Effects of plant diversity on biomass production and substrate nitrogen in a subsurface vertical flow constructed wetland

Most biodiversity experiments have been conducted in grassland ecosystems with nitrogen limitation, while little research has been conducted on relationships between plant biomass production, substrate nitrogen retention and plant diversity in wetlands with continuous nitrogen supply. We conducted a plant diversity experiment in a subsurface vertical flow constructed wetland for treating domestic wastewater in southeastern China. Plant aboveground biomass production ranged from 20 to 3121 g m^?2 yr^?1 across all plant communities. In general, plant biomass production was positively correlated with species richness (P = 0.001) and functional group richness (P = 0.001). Substrate nitrate concentration increased significantly with increasing plant species richness (P = 0.046), but not with functional group richness (P = 0.550). Furthermore, legumes did not affect biomass production (P = 0.255), retention of substrate nitrate (P = 0.280) and ammonium (P = 0.269). Compared to the most productive of the corresponding monocultures, transgressive overyielding of mixed plant communities did not occur in most polycultures. Because greater diversity of plant community led to higher biomass production and substrate nitrogen retention, thus we recommend that plant biodiversity should be incorporated in constructed wetlands to improve wastewater treatment efficiency.     

Taxonomic and functional diversity of stream invertebrates along an environmental stress gradient

Anthropogenic stress has been identified as main driver of freshwater biodiversity loss. Adverse effects on the biodiversity of freshwater organisms, such as macroinvertebrates, may propagate to associated ecosystem functions, such as organic matter breakdown (OMB). In this context, the functional diversity (FD) of communities has been suggested to be a more suitable predictor of changes in ecosystem functions than taxonomic diversity (TD). We investigated the response of TD and FD of invertebrate communities to an environmental stress gradient and the relation of both metrics to the rate of organic matter breakdown. For this, we sampled macroinvertebrates and determined OMB using leaf bags along an environmental stress gradient (i.e. changes in physicochemical and hydromorphological conditions) in 29 low-order streams. Taxonomic richness decreased with increasing environmental stress (r = −0.55) but was not related to OMB. Conversely, the Simpson diversity of communities was not associated with the gradient but correlated moderately (r = 0.41) with OMB. Of three functional diversity indices (functional richness, evenness and divergence), only functional richness correlated moderately with the stress gradient (r = −0.41) and any of the indices correlated with OMB. Nevertheless, functional metrics such as specific trait modalities and the total abundance of the dominant shredders correlated higher (r = 0.46 and 0.48) with OMB than the TD indices. Given a relatively small species pool in our study and methodical constraints such as the limited resolution of autecological information, the FD might perform better in other contexts and if focusing on response and effect traits for the stressor and ecosystem function under scrutiny, respectively.     

The reliability of a composite biodiversity indicator in predicting bird species richness at different spatial scales

Several biodiversity features can be linked to landscape heterogeneity, that, in turn, can be informative for management and conservation purposes. Usually, the more the landscape is complex the more the biodiversity increases. Biodiversity indicators can be a useful tool to assess biodiversity status, in function of landscape heterogeneity. In this study, we developed a biodiversity indicator, based on Shannon diversity index and built from distribution maps of protected species. With such an approach, we seek to evaluate the feasibility of using a combination of target species as a surrogate for assessing the status of the whole bird community. Our approach was spread over multiple spatial scales, to determine which was the most informative. We selected four species protected by European regulation and generated a presence-absence map from species distribution modelling. We, therefore, used the FRAGSTATS biodiversity metric to calculate Shannon index for the overlapped presence-absence maps, at two spatial scales (500 m and 1000 m). Then, the relationships with the whole community was assessed through generalised least square models, at the spatial scale of 4 ha, 9 ha and 25 ha. Results showed that the higher rate of variability of community was explained by the biodiversity indicator at 1000 m scale. Indeed, the more informative spatial scale for the whole bird community was 9 ha. In addition, a pattern emerged about the relationships between biodiversity indicator and community richness, that is worth of further research. Our study demonstrates that the usefulness of surrogate species for biodiversity and community assessment can become clear only at a certain spatial scales. Indeed, they can be highly predictive of the whole community, and highly informative for conservation planning. Moreover, their use can optimize biodiversity monitoring and conservation, focusing on a small number of noteworthy species.     

The distribution of vascular plant species of conservation concern in Ireland,and their coincidence with designated areas

Protected areas (that are usually designated) play an important role in the effort to halt on-going losses of biodiversity. However, areas outside of designated sites for protection can also hold important elements of biodiversity, and knowledge of their distribution is necessary to ensure effective conservation strategies. We collated and mapped vascular plant distribution data for species of conservation concern on the island of Ireland. For the first time in Ireland, we extracted 6078 distribution records of 176 species of conservation concern and mapped them at the tetrad (2 km × 2 km) scale. We examined the extent to which tetrads with records of species of conservation concern overlapped with designated areas (Natura 2000, Natural Heritage Areas, Areas of Special Scientific Interest). A conservative estimate suggests that many of these tetrads do not overlap with designated areas (in the range of 22–40% for available records). The coincidence of records of individual species with designated areas ranged from 0% to 100% (mean = 79%). The mapped distribution data for all vascular plant species offers guidance to where additional recording may be helpful in supporting conservation activities. The analysis of the distribution of species of conservation concern indicates the importance of both designated areas and the (non-designated) wider countryside for biodiversity conservation. In particular the presence of species of conservation concern in non-designated areas highlights the need for conservation measures outside of designated areas.     

A multivariate analysis integrating ecological,socioeconomic and physical characteristics to investigate urban forest cover and plant diversity in Beijing,China

Understanding the factors driving the variation in urban green space and plant communities in heterogeneous urban landscapes is crucial for maintaining biodiversity and important ecosystem services. In this study, we used a combination of field surveys, remote sensing, census data and spatial analysis to investigate the interrelationships among geographical and social-economic variables across 328 different urban structural units (USUs) and how they may influence the distributions of urban forest cover, plant diversity and abundance, within the central urban area of Beijing, China. We found that the urban green space coverage varied substantially across different types of USUs, with higher in agricultural lands (N = 15), parks (N = 46) and lowest in utility zones (N = 36). The amount of urban green space within USUs declines exponentially with the distance to urban center. Our study suggested that geographical, social and economic factors were closely related with each other in urban ecological systems, and have important impacts on urban forest coverage and abundance. The percentage of forest as well as high and low density urban areas were mainly responsible for variations in the data across all USUs and all land use/land cover types, and thus are important constituents and ecological indicators for understanding and modeling urban environment. Herb richness is more strongly correlated with tree and shrub density than with tree and shrub richness (r = −0.472, p < 0.05). However, other geographic and socioeconomic factors showed no significant relationships with urban plant diversity or abundance.     

Mapping biodiversity in three-dimensions challenges marine conservation strategies: The example of coralligenous assemblages in North-Western Mediterranean Sea

Multi-facet diversity indices have been increasingly widely used in conservation ecology but congruence analyses both on horizontal and vertical axes have not yet been explored. We investigated the vertical and horizontal distributions of α and β taxonomic (TD), functional (FD) and phylogenetic diversity (PD) in a three-dimensional structured ecosystem. We focused on the Mediterranean coralligenous assemblages which form complex structures both vertically and horizontally, and are considered as the most diverse and threatened communities of the Mediterranean Sea. Although comparable to tropical reef assemblages in terms of richness, biomass and production, coralligenous assemblages are less known and more rarely studied, in particular because of their location in deep waters. Our study covers the entire range of distribution of coralligenous habitats along the French Mediterranean coasts, representing the most complete database so far developed for this important ecosystem. To our knowledge, this is the first analysis of spatial diversity patterns of marine biodiversity on both horizontal and vertical scales.Our study revealed that taxonomic diversity differed from functional and phylogenetic diversity patterns at the station level, the latter two being strongly structured by depth, with shallower stations generally richer than deeper ones. Considering all stations, phylogenetic diversity was less congruent to taxonomic diversity (Pearson's correlation of r = 0.48) but more congruent to functional diversity (r = 0.69) than randomly expected. Similar congruence patterns were revealed for stations deeper than 50 m (r = 0.44 and r = 0.84, respectively) but no significantly different congruence level than randomly expected was revealed among diversity facets for more shallow stations. Mean functional α- and β-diversity were lower than phylogenetic diversity and even lower than taxonomic α- and β-diversity for both vertical and horizontal scales. Low FD and PD values at both α- and β-diversity indicated functional and phylogenetic clustering. Community dissimilarities (β-diversity) increased over depth especially in central and eastern part of the French Mediterranean littoral and in northern Corsica, indicating coralligenous vertical structure within these regions. Overall horizontal β-diversity was higher within the 50–70 m depth belts.We conclude that taxonomic diversity alone is inadequate as a basis for setting conservation goals for this ecosystem and additional information, at least on phylogenetic diversity, is needed to preserve the ecosystem functioning and coralligenous evolutionary history. Our results highlight the necessity of considering different depth belts as a basis for regional scale conservation efforts. Current conservation approaches, such as the existing marine protected areas, are insufficient in preserving coralligenous habitats. The use of multi-facet indices should be considered, focusing on preserving local diversity patterns and compositional dissimilarities, both vertically and horizontally.     

Landscape heterogeneity metrics as indicators of bird diversity: Determining the optimal spatial scales in different landscapes

Species distribution models are often used to study the biodiversity of ecosystems. The modelling process uses a number of parameters to predict others, such as the occurrence of determinate species, population size, habitat suitability or biodiversity. It is well known that the heterogeneity of landscapes can lead to changes in species’ abundance and biodiversity. However, landscape metrics depend on maps and spatial scales when it comes to undertaking a GIS analysis.We explored the goodness of fit of several models using the metrics of landscape heterogeneity and altitude as predictors of bird diversity in different landscapes and spatial scales. Two variables were used to describe biodiversity: bird richness and trophic level diversity, both of which were obtained from a breeding bird survey by means of point counts. The relationships between biodiversity and landscape metrics were compared using multiple linear regressions. All of the analyses were repeated for 14 different spatial scales and for cultivated, forest and grassland environments to determine the optimal spatial scale for each landscape typology.Our results revealed that the relationships between species’ richness and landscape heterogeneity using 1:10,000 land cover maps were strongest when working on a spatial scale up to a radius of 125–250 m around the sampled point (circa 4.9–19.6 ha). Furthermore, the correlation between measures of landscape heterogeneity and bird diversity was greater in grasslands than in cultivated or forested areas. The multi-spatial scale approach is useful for (a) assessing the accuracy of surrogates of bird diversity in different landscapes and (b) optimizing spatial model procedures for biodiversity mapping, mainly over extensive areas.     

A habitat quality indicator for common birds in Europe based on species distribution models

The EU 2020 Biodiversity Strategy requires the gathering of information on biodiversity to aid in monitoring progress towards its main targets. Common species are good proxies for the diversity and integrity of ecosystems, since they are key elements of the biomass, structure, functioning of ecosystems, and therefore of the supply of ecosystem services. In this sense, we aimed to develop a spatially-explicit indicator of habitat quality (HQI) at European level based on the species included in the European Common Bird Index, also grouped into their major habitat types (farmland and forest). Using species occurrences from the European Breeding Birds Atlas (at 50 km × 50 km) and the maximum entropy algorithm, we derived species distribution maps using refined occurrence data based on species ecology. This allowed us to cope with the limitations arising from modelling common and widespread species, obtaining habitat suitability maps for each species at finer spatial resolution (10 km × 10 km grid), which provided higher model accuracy. Analysis of the spatial patterns of local and relative species richness (defined as the ratio between species richness in a given location and the average richness in the regional context) for the common birds analysed demonstrated that the development of a HQI based on species richness needs to account for the regional species pool in order to make objective comparisons between regions. In this way, we proved that relative species richness compensated for the bias caused by the inherent heterogeneous patterns of the species distributions that was yielding larger local species richness in areas where most of the target species have the core of their distribution range. The method presented in this study provides a robust and innovative indicator of habitat quality which can be used to make comparisons between regions at the European scale, and therefore potentially applied to measure progress towards the EU Biodiversity Strategy targets. Finally, since species distribution models are based on breeding birds, the HQI can be also interpreted as a measure of the capacity of ecosystems to provide and maintain nursery/reproductive habitats for terrestrial species, a key maintenance and regulation ecosystem service.     

Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity?

Different approaches for the assessment of biodiversity by means of remote sensing were developed over the last decades. A new approach, based on the spectral variation hypothesis, proposes that the spectral heterogeneity of a remotely sensed image is correlated with landscape structure and complexity which also reflects habitat heterogeneity which itself is known to enhance species diversity. In this context, previous studies only applied species richness as a measure of diversity. The aim of this paper was to analyze the relationship of richness and abundance-based diversity measures with spectral variability and compare the results at two scales. At three different test sites in Central Namibia, measures of vascular plant diversity was sampled at two scales – 100 m² and 1000 m². Hyperspectral remote sensing data were collected for the study sites and spectral variability, was calculated at plot level. Ordinary least square regression was used to test the relationship between species richness and the abundance-based Shannon Index and spectral variability. We found that Shannon Index permanently achieved better results at all test sites especially at 1000 m², Even when all sites where pooled together, Shannon Index was still significantly related with spectral variability at 1000 m². We suggest incorporating abundance-based diversity measures in studies of relationships between ecological and spectral variability. The contribution made by the high spectral and spatial resolution of the hyperspectral sensor is discussed.     

High genetic diversity in fragmented Iris pumila L. populations in Ukrainian steppe enclaves

Habitat fragmentation can prevent gene flow between plant populations and lead to a loss of genetic diversity. However, such impact of fragmentation has not always been consistently confirmed by previous studies and the issue still needs further research. Particularly little is known about the impact of fragmentation on steppe plants. Steppe once covered vast, continuous areas, and nowadays is among the most fragmented biomes. In Ukraine, remnants of this habitat survived in large but few nature reserves and loess ravines as well as on kurgans (burial mounds of ancient nomadic people), which, despite their small size, are still numerous and scattered throughout the landscape.We studied the impact of fragmentation on the genetic diversity and structure of Iris pumila, a typical species of European steppes. Our main focus was to compare the genetic characteristics between kurgan populations (n = 8), and populations from larger refugia (n = 6). We assessed the genetic diversity of the studied populations with Universal Rice Primers.Our analyses revealed high genetic diversity across all investigated populations (mean He: 0.233; mean PPB: 58.57). However in kurgan populations genetic diversity was significantly higher than in larger refugia. Genetic diversity (He) was negatively correlated with population size. Most of the molecular variance (82%) was represented within populations, whereas genetic differentiation among populations was moderate (Φ_ST = 0.160), and low among refugia types (Φ_RT = 0.026).The maintenance of high genetic diversity despite two centuries of fragmentation may be related to the moderate disturbance occurring on kurgans, which enhances the sexual reproduction of the species. Moreover, we assume that species traits such as longevity and polyploidy might counterbalance genetic drift, while its self-incompatibility and presence of a soil seed bank allows for the replenishment of the gene pool. Overall, our results suggest that kurgans can protect genetic diversity of steppe species.     

Supplemental energy and protein increase use of sagebrush by sheep

The ability of sheep to consume big sagebrush (Artemisia tridentata Nutt.), a shrub that contains terpenes, may be improved with supplemental energy and protein needed for detoxification processes. We compared feeding behavior of supplemented and unsupplemented ewes grazing separately in three 0.5 ha plots of 40 m × 120 m during October 2001. Supplemented ewes were offered a choice of a high-energy (50% corn and 50% beet pulp—3.62 Mcal/kg DE and 9.5% CP) and a high-protein (85% alfalfa and 15% soybean meal—2.89 Mcal/kg DE and 15% CP) supplement for 15 min/day. Supplemented ewes consumed 492 g (S.E. = 24.3) of the high-energy supplement and 140 g (S.E. = 9.8) of the high-protein supplement. The incidence of feeding on sagebrush was recorded using scan sampling at 10-min intervals from 09:00 to 17:00 h every other day for 10 days. Incidence of feeding on sagebrush increased gradually for both treatments from 0.4% on day 1 to 28% on day 10 (P < 0.01), but supplemented ewes increased feeding frequency on sagebrush to nearly twice that of unsupplemented ewes by the end of the trial. Averaged throughout the trial, incidence of eating sagebrush was twice as high for supplemented compared to unsupplemented ewes (22% versus 11% of the total time feeding, P < 0.01). The results of this study show that supplemental macronutrients increase use of sagebrush by ewes. Thus, strategic supplementation during fall and winter may be a way to increase intake of sagebrush by sheep and enhance and maintain biodiversity in areas of the sagebrush steppe where sagebrush is deemed too abundant.     

Remote sensing improves prediction of tropical montane species diversity but performance differs among taxa

Texture information from passive remote sensing images provides surrogates for habitat structure, which is relevant for modeling biodiversity across space and time and for developing effective ecological indicators. However, the applicability of this information might differ among taxa and diversity measures. We compared the ability of indicators developed from texture analysis of remotely sensed images to predict species richness and species turnover of six taxa (trees, pyraloid moths, geometrid moths, arctiinae moths, ants, and birds) in a megadiverse Andean mountain rainforest ecosystem. Partial least-squares regression models were fitted using 12 predictors that characterize the habitat and included three topographical metrics derived from a high-resolution digital elevation model and nine texture metrics derived from very high-resolution multi-spectral orthophotos. We calculated image textures derived from mean, correlation, and entropy statistics within a relatively broad moving window (102 m × 102 m) of the near infra-red band and two vegetation indices. The model performances of species richness were taxon dependent, with the lowest predictive power for arctiinae moths (4%) and the highest for ants (78%). Topographical metrics sufficiently modeled species richness of pyraloid moths and ants, while models for species richness of trees, geometrid moths, and birds benefited from texture metrics. When more complexity was added to the model such as additional texture statistics calculated from a smaller moving window (18 m × 18 m), the predictive power for trees and birds increased significantly from 12% to 22% and 13% to 27%, respectively. Gradients of species turnover, assessed by non-metric two-dimensional scaling (NMDS) of Bray-Curtis dissimilarities, allowed the construction of models with far higher predictability than species richness across all taxonomic groups, with predictability for the first response variable of species turnover ranging from 64% (birds) to 98% (trees) of the explained change in species composition, and predictability for the second response variable of species turnover ranging from 33% (trees) to 74% (pyraloid moths). The two NMDS axes effectively separated compositional change along the elevational gradient, explained by a combination of elevation and texture metrics, from more subtle, local changes in habitat structure surrogated by varying combinations of texture metrics. The application of indicators arising from texture analysis of remote sensing images differed among taxa and diversity measures. However, these habitat indicators improved predictions of species diversity measures of most taxa, and therefore, we highly recommend their use in biodiversity research.     

Mapping tree species diversity of a tropical montane forest by unsupervised clustering of airborne imaging spectroscopy data

With the ongoing global biodiversity loss, approaches to measuring and monitoring biodiversity are necessary for effective conservation planning, especially in tropical forests. Remote sensing has much potential for biodiversity mapping, and high spatial resolution imaging spectroscopy (IS) allows for direct prediction of tree species diversity based on spectral reflectance. The objective of this study was to test an approach for mapping tree species alpha diversity that takes advantage of an unsupervised object-based clustering. Tree species diversity of a tropical montane forest in the Taita Hills, Kenya, was mapped based on spectral variation of high spatial resolution IS data.Airborne IS data and species data from 31 field plots were collected in the study area. Species diversity measures were obtained from the IS data by clustering spectrally similar image segments representing tree crowns. In order to do this, the image was segmented to objects that represented tree crowns. Three measures of species diversity were calculated based on the field data and on the clustering results, and the relationships were statistically analyzed.According to the results, the approach succeeded well in revealing tree species diversity patterns. Especially, tree species richness was well predicted (RMSE = 3 species; r² = 0.50) directly based on the clustering results. The optimal number of clusters was found to be close to the estimated number of tree species in the forest. Minimum tree size was an important determinant of the relationships, because only part of the trees are visible to the airborne sensor in the multi-layered closed canopy forest.In general, the object-based approach proved to be a viable alternative to a pixel-based clustering. The approach takes advantage of the capability of IS to detect spectral differences among tree crowns, but without the need for spectral training data, which is expensive to collect. With further development, the approach could be applied also for estimating beta diversity.     

Micro-geographic landscape features demarcate seedling genetic structure in the stream lily,Helmholtzia glaberrima

In this study, 169 stream lily (Helmholtzia glaberrima) seedlings from six micro-drainages were genotyped with AFLP markers to quantify the impact that topographic landscape features and altitude may have in shaping patterns of genetic diversity within individual populations. A global analysis of genetic diversity detected significant genetic differentiation among micro-drainages (F_ST = 0.22, P < 0.01). The observed genetic structure of sampled sites conformed to a hierarchical model of gene flow. Assignment tests also supported a hierarchical model of gene flow as only one dispersal event among the sampled micro-drainages was detected. This suggests that opportunities for seed dispersal in H. glaberrima are highly constrained by patterns of hydrographic networks even at a local scale. In contrast, altitude had little impact on partitioning of genetic diversity as no increase in genetic diversity was evident among individuals in the upper (0.18 ± 0.02), and lower (0.17 ± 0.02) areas of micro-drainages. Overall these results suggest that the influence of freshwater landscape features can vary widely the effect on the patterns of genetic diversity of seedlings in stream lily populations.     

Landscape-scale crop diversity interacts with local management to determine ground beetle diversity

Crop diversification and maintenance of semi-natural habitats (grasslands and field boundaries) are suggested to enhance farmland biodiversity, but the relative importance of these factors remains poorly known. We evaluated how crop diversity and availability of semi-natural grasslands at a landscape-scale interacted with local farming management (three management types from low to high intensity: ley < winter wheat < sugar beet) in their effect on ground beetle assemblages in southern Sweden. Ground beetle diversity increased with crop diversity either independently of local management (Simpson species diversity), or only in the less intensively managed habitats (rarefied species richness). While ground beetle diversity in leys tended to increase with field boundary length, no such relationship was observed in winter wheat or sugar beet fields. In contrast, the landscape proportions of leys and semi-natural grasslands did not affect ground beetle species richness and diversity. We conclude that (a) semi-natural grasslands and leys may not function as source habitats at a landscape-scale if they comprise a low proportion of the total land-use, while (b) increasing crop diversity is correlated to ground beetle richness and diversity in agricultural landscapes dominated by arable land. The beneficial effect of landscape-scale crop diversification on farmland biodiversity may depend on the general level of agricultural intensity of a region.     

Determination of priority nature conservation areas and human disturbances in the Yangtze River Basin,China

Because of limitation of manpower, funding, and land available in conservation, the problem of how to select essential regions to establish protection systems for biodiversity maintenance has been widely discussed. In an effort to address the problem, this study has aimed to select a set of priority areas and to determine their priority order by quantifying human disturbances for each area in the Yangtze River Basin (YRB). This basin covers 2.143 million km², or more than 20% of China's territory. The habitats of 627 indicator species were predicted as a proxy for biodiversity. A conservation planning tool, MARXAN, was used to determine the optimal set of planning units, and three different target scenarios were generated. In addition, under the assumption that if two areas have equal value for conservation, the one suffering more severe disturbance needs more urgent protection than the other, priority ranking analysis was carried out using a 6-12-1 BP artificial neural network. Then hierarchical cluster analysis was applied to the classifications of human disturbances to formulate more detailed conservation strategies. By integrating the degree of irreplaceability of each unit, expert experience, and mountain boundaries, 17 biodiversity priority areas containing 33,200 units over an area of 0.83 million km² were defined. These areas also protected 56% of 32 types of rare forest ecosystem and 76.4% of six types of rare grassland ecosystem on average. According to the evaluation of human impact, a priority order and five types of human disturbance areas were generated. Some protection gaps were also identified, such as the northern part of the Wuyi Mountains. Moreover, the determination of priority nature conservation areas on a large scale can be used to influence the building of a well-connected protection network in each individual area, so that effective genetic communication can occur between species or groups of species. Conservation decisions focusing on the dominant impact factors that are threatening biodiversity sustainability are required as well.     

Population densities,group size and biomass of ungulates in a lowland tropical rainforest forest of the eastern Himalayas

Large ungulate population monitoring is a crucial wildlife management tool as ungulates help in structuring and maintaining the large carnivore populations. Reliable data on population status of major ungulate prey species are still non-existent for most of the protected areas in the Indian part of the eastern Himalayan biodiversity hotspot. Twenty transects were monitored over a period of three years (2009–2011) totaling 600 km with an average length of 2 km. The estimated mean density of ungulates was 17.5 km⁻² with overall density of 48.7 km⁻². The wild pig Sus scrofa had the highest density (6.7 ± 1.2 km⁻²) among all the prey species followed by barking deer Muntiacus muntjak (3.9 ± 0.6 km⁻²), sambar Rusa unicolor (3.8 ± 0.5) and gaur Bos gaurus (3.5 ± 0.9 km⁻²). The estimated total ungulate biomass density was 2182.56 kg km⁻². This prey biomass can support up to 7.2 tigers per 100 km⁻². However, with two other sympatric carnivores sharing the same resources, the actual tiger numbers that can be supported will be lower. The estimated minor prey species was 31 km⁻² significantly 30.6% crop damages were reported by wild pig (p = 0.01) and 35.4% was elephant (p = 0.004). This data on ungulate densities and biomass will be crucial for carnivore conservation in this understudied globally significant biodiversity hotspot.     

Impacts of forest gaps on butterfly diversity in a Bornean peat-swamp forest

Forest degradation is leading to widespread negative impacts on biodiversity in South-east Asia. Tropical peat-swamp forests are one South-east Asian habitat in which insect communities, and the impacts of forest degradation on them, are poorly understood. To address this information deficit, we investigated the impacts of forest gaps on fruit-feeding butterflies in the Sabangau peat-swamp forest, Central Kalimantan, Indonesia. Fruit-baited traps were used to monitor butterflies for 3 months during the 2009 dry season. A network of 34 traps (n_gap = 17, n_shade = 17) was assembled in a grid covering a 35 ha area. A total of 445 capture events were recorded, comprising 384 individuals from 8 species and 2 additional species complexes classified to genera. On an inter-site scale, canopy traps captured higher species richness than understory traps; however, understory traps captured higher diversity within each site. Species richness was positively correlated with percent canopy cover and comparisons of diversity indices support these findings. Coupled with results demonstrating morphological differences in thorax volume and forewing length between species caught in closed-canopy traps vs. those in gaps, this indicates that forest degradation has a profound effect on butterfly communities in this habitat, with more generalist species being favored in disturbed conditions. Further studies are necessary to better understand the influences of macro-habitat quality and seasonal variations on butterfly diversity and community composition in South-east Asian peat-swamp forests.     

Agri-environment incentive payments and plant species richness under different management intensities in mountain meadows of Switzerland

We investigated whether agri-environmental incentive payments help to maintain biodiversity. We studied the effect of agricultural management intensity on vascular plant species richness and plant assemblages of mountain meadows in Switzerland. Other factors such as slope, altitude or accessibility (distance from farmyard) were also taken into account. Vegetation sampling was conducted at 69 sites representing five different management types, differing with respect to nutrient input and soil moisture: (i) dry extensive meadows; (ii) extensive meadows; (iii) dry low-intensive meadows; (iv) low-intensive meadows; (v) intensive meadows. There was a significant negative relationship between plant species richness and management intensity: The mean number of plant species per management type declined markedly when management intensity increased, although dry sites harboured slightly more species regardless of management intensity (dry extensive > dry low intensive > extensive > low intensive >> intensive meadows). Species richness was clearly affected by management intensity, but not so by slope, altitude or accessibility. There was a gradual shift in plant assemblages among management types with only intensive meadows differing from the other four types of differently managed meadows. We therefore found, in contrast to many studies done in the European lowlands, positive effects of incentive payments on plant species richness.     

Optimization of short-term storage of pikeperch semen: an applicable approach

Contamination of semen with urine and asynchronous maturation of males and females are main obstacles in artificial reproduction of pikeperch Sander lucioperca. The objective of this study was to overcome these obstacles using optimization of a procedure for short-term storage of pikeperch semen at 4 °C using two immobilizing media (IM): (a) IM1, 180 mM NaCl, 2.68 mM KCl, 1.36 mM CaCl₂ ⋅ 2H₂O and 2.38 mM NaHCO₃, 343 mOsm/kg; and (b) IM2, 200 mM NaCl, 2.68 mM KCl, 1.36 mM CaCl₂ ⋅ 2H₂O and 2.38 mM NaHCO₃, 381 mOsm/kg. Undiluted sperm was used as the control. At 6 h poststorage, there were no substantial changes in spermatozoa motility and velocity at 30 s postactivation in all groups. Over 48 h of storage, the highest spermatozoa motility and velocity were obtained in sperm diluted in IM2 compared to the other groups. IM2 could maintain a significantly higher ATP content of diluted sperm than IM1 and undiluted treatment for 2 days. Similarly, the highest values of eyeing and hatching rates were observed in sperm diluted in IM2 compared to sperm in the other studied groups. It can be concluded that the obtained result is a novel and applicable approach to maintain semen quality of pikeperch during short-term storage, suggesting IM2 as a promising medium for short-term storage. The present study also opens possibilities for ensuring a reliable source of semen as a convenient approach for increasing genetic diversity in hatcheries.