Applying conservation reserve design strategies to define ecosystem monitoring priorities

In an era of unprecedented ecological upheaval, monitoring ecosystem change at large spatial scales and over long‐time frames is an essential endeavor of effective environmental management and conservation. However, economic limitations often preclude revisiting entire monitoring networks at high frequency. We aimed here to develop a prioritization strategy for monitoring networks to select a subset of existing sites that meets the principles of complementarity and representativeness of the whole ecological reality, and maximizes ecological complementarity (species accumulation) and the spatial and environmental representativeness. We applied two well‐known approaches for conservation design, the “minimum set” and the “maximal coverage” problems, using a suite of alpha and beta biodiversity metrics. We created a novel function for the R environment that performs biodiversity metric comparisons and site prioritization on a plot‐by‐plot basis. We tested our procedures using plot data provided by the Terrestrial Ecosystem Research Network (TERN) AusPlots, an Australian long‐term monitoring network of 774 vegetation and soil monitoring plots. We selected 250 plots and 80% of the total species recorded as targets for the maximal coverage and minimum set problems, respectively. We compared the subsets selected by the different biodiversity metrics in terms of complementarity and spatial and environmental representativeness. We found that prioritization based on species turnover (i.e., iterative selection of the most dissimilar plot to a cumulative sample in terms of species replacement) maximized ecological complementarity and spatial representativeness, while also providing high environmental coverage. Species richness was an unreliable metric for spatial representation. Selection based on range‐rarity‐richness was balanced in terms of complementarity and representativeness, whereas its richness‐corrected implementation failed to capture ecological and environmental variation. Prioritization based on species turnover is desirable to cover the maximum variability of the whole network. Synthesis and applications: Our results inform monitoring design and conservation priorities, which can benefit by considering the turnover component of beta diversity in addition to univariate metrics. Our tool is computationally efficient, free, and can be readily applied to any species versus sites dataset, facilitating rapid decision‐making.     

Assessing invertebrate herbivory in human‐modified tropical forest canopies

1. Studies on the effects of human‐driven forest disturbance usually focus on either biodiversity or carbon dynamics but much less is known about ecosystem processes that span different trophic levels. Herbivory is a fundamental ecological process for ecosystem functioning, but it remains poorly quantified in human‐modified tropical rainforests.
2. Here, we present the results of the largest study to date on the impacts of human disturbances on herbivory. We quantified the incidence (percentage of leaves affected) and severity (the percentage of leaf area lost) of canopy insect herbivory caused by chewers, miners, and gall makers in leaves from 1,076 trees distributed across 20 undisturbed and human‐modified forest plots in the Amazon.
3. We found that chewers dominated herbivory incidence, yet were not a good predictor of the other forms of herbivory at either the stem or plot level. Chewing severity was higher in both logged and logged‐and‐burned primary forests when compared to undisturbed forests. We found no difference in herbivory severity between undisturbed primary forests and secondary forests. Despite evidence at the stem level, neither plot‐level incidence nor severity of the three forms of herbivory responded to disturbance.
4. Synthesis. Our large‐scale study of canopy herbivory confirms that chewers dominate the herbivory signal in tropical forests, but that their influence on leaf area lost cannot predict the incidence or severity of other forms. We found only limited evidence suggesting that human disturbance affects the severity of leaf herbivory, with higher values in logged and logged‐and‐burned forests than undisturbed and secondary forests. Additionally, we found no effect of human disturbance on the incidence of leaf herbivory.

     

Bat point counts: A novel sampling method shines light on flying bat communities

Emerging technologies based on the detection of electro‐magnetic energy offer promising opportunities for sampling biodiversity. We exploit their potential by showing here how they can be used in bat point counts—a novel method to sample flying bats—to overcome shortcomings of traditional sampling methods, and to maximize sampling coverage and taxonomic resolution of this elusive taxon with minimal sampling bias. We conducted bat point counts with a sampling rig combining a thermal scope to detect bats, an ultrasound recorder to obtain echolocation calls, and a near‐infrared camera to capture bat morphology. We identified bats with a dedicated identification key combining acoustic and morphological features, and compared bat point counts with the standard bat sampling methods of mist‐netting and automated ultrasound recording in three oil palm plantation sites in Indonesia, over nine survey nights. Based on rarefaction and extrapolation sampling curves, bat point counts were similarly effective but more time‐efficient than the established methods for sampling the oil palm species pool in our study. Point counts sampled species that tend to avoid nets and those that are not echolocating, and thus cannot be detected acoustically. We identified some bat sonotypes with near‐infrared imagery, and bat point counts revealed strong sampling biases in previous studies using capture‐based methods, suggesting similar biases in other regions might exist. Our method should be tested in a wider range of habitats and regions to assess its performance. However, while capture‐based methods allow to identify bats with absolute and internal morphometry, and unattended ultrasound recorders can effectively sample echolocating bats, bat point counts are a promising, non‐invasive, and potentially competitive new tool for sampling all flying bats without bias and observing their behavior in the wild.     

How does variation in total and relative abundance contribute to gradients of species diversity?

Patterns of biodiversity provide insights into the processes that shape biological communities around the world. Variation in species diversity along biogeographical or ecological gradients, such as latitude or precipitation, can be attributed to variation in different components of biodiversity: changes in the total abundance (i.e., more‐individual effects) and changes in the regional species abundance distribution (SAD). Rarefaction curves can provide a tool to partition these sources of variation on diversity, but first must be converted to a common unit of measurement. Here, we partition species diversity gradients into components of the SAD and abundance using the effective number of species (ENS) transformation of the individual‐based rarefaction curve. Because the ENS curve is unconstrained by sample size, it can act as a standardized unit of measurement when comparing effect sizes among different components of biodiversity change. We illustrate the utility of the approach using two data sets spanning latitudinal diversity gradients in trees and marine reef fish and find contrasting results. Whereas the diversity gradient of fish was mostly associated with variation in abundance (86%), the tree diversity gradient was mostly associated with variation in the SAD (59%). These results suggest that local fish diversity may be limited by energy through the more‐individuals effect, while species pool effects are the larger determinant of tree diversity. We suggest that the framework of the ENS‐curve has the potential to quantify the underlying factors influencing most aspects of diversity change.     

Are native and non‐native pollinator friendly plants equally valuable for native wild bee communities?

Bees rely on floral pollen and nectar for food. Therefore, pollinator friendly plantings are often used to enrich habitats in bee conservation efforts. As part of these plantings, non‐native plants may provide valuable floral resources, but their effects on native bee communities have not been assessed in direct comparison with native pollinator friendly plantings. In this study, we performed a common garden experiment by seeding mixes of 20 native and 20 non‐native pollinator friendly plant species at separate neighboring plots at three sites in Maryland, USA, and recorded flower visitors for 2 years. A total of 3,744 bees (120 species) were collected. Bee abundance and species richness were either similar across plant types (midseason and for abundance also late season) or lower at native than at non‐native plots (early season and for richness also late season). The overall bee community composition differed significantly between native and non‐native plots, with 11 and 23 bee species being found exclusively at one plot type or the other, respectively. Additionally, some species were more abundant at native plant plots, while others were more abundant at non‐natives. Native plants hosted more specialized plant–bee visitation networks than non‐native plants. Three species out of the five most abundant bee species were more specialized when foraging on native plants than on non‐native plants. Overall, visitation networks were more specialized in the early season than in late seasons. Our findings suggest that non‐native plants can benefit native pollinators, but may alter foraging patterns, bee community assemblage, and bee–plant network structures.     

Mass‐ratio and complementarity effects simultaneously drive aboveground biomass in temperate Quercus forests through stand structure

Forests play a key role in regulating the global carbon cycle, a substantial portion of which is stored in aboveground biomass (AGB). It is well understood that biodiversity can increase the biomass through complementarity and mass‐ratio effects, and the contribution of environmental factors and stand structure attributes to AGB was also observed. However, the relative influence of these factors in determining the AGB of Quercus forests remains poorly understood. Using a large dataset retrieved from 523 permanent forest inventory plots across Northeast China, we examined the effects of integrated multiple tree species diversity components (i.e., species richness, functional, and phylogenetic diversity), functional traits composition, environmental factors (climate and soil), stand age, and structure attributes (stand density, tree size diversity) on AGB based on structural equation models. We found that species richness and phylogenetic diversity both were not correlated with AGB. However, functional diversity positively affected AGB via an indirect effect in line with the complementarity effect. Moreover, the community‐weighted mean of specific leaf area and height increased AGB directly and indirectly, respectively; demonstrating the mass‐ratio effect. Furthermore, stand age, density, and tree size diversity were more important modulators of AGB than biodiversity. Our study highlights that biodiversity–AGB interaction is dependent on the regulation of stand structure that can be even more important for maintaining high biomass than biodiversity in temperate Quercus forests.     

Using fractal self‐similarity to increase precision of shrub biomass estimates

We show that aerial tips are self‐similar fractals of whole shrubs and present a field method that applies this fact to improves accuracy and precision of biomass estimates of tall‐shrubs, defined here as those with diameter at root collar (DRC) ≥ 2.5 cm. Power function allometry of biomass to stem diameter generates a disproportionate prediction error that increases rapidly with diameter. Thus, biomass should be modeled as a single measure of stem diameter only if stem diameter is less than a threshold D_max. When stem diameter exceeds D_max, then the stem internode should be treated as a conic frustrum requiring two additional measures: a second, node‐adjacent diameter and a length. If the second diameter is less than D_max, then the power function allometry can be applied to the aerial tip; otherwise an additional internode is measured. This “two‐component” allometry—internodes as frustra and aerial tips as shrubs—can reduce estimated biomass error propagated to the plot‐level by as much as 50% or more where very large shrubs are present D_max is any diameter such that the ratio of single‐component to two‐component uncertainty exceeds the ratio of two‐component to single‐component measurement time. Guidelines for estimating D_max based on pilot field data are provided. Tall shrubs are increasing in abundance and distribution across Arctic, alpine, boreal, and dryland ecosystems. Estimating their biomass is important for both ecological studies and carbon accounting. Reducing field‐sample prediction error increases precision in multi‐stage modeling because additional measures efficiently improve plot‐level biomass precision, reducing uncertainty for shrub biomass estimates.     

Plant history and soil history jointly influence the selection environment for plant species in a long‐term grassland biodiversity experiment

Long‐term biodiversity experiments have shown increasing strengths of biodiversity effects on plant productivity over time. However, little is known about rapid evolutionary processes in response to plant community diversity, which could contribute to explaining the strengthening positive relationship. To address this issue, we performed a transplant experiment with offspring of seeds collected from four grass species in a 14‐year‐old biodiversity experiment (Jena Experiment). We used two‐ and six‐species communities and removed the vegetation of the study plots to exclude plant–plant interactions. In a reciprocal design, we transplanted five “home” phytometers (same origin and actual environment), five “away‐same” phytometers (same species richness of origin and actual environment, but different plant composition), and five “away‐different” phytometers (different species richness of origin and actual environment) of the same species in the study plots. In the establishment year, plants transplanted in home soil produced more shoots than plants in away soil indicating that plant populations at low and high diversity developed differently over time depending on their associated soil community and/or conditions. In the second year, offspring of individuals selected at high diversity generally had a higher performance (biomass production and fitness) than offspring of individuals selected at low diversity, regardless of the transplant environment. This suggests that plants at low and high diversity showed rapid evolutionary responses measurable in their phenotype. Our findings provide first empirical evidence that loss of productivity at low diversity is not only caused by changes in abiotic and biotic conditions but also that plants respond to this by a change in their micro‐evolution. Thus, we conclude that eco‐evolutionary feedbacks of plants at low and high diversity are critical to fully understand why the positive influence of diversity on plant productivity is strengthening through time.     

Reproductive trait differences drive offspring production in urban cavity‐nesting bees and wasps

The contrasting and idiosyncratic changes in biodiversity that have been documented across urbanization gradients call for a more mechanistic understanding of urban community assembly. The reproductive success of organisms in cities should underpin their population persistence and the maintenance of biodiversity in urban landscapes. We propose that exploring individual‐level reproductive traits and environmental drivers of reproductive success could provide the necessary links between environmental conditions, offspring production, and biodiversity in urban areas. For 3 years, we studied cavity‐nesting solitary bees and wasps in four urban green space types across Toronto, Canada. We measured three reproductive traits of each nest: the total number of brood cells, the proportion of parasite‐free cells, and the proportion of non‐emerged brood cells that were parasite‐free. We determined (a) how reproductive traits, trait diversity and offspring production respond to multiple environmental variables and (b) how well reproductive trait variation explains the offspring production of single nests, by reflecting the different ways organisms navigate trade‐offs between gathering of resources and exposure to parasites. Our results showed that environmental variables were poor predictors of mean reproductive trait values, trait diversity, and offspring production. However, offspring production was highly positively correlated with reproductive trait evenness and negatively correlated with trait richness and divergence. This suggests that a narrow range of reproductive traits are optimal for reproduction, and the even distribution of individual reproductive traits across those optimal phenotypes is consistent with the idea that selection could favor diverse reproductive strategies to reduce competition. This study is novel in its exploration of individual‐level reproductive traits and its consideration of multiple axes of urbanization. Reproductive trait variation did not follow previously reported biodiversity‐urbanization patterns; the insensitivity to urbanization gradients raise questions about the role of the spatial mosaic of habitats in cities and the disconnections between different metrics of biodiversity.     

Accelerated vegetation succession but no hydrological change in a boreal fen during 20 years of recent climate change

Northern mires (fens and bogs) have significant climate feedbacks and contribute to biodiversity, providing habitats to specialized biota. Many studies have found drying and degradation of bogs in response to climate change, while northern fens have received less attention. Rich fens are particularly important to biodiversity, but subject to global climate change, fen ecosystems may change via direct response of vegetation or indirectly by hydrological changes. With repeated sampling over the past 20 years, we aim to reveal trends in hydrology and vegetation in a pristine boreal fen with gradient from rich to poor fen and bog vegetation. We resampled 203 semi‐permanent plots and compared water‐table depth (WTD), pH, concentrations of mineral elements, and dissolved organic carbon (DOC), plant species occurrences, community structure, and vegetation types between 1998 and 2018. In the study area, the annual mean temperature rose by 1.0°C and precipitation by 46 mm, in 20‐year periods prior to sampling occasions. We found that wet fen vegetation decreased, while bog and poor fen vegetation increased significantly. This reflected a trend of increasing abundance of common, generalist hummock species at the expense of fen specialist species. Changes were the most pronounced in high pH plots, where Sphagnum mosses had significantly increased in plot frequency, cover, and species richness. Changes of water chemistry were mainly insignificant in concentration levels and spatial patterns. Although indications toward drier conditions were found in vegetation, WTD had not consistently increased, instead, our results revealed complex dynamics of WTD as depending on vegetation changes. Overall, we found significant trend in vegetation, conforming to common succession pattern from rich to poor fen and bog vegetation. Our results suggest that responses intrinsic to vegetation, such as increased productivity or altered species interactions, may be more significant than indirect effects via local hydrology to the ecosystem response to climate warming.     

Functional diversity and habitat preferences of native grassland plants and ground‐dwelling invertebrates in private gardens along an urbanization gradient

Urbanization is occurring around the globe, changing environmental conditions and influencing biodiversity and ecosystem functions. Urban domestic gardens represent a small‐grained mosaic of diverse habitats for numerous species. The challenging conditions in urban gardens support species possessing certain traits, and exclude other species. Functional diversity is therefore often altered in urban gardens. By using a multi‐taxa approach focused on native grassland plants and ground‐dwelling invertebrates with overall low mobility (snails, slugs, spiders, millipedes, woodlice, ants, rove beetles), we examined the effects of urbanization (distance to city center, percentage of sealed area) and garden characteristics on functional dispersion, functional evenness, habitat preferences and body size. We conducted a field survey in 35 domestic gardens along a rural–urban gradient in Basel, Switzerland. The various groups showed different responses to urbanization. Functional dispersion of native grassland plants decreased with increasing distance to the city center, while functional dispersion of ants decreased with increasing percentage of sealed area. Functional evenness of ants increased with increasing distance to the city center and that of rove beetles decreased with increasing percentage of sealed area. Contrary to our expectation, in rove beetles, the proportion of generalists decreased with increasing percentage of sealed area in the surroundings, and the proportion of species preferring dry conditions increased with increasing distance to the city center. Body size of species increased with distance to city center for slugs, spiders, millipedes, ants, and rove beetles. Local garden characteristics had few effects on functional diversity and habitat preferences of the groups examined. Our study supports the importance of using multi‐taxa approaches when examining effects of environmental change on biodiversity. Considering only a single group may result in misleading findings for overall biodiversity. The ground‐dwelling invertebrates investigated may be affected in different ways from the more often‐studied flying pollinators or birds.     

A genotyping‐in‐thousands by sequencing panel to inform invasive deer management using noninvasive fecal and hair samples

Studies in ecology, evolution, and conservation often rely on noninvasive samples, making it challenging to generate large amounts of high‐quality genetic data for many elusive and at‐risk species. We developed and optimized a Genotyping‐in‐Thousands by sequencing (GT‐seq) panel using noninvasive samples to inform the management of invasive Sitka black‐tailed deer (Odocoileus hemionus sitkensis) in Haida Gwaii (Canada). We validated our panel using paired high‐quality tissue and noninvasive fecal and hair samples to simultaneously distinguish individuals, identify sex, and reconstruct kinship among deer sampled across the archipelago, then provided a proof‐of‐concept application using field‐collected feces on SGang Gwaay, an island of high ecological and cultural value. Genotyping success across 244 loci was high (90.3%) and comparable to that of high‐quality tissue samples genotyped using restriction‐site associated DNA sequencing (92.4%), while genotyping discordance between paired high‐quality tissue and noninvasive samples was low (0.50%). The panel will be used to inform future invasive species operations in Haida Gwaii by providing individual and population information to inform management. More broadly, our GT‐seq workflow that includes quality control analyses for targeted SNP selection and a modified protocol may be of wider utility for other studies and systems where noninvasive genetic sampling is employed.     

Individual‐level leaf trait variation and correlation across biological and spatial scales

Even with increasing interest in the ecological importance of intraspecific trait variation (ITV) for better understanding ecological processes, few studies have quantified ITV in seedlings and assessed constraints imposed by trade‐offs and correlations among individual‐level leaf traits. Estimating the amount and role of ITV in seedlings is important to understand tree recruitment and long‐term forest dynamics. We measured ten different size, economics, and whole leaf traits (lamina and petiole) for more than 2,800 seedlings (height ≥ 10 cm and diameter at breast height < 1 cm) in 283 seedling plots and then quantified the amount of ITV and trait correlations across two biological (intraspecific and interspecific) and spatial (within and among plots) scales. Finally, we explored the effects of trait variance and sample size on the strength of trait correlations. We found about 40% (6%–63%) variation in leaf‐level traits was explained by ITV across all traits. Lamina and petiole traits were correlated across biological and spatial scales, whereas leaf size traits (e.g., lamina area) were weakly correlated with economics traits (e.g., specific lamina area); lamina mass ratio was strongly related to the petiole length. Trait correlations varied among species, plots, and different scales but there was no evidence that the strength of trait relationships was stronger at broader than finer biological and spatial scales. While larger trait variance increased the strength of correlations, the sample size was the most important factor that was negatively related to the strength of trait correlations. Our results showed that a large amount of trait variation was explained by ITV, which highlighted the importance of considering ITV when using trait‐based approaches in seedling ecology. In addition, sample size was an important factor that influenced the strength of trait correlations, which suggests that comparing trait correlations across studies should consider the differences in sample size.     

Incorporating functional dissimilarities into sample‐based rarefaction curves: from taxon resampling to functional resampling

Question: Indices of functional diversity have been seen as the key for integrating information on species richness with measures that focus on those components of community composition related to ecosystem functioning. For comparing species richness among habitats on an equal‐effort basis, so‐called sample‐based rarefaction curves may be used. Given a study area that is sampled for species presence and absence in N plots, sample‐based rarefaction generates the expected number of accumulated species as the number of sampled plots increases from 1 to N. Accordingly, the question for this study is: can we construct a ‘functional rarefaction curve’ that summarizes the expected functional dissimilarity between species when n plots are drawn at random from a larger pool of N plots? Methods: In this paper, we propose a parametric measure of functional diversity that is obtained by combining sample‐based rarefaction techniques that are usually applied to species richness with Rao's quadratic diversity. For a given set of N presence/absence plots, the resulting measure summarizes the expected functional dissimilarity at an increasingly larger cumulative number of plots n (n≤N). Results and Conclusions: Due to its parametric nature, the proposed measure is progressively more sensitive to rare species with increasing plot number, thus rendering this measure adequate for comparing the functional diversity of species assemblages that have been sampled with variable effort.     

Using genomics to guide seed‐sourcing at the right taxonomical level for ecological restoration projects: The complex case of Carex bigelowii s.lat. in Norway

There is a growing demand for ecological restoration using suitable seeds following international standards or national legal demands for local seed‐sourcing. However, before selecting the appropriate geographic origin of seeds, it is vital to explore taxonomic complexity related to the focal taxa. We used ddRAD‐seq to screen genomic diversity within Carex bigelowii s.lat. focussing on Norway. This species complex is considered a candidate for seeding, but presents considerable morphological, ecological, and genetic variation. The genetic structure of 132 individuals of C. bigelowii s.lat., including Carex nigra as an outgroup, was explored using ordinations, clustering analyses, and a genetic barrier algorithm. Two highly divergent clusters were evident, supporting the recognition of two taxonomic units “C. dacica” and C. bigelowii “subsp. bigelowii”. Previously defined seed‐sourcing regions for C. bigelowii s.lat. did not consider the known taxonomic complexity, and therefore interpreted the overall genetic structure as seed‐sourcing regions, not taxa. We estimated genetic neighborhood sizes within each taxon to be 100–150 km and 300 km, respectively, indicating species‐specific delimitations of local seed‐sourcing regions. Frequent hybrids, local genetic distinctiveness, and suggested ecotypes add complexity to the discussed seed‐sourcing regions. Our results show how genomic screening of diversity and structure in a species complex can alleviate the taxonomic impediment, inform practical questions, and legal requirements related to seed‐sourcing, and together with traditional taxonomic work provide necessary information for a sound management of biodiversity.     

Rodent‐mediated plant seed dispersal: What happens to the seeds after entering the gaps with different sizes?

In general, it is accepted that gap formation significantly affects the placement of scatter‐hoarded seeds by small rodents, but the effects of different forest gap sizes on the seed‐eating and scatter‐hoarding behaviors of small rodents remain unclear. Thus, we examined the effects of a closed‐canopy forest, forest edge, and gaps with different sizes on the spatial dispersal of Quercus variabilis acorns and cache placement by small rodents using coded plastic tags in the Taihang Mountains, China. The seeds were removed rapidly, and there were significant differences in the seed‐eating and caching strategies between the stand types. We found that Q. variabilis acorns were usually eaten after being removed from the closed‐canopy forest and forest edges. By contrast, the Q. variabilis acorns in the forest gap stands were more likely to be scatter‐hoarded. The dispersal distances of Q. variabilis acorns were significantly longer in the forest gap plots compared with the closed canopy and forest edge plots. However, the proportion of scatter‐hoarded seeds did not increase significantly as the gap size increased. In small‐scale oak reforestation projects or research, creating small gaps to promote rodent‐mediated seed dispersal may effectively accelerate forest recovery and successional processes.     

Plant–plant interactions determine natural restoration of plant biodiversity over time,in a degraded mined land

Restoration of degraded environments is essential to mitigate adverse impacts of human activities on ecosystems. Plant–plant interactions may provide effective means for restoring degraded arid lands, but little is understood about these impacts. In this regard, we analyzed the effects of two dominant nurse plants (i.e., Artemisia sieberi and Stipa arabica) on taxonomic, functional, and phylogenetic diversity across different ages of land abandonment (i.e., control, recent, and old ages) in a limestone mine site in Iran. In addition, we considered two spatial scales: i) the plot scale (i.e., under 1m2 plots) and ii) the vegetation‐patch scale (i.e., under the canopies of nurse plants), to assess nurse plant effects, land abandonment ages, and their relative importance on biodiversity facets by performing Kruskal–Wallis H test and variation partitioning analysis. Our results indicated an increase in taxonomic, functional, and phylogenetic diversity at the plot scale, when considering the presence of nurse plants under old ages of land abandonment. Such significant differences were consistent with the positive effects of Artemisia patches on taxonomic diversity and Stipa patches on functional and phylogenetic diversity. In addition, we found a larger contribution from nurse plants than land abandonment age on biodiversity variation at both spatial scales studied. Therefore, these results indicate the importance of plant–plant interactions in restoring vegetation, with their effects on the presence of beneficiary species and their functional and phylogenetic relatedness depending on the nurse life forms under the stress‐gradient hypothesis.     

Soil microarthropods respond differently to simulated drought in organic and conventional farming systems

In Central Europe, summer droughts are increasing in frequency which threatens production and biodiversity in agroecosystems. The potential of different farming systems to mitigate detrimental drought effects on soil animals is largely unknown. We investigated the effects of simulated drought on the abundance and community composition of soil microarthropods (Collembola and Oribatida and Meso‐, Pro‐, and Astigmata) in winter wheat fields under long‐term conventional and organic farming in the DOK trial, Switzerland. We simulated drought by excluding 65% of the ambient precipitation during the wheat‐growing season from March to June 2017. The abundance of Collembola and Oribatida declined more consistently in conventionally managed fields compared to organically managed fields under simulated drought. The abundance of Collembola as well as Meso‐, Pro‐ and Astigmata, but not the abundance of Oribatida, increased in deeper soil layers due to simulated drought, suggesting vertical migration as a drought avoidance strategy. The species composition of Oribatida communities, but not of Collembola communities, differed significantly between drought treatments and between farming systems. Soil carbon content was a major factor structuring Oribatida communities. Our results suggest that organic farming buffers negative effects of drought on soil microarthropods, presumably due to higher soil carbon content and associated higher soil moisture and improved soil structure. This potential of organic farming systems to mitigate consequences of future droughts on soil biodiversity is promising and needs further exploration across larger climatic and spatial scales and should be extended to other groups of soil biota.     

Plotting receiver operating characteristic and precision–recall curves from presence and background data

1. The receiver operating characteristic (ROC) and precision–recall (PR) plots have been widely used to evaluate the performance of species distribution models. Plotting the ROC/PR curves requires a traditional test set with both presence and absence data (namely PA approach), but species absence data are usually not available in reality. Plotting the ROC/PR curves from presence‐only data while treating background data as pseudo absence data (namely PO approach) may provide misleading results.
2. In this study, we propose a new approach to calibrate the ROC/PR curves from presence and background data with user‐provided information on a constant c, namely PB approach. Here, c defines the probability that species occurrence is detected (labeled), and an estimate of c can also be derived from the PB‐based ROC/PR plots given that a model with good ability of discrimination is available. We used five virtual species and a real aerial photography to test the effectiveness of the proposed PB‐based ROC/PR plots. Different models (or classifiers) were trained from presence and background data with various sample sizes. The ROC/PR curves plotted by PA approach were used to benchmark the curves plotted by PO and PB approaches.
3. Experimental results show that the curves and areas under curves by PB approach are more similar to that by PA approach as compared with PO approach. The PB‐based ROC/PR plots also provide highly accurate estimations of c in our experiment.
4. We conclude that the proposed PB‐based ROC/PR plots can provide valuable complements to the existing model assessment methods, and they also provide an additional way to estimate the constant c (or species prevalence) from presence and background data.

     

The Latent Dirichlet Allocation model with covariates (LDAcov): A case study on the effect of fire on species composition in Amazonian forests

Understanding and predicting the effect of global change phenomena on biodiversity is challenging given that biodiversity data are highly multivariate, containing information from tens to hundreds of species in any given location and time. The Latent Dirichlet Allocation (LDA) model has been recently proposed to decompose biodiversity data into latent communities. While LDA is a very useful exploratory tool and overcomes several limitations of earlier methods, it has limited inferential and predictive skill given that covariates cannot be included in the model. We introduce a modified LDA model (called LDAcov) which allows the incorporation of covariates, enabling inference on the drivers of change of latent communities, spatial interpolation of results, and prediction based on future environmental change scenarios. We show with simulated data that our approach to fitting LDAcov is able to estimate well the number of groups and all model parameters. We illustrate LDAcov using data from two experimental studies on the long‐term effects of fire on southeastern Amazonian forests in Brazil. Our results reveal that repeated fires can have a strong impact on plant assemblages, particularly if fuel is allowed to build up between consecutive fires. The effect of fire is exacerbated as distance to the edge of the forest decreases, with small‐sized species and species with thin bark being impacted the most. These results highlight the compounding impacts of multiple fire events and fragmentation, a scenario commonly found across the southern edge of Amazon. We believe that LDAcov will be of wide interest to scientists studying the effect of global change phenomena on biodiversity using high‐dimensional datasets. Thus, we developed the R package LDAcov to enable the straightforward use of this model.