Hierarchical distance sampling to estimate population sizes of common lizards across a desert ecoregion

Multispecies wildlife monitoring across large geographical regions is important for effective conservation planning in response to expected impacts from climate change and land use. Unlike many species of birds, mammals, and amphibians which can be efficiently sampled using automated sensors including cameras and sound recorders, reptiles are often much more challenging to detect, in part because of their typically cryptic behavior and generally small body sizes. Although many lizard species are more active during the day which makes them easier to detect using visual encounter surveys, they may be unavailable for sampling during certain periods of the day or year due to their sensitivity to temperature. In recognition of these sampling challenges, we demonstrate application of a recent innovation in distance sampling that adjusts for temporary emigration between repeat survey visits. We used transect surveys to survey lizards at 229 sites throughout the Mojave Desert in California, USA, 2016. We estimated a total population size of 82 million (90% CI: 65–99 million) for the three most common species of lizards across this 66,830 km² ecoregion. We mapped how density at the 1‐km² scale was predicted to vary with vegetation cover and human development. We validated these results against independent surveys from the southern portion of our study area. Our methods and results demonstrate how multispecies monitoring programs spanning arid ecoregions can better incorporate information about reptiles.     

Beyond Surrogacy—A Multi‐taxon Approach to Conservation Biogeography

Biogeographic analysis of species turnover (β diversity) of plants and animals among regions often yields conflicting results, with regions of high β diversity identified for some taxonomic groups but not others. Such discordance calls into question the use of surrogate taxa to forge conservation plans. This discordance begs for a means of comparing multiple taxa across phyla in a manner that is cost‐effective, considers limitations in computer resources in certain global regions, and is understood by policy makers and land managers. As a test case for a method taking into account these considerations, we used species lists for ten organismal groups (spanning plants, vertebrates, and invertebrates) to identify regions of high β diversity using Monmonier's algorithm, a spatially explicit technique that is readily implemented and interpreted. Data were for montane (>1000 m elevation) species across the Eastern Arc of Tanzania and Kenya and surrounding areas. Our results indicate that surrogacy does not make for the most effective expenditure of conservation efforts. We also show that to use a multi‐taxon approach one need not rely on intensive surveys of areas in order to make conservation decisions, including reserve selection. Our approach also eliminates the need for complex modeling and comparisons common to many GIS‐based complementarity techniques. Additionally, a wide variety of socioeconomic, political, demographic, geological, climatological, and evolutionary factors can be incorporated into the technique to help shape conservation biogeography from a local and regional perspective. This technique can bridge the gap between conservation biogeography theory and application in tropical regions and beyond.     

Highly incomplete taxa can rescue phylogenetic analyses from the negative impacts of limited taxon sampling

Background

Phylogenies are essential to many areas of biology, but phylogenetic methods may give incorrect estimates under some conditions. A potentially common scenario of this type is when few taxa are sampled and terminal branches for the sampled taxa are relatively long. However, the best solution in such cases (i.e., sampling more taxa versus more characters) has been highly controversial. A widespread assumption in this debate is that added taxa must be complete (no missing data) in order to save analyses from the negative impacts of limited taxon sampling. Here, we evaluate whether incomplete taxa can also rescue analyses under these conditions (empirically testing predictions from an earlier simulation study).

Methodology/Principal Findings

We utilize DNA sequence data from 16 vertebrate species with well-established phylogenetic relationships. In each replicate, we randomly sample 4 species, estimate their phylogeny (using Bayesian, likelihood, and parsimony methods), and then evaluate whether adding in the remaining 12 species (which have 50, 75, or 90% of their data replaced with missing data cells) can improve phylogenetic accuracy relative to analyzing the 4 complete taxa alone. We find that in those cases where sampling few taxa yields an incorrect estimate, adding taxa with 50% or 75% missing data can frequently (>75% of relevant replicates) rescue Bayesian and likelihood analyses, recovering accurate phylogenies for the original 4 taxa. Even taxa with 90% missing data can sometimes be beneficial.

Conclusions

We show that adding taxa that are highly incomplete can improve phylogenetic accuracy in cases where analyses are misled by limited taxon sampling. These surprising empirical results confirm those from simulations, and show that the benefits of adding taxa may be obtained with unexpectedly small amounts of data. These findings have important implications for the debate on sampling taxa versus characters, and for studies attempting to resolve difficult phylogenetic problems.     

Phylogenetic analysis of RAD‐seq data: examining the influence of gene genealogy conflict on analysis of concatenated data

One of the major issues in phylogenetic analysis is that gene genealogies from different gene regions may not reflect the true species tree or history of speciation. This has led to considerable debate about whether concatenation of loci is the best approach for phylogenetic analysis. The application of Next‐generation sequencing techniques such as RAD‐seq generates thousands of relatively short sequence reads from across the genomes of the sampled taxa. These data sets are typically concatenated for phylogenetic analysis leading to data sets that contain millions of base pairs per taxon. The influence of gene region conflict among so many loci in determining the phylogenetic relationships among taxa is unclear. We simulated RAD‐seq data by sampling 100 and 500 base pairs from alignments of over 6000 coding regions that each produce one of three highly supported alternative phylogenies of seven species of Drosophila. We conducted phylogenetic analyses on different sets of these regions to vary the sampling of loci with alternative gene trees to examine the effect on detecting the species tree. Irrespective of sequence length sampled per region and which subset of regions was used, phylogenetic analyses of the concatenated data always recovered the species tree. The results suggest that concatenated alignments of Next‐generation data that consist of many short sequences are robust to gene tree/species tree conflict when the goal is to determine the phylogenetic relationships among taxa.     

The ‘standardized search’: An improved way to conduct bird surveys

Abstract Bird surveys are among the most widely used biodiversity inventories and serve as the basis for an increasing proportion of pure and applied ecological research. It is rarely possible to conduct exhaustive censuses of all individuals present at a particular site, so stopping rules are routinely used to determine when sampling should finish. Most bird survey methods use (implicit) effort‐based stopping rules, either fixed times, fixed sampling areas (quadrats) or both, to standardize samples of different sites. If between‐site variation is high, however, a fixed sampling effort will generate samples of variable completeness with samples from smaller, less complex sites being more representative and complete than samples from larger, more complex sites. More importantly, quadrat‐based methods shift the scope of the overall study from bird occurrence in sites to bird occurrence in quadrats within sites, diminishing the impact of the research given that results cannot be extrapolated to relevant biological and management scales. Here I advocate an alternative means of conducting bird surveys, whereby the entire site is sampled and a results‐based stopping rule is used to ensure sample completeness is uniform across all sites. For example, a researcher may decide to continue sampling each site until two or fewer previously unencountered species are recorded in a 40‐min period. Samples of different sites will vary in both area and duration but will all be equivalently accurate estimates of species richness. This approach allows the avifauna of entire sites (whether territories, woodland remnants or catchments) to be sampled and compared directly, generating results and implications at the appropriate scale. In addition to yielding reliable measures of species richness, data collected this way can be used to calculate estimates of sample completeness and species incidence, two valuable metrics for ecological studies. This paper includes detailed worked examples of how to conduct a ‘standardized search’ and calculate sample completeness and species incidence estimates. I encourage further research on bird survey methods, and suggest that most current methods are insufficient, inconsistent and unreliable.     

Predicting species distributions based on incomplete survey data: the trade‐off between precision and scale

Systematic species surveys over large areas are mostly not affordable, constraining conservation planners to make best use of incomplete data. Spatially explicit species distribution models (SDM) may be useful to detect and compensate for incomplete information. SDMs can either be based on standardized, systematic sampling in a restricted subarea, or – as a cost‐effective alternative – on data haphazardly collated by “volunteer‐based monitoring schemes” (VMS), area‐wide but inherently biased and of heterogeneous spatial precision. Using data on capercaillie Tetrao urogallus, we evaluated the capacity of SDMs generated from incomplete survey data to localise unknown areas inhabited by the species and to predict relative local observation density. Addressing the trade‐off between data precision, sample size and spatial extent of the sampling area, we compared three different sampling strategies: VMS‐data collected throughout the whole study area (7000 km²) using either 1) exact locations or 2) locations aggregated to grid cells of the size of an average individual home range, and 3) systematic transect counts conducted within a small subarea (23.8 km²). For each strategy, we compared two sample sizes and two modelling methods (ENFA and Maxent), which were evaluated using cross‐validation and independent data. Models based on VMS‐data (strategies 1 and 2) performed equally well in predicting relative observation density and in localizing “unknown” occurrences. They always outperformed strategy 3‐models, irrespective of sample size and modelling method, partly because the VMS‐data provided the more comprehensive clues for setting the discrimination‐threshold for predicting presence or absence. Accounting for potential errors due to extrapolation (e.g. projections outside the environmental domain or potentially biasing variables) reduced, but did not fully compensate for the observed discrepancies. As they cover a broader range of species‐habitat relations, the area‐wide data achieved a better model quality with less a‐priori knowledge. Furthermore, in a highly mobile species like capercaillie a sampling resolution corresponding to an individuals' home range can lead to equally good predictions as the use of exact locations. Consequently, when a trade‐off between the sampling effort and the spatial extent of the sampling area is necessary, less precise data unsystematically collected over a large representative region are preferable to systematically sampled data from a restricted region.     

Towards systematic and evidence‐based conservation planning for western chimpanzees

As animal populations continue to decline, frequently driven by large‐scale land‐use change, there is a critical need for improved environmental planning. While data‐driven spatial planning is widely applied in conservation, as of yet it is rarely used for primates. The western chimpanzee (Pan troglodytes verus) declined by 80% within 24 years and was uplisted to Critically Endangered by the IUCN Red List of Threatened Species in 2016. To support conservation planning for western chimpanzees, we systematically identified geographic areas important for this taxon. We based our analysis on a previously published data set of modeled density distribution and on several scenarios that accounted for different spatial scales and conservation targets. Across all scenarios, typically less than one‐third of areas we identified as important are currently designated as high‐level protected areas (i.e., national park or IUCN category I or II). For example, in the scenario for protecting 50% of all chimpanzees remaining in West Africa (i.e., approximately 26,500 chimpanzees), an area of approximately 60,000 km² was selected (i.e., approximately 12% of the geographic range), only 24% of which is currently designated as protected areas. The derived maps can be used to inform the geographic prioritization of conservation interventions, including protected area expansion, “no‐go‐zones” for industry and infrastructure, and conservation sites outside the protected area network. Environmental guidelines by major institutions funding infrastructure and resource extraction projects explicitly require corporations to minimize the negative impact on great apes. Therefore, our results can inform avoidance and mitigation measures during the planning phases of such projects. This study was designed to inform future stakeholder consultation processes that could ultimately integrate the conservation of western chimpanzees with national land‐use priorities. Our approach may help in promoting similar work for other primate taxa to inform systematic conservation planning in times of growing threats.     

Acoustic estimation of wildlife abundance: methodology for vocal mammals in forested habitats

Habitat loss and hunting pressure threaten mammal populations worldwide, generating critical time constraints on trend assessment. This study introduces a new survey method that samples continuously and non‐invasively over long time periods, obtaining estimates of abundance from vocalization rates. We present feasibility assessment methods for acoustic surveys and develop equations for estimating population size. As an illustration, we demonstrate the feasibility of acoustic surveys for African forest elephants (Loxodonta africana cyclotis). Visual surveys and vocalizations from a forest clearing in the Central African Republic were used to establish that low‐frequency elephant calling rate is a useful index of elephant numbers (linear regression P < 0.001, r_adj.² = 0.58). The effective sampling area was 3.22 km² per acoustic sensor, a dramatic increase in coverage over dung survey transects. These results support the use of acoustic surveys for estimating elephant abundance over large remote areas and in diverse habitats, using a distributed network of acoustic sensors. The abundance estimation methods presented can be applied in surveys of any species for which an acoustic abundance index and detection function have been established. This acoustic survey technique provides an opportunity to improve management and conservation of many acoustically‐active taxa whose populations are currently under‐monitored.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.     

Simulations inform design of regional occupancy‐based monitoring for a sparsely distributed,territorial species

Sparsely distributed species attract conservation concern, but insufficient information on population trends challenges conservation and funding prioritization. Occupancy‐based monitoring is attractive for these species, but appropriate sampling design and inference depend on particulars of the study system. We employed spatially explicit simulations to identify minimum levels of sampling effort for a regional occupancy monitoring study design, using white‐headed woodpeckers (Picoides albolvartus), a sparsely distributed, territorial species threatened by habitat decline and degradation, as a case study. We compared the original design with commonly proposed alternatives with varying targets of inference (i.e., species range, space use, or abundance) and spatial extent of sampling. Sampling effort needed to achieve adequate power to observe a long‐term population trend (≥80% chance to observe a 2% yearly decline over 20 years) with the previously used study design consisted of annually monitoring ≥120 transects using a single‐survey approach or ≥90 transects surveyed twice per year using a repeat‐survey approach. Designs that shifted inference toward finer‐resolution trends in abundance and extended the spatial extent of sampling by shortening transects, employing a single‐survey approach to monitoring, and incorporating a panel design (33% of units surveyed per year) improved power and reduced error in estimating abundance trends. In contrast, efforts to monitor coarse‐scale trends in species range or space use with repeat surveys provided extremely limited statistical power. Synthesis and applications. Sampling resolutions that approximate home range size, spatially extensive sampling, and designs that target inference of abundance trends rather than range dynamics are probably best suited and most feasible for broad‐scale occupancy‐based monitoring of sparsely distributed territorial animal species.     

Range‐constrained co‐occurrence simulation reveals little niche partitioning among rock‐dwelling Montenegrina land snails (Gastropoda: Clausiliidae)

Aim

Taxon co‐occurrence analysis is commonly used in ecology, but it has not been applied to range‐wide distribution data of partly allopatric taxa because existing methods cannot differentiate between distribution‐related effects and taxon interactions. Our first aim was to develop a taxon co‐occurrence analysis method that is also capable of taking into account the effect of species ranges and can handle faunistic records from museum databases or biodiversity inventories. Our second aim was to test the independence of taxon co‐occurrences of rock‐dwelling gastropods at different taxonomic levels, with a special focus on the Clausiliidae subfamily Alopiinae, and in particular the genus Montenegrina.

Location

Balkan Peninsula in south‐eastern Europe (46N–36N, 13.5E–28E).

Methods

We introduced a taxon‐specific metric that characterizes the occurrence probability at a given location. This probability was calculated as a distance‐weighted mean of the taxon's presence and absence records at all sites. We applied corrections to account for the biases introduced by varying sampling intensity in our dataset. Then we used probabilistic null‐models to simulate taxon distributions under the null hypothesis of no taxon interactions and calculated pairwise and cumulated co‐occurrences. Independence of taxon occurrences was tested by comparing observed co‐occurrences to simulated values.

Results

We observed significantly fewer co‐occurrences among species and intra‐generic lineages of Montenegrina than expected under the assumption of no taxon interaction.

Main conclusions

Fewer than expected co‐occurrences among species and intra‐generic clades indicate that species divergence preceded niche partitioning. This suggests a primary role of non‐adaptive processes in the speciation of rock‐dwelling gastropods. The method can account for the effects of distributional constraints in range‐wide datasets, making it suitable for testing ecological, biogeographical, or evolutionary hypotheses where interactions of partly allopatric taxa are in question.     

A cryptic genetic boundary in remnant populations of a long‐lived,bird‐pollinated shrub Banksia sphaerocarpa var. caesia (Proteaceae)

Plant species often exhibit genetic structure at multiple spatial scales. Detection of this structure may depend on the sampling strategy used. We intensively sampled a common, naturally patchy Banksia species within a 200 km² region, in order to assess patterns of genetic diversity and structure at multiple spatial scales. In total, 1321 adult shrubs from 37 geographical populations were genotyped using eight highly polymorphic microsatellite markers developed for the species. Genetic structure was detected at three spatial scales. First, we identified a stark and unexpected division of the landscape into two genetic subregions, one to the north‐east and one to the south‐west of the sampling grid. This differentiation was based on sudden, highly structured differences in common allele frequencies, the cause of which is unknown but that may relate to physical and reproductive barriers to gene flow, localised selection, and/or historical processes. Second, we observed genetic differentiation of populations within these subregions, reflecting previously described patterns of restricted pollen flow in this species. Finally, fine‐scale genetic structure, although weak, was observed within some of the populations (mean S_P = 0.01837). When feasible, intensive sampling may uncover cryptic patterns of genetic structure that would otherwise be overlooked when sampling at broader spatial scales. Further studies using a similar sampling strategy may reveal this type of discontinuity to be a feature of other south‐western Australian taxa and has implications for our understanding of evolution in this landscape as well as conservation into the future. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115 , 241–255.     

A novel supermatrix approach improves resolution of phylogenetic relationships in a comprehensive sample of danthonioid grasses

Phylogeny reconstruction is challenging when branch lengths vary and when different genetic loci show conflicting signals. The number of DNA sequence characters required to obtain robust support for all the nodes in a phylogeny becomes greater with denser taxon sampling. We test the usefulness of an approach mixing densely sampled, variable non-coding sequences (trnL-F; rpl16; atpB-rbcL; ITS) with sparsely sampled, more conservative protein coding and ribosomal sequences (matK; ndhF; rbcL; 26S), for the grass subfamily Danthonioideae. Previous phylogenetic studies of Danthonioideae revealed extensive generic paraphyly, but were often impeded by insufficient character and taxon sampling and apparent inter-gene conflict. Our variably-sampled supermatrix approach allowed us to represent 79% of the species with up to c. 9900 base pairs for taxa representing the major clades. A 'taxon duplication' approach for taxa with conflicting phylogenetic signals allowed us to combine the data whilst representing the differences between chloroplast and nuclear encoded gene trees. This approach efficiently improves resolution and support whilst maximising representation of taxa and their sometimes composite evolutionary histories, resulting in a phylogeny of the Danthonioideae that will be useful both for a wide range of evolutionary studies and to inform forthcoming realignment of generic delimitations in the subfamily.     

Using citizen‐based survey data to determine densities of large mammals: a case study from Mana Pools National Park,Zimbabwe

Since 1993, members of the national wildlife society have undertaken annual surveys of large mammals in the Zambezi alluvial woodlands of Mana Pools National Park, Zimbabwe. Data are collected along 36 systematically‐arranged transects. We provide the first thorough assessment of the data from any survey within this long‐term project. The transect data from 2011 were analysed with DISTANCE software to assess if the data were suitable for determining the densities of large mammals using distance sampling techniques. Successful application of distance sampling depended on observers using printed, large‐scale, georeferenced satellite images onto which they mapped the location of animal groups detected. The assumptions of the distance sampling were well met and thus the 2011 survey provided reliable estimates of the densities of nine species of common large mammals on the Zambezi alluvium during the late dry season. Estimated density in this dry‐season concentration area varied from 3.6 km^?2 for kudu, to 204 km^?2 for impala. The precision of the estimates ranged from a coefficient of variation of 7.9% for elephant, to 25.5% for buffalo. For elephant, warthog and baboon, the morning and afternoon densities differed significantly.     

Genome‐skimming provides accurate quantification for pollen mixtures

Studies on foraging partitioning in pollinators can provide critical information to the understanding of food‐web niche and pollination functions, thus aiding conservation. Metabarcoding based on PCR amplification and high‐throughput sequencing has seen increasing applications in characterizing pollen loads carried by pollinators. However, amplification bias across taxa could lead to unpredictable artefacts in estimation of pollen compositions. We examined the efficacy of a genome‐skimming method based on direct shotgun sequencing in quantifying mixed pollen, using mock samples (five and 14 mocks of flower and bee pollen, respectively). The results demonstrated a high level of repeatability and accuracy in identifying pollen from mixtures of varied species ratios. All pollen species were detected in all mocks, and pollen frequencies estimated from the number of sequence reads of each species were significantly correlated with pollen count proportions (linear model, R² = 86.7%, p = 2.2e?16). For >97% of the mixed taxa, pollen proportion could be quantified by sequencing to the correct order of magnitude, even for species which constituted only 0.2% of the total pollen. In addition, DNA extracted from pollen grains equivalent to those collected from a single honeybee corbicula was sufficient for genome‐skimming. We conclude that genome‐skimming is a feasible approach to identifying and quantifying mixed pollen samples. By providing reliable and sensitive taxon identification and relative abundance, this method is expected to improve our understanding in studies that involve plant–pollinator interactions, such as pollen preference in corbiculate bees, pollen diet analyses and identification of landscape pollen resource use from beehives.     

Comparing four simple,inexpensive methods for sampling forest arthropod communities

Terrestrial arthropods are diverse, and quantifying their availability to consumers is important for understanding both consumer and insect distribution, abundance, and communities. However, characterizing arthropod communities in complex forest ecosystems is challenging. We compared arthropod communities in a wet‐limestone forest in Jamaica during the dry season sampled by four methods: branch clips, sweep netting, and sticky traps applied to tree trunks and hanging free of vegetation. We found no effect of relative height in the canopy for the two methods that could be used at different heights, i.e., hanging sticky traps and branch clips. In addition, the arthropod community sampled changed over time (season) for sweep nets and branch clips. We also found that branch clips and sweep nets sampled more arthropod taxa than the two sticky‐trap methods. In addition, branch clips and sweep nets sampled more ants and spiders than the two sticky‐trap methods, whereas collar sticky traps on tree trunks sampled more bark lice (Psocoptera), and hanging sticky traps more flies (Diptera) than the other methods. Percentages of flying insects and strong‐flying insects sampled did not differ between sweep netting and branch clipping, but a higher percentage of both groups were captured with collar and hanging sticky traps. Because we found that the different methods sampled different subsets of the arthropod community, both taxonomically and in terms of aerial versus non‐aerial taxa, investigators should choose the arthropod sampling methods that most closely align with their focal species and study questions. For example, investigators might use collar traps for studies of bark gleaners, hanging sticky traps for aerial foragers, and branch clips or sweep nets for foliage gleaners. Alternatively, if a focal species is known to prefer certain prey items, investigators may instead select a method that effectively samples those prey taxa. Finally, for some studies, using multiple sampling methods may be the best option.     

Optimal taxonomic groups for biodiversity assessment: a meta‐analytic approach

A fundamental decision in biodiversity assessment is the selection of one or more study taxa, a choice that is often made using qualitative criteria such as historical precedent, ease of detection, or available technical or taxonomic expertise. A more robust approach would involve selecting taxa based on the a priori expectation that they will provide the best possible information on unmeasured groups, but data to inform such hypotheses are often lacking. Using a global meta‐analysis, we quantified the proportion of variability that each of 12 taxonomic groups (at the Order level or above) explained in the richness or composition of other taxa. We then applied optimization to matrices of pairwise congruency to identify the best set of complementary surrogate groups. We found that no single taxon was an optimal surrogate for both the richness and composition of unmeasured taxa if we used simple methods to aggregate congruence data between studies. In contrast, statistical methods that accounted for well‐known drivers of cross‐taxon congruence (spatial extent, grain size, and latitude) lead to the prioritization of similar surrogates for both species richness and composition. Advanced statistical methods were also more effective at describing known ecological relationships between taxa than simple methods, and show that congruence is typically highest between taxonomically and functionally dissimilar taxa. Birds and vascular plants were most frequently selected by our algorithm as surrogates for other taxonomic groups, but the extent to which any one taxon was the ‘optimal’ choice of surrogate for other biodiversity was highly context‐dependent. In the absence of other information – such as in data‐poor areas of the globe, and under limited budgets for monitoring or assessment – ecologists can use our results to assess which taxa are most likely to reflect the distribution of the richness or composition of ‘total’ biodiversity.     

Shortcuts in biodiversity research: What determines the performance of higher taxa as surrogates for species?

Biodiversity research is often impeded by the time and resources required to identify species. One possible solution is to use higher taxa to predict species richness and community composition. However, previous studies have shown that the performance of higher taxa as surrogates for species is highly variable, making it difficult to predict whether the method will be reliable for a particular objective. Using 8 independent datasets, I tested whether higher taxa accurately characterize the responses of beetle and ant communities to environmental drivers. For each dataset, ordinations were carried out using species and higher taxa, and the two compared using the Procrustes m² statistic (a scale‐independent variant of Procrustes sum of squares). I then modelled the relationship between five hypothesised explanatory variables and 1) Procrustes m², and 2) the coefficient of determination (R²) for the correlation between richness of species and higher taxa. The species to higher taxon ratio, community structure, beta diversity, completeness of sampling, and taxon (beetles or ants) were all significant predictors of m², together explaining 88% of the variance. The only significant predictor of R² was the species to higher taxon ratio, which explained 45% of the variance. When using higher taxa to predict community composition, better performance is expected when the ratio of species to higher taxa is low, in communities with high evenness and high species turnover, and when there is niche conservation within higher taxa. When using higher taxa to predict species richness, effective surrogacy can be expected when the species to higher taxon ratio is very low. When it is not, surrogacy performance may be strongly influenced by stochastic factors, making predictions of performance difficult.     

Long‐term population monitoring of the threatened and endemic black‐headed squirrel monkey (Saimiri vanzolinii) shows the importance of protected areas for primate conservation in Amazonia

Population monitoring of endangered species is essential to the improvement of their management and conservation plans. The black‐headed squirrel monkey (Saimiri vanzolinii) is a vulnerable species on the IUCN Red List and has extreme geographical endemism, exhibiting the smallest known distribution among Neotropical primates (ca. 870 km²), over 90% of which occurs in white‐water flooded forests within the Mamirauá Sustainable Development Reserve (MSDR), Brazilian Amazonia. To assess the effectiveness of this protected area in conserving the species, we conducted population monitoring of black‐headed squirrel monkeys across five consecutive years (2009–2013) on nine trails 2 km each. Each year samples included both low and high river water periods. We used the distance sampling method, recording the distance to each observed social group as well as counting component individuals. We also calculated annual encounter rates based on the number of individuals sighted every 10 km traveled. Densities ranged from 256 individuals/km² (2011) to 453 individuals/km² (2013), and no seasonal differences were detected. Population size was estimated to be 147,848 mature individuals. Encounter rates ranged from 100 individuals/10 km (2010) to 179 individuals/10 km (2013); no significant difference among years was found. We found that S. vanzolinii populations remained stable throughout the years, which indicates that the MSDR has been playing an essential role on protecting this species. Due to difficulties of fulfilling assumptions of the distance sampling method, we consider the encounter rate analysis to be more effective for monitoring this and other Saimiri species. Given the critical endemism and worrying conservation status of S. vanzolinii, we suggest that monitoring of the species population should be carried out regularly.     

Characterising the phytophagous arthropod fauna of a single host plant species: assessing survey completeness at continental and local scales

Quantifying survey completeness is a key step in designing and interpreting biodiversity assessments. To date this has only been examined either at a local scale through repetitive sampling, or across broader geographic areas through multiple survey sites. In this paper, we determine the completeness of sampling at both local and continental scales, of the phytophagous arthropod assemblage on the Neotropical shrub Parkinsonia aculeata (Leguminosae). We used survey gap analysis (SGA) to determine whether existing surveys adequately sampled the diversity of environments and geographic space covered by the plant. Within defined geographic regions, we determined survey completeness at a local scale with species accumulation curves. SGA identified the highest priority sites for future sampling in the Sonoran Desert and the Pacific Coast of South America. The arthropods sampled on P. aculeata differed significantly between seasons, highlighting the importance of including surveys throughout the year. At the local scale, surveys in most regions were estimated to have sampled <50 % of all species. Only the Mexican Gulf, following 84 samples including 902 individuals, had a reasonably complete sample of all species (more than 50 %). As in other studies, rare species will continue to be detected even after extensive surveying, and it is likely that close to 100 samples or 1,000 individuals will be needed to attain 50 % survey completeness in a region. However, if the objective is to document close “host-associations” then effort may be better directed at surveying ecologically distinct new areas rather than exhaustive sampling in existing ones. Methods such as SGA can direct such surveys, and in conjunction with species-richness estimates, can be used to assess the adequacy of existing surveys.