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Successful conservation efforts have led to recent increases of large mammals such as European bison Bison bonasus, moose Alces alces and grey wolf Canis lupus and their return to former habitats in central Europe.
While embraced by some, the recovery of these species is a controversial topic and holds potential for human-wildlife conflicts.
Involving the public has been suggested to be an effective method for monitoring wildlife and mitigating associated conflicts.
To assess two interrelated prerequisites for engaging people in Citizen Science (CS)-knowledge of returning species and respondents' readiness to participate in CS activities for monitoring and managing these species-we conducted a survey (questionnaire) in two wildlife parks located in different states of Germany.
Based on 472 complete questionnaires, we developed generalized linear models to understand how sociodemographic variables and exposure to the species affected visitors' knowledge of each species, and to investigate if sociodemographic variables and knowledge influenced the likelihood of visitors to participate in CS activities.
Almost all visitors were aware of the returning wolf population, while knowledge and awareness about bison and moose were significantly lower.
Knowledge of the two herbivores differed geographically (higher knowledge of moose in the north-eastern state), possibly indicating a positive association between exposure to the species and knowledge.
However, models generally performed poorly in predicting knowledge about wildlife, suggesting that such specific knowledge is insufficiently explained by sociodemographic variables. Our model, which explained stated willingness in CS indicated that younger participants and those with higher knowledge scores in the survey were more willing to engage in CS activities.
Overall, our analyses highlight how exposure to large mammals, knowledge about wildlife and human demographics are interrelated-insights that are helpful for effectively recruiting citizen scientists for wildlife conservation.
Read the free Plain Language Summary for this article on the Journal blog.
Fatty acids are widely used to study trophic interactions in food web assemblages. Generally, it is assumed that there is a very small modification of fatty acids from one trophic step to another, making them suitable as trophic biomarkers. However, recent literature provides evidence that many fishes possess genes encoding enzymes with a role in bioconversion, thus the capability for bioconversion might be more widespread than previously assumed. Nonetheless, empirical evidence for biosynthesis occurring in natural populations remains scarce. In this study, we investigated different feeding types of perch (Perca fluviatilis) that are specialized on specific resources with different levels of highly unsaturated fatty acids (HUFAs), and analyzed the change between HUFA proportions in perch muscle tissue compared to their resources. Perch showed matching levels to their resources for EPA, but ARA and especially DHA were accumulated. Compound-specific stable isotope analyses helped us to identify the origin of HUFA carbon. Our results suggest that perch obtain a substantial amount of DHA via bioconversion when feeding on DHA-poor benthic resources. Thus, our data indicate the capability of bioconversion of HUFAs in a natural freshwater fish population.
Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors.
Supergenes are nonrecombining genomic regions ensuring the coinheritance of multiple, coadapted genes. Despite the importance of supergenes in adaptation, little is known on how they originate. A classic example of supergene is the S locus controlling heterostyly, a floral heteromorphism occurring in 28 angiosperm families. In Primula, heterostyly is characterized by the cooccurrence of two complementary, self-incompatible floral morphs and is controlled by five genes clustered in the hemizygous, ca. 300-kb S locus. Here, we present the first chromosome-scale genome assembly of any heterostylous species, that of Primula veris (cowslip). By leveraging the high contiguity of the P. veris assembly and comparative genomic analyses, we demonstrated that the S-locus evolved via multiple, asynchronous gene duplications and independent gene translocations. Furthermore, we discovered a new whole-genome duplication in Ericales that is specific to the Primula lineage. We also propose a mechanism for the origin of S-locus hemizygosity via nonhomologous recombination involving the newly discovered two pairs of CFB genes flanking the S locus. Finally, we detected only weak signatures of degeneration in the S locus, as predicted for hemizygous supergenes. The present study provides a useful resource for future research addressing key questions on the evolution of supergenes in general and the S locus in particular: How do supergenes arise? What is the role of genome architecture in the evolution of complex adaptations? Is the molecular architecture of heterostyly supergenes across angiosperms similar to that of Primula?
Ancient genome provides insights into the history of Eurasian lynx in Iberia and Western Europe
(2022)
The Eurasian lynx (Lynx lynx) is one of the most widely distributed felids in the world. However, most of its populations started to decline a few millennia ago. Historical declines have been especially severe in Europe, and particularly in Western Europe, from where the species disappeared in the last few centuries. Here, we analyze the genome of an Eurasian lynx inhabiting the Iberian Peninsula 2500 ya, to gain insights into the phylogeographic position and genetic status of this extinct population. Also, we contextualize previous ancient data in the light of new phylogeographic studies of the species. Our results suggest that the Iberian population is part of an extinct European lineage closely related to the current Carpathian-Baltic lineages. Also, this sample holds the lowest diversity reported for the species so far, and similar to that of the highly endangered Iberian lynx. A combination of historical factors, such as a founder effect while colonizing the peninsula, together with intensified human impacts during the Holocene in the Cantabrian strip, could have led to a genetic impoverishment of the population and precipitated its extinction. Mitogenomic lineages distribution in space and time support the long-term coexistence of several lineages of Eurasian lynx in Western Europe with fluctuating ranges. While mitochondrial sequences related to the lineages currently found in Balkans and Caucasus were predominant during the Pleistocene, those more closely related to the lineage currently distributed in Central Europe prevailed during the Holocene. The use of ancient genomics has proven to be a useful tool to understand the biogeographic pattern of the Eurasian lynx in the past.
Many animals form aggregations with individuals of the same species (single-species aggregations, SSA). Less frequently, individuals may also aggregate with individuals of other species (mixed-species aggregations, MSA). Although the benefits and costs of SSA have been intensively studied, the same is not true for MSA. Here, we first review the cases of MSA in harvestmen, an arachnid order in which the records of MSA are more frequent than other arthropod orders. We then propose several benefits and costs of MSA in harvestmen, and contrast them with those of SSA. Second, using field-gathered data we describe gregariousness in seven species of Prionostemma harvestmen from Costa Rica. These species form MSA, but individuals are also found solitarily or in SSA. We tested one possible benefit and one possible cost of gregariousness in Prionostemma harvestmen. Regarding the benefit, we hypothesized that individuals missing legs would be more exposed to predation than eight-legged individuals and thus they should be found preferentially in aggregations, where they would be more protected from predators. Our data, however, do not support this hypothesis. Regarding the cost, we hypothesized that gregariousness increases the chances of parasitism. We found no support for this hypothesis either because both mite prevalence and infestation intensity did not differ between solitary or aggregated individuals. Additionally, the type of aggregation (SSA or MSA) was not associated with the benefit or the cost we explored. This lack of effect may be explained by the fluid membership of the aggregations, as we found high turnover over time in the number of individuals and species composition of the aggregations. In conclusion, we hope our review and empirical data stimulate further studies on MSA, which remains one of the most elusive forms of group living in animals.
Seed dispersal plays an important role in population dynamics in agricultural ecosystems, but the effects of surrounding vegetation height on seed dispersal and population connectivity on the landscape scale have rarely been studied. Understanding the effects of surrounding vegetation height on seed dispersal will provide important information for land-use management in agricultural landscapes to prevent the spread of undesired weeds or enhance functional connectivity. We used two model species, Phragmites australis and Typha latifolia, growing in small natural ponds known as kettle holes, in an agricultural landscape to evaluate the effects of surrounding vegetation height on wind dispersal and population connectivity between kettle holes. Seed dispersal distance and the probability of long-distance dispersal (LDD) were simulated with the mechanistic WALD model under three scenarios of "low", "dynamic" and "high" surrounding vegetation height. Connectivity between the origin and target kettle holes was quantified with a connectivity index adapted from Hanski and Thomas (1994). Our results show that mean seed dispersal distance decreases with the height of surrounding matrix vegetation, but the probability of long-distance dispersal (LDD) increases with vegetation height. This indicates an important vegetation-based trade-off between mean dispersal distance and LDD, which has an impact on connectivity. Matrix vegetation height has a negative effect on mean seed dispersal distance but a positive effect on the probability of LDD. This positive effect and its impact on connectivity provide novel insights into landscape level (meta-)population and community dynamics - a change in matrix vegetation height by land-use or climatic changes could strongly affect the spread and connectivity of wind-dispersed plants. The opposite effect of vegetation height on mean seed dispersal distance and the probability of LDD should therefore be considered in management and analyses of future land-use and climate change effects.
Deciphering chemical mediators regulating specialized metabolism in a symbiotic cyanobacterium
(2022)
Genomes of cyanobacteria feature a variety of cryptic biosynthetic pathways for complex natural products, but the peculiarities limiting the discovery and exploitation of the metabolic dark matter are not well understood. Here we describe the discovery of two cell density-dependent chemical mediators, nostoclide and nostovalerolactone, in the symbiotic model strain Nostoc punctiforme, and demonstrate their pronounced impact on the regulation of specialized metabolism. Through transcriptional, bioinformatic and labeling studies we assigned two adjacent biosynthetic gene clusters to the biosynthesis of the two polyketide mediators. Our findings provide insight into the orchestration of specialized metabolite production and give lessons for the genomic mining and high-titer production of cyanobacterial bioactive compounds.
Forage availability has been suggested as one driver of the observed decline in honey bees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modeling framework for assessing honey bee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honey bee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honey bee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g., brood mortality). To assess overall colony viability, we developed metrics,P(H)andP(P,)which quantified how much nectar and pollen provided by a cropping system per year was converted into a colony's adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize, and sunflower,P(H)andP(P)were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower, and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 yr, andP(H)(269.5 kg) andP(P)(108 kg) being above viability thresholds for 5 yr. Overall, trefoil-grass pasture, oilseed rape, buckwheat, and phacelia improved the temporal continuity in forage supply and colony's viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honey bee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.
We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats.
All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection.
The most common control points for the chronologies are radiocarbon dates (86.1 %), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials).
The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8% of records), reservoir effect (4.9 %), and sediment deposition discontinuity (4.4 %).
Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4% of records could be improved according to our assessment.
Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change.
The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is openaccess and available at PANGAEA (https://doi.org/10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (https://doi.org/10.5281/zenodo.5815192; Li et al., 2022), respectively.