for Transmission of Mycobacterium bovis at Human–livestock–wildlife Interface of the Serengeti Ecosystem, Northern Tanzania

Isolation and Potential for Transmission of Mycobacterium bovis at Human–livestock–wildlife Interface of the Serengeti Ecosystem, Northern Tanzania

introduction and maintenance of infection in a wild animal population have been identified in South Africa (Renwick et al., 2007) and the rest of the world (Rhyan and Spraker, 2010; de Garine-Wichatitsky et al., 2013). They include species diversity (maintenance or spillover hosts), social behaviour of wildlife hosts, wildlife densities (threshold population/community densities), movements of animal populations (possible introduction through migratory indi- viduals or confinement), and the absence or inefficiency of wildlife bTB surveillance and control (de Garine-Wicha- titsky et al., 2013). All these risk factors may characterize the Serengeti ecosystem. However, it can be argued that the lack of bTB surveillance and control does not only apply to wildlife species, but also to livestock. The Serengeti ecosys- tem is characterized by high indirect contacts between live- stock and wildlife (Katale et al., 2013), which favours disease transmission between species. However, strain diversity of M. bovis and its potential dynamics of dissemi- nation across species in the ecosystem have not been fully explored. Moreover, the husbandry practices, proximity to wildlife and tradition customs of consuming raw meat/milk by the pastoralist community in the ecosystem, epidemio- logical studies are needed to explore the disease dynamics in the ecosystem and bTB infection in animals and ulti- mately also humans (Katale et al., 2013).
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Range expansion of the globally Vulnerable Karamoja apalis Apalis karamojae in the Serengeti ecosystem

Range expansion of the globally Vulnerable Karamoja apalis Apalis karamojae in the Serengeti ecosystem

Vegetation coverage of the Serengeti National Park has been mapped by Herlocker (1974) from aerial photographs with extensive ground-truthing. Both A. drepanolobium and A. seyal are widespread in the Serengeti, where they occur on impeded drainage soils that become inundated during the rainy season. This type of silty soil has not changed in area over the past decades, although the density of trees on it has changed, as described below. The combined area of the two vegetation types, based on Geographic Information System analysis, comprises 13% of the savanna woodland, covering c. 1,000 km 2 . Within the Serengeti ecosystem the density of A. drepanolobium has been measured since the 1960s in two ways. First, present density (2006) was measured at permanent bird survey sites across the Serengeti Ecosystem using Point Centre Quarter methods (Krebs, 2001). Similar methods were used for other sites in stands of A. drepanolobium in 1999 (K. Metzger unpublished) and 2005 (P. Shaw unpublished). Density values for 1986 are given by Stronach (1988). Second, a number of locations have been monitored using oblique photographs repeated at intervals from 1965 up to the present time (Sinclair et al., 2007). On these photographs the same area was demarcated and the number of trees counted, and a relative density was calculated, with the present time set at unity. These relative densities were transformed to actual densities from the measurements taken in 2006.
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Mathematical Model for the Serengeti Ecosystem under Normal Climate Conditions

Mathematical Model for the Serengeti Ecosystem under Normal Climate Conditions

Ngana et al. (2014) did a research on the modeling of the population dynamics and the Great Migration of the Serengeti ecosystem. They used a prey-predator model and the migration equation to get the ODE’s of the Grass, Herbivores and the Lions and Crocodiles, and did a simulation to get the population dynamics, without impact of climate change on the population dynamics. The result was that the Herbivores population was increasing, as well as the

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Genetic diversity of Mycobacterium tuberculosis isolated from tuberculosis patients in the Serengeti ecosystem in Tanzania

Genetic diversity of Mycobacterium tuberculosis isolated from tuberculosis patients in the Serengeti ecosystem in Tanzania

This study was part of a larger cross-sectional survey that was evaluating tuberculosis (TB) infection in humans, livestock and wildlife in the Serengeti ecosystem in Tanzania. The study aimed at evaluating the genetic diversity of Mycobacterium tuberculosis isolates from TB patients attending health facilities in the Serengeti ecosystem. DNA was extracted from 214 sputum cultures obtained from consecutively enrolled newly diagnosed untreated TB patients aged 18 years. Spacer oligonucleotide typing (spoligotyping) and Mycobacterium Interspersed Repetitive Units and Variable Number Tandem Repeat (MIRU-VNTR) were used to genotype M. tuberculosis to establish the circulating lineages. Of the214 M. tuberculosis isolates genotyped, 55 (25.7%) belonged to the Central Asian (CAS) family, 52 (24.3%) were T family (an ill-de fi ned family), 38 (17.8%) belonged to the Latin American Mediterranean (LAM) family, 25 (11.7%) to the East-African Indian (EAI) family, 25 (11.7%) comprised of different unassigned (‘Serengeti’) strain families, while 8 (3.7%) belonged to the Beijing family. A minority group that included Haarlem, X, U and S altogether accounted for 11 (5.2%) of all genotypes. MIRU-VNTR typing produced diverse patterns within and between families indicative of unlinked transmission chains. We conclude that, in the Serengeti ecosystem only a few successful families predominate namely CAS, T, LAM and EAI families. Other types found in lower prevalence are Beijing, Haarlem, X, S and MANU. The Haarlem, EAI_Somalia, LAM3 and S/convergent and X2 subfamilies found in this study were not reported in previous studies in Tanzania.
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Optimal Control of a Threatened Wildebeest Lion Prey Predator System in the Serengeti Ecosystem

Optimal Control of a Threatened Wildebeest Lion Prey Predator System in the Serengeti Ecosystem

Few studies on optimal control of Prey-Predator system such as those by Chakraborty et al., [1], Kar and Ghosh [14] have determined various optimal control strategies. In particular, Kar and Ghosh [14] controlled al- ternative food to predator to an exploited prey-predator system. However, none of these studies have considered the aspect of drought, poaching and retaliatory killing as threats to be controlled for survival of prey-predator system particularly wildebeest and lions in the Serengeti ecosystem. Therefore, this study intends to apply op- timal control theory to maximize Wildebeest-Lion prey-predator population in the Serengeti Ecosytem under threat of drought, poaching and retaliatory killings and ensuring the cost of applying these controls is minimum.
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Species diversity of non tuberculous mycobacteria isolated from humans, livestock and wildlife in the Serengeti ecosystem, Tanzania

Species diversity of non tuberculous mycobacteria isolated from humans, livestock and wildlife in the Serengeti ecosystem, Tanzania

This study has shown that, 16 species of NTM were isolated from humans, indigenous cattle and wildlife, in the Serengeti ecosystem, of which the majority were M. intracellulare, M. lentiflavum and M. fortuitum. Other NTM species including M. cholenae-abscessus group, M. simiae, M. neoaurum, M. nonchromogenicum, M. spaghni, M. terrae, M. confluentis, M. genavense, M. gilvum, M. gordonae, M. intermedium, M. poriferae and M. thermore- sistibile were isolated at a lower rate, ranging between 5.5% and 1.8%. Comparison of the NTM species iso- lated in this study indicate that most of them have pre- viously been found in humans, animals, or the environment in Ethiopia, Kenya, Uganda, South Africa and Zambia (Table 2). In the present study, given the nature of sample acquisition for both cattle and wildlife specimens, isolation of M. gordonae and M. terrae complex as environmental contaminants [22] might occur. Thus there is unjustifiable potential for specimens’ environmental contamination which might obscure our findings. M. genavense, M. poriferae and M. spaghni are not common or have not previously been isolated in East Africa (Table 2). In con- trast to our study where all NTM species were isolated from sputum samples and animals tissues. Previous studies found M .simiae, M. fortuitum, M. gordonae, M. intermedium, M. intracellulare, M. nonchromogenicum and M. terrae in soil and water (Table 2). The correlation of NTM between soil on one hand and animals on the other hand indicates that NTM are readily exchanged between animals and environments [23]. However, in our study no any environmental sample was taken to correlate between NTM species found in animals and environments. M. intracellulare, which is a member of Mycobacterium avium complex (MAC) was the most frequently isolated species, consistent with a report from study of NTM in Uganda, South Africa and Australia [24,25]. However, this finding differs from other studies in Kenya, South Africa and Uganda where M. mucogenicum, M. terrae and M. fortuitum were the most frequently isolated species re- spectively [14,16]. The high prevalence of M. intracellulare is of concern in this setting, given a high HIV prevalence and the ability of M. intracellulare to cause pulmonary and extrapulmonary TB in such individuals [26,27] such as has been reported in Kenya [28]. In the current study, M. intracellulare species were isolated from human, cattle and wildlife.
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Sero prevalence and spatial distribution of Rift Valley fever infection among agro pastoral and pastoral communities during Interepidemic period in the Serengeti ecosystem, northern Tanzania

Sero prevalence and spatial distribution of Rift Valley fever infection among agro pastoral and pastoral communities during Interepidemic period in the Serengeti ecosystem, northern Tanzania

Despite the severity of the RVF, little is known regarding prevalence and exposure status of humans in different ecosystems in Tanzania. Previous studies conducted in Kilombero valley in eastern Tanzania showed high trans- mission of the disease in livestock, with sero-prevalence of 5.5% among animals born after last epidemic of 2007 [9]. Correspondingly, current study in the Serengeti ecosys- tem, which is the sister study to this, has found recent ex- posure among domestic animals and wildlife. Cattle and sheep recorded IgM prevalence of 5.7% while buffaloes re- corded 3.1% of IgM prevalence (Nyarobi unpublished). RVFV-RNA was extracted from 2.7% of mosquitoes pools studied in the ecosystem (Nyarobi unpublished). This has raised need to understand the current disease burden in humans and predict the possibility of future outbreak. Therefore, this study was done to determine the exposure status of RVFV, its spatial distribution and factors associ- ated with exposure to RVFV among pastoral and agro-pastoral communities of the Serengeti ecosystem.
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Mathematical Model for the Serengeti Ecosystem under Weather Variations

Mathematical Model for the Serengeti Ecosystem under Weather Variations

In this paper, we consider the dynamics of the Serengeti Ecosystem under consistent rainfall including the impact of the Great Migration. We formulate a Food Chain Model consisting five Ordinary Differential Equations for the interaction between, Vegetation; Herbivores: Wildebeests, Zebra and Thompson’s Gazelles; and the Carnivores: the Lions, the Cheetahs and the Crocodiles. We analyze the model using the estimated initial values of the variables values. By simulation, we get estimated values of the parameters and then deduce the Population Dynamics of the five species. The Vegetation biomass is the food for the Herbivores. The Herbivores are preyed on by the Carnivores: the Lions, the Cheetahs and the Crocodiles.
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Mathematical Model for the Population Dynamics of the Serengeti Ecosystem

Mathematical Model for the Population Dynamics of the Serengeti Ecosystem

increased by a factor of five, and remained at approximately 1.3 million with slight variations [14, 3, 12]. Reconstruction of 100 years of the vegetation dynamics in the Serengeti ecosystem gives an insight of what might happen if the wildebeest population is reduced to about 200,000, as it is believed to have been following the Rinderpest epidemic in the early 1900s [4].

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Spillover of Peste des Petits Ruminants Virus from Domestic to Wild Ruminants in the Serengeti Ecosystem, Tanzania

Spillover of Peste des Petits Ruminants Virus from Domestic to Wild Ruminants in the Serengeti Ecosystem, Tanzania

Absence of clinical evidence in wildlife does not con- stitute evidence of absence of the disease. Antibodies were present in many wildlife we sampled, and the genome was present in 1 Grant’s gazelle in the Esieki plains, where on- going outbreaks were confirmed in domestic sheep. Clini- cal infections caused by PPRV have been recorded often in captive gazelle (Gazella species) (15) in United Arab Emir- ates. Currently, no evidence of wildlife disease exists, but cases or carcasses might go unnoticed because of deaths from other causes and rapid removal of dead animals by scavengers. These findings confirm endemic PPRV in the Greater Serengeti Ecosystem and suggest that free-ranging wildlife are susceptible to infection and can act as sentinels of livestock disease but do not appear to be maintaining infection across their populations.
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Community-Based Conservation, Income Governance, and Poverty Alleviation in Tanzania: The Case of Serengeti Ecosystem

Community-Based Conservation, Income Governance, and Poverty Alleviation in Tanzania: The Case of Serengeti Ecosystem

Because of this there is a lack of appreciation of conservation by the majority of communities in the Serengeti ecosystem. Kaltenborn, Nyahongo, Kideghesho, & Haaland, (2008) indicated that local people in the Serengeti perceived the existing wildlife protected areas as a burden, due to competition for land and other resources, damage to property, and risk to life. Consequently, there have been an increasing num- ber of poaching incidents in all the national parks and other conservation areas in Tanzania. Significant costs are incurred by TANAPA in terms of cracking down on poaching activities. For instance, SENAPA alone spends about US$1.2 million per annum on antipoaching initiatives, which is about 24% of its budget per annum (Wakibara; personal communication, 2010). At Selous Game Reserve, half of the income generated from tourist hunting is spent on antipoaching (around US$1.8 mil- lion per annum (Baldur, Kibonde, & Siege, 2003). Although Hilborn et. al. (2006) showed that expanded budgets and an increased number of antipoaching patrols since the mid-1980s have greatly reduced poaching and allowed populations of buffalo, elephants, and rhinoceros to rebuild in SENAPA, the question is whether this is the best way of solving the problem by utilizing such huge sums of money in a poor coun- try like Tanzania.
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Modelling the Migratory Population Dynamics of the Serengeti Ecosystem

Modelling the Migratory Population Dynamics of the Serengeti Ecosystem

The Great Migration, is one of the “Seven New Wonders of the World”. There is nowhere else in the world where there is such a movement of animals as immense as the wildebeests (Connochaetes taurinus), zebras (Equus burchelli) and Thomson’s gazelle (Gazella thomsoni), migrating from Serengeti National Park in Tanzania to Masai Mara National Reserve in Kenya and back. Over two million animals migrate from the Serengeti to the greener pastures of the Maasai Mara. The lions, hyenas, leopards, cheetahs, crocodiles and lesser predators await the annual coming of the migration for predation.
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Mapping of Mycobacterium tuberculosis Complex Genetic Diversity Profiles in Tanzania and Other African Countries

Mapping of Mycobacterium tuberculosis Complex Genetic Diversity Profiles in Tanzania and Other African Countries

Human tuberculosis remains a global leading devastating, often severe and contagious chronic respiratory disease. People with immune-suppression are more susceptible to tuberculosis (TB). With the Global Tuberculosis Report indicating 13% of new TB cases being HIV-positive worldwide and up to 78% of TB cases among people living with HIV worldwide found in Afri- can region [1], the disease impact becomes further magnified especially in developing coun- tries. In Tanzania various studies have been conducted using both conventional and non- conventional means to characterize the disease and its spread. Some of these studies focus on epidemiology [2–5], diagnostics [6–9], treatment and control [2, 10–12], strain molecular char- acterization [13 – 16], TB-HIV co-infections [17 – 20], challenges and resource limitation [21], and more recently, TB cross-species transmission at the human-animal interface [22–24]. In the recent study by our group in Serengeti ecosystem [15], a strain unassigned to neither of known spoligotypes, but resembling the CAS strain family was identified and tentatively named ‘ Serengeti strain ’ . Although various TB studies have been conducted in Tanzania so far, none of them has given detailed information on all the major phylogenetic lineages of tubercle bacilli and their distribution. In addition, none of the studies compared Tanzanian strain pat- terns with those prevailing in neighbouring countries and sub-regions to underline differences relating to the presence of specific lineages. All this information is important in establishing phylogenetical relatedness of the strains causing disease within and between countries as well as establishing transmission links between individuals. This study aimed to specifically describe the genotypic diversity of Mycobacterium tuberculosis complex (MTBC) in Tanzania, as well as neighbouring and other countries in Africa (having spoligotyping data deposited in SITVIT database), with reference to their global distribution. The study also assessed the association between HIV serological status and M . tuberculosis lineages for people who apart from TB had HIV. To better highlight region-specificity or similarity and get a larger view on MTBC distri- bution in Tanzania, Mycobacterium tuberculosis complex (MTBC) genotypic diversity was characterized and compared to diverse genotypes available in other African countries. Basing on genotyping information, this paper also tentatively proposes a sublineage which seems to be phylogeographically specific for Tanzania.
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An ecosystem approach to understanding and managing within-host parasite community dynamics

An ecosystem approach to understanding and managing within-host parasite community dynamics

A key point when considering the host as an ecosystem is to recognize that individual hosts are not homogenous environments in which parasites, resources, and immune components are fully mixed. Free-living ecosystems are typically structured into connected ‘patches’, comprising subsets of potentially strongly-interacting species (e.g., via resource competition or predator–prey interactions) that are linked with other patches by flows of energy, nutrients, or species (e.g., salmon migration linking sea and freshwa- ter stream habitats [27]; conversion of nutrients as in above- and below-ground plant–soil communities [28]). In the same way, the internal environment of an individual host will be structured into ‘compartments’ (e.g., organs, tissues, cells) such that parasites typically occupy different habitats within the host (e.g., the gut, blood, liver, or skin), but with some potential for movement of nutrients, energy, and ‘species’ (parasites, but also cell types and molecules that use or convert within-host energy and nutrients, including immune components) between compartments [6,29]). Within these compartments, species abundances and dynamics are affected by both ‘bottom-up’ interactions due to shared resources or space, and by ‘top-down’ inter- actions due to a shared immune response (Figure 1) [30]. Recognizing the compartmentalization of the host is Glossary
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Quantifying and valuing the ecosystem services of pastoral soils under a dairy use : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Ecological Economics at Massey University, Palmerston North, New Ze

Quantifying and valuing the ecosystem services of pastoral soils under a dairy use : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Ecological Economics at Massey University, Palmerston North, New Zealand

Ecosystem services exist because they meet a human need. This is the very essence of the anthropocentric concept of ecosystem services. However, few studies in the ecosystem services literature go as far as specifying how and what human needs are potentially or actually fulfilled by ecosystem services. One very notable exception is the Millennium Ecosystem Assessment (2005), which, although not explicitly acknowledging it, shows how ecosystem services contribute to human well-being by using a framework that resembles Maslow’s “Hierarchy of needs” (1943). Maslow’s (1943) classic study of the so-called “Hierarchy of needs” is the foundation study in this domain. This hierarchy has five levels: the first four levels are deficiency needs: physiological needs, safety and security needs, social (love and belonging) needs, and esteem (psychological) needs; the last level is self-actualisation needs. Deficiency needs must be met first, the individual prioritises them; the higher needs can be considered only when the lower needs are met. Maslow’s framework has been widely criticised (Wahba and Bridwell, 1976) on a number of grounds. Probably the most persistent critique is that Maslow’s framework is based on a hierarchal structure for which there is a lack of strong evidence. For example, a starving artist may be self-actualised while his/her physiological needs (e.g. food) may be inadequately fulfilled. In this context, Chilean economist Manfred Max-Neef’s “matrix of needs” (1992) is perhaps a better reflection of reality. In this framework many needs are complementary and different needs can be fulfilled simultaneously. Max-Neef classifies fundamental “axiological categories” – subsistence, protection, affection, understanding, participation, idleness, creation, identity, and freedom – that are split into four “existential categories” (being, having, doing and interacting), thereby forming a matrix of needs. Ecological economist Herman Daly somewhat bravely presents an even broader contextualisation of human needs, in terms of his “end-means” spectrum (Daly and Farley, 2003). This spectrum links ultimate ends (final cause and “God”) to intermediate ends (health, safety, comfort) to ultimate means (material cause, low entropy matter energy). However, whatever philosophical construct of human needs is selected, it is inevitably a poor representation of the complexity, subtlety or ever-changing nature of human needs.
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Medicinal and commercial uses of ostrich products in Tanzania

Medicinal and commercial uses of ostrich products in Tanzania

At the onset of incubation, some of the eggs, which are believed to belong to minor females, are ejected from the nest [26, 38, 39], but ostriches also sometimes randomly lay eggs as ‘singletons’ on the ground away from the nests when disturbed [40]. These ejected and singleton eggs are never incubated but left unattended and ultimately decay or are predated. Therefore there is a good chance for communities residing near the protected area to seek permits for collecting such eggs and capitalize on the opportunity to establish ostrich farms and thus reduce pressure on the wild population. However, control by the park authority should be in place so that no just any eggs (nests) are taken. In addition, it is farming, which could help to improve the post hatching survival following the differential preda- tion on males [41] coupled with nest and brood preda- tion [40].. The villages bordering Serengeti National Park (SNP) and Ngorongoro Conservation Area in northern Tanzania are at an advantage in developing small-scale farms to boost their economy by taking advantage of these deserted eggs.
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Innovative Business Model of the Cluster as an Ecosystem

Innovative Business Model of the Cluster as an Ecosystem

In conclusion, it can be noted that the parameters of the cluster as an innovation ecosystem vary from ecosystem to ecosystem, but in any of the metrics are based on measuring and measuring performance functioning in several aspects: 1) participants – financial analysis and organizational characteristics, roles and functions in a cluster, business models economic entities, their strategic and tactical behavior, capabilities and potential development companies, input and output material flows, production capacity and output, sales volumes and sales, the history of the development of successful firms; 2) structure – “types” of companies and their dynamics, information value channels and values business platforms, ways interactions and forms of cooperation, institutional aspects of economic practice; 3) competitiveness in comparison with other ecosystems, including by product, services, innovations, technologies, personnel, brands; 4) business activity in terms of interaction, network formation, transactionality, trade turnover between partners; 5) strategic vision in terms of opportunities, risk, and development. If you summarize the parameters of the cluster as innovation ecosystem and metrics to measure effectiveness then can be traced four basic principles of construction and organization this kind of systems: complexity, self- organization, coevolution, and adaptation. Generally, these principles are properties of any complex socio-economic systems and are the result interdisciplinary synthesis of the following scientific directions: systems theory, synergetic and technology. It may be noted that the theory of clusters also appeals to them. It means, that between ecosystems and clusters more common than differences. The formation and functioning of clusters represent the stage of development of the innovation ecosystem, and the cluster itself is a transitional form ecosystem in terms of evolution economic space. As they accumulate critical mass and capital cluster becoming a full-fledged business ecosystem.
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Worldwide Occurrence of Feline Hemoplasma Infections in Wild Felid Species

Worldwide Occurrence of Feline Hemoplasma Infections in Wild Felid Species

Hemoplasma infections were significantly associated with wild felid species, and concurrent infections with several he- moplasmas were most frequently detected in the Serengeti lions. Different susceptibilities of animals of different wild felid species to hemoplasma infections cannot be excluded, but the dissimilar living environment and health status of the wild felids under investigation seem a more likely explanation for this association. Correspondingly, we also found a lower prev- alence of feline hemoplasma infections in captive than in free- ranging animals. The hemoplasma prevalence in wild felids kept at Sa ˜o Paulo Zoo in Brazil was comparable to the prev- alence reported in a study investigating 54 captive nondomestic cats in the United States (11). In contrast, free-ranging animals may be more exposed to bloodsucking arthropods and exhibit higher fighting activity than nondomestic cats in a zoo envi- ronment; thus, they might experience a higher infection risk with agents such as hemoparasites or retroviruses. It has been shown that free-ranging felids often exhibit multiple infections with different pathogens (7, 13, 17); in particular all except two African lions included in the present study had CDV and feline immunodeficiency virus infections, and many of the animals showed distinct lymphopenia (22, 23). Additionally, Hepato- zoon as well as Babesia and Theileria/Cytauxoon-like organisms were identified by microscopic evaluation on blood smears of the Serengeti lions (data not shown). Concurrent infections, especially those with immunosuppressive agents, such as CDV, retroviruses, and Theileria spp., could have influenced the fre- quency of hemoplasma infections. This has also been suspected for domestic cats (10, 12) and would be in agreement with the finding that hemotropic mycoplasmas were more common in FeLV-infected than FeLV-uninfected European wildcats in the present study.
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Solutions for sustaining natural capital and ecosystem services

Solutions for sustaining natural capital and ecosystem services

Proper ecosystem service classification and valuation are needed to evaluate trade-offs (Koschke et al., 2012), taking into account scale peculiarities, synergies and non-accountable ser- vices (Busch et al., 2012). Spatially explicit assessments of multiple ecosystem service supply and demand areas provide appropriate information for trade-off evaluation (Syrbe and Walz, 2012; Bastian et al., 2012; Nedkov and Burkhard, 2012; Burkhard et al., 2012). Monitoring schemes especially dedicated to ecosystem services are suggested as a solution for the lack of data, which often hampers appropriate assessments (Burkhard et al., 2012). Benefit transfer and expert evaluation are further possible ways of acquiring data for land cover-related ecosystem service assessments (Koschke et al., 2012). Scolozzi et al. (2012) derived a “surrogate market” for ecosystem services based on a collection of economic values from a literature review, in combination with a Delphi expert survey on ecosystem services to produce spatial ecosystem service rep- resentations and assess changes of “potential economic ecosystem service values”.
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