Genetic diversity of the Nubian ibex in Oman as revealed by mitochondrial DNA.

The Nubian ibex (Capra nubiana) is patchily distributed across parts of Africa and Arabia. In Oman, it is one of the few free-ranging wild mammals found in the central and southern regions. Its population is declining due to habitat degradation, human expansion, poaching and fragmentation. Here, we investigated the population's genetic diversity using mitochondrial DNA (D-loop 186 bp and cytochrome b 487 bp). We found that the Nubian ibex in the southern region of Oman was more diverse (D-loop HD; 0.838) compared with the central region (0.511) and gene flow between them was restricted. We compared the genetic profiles of wild Nubian ibex from Oman with captive ibex. A Bayesian phylogenetic tree showed that wild Nubian ibex form a distinct clade independent from captive animals. This divergence was supported by high mean distances (D-loop 0.126, cytochrome b 0.0528) and high F ST statistics (D-loop 0.725, cytochrome b 0.968). These results indicate that captive ibex are highly unlikely to have originated from the wild population in Oman and the considerable divergence suggests that the wild population in Oman should be treated as a distinct taxonomic unit. Further nuclear genetic work will be required to fully elucidate the degree of global taxonomic divergence of Nubian ibex populations.

Increasing intensities of Anisakis simplex third-stage larvae (L3) in Atlantic salmon of coastal waters of Scotland.

BACKGROUND: Red Vent Syndrome (RVS), a haemorrhagic inflammation of the vent region in Atlantic salmon, is associated with high abundance of Anisakis simplex (s.s.) third-stage larvae (L3) in the vent region. Despite evidence suggesting that increasing A. simplex (s.s.) intensity is a causative factor in RVS aetiology, the definitive cause remains unclear. METHODS: A total of 117 Atlantic salmon were sampled from commercial fisheries on the East, West, and North coasts of Scotland and examined for ascaridoid parasites. Genetic identification of a subsample of Anisakis larvae was performed using the internal transcribed spacer (ITS) region of ribosomal DNA. To assess the extent of differentiation of feeding grounds and dietary composition, stable isotope analysis of carbon and nitrogen was carried out on Atlantic salmon muscle tissue. RESULTS: In the present study, the obtained ITS rDNA sequences matched A. simplex (s.s.) sequences deposited in GenBank at 99-100%. Not all isolated larvae (n = 30,406) were genetically identified. Therefore, the morphotype found in this study is referred to as A. simplex (sensu lato). Anisakis simplex (s.l.) was the most prevalent (100%) nematode with the highest mean intensity (259.9 ± 197.3), in comparison to Hysterothylacium aduncum (66.7%, 6.4 ± 10.2) and Pseudoterranova decipiens (s.l.) (14.5%, 1.4 ± 0.6). The mean intensity of A. simplex (s.l.) represents a four-fold increase compared to published data (63.6 ± 31.9) from salmon captured in Scotland in 2009. Significant positive correlations between A. simplex (s.l.) larvae intensities from the body and the vent suggest that they play a role in the emergence of RVS. The lack of a significant variation in stable isotope ratios of Atlantic salmon indicates that diet or feeding ground are not driving regional differences in A. simplex (s.l.) intensities. CONCLUSIONS: This paper presents the most recent survey for ascaridoid parasites of wild Atlantic salmon from three coastal regions in Scotland. A significant rise in A. simplex (s.l.) intensity could potentially increase both natural mortality rates of Atlantic salmon and possible risks for salmon consumers due to the known zoonotic role of A. simplex (s.s.) and A. pegreffii within the A. simplex (s.l.) species complex.

From DNA to ecological performance: Effects of anthropogenic noise on a reef-building mussel.

Responses of marine invertebrates to anthropogenic noise are insufficiently known, impeding our understanding of ecosystemic impacts of noise and the development of mitigation strategies. We show that the blue mussel, Mytilus edulis, is negatively affected by ship-noise playbacks across different levels of biological organization. We take a novel mechanistic multi-method approach testing and employing established ecotoxicological techniques (i.e. Comet Assay and oxidative stress tests) in combination with behavioral and physiological biomarkers. We evidence, for the first time in marine species, noise-induced changes in DNA integrity (six-fold higher DNA single strand-breaks in haemocytes and gill epithelial cells) and oxidative stress (68% increased TBARS in gill cells). We further identify physiological and behavioral changes (12% reduced oxygen consumption, 60% increase in valve gape, 84% reduced filtration rate) in noise-exposed mussels. By employing established ecotoxicological techniques we highlight impacts not only on the organismal level, but also on ecological performance. When investigating species that produce little visually obvious responses to anthropogenic noise, the above mentioned endpoints are key to revealing sublethal effects of noise and thus enable a better understanding of how this emerging, but often overlooked stressor, affects animals without complex behaviors. Our integrated approach to noise research can be used as a model for other invertebrate species and faunal groups, and inform the development of effective methods for assessing and monitoring noise impacts. Given the observed negative effects, noise should be considered a potential confounding factor in studies involving other stressors.

The thin(ning) green line? Investigating changes in Kenya's seagrass coverage.

Knowledge of seagrass distribution is limited to a few well-studied sites and poor where resources are scant (e.g. Africa), hence global estimates of seagrass carbon storage are inaccurate. Here, we analysed freely available Sentinel-2 and Landsat imagery to quantify contemporary coverage and change in seagrass between 1986 and 2016 on Kenya's coast. Using field surveys and independent estimates of historical seagrass, we estimate total cover of Kenya's seagrass to be 317.1 ± 27.2 km2, following losses of 0.85% yr-1 since 1986. Losses increased from 0.29% yr-1 in 2000 to 1.59% yr-1 in 2016, releasing up to 2.17 Tg carbon since 1986. Anecdotal evidence suggests fishing pressure is an important cause of loss and is likely to intensify in the near future. If these results are representative for Africa, global estimates of seagrass extent and loss need reconsidering.

Urban ponds as an aquatic biodiversity resource in modified landscapes.

Urbanization is a global process contributing to the loss and fragmentation of natural habitats. Many studies have focused on the biological response of terrestrial taxa and habitats to urbanization. However, little is known regarding the consequences of urbanization on freshwater habitats, especially small lentic systems. In this study, we examined aquatic macro-invertebrate diversity (family and species level) and variation in community composition between 240 urban and 782 nonurban ponds distributed across the United Kingdom. Contrary to predictions, urban ponds supported similar numbers of invertebrate species and families compared to nonurban ponds. Similar gamma diversity was found between the two groups at both family and species taxonomic levels. The biological communities of urban ponds were markedly different to those of nonurban ponds, and the variability in urban pond community composition was greater than that in nonurban ponds, contrary to previous work showing homogenization of communities in urban areas. Positive spatial autocorrelation was recorded for urban and nonurban ponds at 0-50 km (distance between pond study sites) and negative spatial autocorrelation was observed at 100-150 km and was stronger in urban ponds in both cases. Ponds do not follow the same ecological patterns as terrestrial and lotic habitats (reduced taxonomic richness) in urban environments; in contrast, they support high taxonomic richness and contribute significantly to regional faunal diversity. Individual cities are complex structural mosaics which evolve over long periods of time and are managed in diverse ways. This facilitates the development of a wide range of environmental conditions and habitat niches in urban ponds which can promote greater heterogeneity between pond communities at larger scales. Ponds provide an opportunity for managers and environmental regulators to conserve and enhance freshwater biodiversity in urbanized landscapes whilst also facilitating key ecosystem services including storm water storage and water treatment.

Evaluating, predicting and mapping belowground carbon stores in Kenyan mangroves.

Despite covering only approximately 138 000 km2 , mangroves are globally important carbon sinks with carbon density values three to four times that of terrestrial forests. A key challenge in evaluating the carbon benefits from mangrove forest conservation is the lack of rigorous spatially resolved estimates of mangrove sediment carbon stocks; most mangrove carbon is stored belowground. Previous work has focused on detailed estimations of carbon stores over relatively small areas, which has obvious limitations in terms of generality and scope of application. Most studies have focused only on quantifying the top 1 m of belowground carbon (BGC). Carbon stored at depths beyond 1 m, and the effects of mangrove species, location and environmental context on these stores, are poorly studied. This study investigated these variables at two sites (Gazi and Vanga in the south of Kenya) and used the data to produce a country-specific BGC predictive model for Kenya and map BGC store estimates throughout Kenya at spatial scales relevant for climate change research, forest management and REDD+ (reduced emissions from deforestation and degradation). The results revealed that mangrove species was the most reliable predictor of BGC; Rhizophora muronata had the highest mean BGC with 1485.5 t C ha-1 . Applying the species-based predictive model to a base map of species distribution in Kenya for the year 2010 with a 2.5 m2 resolution produced an estimate of 69.41 Mt C [±9.15 95% confidence interval (C.I.)] for BGC in Kenyan mangroves. When applied to a 1992 mangrove distribution map, the BGC estimate was 75.65 Mt C (±12.21 95% C.I.), an 8.3% loss in BGC stores between 1992 and 2010 in Kenya. The country-level mangrove map provides a valuable tool for assessing carbon stocks and visualizing the distribution of BGC. Estimates at the 2.5 m2 resolution provide sufficient details for highlighting and prioritizing areas for mangrove conservation and restoration.

Applying Climate Compatible Development and economic valuation to coastal management: A case study of Kenya's mangrove forests.

Mangrove forests are under global pressure. Habitat destruction and degradation persist despite longstanding recognition of the important ecological functions of mangroves. Hence new approaches are needed to help stakeholders and policy-makers achieve sound management that is informed by the best science. Here we explore how the new policy concept of Climate Compatible Development (CCD) can be applied to achieve better outcomes. We use economic valuation approaches to combine socio-economic data, projections of forest cover based on quantitative risk mapping and storyline scenario building exercises to articulate the economic consequences of plausible alternative future scenarios for the mangrove forests of the South Kenya coast, as a case study of relevance to many other areas. Using data from 645 household surveys, 10 focus groups and 74 interviews conducted across four mangrove sites, and combining these with information on fish catches taken at three landing sites, a mangrove carbon trading project and published data allowed us to make a thorough (although still partial) economic valuation of the forests. This gave a current value of the South Coast mangroves of USD 6.5 million, or USD 1166 ha(-1), with 59% of this value on average derived from regulating services. Quantitative risk mapping, projecting recent trends over the next twenty years, suggests a 43% loss of forest cover over that time with 100% loss at the most vulnerable sites. Much of the forest lost between 1992 and 2012 has not been replaced by high value alternative land uses hence restoration of these areas is feasible and may not involve large opportunity costs. We invited thirty eight stakeholders to develop plausible storyline scenarios reflecting Business as Usual (BAU) and CCD - which emphasises sustainable forest conservation and management - in twenty years time, drawing on local and regional expert knowledge of relevant policy, social trends and cultures. Combining these scenarios with the quantitative projections and economic baseline allowed the modelling of likely value added and costs avoided under the CCD scenario. This suggests a net present value of more than US$20 million of adoption of CCD rather than BAU. This work adds to the economic evidence for mangrove conservation and helps to underline the importance of new real and emerging markets, such as for REDD + projects, in making this case for carbon-rich coastal habitats. It demonstrates a policy tool - CCD - that can be used to engage stakeholders and help to co-ordinate policy across different sectors towards mangrove conservation.

Making predictions of mangrove deforestation: a comparison of two methods in Kenya.

Deforestation of mangroves is of global concern given their importance for carbon storage, biogeochemical cycling and the provision of other ecosystem services, but the links between rates of loss and potential drivers or risk factors are rarely evaluated. Here, we identified key drivers of mangrove loss in Kenya and compared two different approaches to predicting risk. Risk factors tested included various possible predictors of anthropogenic deforestation, related to population, suitability for land use change and accessibility. Two approaches were taken to modelling risk; a quantitative statistical approach and a qualitative categorical ranking approach. A quantitative model linking rates of loss to risk factors was constructed based on generalized least squares regression and using mangrove loss data from 1992 to 2000. Population density, soil type and proximity to roads were the most important predictors. In order to validate this model it was used to generate a map of losses of Kenyan mangroves predicted to have occurred between 2000 and 2010. The qualitative categorical model was constructed using data from the same selection of variables, with the coincidence of different risk factors in particular mangrove areas used in an additive manner to create a relative risk index which was then mapped. Quantitative predictions of loss were significantly correlated with the actual loss of mangroves between 2000 and 2010 and the categorical risk index values were also highly correlated with the quantitative predictions. Hence, in this case the relatively simple categorical modelling approach was of similar predictive value to the more complex quantitative model of mangrove deforestation. The advantages and disadvantages of each approach are discussed, and the implications for mangroves are outlined.

Range limits and parasite prevalence in a freshwater snail.

Geographical range limits are thought to be set by species' physiological or ecological adaptation to abiotic factors, but the importance of biotic factors such as parasitism in determining range limits has not been well explored. In this study the prevalence of trematode parasitism in populations of a freshwater gastropod snail, Lymnaea stagnalis, increased sharply as this species approached its western UK range limit. The likelihood of trematode infection increased with snail size, but high prevalence at the range edge was not a result of interpopulation variation in snail size. Changes in population growth rates resulting from high rates of parasitism at the range edge could contribute to range limitation. The mechanism driving high rates of parasitism at the range edge is not clear, but changes in abiotic factors towards the range limit may influence snail life history and immune response to trematode infection, indirectly altering the prevalence of parasites in marginal host populations.

Selection of a minimum-boundary reserve network using integer programming.

In the conservation literature, heuristic procedures have been employed to incorporate spatial considerations in reserve network selection with the presumption that computationally convenient optimization models would be too difficult or impossible to formulate. This paper extends the standard set-covering formulation to incorporate a particular spatial selection criterion, namely reducing the reserve boundary to the extent possible, when selecting a reserve network that represents a set of target species at least once. Applying the model to a dataset on the occurrence of breeding birds in Berkshire, UK, demonstrated that the technique resulted in significant reductions in reserve boundary length relative to solutions produced by the standard set-covering formulation. Computational results showed that moderately large reserve network selection problems could be solved without issue. Alternative solutions may be produced to explore trade-offs between boundary length, number of sites required or alternative criteria.

Incorporating spatial criteria in optimum reserve network selection.

Considering the spatial location of sites that are to be selected for inclusion in a protected reserve network may be necessary to facilitate dispersal and long-term persistence of species in the selected sites. This paper presents an integer programming (IP) approach to the reserve network selection problem where spatial considerations based on intersite distances are taken into account when selecting reserve sites. The objective is to reduce the fragmentation of preserved sites and design a compact reserve network. Two IP formulations are developed which minimize the sum of pairwise distances and the maximum intersite distance between all sites in the reserve network, respectively, while representing all species under consideration. This approach is applied to a pond invertebrate dataset consisting of 131 sites containing 256 species in Oxfordshire, UK. The results show that significant reductions in reserve fragmentation can be achieved, compared with spatially unrestricted optimum reserve selection, at the expense of a small loss in reserve efficiency.