Standardized Sampling Design Research Articles

Geospatial analysis of Plasmodium falciparum serological indicators: school versus community sampling in a low-transmission malaria setting

BackgroundDue to low numbers of active infections and persons presenting to health facilities for malaria treatment, case-based surveillance is inefficient for understanding the remaining disease burden in low malaria transmission settings. Serological data through the detection of IgG antibodies from previous malaria parasite exposure can fill this gap by providing a nuanced picture of where sustained transmission remains. Study enrollment at sites of gathering provides a potential approach to spatially estimate malaria exposure and could preclude the need for more intensive community-based sampling.MethodsThis study compared spatial estimates of malaria exposure from cross-sectional school- and community-based sampling in Haiti. A total of 52,405 blood samples were collected from 2012 to 2017. Multiplex bead assays (MBAs) tested IgG against P. falciparum liver stage antigen-1 (LSA-1), apical membrane antigen 1 (AMA1), and merozoite surface protein 1 (MSP1). Predictive geospatial models of seropositivity adjusted for environmental covariates, and results were compared using correlations by coordinate points and communes across Haiti.ResultsConsistent directional associations were observed between seroprevalence and environmental covariates for elevation (negative), air temperature (negative), and travel time to urban centers (positive). Spearman’s rank correlation for predicted seroprevalence at coordinate points was lowest for LSA-1 (ρ = 0.10, 95% CI: 0.09–0.11), but improved for AMA1 (ρ = 0.36, 95% CI: 0.35–0.37) and MSP1 (ρ = 0.48, 95% CI: 0.47–0.49).ConclusionsIn settings approaching P. falciparum elimination, case-based prevalence data does not provide a resolution of ongoing malaria transmission in the population. Immunogenic antigen targets (e.g., AMA1, MSP1) that give higher population rates of seropositivity provide moderate correlation to gold standard community sampling designs and are a feasible approach to discern foci of residual P. falciparum transmission in an area.

Optimal two-stage spatial sampling design for estimating critical parameters of SARS-CoV-2 epidemic: Efficiency versus feasibility

The COVID-19 pandemic presents an unprecedented clinical and healthcare challenge for the many medical researchers who are attempting to prevent its worldwide spread. It also presents a challenge for statisticians involved in designing appropriate sampling plans to estimate the crucial parameters of the pandemic. These plans are necessary for monitoring and surveillance of the phenomenon and evaluating health policies. In this respect, we can use spatial information and aggregate data regarding the number of verified infections (either hospitalized or in compulsory quarantine) to improve the standard two-stage sampling design broadly adopted for studying human populations. We present an optimal spatial sampling design based on spatially balanced sampling techniques. We prove its relative performance analytically in comparison to other competing sampling plans, and we also study its properties through a series of Monte Carlo experiments. Considering the optimal theoretical properties of the proposed sampling plan and its feasibility, we discuss suboptimal designs that approximate well optimality and are more readily applicable.

Comparing GPS collar and fecal sampling using detection dogs for habitat selection analysis in brocket deer (Mazama)

Abstract Habitat use data are key to understanding species ecology and extinction risk. However, such information is lacking for the elusive deer species of Neotropical region. In this context, fecal sampling has emerged as an alternative tool, in which development and evaluation are essential to obtaining unbiased ecological data. We aimed to compare data from GPS-tracked animals and fecal sampling using scat detection dogs to evaluate the noninvasive performance of this method in habitat selection analysis. We carried out the study in the Brazilian Pantanal, where we monitored six free-living Gray Brocket Deer (Mazama gouazoubira) with GPS collars for 1 year (average of 584 GPS locations/animal) and collected fecal samples (n = 649) simultaneously along a set of transects designed for a scat detection dog survey. We evaluated habitat selection using the chi-square test in an availability/utilization analysis and submitted both data to a bootstrap procedure to assess its precision and accuracy with increasing sample size. GPS data indicated habitat selection at a fine utilization scale, in which savanna and cerrado were preferred and open grassland habitat was avoided. Exclusive fecal sampling also indicated habitat selection, revealing the preference for cerrado and avoidance of open grassland. The GPS and fecal habitat utilization estimates did not differ significantly and fecal sampling increased precision and accuracy with increased sample size, reaching minimal values once n = 200 which should be considered a sufficient survey effort. The similarity between the two methods suggested the reliability of fecal sampling, as long as a standardized sampling design is used. This noninvasive sampling framework can provide previously unavailable ecological data for threatened Neotropical deer as well as other elusive species.

Soil resistance and recovery during neotropical forest succession.

The recovery of soil conditions is crucial for successful ecosystem restoration and, hence, for achieving the goals of the UN Decade on Ecosystem Restoration. Here, we assess how soils resist forest conversion and agricultural land use, and how soils recover during subsequent tropical forest succession on abandoned agricultural fields. Our overarching question is how soil resistance and recovery depend on local conditions such as climate, soil type and land-use history. For 300 plots in 21 sites across the Neotropics, we used a chronosequence approach in which we sampled soils from two depths in old-growth forests, agricultural fields (i.e. crop fields and pastures), and secondary forests that differ in age (1-95 years) since abandonment. We measured six soil properties using a standardized sampling design and laboratory analyses. Soil resistance strongly depended on local conditions. Croplands and sites on high-activity clay (i.e. high fertility) show strong increases in bulk density and decreases in pH, carbon (C) and nitrogen (N) during deforestation and subsequent agricultural use. Resistance is lower in such sites probably because of a sharp decline in fine root biomass in croplands in the upper soil layers, and a decline in litter input from formerly productive old-growth forest (on high-activity clays). Soil recovery also strongly depended on local conditions. During forest succession, high-activity clays and croplands decreased most strongly in bulk density and increased in C and N, possibly because of strongly compacted soils with low C and N after cropland abandonment, and because of rapid vegetation recovery in high-activity clays leading to greater fine root growth and litter input. Furthermore, sites at low precipitation decreased in pH, whereas sites at high precipitation increased in N and decreased in C : N ratio. Extractable phosphorus (P) did not recover during succession, suggesting increased P limitation as forests age. These results indicate that no single solution exists for effective soil restoration and that local site conditions should determine the restoration strategies. This article is part of the theme issue 'Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration'.

Additional deepwater sampling of prey fish in Lake Michigan annual bottom trawl survey reveals new insights for depth distribution dynamics

Beginning in 2013, sites at the 128-m bottom depth contour were added to the sampling design of the annual Lake Michigan bottom trawl survey for prey fish, which has been conducted by the U.S. Geological Survey Great Lakes Science Center (GLSC) each fall since 1973, to better assess fish depth distributions in a changing ecosystem. The standard sampling design included bottom depths from 9 to 110 m, although the GLSC also sporadically conducted bottom trawl tows at the 128-m bottom depth contour during 1973–1988. Enactment of this new sampling design in 2013 revealed that mean biomass density of deepwater sculpins (Myoxocephalus thompsonii) at the 128-m depth exceeded the sum of mean biomass densities at shallower depths, indicating that the bulk of the deepwater sculpin population is residing in waters deeper than 110 m. Thus, our findings supported the hypothesis that the depth distribution of the deepwater sculpin population had shifted to deeper waters beginning in 2007, thereby explaining, at least in part, the marked decline in deepwater sculpin abundance since 2006 based on the standard sampling design. In contrast, our results did not support the hypothesis that the slimy sculpin (Cottus cognatus) population had shifted to deeper waters sometime after 2000. A portion of the burbot (Lota lota) population may have also shifted in depth distribution to waters deeper than 110 m after 2007, based on our results. Our findings have served as an impetus to further expand the range of depths sampled in our bottom trawl survey.

Combining scientific survey and commercial catch data to map fish distribution

AbstractDeveloping Species Distribution Models (SDM) for marine exploited species is a major challenge in fisheries ecology. Classical modelling approaches typically rely on fish research survey data. They benefit from a standardized sampling design and a controlled catchability, but they usually occur once or twice a year and they may sample a relatively small number of spatial locations. Spatial monitoring of commercial data (based on logbooks crossed with Vessel Monitoring Systems) can provide an additional extensive data source to inform fish spatial distribution. We propose a spatial hierarchical framework integrating both data sources while accounting for preferential sampling (PS) of commercial data. From simulations, we demonstrate that PS should be accounted for in estimation when PS is actually strong. When commercial data far exceed scientific data, the later bring little information to spatial predictions in the areas sampled by commercial data, but bring information in areas with low fishing intensity and provide a validation dataset to assess the integrated model consistency. We applied the framework to three demersal species (hake, sole, and squids) in the Bay of Biscay that emphasize contrasted PS intensity and we demonstrate that the framework can account for several fleets with varying catchabilities and PS behaviours.

Decay of similarity across tropical forest communities: integrating spatial distance with soil nutrients.

Understanding the mechanisms that drive the change of biotic assemblages over space and time is the main quest of community ecology. Assessing the relative importance of dispersal and environmental species selection in a range of organismic sizes and motilities has been a fruitful strategy. A consensus for whether spatial and environmental distances operate similarly across spatial scales and taxa, however, has yet to emerge. We used censuses of four major groups of organisms (soil bacteria, fungi, ground insects, and trees) at two observationscales (1-m2 sampling point vs. 2,500-m2 plots) in a topographically standardized sampling design replicated in two tropical rainforests with contrasting relationships between spatial distance and nutrient availability. We modeled the decay of assemblage similarity for each taxon set and site to assess the relative contributions of spatial distance and nutrient availability distance. Then, we evaluated the potentially structuring effect of tree composition over all other taxa. The similarity of nutrient content in the litter and topsoil had a stronger and more consistent selective effect than did dispersal limitation, particularly for bacteria, fungi, and trees at the plot level. Ground insects, the only group assessed with the capacity of active dispersal, had the highest species turnover and the flattest nonsignificant distance-decay relationship, suggesting that neither dispersal limitation nor nutrient availability were fundamental drivers of their community assembly at this scale of analysis. Only the fungal communities at one of our study sites were clearly coordinated with tree composition. The spatial distance at the smallest scale was more important than nutrient selection for the bacteria, fungi, and insects. The lower initial similarity and the moderate variation in composition identified by these distance-decay models, however, suggested that the effects of stochastic sampling were important at this smaller spatial scale. Our results highlight the importance of nutrients as one of the main environmental drivers of rainforest communities irrespective of organismic or propagule size and how the overriding effect of the analytical scale influences the interpretation, leading to the perception of greater importance of dispersal limitation and ecological drift over selection associated with environmental niches at decreasing observation scales.

No overall effect of urbanization on nest-dwelling arthropods of great tits (Parus major).

Urbanization has been shown to strongly affect community composition of various taxa with potentially strong shifts in ecological interactions, including those between hosts and parasites. We investigated the effect of urbanization on the composition of arthropods in nests of great tits in Flanders, Belgium. These nests contain taxonomically and functionally diverse arthropod communities including parasites, predators, detritivores and accidental commensals. Using a standardized hierarchical sampling design with subplots (200 m × 200 m) nested in plots (3 km × 3 km) of varying urbanization levels, we collected arthropods from nests of resident great tits after the young had fledged. Arthropods were extracted, identified to Primary Taxonomical Groups (PTG) and counted. Using generalized linear mixed models (GLMMs) we found diverging effects of urbanization on PTG occurrences and abundances at various levels, but we did not find an overall signal in arthropod diversity or richness. Also, visual inspection of non-metric multidimensional scaling (NMDS) plots did not reveal any community differences between urbanization levels at plot or subplot scales. Land use and environmental variables at different distances around nestboxes did not contribute much to the variation between communities. Our results indicate that arthropod nestbox communities are generally not adversely affected by urbanization, and even city gardens and parks harbor comparable communities to forests and suburban areas. We thus found no evidence for a parasite release effect due to urbanization, nor an increased risk of parasitism in human-dominated environments.

Which patients to sample in clinical cohort studies when the number of events is high and measurement of additional markers is constrained by limited resources.

PurposeWe consider an existing clinical cohort with events but limited resources for the investigation of a further potentially expensive marker. Biological material of the patients is stored in a biobank, but only a limited number of samples can be analyzed with respect to the marker. The question arises as to which patients to sample, if the number of events preclude standard sampling designs.MethodsModifications of the nested case‐control and the case‐cohort design for the proportional hazards model are applied, that allow efficient sampling in situations where standard nested case‐control and case‐cohort are not feasible. These sampling designs are compared to simple random sampling and extreme group sampling, the latter including only patients with extreme outcomes, ie either with an event early in time or without an event until at least a point later in time.ResultsThe modified nested case‐control design and the modified case‐cohort design provide powerful methods for sampling in a clinical cohort with many events. The simple random sampling usually is less efficient. If focus is on precise estimation of a potential effect in terms of a hazard ratio, extreme group sampling is not competitive. If focus is on screening for important biomarkers, extreme group sampling markedly outperforms the other sampling designs.ConclusionsWhen it is not feasible to sample all events, a modified nested case‐control design or case‐cohort design leads to efficient effect estimates in the proportional hazards model. If screening for important biomarkers is the primary objective, extreme group sampling is preferable.

A replication approach to controlled selection for catch sampling intercept surveys

Intercept surveys following probability sampling designs are widely used for fisheries data collection, but limited resources often make implementing such designs challenging. Adjustments that field staff make after sample selection may create deviations from the initial sampling design, introducing data quality concerns. Currently available controlled selection techniques designed to handle logistical constraints can be complicated to develop and implement, and limited in versatility and practicality. We examined the utility of a novel constrained draw replication approach for selecting sampling units for intercept surveys, which first uses standard probability sampling to draw a large set of initial replicated samples. This set is then screened against customizable constraints to create a survivor subset prior to selecting a final sample for the survey. Using a simulation study, we tested the performance of this method in comparison to a standard probability sampling design for selecting site-day sampling units. Estimates obtained from the new method were as accurate and precise as the standard probability sampling design at high levels of replication. This flexible method may help fisheries scientists maintain better control of the sample distribution while allowing for calculation of appropriate design-based sample weights, and increase the design options available for fisheries intercept surveys.

Classification of South Brazilian grasslands: Implications for conservation

AbstractAimsWe offer a first classification of South Brazilian grasslands (Campos Sulinos) based on quantitative vegetation data and describing grassland types in terms of dominant and indicator species.LocationSouth Brazilian grasslands (Paraná, Santa Catarina, Rio Grande do Sul states).MethodsWe described vegetation plots in 167 sampling units throughout the region using a stratified nested design, totalizing 1,502 1 m² quadrats. We classified vegetation using cluster analysis based on Bray–Curtis dissimilarities, establishing three vegetation types and ten subtypes. We conducted indicator species analysis within the resulting subtypes, and for all possible combinations of subtypes.ResultsIn the cluster analyses, a clear separation of poorly drained grasslands from the drier sites appeared. Further, a clear distinction between grasslands in the South Brazilian highland region, situated in the Atlantic Forest biome, and the grasslands of the Pampa biome, to the south, emerged, reflecting climatic and management differences. Highland grasslands showed lower species cover dominance, while in the Pampa, Paspalum notatum clearly was the most important species and the abundance of exotic species was higher.ConclusionsOur study provides the first classification of South Brazilian grasslands based on quantitative vegetation data recorded in a standardized sampling design. The data support the division of grasslands into the main phytogeographic units of the region (Brazilian biome classification). Grasslands in these two regions also differ in terms of species dominance pattern (higher dominance in Pampa grasslands, likely also due to higher grazing levels) and in terms of conservation state (low presence of exotic species in highland grasslands). Our results are important for conservation policies, which can now consider the presence of different grassland types in different region, but more data will be necessary for a more detailed classification that considers different abiotic features in more detail.

Small to large-scale patterns of ground-dwelling spider (Araneae) diversity across northern Canada

We examined how Arctic spider (Araneae) biodiversity is distributed at multiple spatial scales in northern Canada using a standardized hierarchical sampling design. We investigated which drivers, environmental or spatial, influence the patterns observed. Spatial patterns of Arctic spider species richness and composition were assessed in 12 sites located in arctic, subarctic, and north boreal ecoclimatic regions, spanning 30 degrees of latitude and 80 degrees of longitude. Variation in diversity was partitioned in relation to multiple environmental and spatial drivers of diversity patterns. Over 23 000 adult spiders, representing 306 species in 14 families, were collected in northern Canada, with 107 species (35% of the total species collected) representing new territorial or provincial records. Spider diversity was structured at the regional scale across ecoclimatic regions but was not structured with latitude. Longitudinal patterns of spider diversity across Canada may be explained by post-glacial dispersal. At local scales, diversity was non-randomly distributed and possibly limited by biotic interactions. We recommend the use of ecoclimatic regions as a framework for conservation of biodiversity in northern Canada and spiders as useful bioindicators that can help us understand the effects of climate change across ecoclimatic regions of northern Canada.

Clonal plasticity and diversity facilitates the adaptation of Rhododendron aureum Georgi to alpine environment.

Four small oval populations and five large intensive populations of Rhododendron aureum growing at the alpine in Changbai Mountain (China) were studied in two types of habitat (in the tundra and in Betula ermanii forest). Identification and delimitation of genets were inferred from excavation in small populations and from amplified fragment length polymorphism (AFLP) markers by the standardized sampling design in large populations. Clonal architecture and clonal diversity were then estimated. For the four small populations, they were monoclonal, the spacer length (18.6 ± 5.6 in tundra, 29.7 ± 9.7 in Betula ermanii forest, P < 0.05) was shorter and branching intensity (136.7 ± 32.9 in tundra, 43.4 ± 12.3 in Betula ermanii forest, P < 0.05) was higher in the tundra than that in Betula ermanii forest. For the five large populations, they were composed of multiple genets with high level of clonal diversity (Simpson’s index D = 0.84, clonal richness R = 0.25, Fager's evenness E = 0.85); the spatial distribution of genets showed that the clonal growth strategy of R. aureum exhibits both guerilla and phalanx. Our results indicate that the clonal plasticity of R. aureum could enhance exploitation of resource heterogeneity and in turn greatly contribute to maintenance or improvement of fitness and the high clonal diversity of R. aureum increase the evolutionary rates to adapt the harsh alpine environment in Changbai Mountain.

Physicochemical characteristics of forest soils in Tarai and Siwalik regions of Nepal

Soils are important components of every terrestrial ecosystem. In Nepal, terrestrial ecosystems of Tarai and Siwalik regions are highly vulnerable due to intense anthropogenic disturbances. Forest depletion and land degradation have posed substantial impacts on soil quality. This review paper focuses on identifying the status of physical and chemical characteristics of forest soils in Tarai and Siwalik regions. For the purpose, published articles from various sources, as well as publications of Government of Nepal were reviewed. The study showed variation in physicochemical characteristics of soils in different regions. The land areas covered with vegetation were found effective in controlling erosion and consequently retention of important chemical properties of soils. The scientific studies on soil physical, chemical and biological quality seem inadequate. Standard research framework and sampling designs are required in future studies, so that comparisons on soil properties across different degraded and/or other land-use categories can be made. There is need of development of scientific database on soil quality for supporting future ecosystem management and restoration programs.

Time-dependent classification accuracy curve under marker-dependent sampling.

Evaluating the classification accuracy of a candidate biomarker signaling the onset of disease or disease status is essential for medical decision making. A good biomarker would accurately identify the patients who are likely to progress or die at a particular time in the future or who are in urgent need for active treatments. To assess the performance of a candidate biomarker, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are commonly used. In many cases, the standard simple random sampling (SRS) design used for biomarker validation studies is costly and inefficient. In order to improve the efficiency and reduce the cost of biomarker validation, marker-dependent sampling (MDS) may be used. In a MDS design, the selection of patients to assess true survival time is dependent on the result of a biomarker assay. In this article, we introduce a nonparametric estimator for time-dependent AUC under a MDS design. The consistency and the asymptotic normality of the proposed estimator is established. Simulation shows the unbiasedness of the proposed estimator and a significant efficiency gain of the MDS design over the SRS design.

Systematic site selection for multispecies monitoring networks

Summary The importance of monitoring biodiversity to detect and understand changes throughout time and to inform management is increasingly recognized. Monitoring schemes should be globally unified, spatially integrated across scales, long term, and cost‐efficient. We propose a framework to design optimized multispecies‐targeted monitoring networks over large areas. The method builds upon previous developments on systematic conservation planning in terms of optimizing resource allocation in space, and comprises seven steps: (a) determine which questions will be addressed, (b) define species to be monitored, (c) compile occurrence data for all defined species, (d) predict the overall distribution of each species, (e) collect relevant environmental data and identify homogeneous strata, (f) set targets for the minimum number of monitoring sites per species and/or stratum and (g) identify optimal monitoring sites. We tested whether the monitoring networks designed with our framework have increased performance when compared to networks obtained with simple‐random or stratified‐random sampling by using a set of different indicators. To that end, we designed monitoring networks using optimized and non‐optimized sampling schemes, applied to a case study in Portugal, where the goal was to design a monitoring network for amphibians and reptiles, to complement the one currently established in Spain. Results allowed us to conclude that monitoring networks designed with our method tend to outperform the non‐optimized ones, in terms of higher species diversity (i.e. higher number of species and equity across monitoring sites), higher representation of environmental strata, and particularly higher coverage of rare species, with less survey effort. Synthesis and applications. We developed a framework to allocate monitoring sites for multiple species at broad scales using predictive models and optimization algorithms currently applied in systematic conservation planning. This framework presents field survey cost‐efficiency advantages when compared to other standard sampling designs and can significantly contribute to improving the design of monitoring schemes. Thus, we recommend its application to design new multispecies monitoring networks or to extend existing ones.

What drives plant species diversity? A global distributed test of the unimodal relationship between herbaceous species richness and plant biomass

AbstractQuestionFor over a century, ecologists have grappled with the question “what drives species diversity?” Urgent global issues such as loss of biodiversity and the relative importance of species richness for ecosystem function and services has heightened the relative importance of understanding processes that control species diversity. Here we present the plans for a global coordinated distributed experiment for herbaceous communities, theHerbDivNet, to test the hump‐backed model, a unimodal relationship between species richness and aboveground plant biomass plus dead plant litterHBM, to determine whether scale may influence theHBM, and to explore drivers of plant diversity.LocationGlobally distributed experiment.MethodsWe propose a nested, standardized sampling design 8 × 8 m, with 1 m2plots, taken from multiple site locations along a range of sites varying in primary productivity.Results and ConclusionsWe welcome others with an interest in using global, standardized, coordinated distributed experiments to explore patterns and processes in herbaceous plant communities to joinHerbDivNet in the search of new insights to drivers of plant species diversity.

Sampling Design Optimization on Arable Lands for Integrated Soil Monitoring for Sustainable Production

Proper experimental design that ensures effective sampling of each recorded environmental variable is essential during planning integrated soil-monitoring programs with the aim of assessing the ecological state of soils. In our study, three different regular sampling designs (standard, 50,000 m2; reduced area, 635 m2; and reduced area and sampling size, 2500 m2) were tested, and the required sampling sizes for 10%, 20%, and 40% minimum detectable change were calculated. Sampling designs were tested from the aspect of the most effective sampling, a sampling with the greatest precision and the least bias. The parameters determined in this study were the following: total microbial activity, concentration of 14 potentially toxic microelements, and basic soil physical and chemical characteristics. The results are presented by the example of total microbial activity and microelement concentration studies. Twenty to 120 soil samples were taken from each selected arable land under intensive and organic cultivation as well as from a pasture and protected grassland, considered as a control. It was concluded that both for microbial activity and microelement concentration measurements of 10% minimum detectable change requires enormous sampling effort at each site and sampling design. The required sampling size is especially high at the organic sites and the grassland, because the high standard deviation, and especially high mean total microbial activity. With a sampling using either the standard or reduced area design, 20% difference in total microbial activity can be detected using a reasonable (<25) sampling size. However, reduced area design minimizes spatial heterogeneity, thus requires smaller sampling effort, and can be an ideal compromise. In the case of microelement concentration, standard sampling design was more sufficient to detect a 20% change. Designs that proved to be most efficient in this study have been combined into a joint sampling design that will be applied in the first cycle of the new Hungarian Soil Degradation Monitoring System.

AFLP markers reveal high clonal diversity and extreme longevity in four key arctic‐alpine species

We investigated clonal diversity, genet size structure and genet longevity in populations of four arctic-alpine plants (Carex curvula, Dryas octopetala, Salix herbacea and Vaccinium uliginosum) to evaluate their persistence under past climatic oscillations and their potential resistance to future climate change. The size and number of genets were determined by an analysis of amplified fragment length polymorphisms and a standardized sampling design in several European arctic-alpine populations, where these species are dominant in the vegetation. Genet age was estimated by dividing the size by the annual horizontal size increment from in situ growth measurements. Clonal diversity was generally high but differed among species, and the frequency distribution of genet size was strongly left-skewed. The largest C.curvula genet had an estimated minimum age of c. 4100 years and a maximum age of c. 5000 years, although 84.8% of the genets in this species were <200 years old. The oldest genets of D.octopetala, S.herbacea and V.uliginosum were found to be at least 500, 450 and 1400 years old, respectively. These results indicate that individuals in the studied populations have survived pronounced climatic oscillations, including the Little Ice Age and the postindustrial warming. The presence of genets in all size classes and the dominance of presumably young individuals suggest repeated recruitment over time, a precondition for adaptation to changing environmental conditions. Together, persistence and continuous genet turnover may ensure maximum ecosystem resilience. Thus, our results indicate that long-lived clonal plants in arctic-alpine ecosystems can persist, despite considerable climatic change.

Wolf monitoring in France : a dual frame process to survey time- and space-related changes in the population

The wolf recovery in France dates back to 1992, following the natural range expansion of the remaining Italian population since the late 1960’s. Facing a high level of interactions between wolves and sheep breeding, decision makers had to quickly balance the need for managing livestock depredations with the conservation of wolves as a protected species. The French authorities therefore required a reliable assessment of changes in the species range and population numbers, as well as a reliable monitoring of depredations on livestock, all being key variables to be further included within the governmental decision making process. Because of their elusive behaviour, high mobility, and territoriality, applying a standard random sampling design to the monitoring of awolf population would lead to almost no chance of collecting any signs of presence. In order to increase detectability, we use a dual frame survey based on two spatial scales (“population range” and “reproductive unit”) investigated sequentially thanks to a network of specifically-trained wolf experts distributed over 80000 km2 to collect the data. First, an extensive sign survey at a large scale provides so-called cross-sectional data (pool of signs from unknown individuals for a given year), thereby allowing the detection of new wolf occurrences, new pack formations, and the documentation of geographical trends. Secondly, an intensive sign survey within each detected wolf territory, based on standard snow tracking and wolf howling playback sessions, provides some yearly updatable proxies of the demographic pattern. The combination with a non invasive molecular tracking provides longitudinal data to develop mark-recapture models and estimate vital rates, population size and growth rate, while accounting for detection probabilities. The latter are used in turn to control for proxies’ reliability and to implement demographic models with local population parameters. Finally, wolf activity patterns in connection with predator-prey dynamics is investigated through a pilot study carried out with both wolves and four ungulate preys radio-collared. A particular attention is paid to checking the reliability of presence sign data, as well as improving the cost-efficiency ratio of the monitoring. Finally, these results are also used by the government as one of the components in the decision making process related to the management of coexistence with wolves