Species Rarefaction Curves Research Articles

Rodents in Xerophilous Shrubland and Semi-Desert Grassland Communities of Southeastern Coahuila, Mexico

Objective: To assess the diversity of rodent communities in semi-desert grasslands and xerophilous shrubland at the "Los Ángeles" Ranch in southeastern Coahuila. Design/methodology/approach: Monthly samplings were carried out from May to November 2020 using Sherman traps. The capture-recapture method was used to estimate species richness and abundance. Non-parametric estimators, species rarefaction curves, and rank abundance plots were utilized to measure species diversity. The Whittaker index was employed to assess species turnover between sampled communities. Results: A total of 205 individuals from three families and eight species of rodents were recorded, with the Cricetidae family being the best represented. The species rarefaction curve showed that the shrubland exhibited greater diversity compared to the grassland. The dominant species were Onychomys arenicola in the semi-desert grassland and Peromyscus zamorae in the xerophilous shrubland. Limitations/implications: There remains a need to extend long-term monitoring efforts to detect how anthropogenic activities influence species composition. Findings/conclusions: The study highlights the importance of grasslands for the conservation of rodents in the state. Semi-desert grasslands and shrublands provide natural resources that should be preserved to maintain biodiversity in semi-arid ecosystems

Multilocus DNA metabarcoding diet analyses of small cetaceans: a case study on highly vulnerable humpback dolphins and finless porpoises from the Pearl River Estuary, China.

Accurate diet identification of top predators is crucial to fully understand their ecological roles. Compared to terrestrial animals, gathering dietary information from cetaceans is notoriously difficult. Here, we applied a multilocus metabarcoding approach to investigate the diet of vulnerable Indo-Pacific humpback dolphins and Indo-Pacific finless porpoises from the Pearl River Estuary (PRE), China. Our analyses identified 21 prey fish species from the 42 humpback dolphin stomachs, as well as 10 species of fish and 1 species of cephalopod from the 13 finless porpoise stomachs. All of the taxa were assigned to the species level, highlighting that the multimarker approach could facilitate species identification. Most of the prey species were small- and medium-sized fishes that primarily fed on zooplankton. The calculated similarity index revealed a moderated dietary overlap between the 2 cetaceans, presumably due to the feeding of the 2 predators in association with fishing vessels in the PRE. A more diverse diet was observed in humpback dolphins in the closed fishing season compared to the fishing season, implying the influence on the dolphin diet due to the availability of commercial fishery resources. However, according to the results of species rarefaction curves, our findings on the feeding habits of the 2 cetaceans are still limited by insufficient sample size and therefore should be interpreted with caution. This study represents a first attempt to apply the multilocus DNA metabarcoding technique in the diet analysis of small cetaceans, although more efforts are needed to improve this type of analysis.

A computationally efficient approach to estimating species richness and rarefaction curve

A computationally efficient approach to estimating species richness and rarefaction curve

Towards a framework for invasive aquatic plant survey design in Great Lakes coastal areas.

At least 65 aquatic plant species have been identified as part of a surveillance list of non-native species that pose a threat to biodiversity and ecosystem services in the Laurentian Great Lakes. Early detection of these potentially invasive aquatic plants (IAP) could minimize impacts of novel incursions and facilitate successful eradication. We developed, implemented, and then adaptively refined a probabilistic boat-based sampling design that aimed to maximize the likelihood of detecting novel IAP incursions in large (400+ hectares) Great Lakes coastal areas. Surveys were conducted from 2017 to 2019 at five Great Lakes locations - St Joseph River (MI), Saginaw River (MI), Milwaukee (WI), Cleveland (OH), and the Detroit River (MI). Aquatic plant communities were characterized across the five sites, with a total of 61 aquatic plant species detected. One-fifth of the species detected in our surveys were non-native to the Great Lakes basin. Sample-based species rarefaction curves, constructed from detection data from all surveys combined at each location, show that the estimated sample effort required for high confidence (> 95%) detection of all aquatic plants at a site, including potentially invasive species, varies (< 100 sample units for Detroit River; > 300 sample units for Milwaukee, roughly equivalent to 6 to 18 days sampling effort, respectively). At least 70% of the estimated species pool was detected at each site during initial 3-day surveys. Leveraging information on detection patterns from initial surveys, including depth and species richness strata, improved survey efficiency and completeness at some sites, with detection of at least 80% of the estimated species pool during subsequent surveys. Based on a forest-based classification and regression method, a combination of just five variables explained 70% or more of the variation in observed richness at all sites (depth, fetch, percent littoral, distance to boat ramps and distance to marinas). We discuss how the model outcomes can be used to inform survey design for other Great Lakes coastal areas. The survey design we describe provides a useful template that could be adaptively improved for early detection of IAP in the Great Lakes.

Structure and spatial distribution of the rotifer assemblages along a tropical reservoir.

The construction of reservoirs is a common practice in the world. These systems modify the hydric landscape and alter the flow of rivers, becoming lotic environments in lentic. Here we investigated the structure and spatial distribution of rotifers along a tropical reservoir. We sampled four points in the Pedra do Cavalo Reservoir, Bahia, Brazil, bimonthly, between August 2014 and June 2015. We registered more than 70 taxa distributed in 17 families, with the majority of species belonging to the Lecanidae, Brachionidae and Trichocercidae families. The species rarefaction curve did not achieve a total asymptote, indicating that species richness in the reservoir is higher than what was registered. Based in the species frequency of occurrence, we identified 48 rare species, 16 common species, five constant species and one frequent species. The highest beta diversity values were registered in riverine P1 (0.513) and intermediate P2 (0.503), although there were no significant differences between the sampling points. Despite the high abundance values in P1, P2 and P3 no significant differences were found between the studied points. Thus, this study substantially increases the knowledge on the rotifer community in the Paraguaçu River and contributes to future studies that focus on biodiversity, ecology and conservation in the Brazilian reservoir ecosystems.

How Much is Enough? Improving Participatory Mapping Using Area Rarefaction Curves

Participatory mapping is a valuable approach for documenting the influence of human activities on species, ecosystems, and ecosystem services, as well as the variability of human activities over space and time. This method is particularly valuable in data-poor systems; however, there has never been a systematic approach for identifying the total number of respondents necessary to map the entire spatial extent of a particular human activity. Here, we develop a new technique for identifying sufficient respondent sample sizes for participatory mapping by adapting species rarefaction curves. With a case study from a heavily fished marine ecosystem in the central Philippines, we analyze participatory maps depicting locations of individuals’ fishing grounds across six decades. Within a specified area, we assessed how different sample sizes (i.e. small vs. large numbers of respondents) would influence the estimated extent of fishing for a specified area. The estimated extent of fishing demonstrated asymptotic behavior as after interviewing a sufficiently large number of individuals, additional respondents did not increase the estimated extent. We determined that 120 fishers were necessary to capture 90% of the maximum spatial extent of fishing within our study area from 1990 to 2010, equivalent to 1.1% of male fishers in the region. However, a higher number of elder fishers need to be interviewed to accurately map fishing extent in 1960 to 1980. Participatory maps can provide context for current ecosystem conditions and can support guidelines for management and conservation. Their utility is strengthened by better consideration of the impacts of respondent sample sizes and how this can vary over time for historical assessments.

Diversity of insects associated with olive (Oleaceae) groves across a dryland climate gradient in Algeria

AbstractThis study investigated insect diversity of olive (Olea europaea Linnaeus (Oleaceae)) groves grown in arid and semiarid climates in northeastern Algeria. Using several sampling techniques, a total of 1326 insect specimens were collected and identified into 151 species, 124 genera, 65 families, and 10 orders. Hymenoptera and Coleoptera were quantitatively the most abundant, whereas the dominant functional feeding groups were phytophages then predators. The entomofauna included several olive pests such as Bactrocera oleae (Rossi) (Diptera: Tephritidae), Parlatoria oleae (Colvée) (Hemiptera: Diaspididae), Euphyllura olivina (Costa) (Hemiptera: Liviidae), and Liothrips oleae Costa (Thysanoptera: Phlaeothripidae). Although insect diversity parameters recorded for both observed and expected species richness were higher in olive groves grown under semiarid compared with arid climate, the completeness rate of species richness obtained using the nonparametric incidence estimators was higher in arid olive groves. Generalised linear models showed that the number of individuals and species richness varied significantly between climates (P &lt; 0.01), whereas the variation of the rest of diversity parameters was not significant. Diversity traits of insect assemblage of each climatic region were positively correlated. Besides, the Mantel permutation test revealed similar patterns (r = 0.91, P &lt; 0.0001) between correlation matrices of the two climates. When increasing the number of samples, species richness extrapolation revealed that diversity is expected to increase by 130% in olive groves grown under arid climate and 93% in semiarid climate. These increases are related to continuous appearance of rare and scarce insects as demonstrated by species rarefaction curves. Even with high evenness values of insect communities, similarity was low between climate indicating the rarity and scarcity of populations.

Richness and composition of anuran assemblages from an Amazonian savanna.

The Amazonian savannas occupy approximately 150,000 km2 of the Brazilian Amazon, occurring in scattered isolated patches over large areas of forest in the states of Amapá, Amazonas, Pará, Roraima and Rondônia. Despite having considerable variation in the Anuran composition between locations and between the savanna’s physiognomies, a systematic and geographically wide sampling has not been performed for the savanna from Amapá yet, located in the north of Brazil, eastern Amazonia. In this perspective, a study was conducted on the richness, composition, diversity, and abundance of Anuran species in a ​​savanna area in Amapá State. For Anuran sampling, we performed 24 samples in four physiognomies (grassland savanna, scrub grassland savanna, parkland savanna, open woodland savanna) through an active and auditory search more than 20 sampling plots of 100 × 50 meters in each physiognomy. Twenty-one (21) species of frogs belonging to five families were registered: Bufonidae, Hylidae, Leptodactylidae, Microhylidae and Phyllomedusidae. Scrub grassland savanna registered a greater number of individuals regarding the species richness by physiognomy. The species rarefaction curve for the total area reached an asymptote, suggesting that the data collection effort was enough to adequately sample the species richness of the area. The Kruskal-Wallis variance analysis revealed significant differences in the species richness and diversity among the physiognomies. The Bray-Curtis similarity analysis grouped the physiognomies into three main groups: open woodland savanna, grassland savanna and scrub grassland savanna and parkland savanna. Through ordering by non-metric multidimensional scaling, the species composition from the savanna anuran assemblage resulted in a separation among three sampled physiognomies with significant differences, indicating differences in assemblage composition of the three sampled physiognomies. The local richness (21 species) corresponds to 14% of the 15 typical species that have strongly associated distribution with the Cerrado from Central Brazil, and 35.6% of 59 typical species of neighboring domains which only marginally occur in the Cerrado, representing a considerable part of frog species richness recorded in the savanna in the eastern portion of the Brazilian Amazon.

Measurement of Biodiversity (MoB): A method to separate the scale‐dependent effects of species abundance distribution, density, and aggregation on diversity change

Abstract Little consensus has emerged regarding how proximate and ultimate drivers such as productivity, disturbance and temperature may affect species richness and other aspects of biodiversity. Part of the confusion is that most studies examine species richness at a single spatial scale and ignore how the underlying components of species richness can vary with spatial scale. We provide an approach for the measurement of biodiversity that decomposes changes in species rarefaction curves into proximate components attributed to: (a) the species abundance distribution, (b) density of individuals and (c) the spatial arrangement of individuals. We decompose species richness by comparing spatial and nonspatial sample‐ and individual‐based species rarefaction curves that differentially capture the influence of these components to estimate the relative importance of each in driving patterns of species richness change. We tested the validity of our method on simulated data, and we demonstrate it on empirical data on plant species richness in invaded and uninvaded woodlands. We integrated these methods into a new r package (mobr). The metrics that mobr provides will allow ecologists to move beyond comparisons of species richness in response to ecological drivers at a single spatial scale toward a dissection of the proximate components that determine species richness across scales.

Mobsim: An r package for the simulation and measurement of biodiversity across spatial scales

Abstract Estimating biodiversity and its change in space and time poses serious methodological challenges. First, there has been a long debate on how to quantify biodiversity, and second, measurements of biodiversity and its change are scale‐dependent. Therefore, comparisons of biodiversity metrics between communities are ideally carried out across scales. Simulations can be used to study the behaviour of biodiversity metrics across scales, but most approaches are system specific, plagued by large parameter spaces, and therefore cumbersome to use and interpret. However, realistic spatial biodiversity patterns can be generated without reference to ecological processes, which suggests a simple simulation framework as important tool for ecologists. Here, we present the r package mobsim that allows users to simulate the abundances and the distributions of individuals of different species in a spatially explicit landscape. Users can define key properties of communities, including the total number of individuals, the species‐abundance distribution (SAD) and the degree of intraspecific spatial aggregation. Furthermore, the package provides functions that derive biodiversity measures, such as rarefaction curves and species–area relationships (SAR), from simulated communities or from observed data, as well as functions that simulate different sampling designs. We show several example applications of the package. First, we illustrate how species rarefaction and accumulation curves can be used to disentangle changes in the fundamental components that underlie biodiversity: (i) total abundance, (ii) species‐abundance distribution and (iii) species aggregation. Second, we demonstrate how mobsim can be applied to assess the performance of species‐richness estimators. The latter indicates how spatial aggregation challenges classical non‐spatial species‐richness estimators. mobsim allows the simulation and analysis of a large range of biodiversity scenarios and sampling designs in a comprehensive way by directly manipulating key community properties. The simplicity and control provided by the package also makes it a useful didactic tool. The combination of controlled simulations and their analysis will facilitate a more rigorous interpretation of real‐world data that exhibit sampling effects and scale dependence.

Relationships between spectral and bird species rarefaction curves in a brutian pine forest ecosystem

Bu calismada Fethiye yoresinde secilen bir kizilcam orman ekosisteminde spektral rarefaksiyon egrileri ile kus turu rarefaksiyon egrileri arasindaki iliskilerin ortaya koyulmasi amaclanmistir. Buyuklugu 0,81 ha (90 x 90 m) olan 40 ornek alan icin, arazi gozlemleriyle kus turleri tespit edilmistir. Ornek alanlara karsilik gelen piksellerin (Aster icin 36, SPOT icin 81 ve RapidEye icin 324 adet) NDVITOA degerleri hesaplanmistir. Sonra, EstimatesS yazilimi vasitasiyla spektral ve kus turu rarefaksiyon egrileri olusturulmustur. Bunlar arasindaki iliskiler regresyon analiziyle incelenmistir. Ayrica “artis oranlari” dikkate alinarak egrilerin benzerligi ortaya koyulmustur. Calisma sonuclari, spektral rarefaksiyon egrileri ile kus turu rarefaksiyon egrisinin genel egilimi arasinda ciddi farkliliklar oldugunu ve bu yorede uydu goruntuleri kullanilarak kus turu rarefaksiyon egrisinin kestirilemeyecegini gostermistir. Bu calismalarin daha kaba cozunurluklu uydu goruntuleriyle daha genis cografyalarda tekrarlanmasinin, spektral rarefaksiyon egrilerinin potansiyelinin daha iyi anlasilmasi bakimindan onemli oldugu dusunulmektedir.

English

Tropical forests generally host high biodiversity and are important sources of ecological, socio-cultural and economic services. There are also many sacred forests in many parts of the world, including burial sites in Gobeya rural administrative, having a significant ecological and socio-economic value. This study aims to quantify species diversity, abundance and vegetation structure, and also to determine the ecological importance of woody plant species in burial forest sites. The study was carried out between February and April, 2015 in Gobeya rural administrative which is located approximately at 430 km North of Addis Ababa, Ethiopia. Three largest burial sites (Sideni, Merma and Gubahil) were inventoried where three quadrats of 20 &times; 20 m at 100 m interval around the edge, and other three quadrats of 20 &times; 20 m at 50 m interval around the interior were randomly laid. A total of 28 woody plant species belonging to 19 families and 26 genera were identified. Analysis of species rarefaction curve at 95% confidence level reveals that Sideni cemetery site tends to have the highest species richness (&alpha;-diversity, n=22) with a possibility of finding new species. Estimation of total species richness using Chao-1 also shows that Sideni site to have the highest richness (n=25). Similarly, non-metric multi-dimensional scaling (MDS) ordination shows that Sideni burial site appears to have the highest species turnover (&beta;-diversity). This is probably due to the presence of an intermediate disturbance in Sideni burial forest site. On the other hand, Acokanthera schimperi (A. DC.) Benth. &amp; Hook. f. (Apocynaceae) is the most abundant tree (56.32%) in Sideni site while Carissa edulis (Forssk.) Vahl (Apocynaceae) is the most abundant shrub in Merma site (29.34%) and Gubahil site (38.13%). In this regard, religious teaching takes the highest social motive behind the tradition of protecting burial sites in the study area. Burial sites provide many socio-economic services including firewood, construction products, livestock forage, medicinal plants and other household products. They also play as important refugia for wild animals such as hyena, fox, porcupine, monkey and many other bird species. So, protection of burial sites should be ensured over long terms, and the indigenous practices of protecting burial forest sites should be preserved.&nbsp; Therefore, burial sites can be delineated as an important landscape to protect and preserve these socio-economically important plant species. Key words: Burial forest, diversity, abundance, species richness, species composition, multi-dimensional

Current knowledge of fungi from Neotropical montane cloud forests: distributional patterns and composition

Montane cloud forests in the Neotropics harbor a great wealth of biological diversity and a large number of endemic species. Here, we present (i) a comprehensive data mining exercise of fungi from Neotropical montane cloud forests (NMCF), (ii) an extensive review of the current knowledge of fungal richness, distribution and composition, and (iii) a preliminary analysis of fungal endemicity in Mexican montane cloud forests. Based on a survey of literature and other sources, we assembled a database of 6349 records representing 2962 fungal species in NMCF. The computed individual-based species rarefaction curve remained non-asymptotic, and the extrapolation curve estimated an expected increment of 42% in the number of species by doubling the sampling effort. Fungal species richness was highest in NMCF from Mesoamerica, particularly from Mexico and Costa Rica. Fungi from Mesoamerica, Caribbean and South America are significantly different at diverse taxonomic levels, and there is a little overlap in the fungal species recorded from these regions. The analyses of endemicity of the Mexican dataset performed with parsimony and Bayesian methods were highly complementary. They showed the following areas of endemicity supported by the congruent distribution of fungal species: (i) two main regions in the Trans-Mexican Volcanic Belt (TMVB); (ii) a region in the southern part of Veracruz; and (iii) a region located in the eastern part of TMVB with affinities with Sierra Madre Oriental and the Chiapan-Guatemala Highlands. This last area was supported by five species of Glomeromycota and is consistent with an area of endemicity previously found in vascular plants. In this study, we provide a perspective on gaps in knowledge regarding the diversity and distribution of fungi in NMCF, and provide a full dataset of fungal records with geographical, bibliographic and taxonomic information.

Evaluating the Woody Species Diversity by Means of Remotely Sensed Spectral and Texture Measures in the Urban Forests

There is an urgent need to obtain an accurate data on biological diversity and its temporal variation, in order to adopt an appropriate protection strategy to manage the urban forest remnants on sustainable manner for future generations. RapidEye Satellite images with spatial resolution of 5 × 5 m (orthorectified pixel size), ASTER VNIR images with spatial resolution of 15 × 15 m and Landsat-8 OLI images with spatial resolution of 30 × 30 m were used to evaluate the woody species diversity in urban forest remnants. Pearson Correlation Coefficient (PCC) was used to determine the relationships between the woody species diversity at Alpha (α) level and the spectral & texture properties derived from the satellite images. PCC test showed a positive significant relationship between the brightness of the RapidEye satellite image (i.e., Atmospherically Resistant Vegetation Index; ARVI) and the Simpson’s Diversity Index (S) (r = 0.80, p < 0.01). In order to also estimate the beta (β) diversity in the study, the relationship between species rarefaction curves and spectral rarefaction curves was calculated through multiple regression analysis i.e., Landsat NDVI, ASTER NDVI and RapidEye NDVI (respectively, R2 = 0.99; 0.99; 0.98, p < 0.01). The findings of the study revealed that satellite image with a resolution of 5 m would be more appropriate to estimate the woody species diversity of urban forest remnants. However, medium resolution satellite images (Landsat) may be used to examine the species rarefaction curve and β diversity in forest remnants.

Exploring diversity and distribution of demersal fish species from the Northern Alboran Sea and Gulf of Vera (Western Mediterranean Sea)

Exploring diversity and distribution of demersal fish species from the Northern Alboran Sea and Gulf of Vera (Western Mediterranean Sea)

Plot-based butterfly surveys: statistical and methodological aspects

Butterflies (Lepidoptera Rhopalocera) are considered good indicators of Europe’s biodiversity, especially for grasslands and other open habitats. Therefore monitoring butterfly communities is a powerful tool to measure biodiversity patterns in relation to pressures and to define management actions aimed at conserving and/or increasing biodiversity. However, the precision and efficiency of the methods used to assess the diversity of butterflies have seldom been examined. A mathematical exploration of the correlation between sampling effort and the resulting exhaustiveness of butterfly surveys should allow to select methodological parameters rationally and to estimate the precision of the results obtained. Optimization of these parameters for a given amount of total time should be done with statistical techniques. The aim of this paper is to provide data to estimate the influence of some of the above mentioned parameters on the exhaustiveness of butterfly data for plot-based surveys. Species-rarefaction curves are used to investigate the influence of the duration of single surveys and of repeated visits to a site on the species richness ascertained. Additionally, correlations of the number of days between two butterfly surveys and community dissimilarities are presented. It was found that species richness increased with the number of surveys but this increase differed between lowland and mountain sites and a correlation of the number of days between two butterfly surveys and community similarity was found for the mountain sites, but not for the lowland plots. The differences between mountain and lowland communities are likely related to differences in voltinism in the species present locally.

青藏高原东部尕海湿地种子库沿水位梯度的分布格局

In recent years, wetland biodiversity and vegetation on the Qinghai-Tibet Plateau have been severely degraded. The seed bank is one of the most important resources available to aid recovery of degraded wetland plant communities. Studies of seed bank heterogeneity are crucial for understanding population formation, vegetation succession, and dynamics. In this study, we investigated the seed bank along water gradients of the Gahai Lake wetland on the eastern Qinghai-Tibet Plateau. We established three sampling lines in lakeside zones and two sampling lines in submerged zones, and looked for differences between lakeside and submerged zones. Seed bank species number and evenness were the same among different sampling lines and different zones, whereas Shannons ( H ) and Simpsons ( D ) formulas revealed that diversity was higher in the lakeside zone than in the submerged zone. A comparison based on Sorensens index indicated the least diverse along the first sampling line. DCA and TWINSPAN analyses separated the sampled species into two clusters: a group consisting of the first and second sampling lines and the first sample of the third line, and a group comprising the remaining samples. Based on species rarefaction curves, more species were found to occur in submerged zones than lakeside zones, although frequency of presence of species found in both zones was similar. Comparisons of species life histories and plateau endemicity revealed that the number of endemic species in the fourth and fifth sampling lines was higher than in the first three lines. Our results indicate that a vegetational zonation pattern based on water gradients exists around Gahai Lake.

Consistent seed bank spatial structure across semi‐natural habitats determines plot sampling

AbstractQuestionSeed bank sampling remains a critical bottleneck to the quality of studies investigating community patterns in the seed bank. The main cause is a large knowledge gap in two aspects critical to sampling, i.e. spatial autocorrelation and species–area relations. The central question of this study is how the seed bank of a single plot should be sampled, in order to obtain more precise estimates on plot seed bank characteristics, without resorting to a disproportionate investment of available resources. Similar seed bank samples may then enable better plot‐based statistical inference of ecological patterns in the seed bank in community ecology studies.LocationSemi‐natural habitats in Flanders (Belgium) and northern France.MethodsWe investigated the fine‐scale spatial structure of individual seed banking species across 12 2.1 m × 2.1 m plots in three widespread habitats: temperate forest, grassland and heathland. Soil core samples (128) were collected in each plot, using a combined systematic (64) and random design (64). This enabled both geostatistical analyses of the fine‐scale spatial structure of individual species–plot combinations as well as the calculation of sampled‐based species rarefaction curves.ResultsFine‐scale (i.e. within plot) spatial seed bank structure was detected in all plots in each habitat, in at least one or usually more plant species. Over half of the species records displayed significant spatial structure – visible as a random distribution of seed clusters – with medium to strong spatial dependence between point observations of a species of ca. 30 cm. Species rarefaction curves did not attain an asymptote at the actual sampling intensity of 128 samples. Seven out of 12 extrapolated species rarefaction curves did reach an asymptote in less than 384 samples.ConclusionsUsing these consistent results in spatial structure and species–area relations across habitats, we present a method of how researchers can develop a tailor‐made seed bank design to accommodate their individual needs, abiding by simple predefined boundaries. When the tailored design samples ca. 3% of a plot surface area along a systematic grid with a mesh width of at least 30 cm, these studies will potentially significantly increase the comparability among future seed bank community studies in semi‐natural habitats.

Landscape partitioning by nocturnal rodent assemblages in the Llanos de Ojuelos, in Mexico’s Central High Plateau

AbstractAim The Llanos de Ojuelos in Mexico’s Central High Plateau supports unique Opuntia scrublands and the southernmost Chihuahuan grasslands. Although human activities have modified strongly its landscape and impacted its biodiversity at an unknown scale, such impacts are poorly known. We aimed at understanding how nocturnal rodent species distributed across the landscape and formed assemblages and on the role and integration of the different habitats at the landscape level.Location The study was carried out at 43 sites in a study area of approximately 3350 km2 in the Llanos de Ojuelos.Methods During the Spring of 2008, we surveyed nocturnal rodents, through live‐trapping. We redefined habitat classes based on log‐linear multinomial regressions of rodent captures. Species rarefaction curves and true alpha, beta and gamma diversities were calculated for the different habitat classes. A map of the different habitats was constructed based on Landsat imagery.Results We captured 458 individuals of 20 rodent species. Multinomial regressions caused the merger of 11 a priori defined habitat classes into 7. Leguminous scrub and mixed nopaleras, both secondary habitats, had the highest alpha and gamma diversity values. Closed arboreal nopaleras and grasslands had the highest within‐habitat variability (1Dβ) and the lowest area coverage. Within‐habitat 1Dβ was larger than landscape 1Dβ, because of the great overlap in rodent assemblage composition between the habitats.Main conclusions There are no ‘typical’ rodent assemblages per habitat class, but they are organized loosely and have fuzzy borders. Rodent community organization was highly species‐centred. At the landscape level, secondary habitats have a profound effect on rodent diversity and should be included in management schemes for biological conservation. The most endangered habitats seem to be the closed arboreal nopaleras and grasslands. Any conservation efforts must consider their conservation and an increase in the size of remaining patches.

Landscape complexity and spatial scale influence the relationship between remotely sensed spectral diversity and survey‐based plant species richness

AbstractQuestions: Species rarefaction curves have long been used for estimating the expected number of species as a function of sampling effort. Nonetheless, sampling species based on standard plant inventories represents an effort‐intensive approach. Hence, rarefaction based on remotely sensed information can provide a rapid tool for identifying regions with exceptional richness and turnover. The aim of this paper is to examine (i) if the rates of spectral and species accumulation are positively correlated with one another at different spatial scales, and (ii) if the strength of this correlation differs between regions of varying landscape complexity.Location: Switzerland, Europe.Methods: The plant species data were derived from the Swiss “Biodiversity Monitoring” programme. Seven Landsat ETM+ images covering the whole study area were acquired. We applied species and spectral rarefaction for five biogeographical areas ranging from flat to mountainous zones. The relative increments (rates) of the species and spectral rarefaction curves were compared using Pearson correlation together with locally weighted scatterplot smoothing (LOWESS).Results: The biogeographic regions differed from one another in both their spectral and species diversity. The relationship between spectrally‐ and species‐derived rates of accumulation was non‐significant in simple landscapes, but we observed a significant positive correlation in complex landscapes over fine‐to‐intermediate spatial scales.Conclusions: Spectral rarefaction represents a powerful tool for measuring landscape diversity and potentially predicting species diversity at regional to global spatial scales. Based on remotely sensed information, more efficient diversity‐based monitoring programmes can be developed.