Using population monitoring programs to detect changes in mammalian communities

On the use of automated cameras to estimate species richness for large‐ and medium‐sized rainforest mammals

We have little knowledge of how climatic variation (and by proxy, habitat variation) influences the phylogenetic structure of tropical communities. Here, we quantified the phylogenetic structure of mammal communities in Africa to investigate how community structure varies with respect to climate and species richness variation across the continent. In addition, we investigated how phylogenetic patterns vary across carnivores, primates, and ungulates. We predicted that climate would differentially affect the structure of communities from different clades due to between-clade biological variation. We examined 203 communities using two metrics, the net relatedness (NRI) and nearest taxon (NTI) indices. We used simultaneous autoregressive models to predict community phylogenetic structure from climate variables and species richness. We found that most individual communities exhibited a phylogenetic structure consistent with a null model, but both climate and species richness significantly predicted variation in community phylogenetic metrics. Using NTI, species rich communities were composed of more distantly related taxa for all mammal communities, as well as for communities of carnivorans or ungulates. Temperature seasonality predicted the phylogenetic structure of mammal, carnivoran, and ungulate communities, and annual rainfall predicted primate community structure. Additional climate variables related to temperature and rainfall also predicted the phylogenetic structure of ungulate communities. We suggest that both past interspecific competition and habitat filtering have shaped variation in tropical mammal communities. The significant effect of climatic factors on community structure has important implications for the diversity of mammal communities given current models of future climate change.

The number of species coexisting in a community may be regulated by local factors (e.g., competitive interactions), or by regional processes (e.g., dispersal from a regional species pool). The relative importance of local and regional processes can be inferred from the shape of the relationship between local and regional species richness. We investigated this relationship in communities of fleas parasitic on small mammals at two spatial scales: between the richness of fleas on individual hosts (infracommunities) and that of fleas on host populations (component communities), and between the richness of component communities and that of the entire regional species pool. We tested linearity (proportional sampling) versus curvilinearity with an asymptote (species saturation) by plotting "local" against "regional" species richness of fleas either among host species or within host species among populations. At the two spatial scales, we found consistent curvilinear relationships between species richness of the more "local" communities and richness of the more "regional" communities. This was true across all host species in the data set and for geographic subsets, even after controlling for the influence of sampling effort on estimates of species richness, and that of host phylogeny in interspecific analyses. We also tested for density compensation in species-poor communities. There was no strong evidence for density compensation at the infracommunity level, although its existence at the component community level appeared likely. Our results suggest that identical patterns in local-versus-regional species richness observed on two different spatial scales arise via different mechanisms: infracommunities appear saturated with flea species most likely because of local processes, such as host immune defenses, whereas component communities are saturated with species through interspecific competition, possibly among larval stages.

In this study we assess the bias in estimates of bird richness in a tropical wetland. We used 18 months of data from point counts to estimate the species richness in a coastal lagoon in Oaxaca and computed eight species richness estimators. We evaluated estimate inaccuracy using the sum of total richness that we obtained with combined sampling techniques between 2006 and 2010. We selected the richness estimator of minimum inaccuracy and used randomized species accumulation curves to investigate differences in species densities obtained with 10 and 20-minute counts. To ascertain if habitat type influenced richness estimates, we compared the bird diversity associated with contrasting mangrove and estuarine environments. The total richness for the lagoon was 185 species and the jackknife 2 richness estimator showed the minimum inaccuracy. The randomized accumulation curves of 10 and 20 minutes displayed partially overlapping confidence intervals and an increasing time lag between the count durations at equivalent densities. The rarefaction curves from contrasting habitat types showed significantly higher richness and species density in the estuary while the jackknife 2 estimator indicated similar sample coverage in both habitats. We identify important consequences of the sampling methodology that we used and conclude that point count sampling resulted in incomplete species detection but facilitated comparative analyses.

Molluskan species richness and endemism on New Caledonian seamounts: Are they enhanced compared to adjacent slopes?

Detecting change in intertidal species richness on sandy beaches: calibrating across sampling designs

Although phytolith analysis is a promising tool for reconstructing the palaeovegetation in grassland ecosystems, no phytolith study has yet attempted to quantitatively reconstruct the corresponding plant community characteristics. Questions remain regarding whether or not soil phytoliths can quantitatively reflect various aspects of grassland physiognomy, and how well modern phytoliths represent the quantitative characteristics of grassland ecosystems. These are important scientific issues in the field of phytolith analysis, which require further research on the modern phytoliths of grassland ecosystems. In order to explore the potential of phytolith analysis in the temperate grassland region, we have for the first time established a modern soil phytolith reference dataset by exploring the relationships between soil phytoliths and plant species inventory data from 77 sites in the Songnen grassland in Northeast China. The results show that phytolith assemblages can clearly distinguish Leymus chinensis grassland, Stipa grassland and mesophytic herb grassland. In addition, we found that the Ic phytolith index could discriminate samples of L. chinensis grassland from the other samples, while the Iph phytolith index proved to be less reliable in the region. In addition, in terms of quantitative plant community characteristics, the soil phytoliths showed a good correspondence with plant community cover and species richness, but not with biomass and diversity index. The transfer functions established in this study can provide reliable estimates of community cover and species richness in the Songnen grassland. In addition, phytoliths are shown to have the potential to reconstruct the taxonomic abundance of the aboveground plant community. This study is a major advance in the application of phytolith analysis to the quantitative estimation of plant community characteristics, and it provides a modern phytolith reference for the quantitative reconstruction of the paleovegetation of grassland ecosystems.

ABSTRACTEcosystem engineers are organisms able to modulate environmental forces and, hence, may change the habitat conditions for other species. In so doing, ecosystem engineers may affect both species richness and evenness of communities and, in consequence, change species diversity. If these changes in community attributes are related to the magnitude of the habitat changes induced by the engineers, it seems likely that engineer species will have greater effects on diversity in sites where they cause larger habitat changes. We addressed this issue by evaluating the effects of three alpine cushion plants on species richness, evenness, and diversity of high‐Andean plant communities. Given that the difference in microclimatic conditions between cushions and the external environment increases with elevation, we proposed that these organisms should have greater effects on community attributes at higher than at lower elevation sites. Results showed that the three cushion species had positive effects on species richness, diversity, and evenness of plant communities. It was also observed that the magnitude of these effects changed with elevation: positive effects on species richness and diversity increased towards upper sites for the three cushions species, whereas positive effects on evenness increased with elevation for one cushion species but decreased with elevation for other two cushion species. These results suggest that the presence of cushions is important to maintain plant diversity in high‐Andean communities, but this positive effect on diversity seems to increase as the difference in environmental conditions between cushions and the external environment increases with elevation.

Macro-scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample-size-correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species-rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second-order Jackknife and Bootstrapping resampling methods, and Hill numbers and rarefaction. Species richness was heavily correlated with sampling effort, and only rarefaction was able to remove this effect, and we recommend this method for estimation of species richness with “big data” collections.

ABSTRACTMammalian communities living in tropical forests, particularly those in ecological transition zones, are under constant threat from human activities. In many regions, baseline data on mammal richness, occupancy, detection probability and the environmental factors that influence these metrics are lacking. As a key metric for guiding conservation decisions, species richness can be underestimated due to varying detection probabilities, leading to species being overlooked. Advances in technology and methodology have revolutionised wildlife monitoring, fostering the increase of multi‐species occupancy models (MSOMs) for efficient studies of community, shifting focus from single species to entire communities. MSOMs, hierarchical models that share information across species via random effects, address imperfect detection to provide accurate and unbiased species richness estimates. To fill this information gap, we used cameras trap data from Mpem and Djim National Park, Central Cameroun. We used generalised linear models and a model selection approach to evaluate factors affecting species detection events. Similarly, we used MSOMs within a Bayesian hierarchical framework to evaluate our initial species richness estimate at each camera trap location and to understand the influence of environmental covariates on the occupancy and detection probability of 19 vertebrates recorded in the area to inform management decisions for these species. From 915 independent photographic events obtained over 1700 days of capture, the study results highlight the importance of habitat, distance to river, normalised difference vegetation index and topographic position index (TPI) in explaining patterns of detection events. We found that forest (GLM: B 0.31, IRR 1.36, CI 0.14–0.48, p < 0.001), NDVI (GLM: B 0.31, IRR 1.36, CI 0.21–0.41, p < 0.001) and TPI (GLM: B 0.17, IRR 1.19, CI 0.08–0.26, p < 0.001) were positively associated with species detection events, whereas distance to river (GLM: B −0,19, IRR 0.83, CI 0.0.27 to (−0.11), p < 0.001) was negatively associated with species detection events. However, the mean probability of community occupancy was 0.33 ± 0.10 [2.5%–97.5% CI: 0.17, 0.54], while the mean probability of community detection was 0.07 ± 0.02 [2.5%–95% CI: 0.04, 0.12], indicating that, on average, approximately 33% of the sites are likely to be occupied by the community of interest, with a 7% probability of detection at occupied sites. After accounting for imperfect detection, the maximum occupancy and detection probability estimated from the MSOMs were 0.88 ± 0.07 (2.5%–97.5% CI: 0.71–0.98) and 0.22 ± 0.2 (2.5%–97.5% CI: 0.18–0.27) for Philantomba monticola, respectively. Globally, the community responses were close to zero and relatively weak, probably due to mixed responses at the species level. Despite their weak effect, distance to road (β: −1.53 ± 1.97 [2.5%–97.5% CI: −1.72–5.62]) and NDVI (β: −0.09 ± 0.22 [2.5%–97.5% CI: −0.50–0.38]) had a negative significant effect on occupancy. However, there were significant responses at the species level with Cephalophus nigrifrons, for example, exhibiting a strong response to NDVI. This study contributes to baseline information on the ecology of mammal communities in Central Cameroon and supports the need for future multi‐season surveys to understand the influence of temporal factors on community occupancy and richness in the area.

Planned fire is increasingly recognized as an important tool in conservation, but other factors such as land-use change may hinder the ability of land managers to use fire for the benefit of biodiversity. The mosaic of past fires in native vegetation may interact with the mosaic of other land-cover types in human-modified landscapes, yet the effects of these interactions on mammal communities are unknown. We investigated the responses of ground-dwelling mammal community composition and species richness to interactions between land cover and post-fire vegetation growth-stage mosaics in southern Australia. This fire-prone, human-modified landscape features a fine-scale fire mosaic in native vegetation patches surrounded by pasture, horticulture, and peri-urban environments. We measured the composition of land-cover types and fire mosaics (landscape structure) at multiple scales of up to 1257 ha surrounding 129 study sites, and considered native and introduced species together and separately. Land-cover composition was the primary driver of community composition: native species favored areas with a greater proportion of native heathy woodland, whereas introduced species were associated with landscapes comprising more cleared land. The fire mosaic also influenced community composition and species richness: greater growth-stage diversity was associated with native habitat-specialist communities and fewer introduced species. In areas with more cleared land, native species richness increased when there was a greater proportion of mid-successional vegetation, demonstrating that the effect of fire mosaics on mammal diversity depended on land-cover composition. The positive relationship between introduced species richness and cleared land extent was also stronger in recently burned sites than in other growth stages, suggesting that introduced species are well suited to more modified areas of the landscape. Land managers need to consider the underlying land-cover composition and the potential interactions it may have with fire mosaics and species composition. In this landscape a greater diversity of growth stages may disadvantage introduced species yet an increase in mid-successional vegetation in more modified areas would be likely to benefit native mammal communities. Our study highlights that fire management may need to be tailored depending on the context of land use and the species of interest.

The role of local and landscape level measures of greenness in modelling boreal plant species richness

We compared the assemblages of phyllostomid bats in three Neotropical rainforests with respect to species richness and assemblage structure and suggested a method to validate estimates of species richness for Neotropical bat assemblages based on mist-netting data. The fully inventoried bat assemblage at La Selva Biological Station (LS, 100 m elevation) in Costa Rica was used as a reference site to evaluate seven estimators of species richness. The Jackknife 2 method agreed best with the known bat species richness and thus was used to extrapolate species richness for an Amazonian bat assemblage (Tiputini Biodiversity Station; TBS, 200 m elevation) and an Andean premontane bat assemblage (Podocarpus National Park; BOM, 1000 m elevation) in Ecuador. Our results suggest that more than 100 bat species occur sympatrically at TBS and about 50 bat species coexist at BOM. TBS harbours one of the most species-rich bat assemblages known, including a highly diverse phyllostomid assemblage. Furthermore, we related assemblage structure to large-scale geographical patterns in floral diversity obtained from botanical literature. Assemblage structure of these three phyllostomid assemblages was influenced by differences in floral diversity at the three sites. At the Andean site, where understorey shrubs and epiphytes exhibit the highest diversity, the phyllostomid assemblage is mainly composed of understorey frugivores and nectarivorous species. By contrast, canopy frugivores are most abundant at the Amazonian site, coinciding with the high abundance of canopy fruiting trees. Assemblage patterns of other taxonomic groups also may reflect the geographical distribution patterns of floral elements in the Andean and Amazonian regions. © 2008 The Linnean Society of London, Biological Journal of the Linnean Society, 2008, 94, 617–629.

How to assess species richness along single environmental gradients? Implications of potential versus realized species distributions

SuMMARY We assessed the performance of ten incidence-based estimators of tree species richness in simulated simple random sampling with fixed-area plots. Stem diameter-limited tree species and location data came from two species-rich wet tropical forest compartments in Panama and India. Lower limits of stem diameter were 1 cm and 30 cm, respectively. Estimators varied widely in their estimates of richness and their rankings changed frequently across sites and sample designs. A gammaPoisson estimator was overall best according to a performance score of three accuracy statistics and sample size. However, until corroborated by further studies, Chao’s 1981 non-parametric estimator is recommended for forest inventories with fixed-area plots.