Predicting species’ abundances from occurrence data: Effects of sample size and bias

Assessing abundance-suitability models to prioritize conservation areas for the dwarf caimans in South America

Species-environment relationships have been extensively explored through species distribution models (SDM) and species abundance models (SAM), which have become key components to understand the spatial ecology and population dynamics directed at biodiversity conservation. Nonetheless, within the internal structure of species' ranges, habitat suitability and species abundance do not always show similar patterns, and using information derived from either SDM or SAM could be incomplete and mislead conservation efforts. We gauged support for the abundance-suitability relationship and used the combined information to prioritize the conservation of South American dwarf caimans (Paleosuchus palpebrosus and P. trigonatus). We used 7 environmental predictor sets (surface water, human impact, topography, precipitation, temperature, dynamic habitat indices, soil temperature), 2 regressions methods (Generalized Linear Models-GLM, Generalized Additive Models-GAM), and 4 parametric distributions (Binomial, Poisson, Negative binomial, Gamma) to develop distribution and abundance models. We used the best predictive models to define four categories (low, medium, high, very high) to plan species conservation. The best distribution and abundance models for both Paleosuchus species included a combination of all predictor sets, except for the best abundance model for P. trigonatus which incorporated only temperature, precipitation, surface water, human impact, and topography. We found non-consistent and low explanatory power of environmental suitability to predict abundance which aligns with previous studies relating SDM-SAM. We extracted the most relevant information from each optimal SDM and SAM and created a consensus model (2,790,583 km2) that we categorized as low (39.6%), medium (42.7%), high (14.9%), and very high (2.8%) conservation priorities. We identified 279,338 km2 where conservation must be critically prioritized and only 29% of these areas are under protection. We concluded that optimal models from correlative methods can be used to provide a systematic prioritization scheme to promote conservation and as surrogates to generate insights for quantifying ecological patterns.

Using species distribution modeling to generate relative abundance information in socio-politically unstable territories: Conservation of Felidae in the central-western region of Mexico

The distribution range and population abundance of species provide fundamental information on the species-habitat relationship required for management and conservation. Abundance inherently provides more information about the ecology of species than do occurrence data. However, information on abundance is scarce for most species, mainly at large spatial scales. The objective of this work was, therefore, to provide information regarding the population status of six wild felids inhabiting territories in Mexico that are inaccessible or politically unstable. This was done using species distribution models derived from occurrence data. We used distribution data at a continental scale for the wild felids inhabiting Mexico: jaguar (Panthera onca), bobcat (Lynx rufus), ocelot (Leopardus pardalis), cougar (Puma concolor), margay (Leopardus wiedii), and jaguarundi (Herpailurus yagouaroundi) to predict environmental suitability (estimated by both Maxent and the distance to niche centroid, DNC). Suitability was then examined by relating to a capture rate-based index, in a well-monitored area in central western Mexico in order to assess their performance as proxies of relative abundance. Our results indicate that the environmental suitability patterns predicted by both algorithms were comparable. However, the strength of the relationship between the suitability and relative abundance of local populations differed across species and between algorithms, with the bobcat and DNC, respectively, having the best fit, although the relationship was not consistent in all the models. This paper presents the potential of implementing species distribution models in order to predict the relative abundance of wild felids in Mexico and offers guidance for the proper interpretation of the relationship between suitability and population abundance. The results obtained provide a robust information base on which to outline specific conservation actions and on which to examine the potential status of endangered species inhabiting remote or politically unstable territories in which on-field monitoring programs are not feasible.

Modeling abundance and risk impact of Vespa velutina nigrithorax (Hymenoptera: Vespidae) in Korea: application of a species abundance model

The Asian yellow-legged hornet, Vespa velutina nigrithorax, is native to Southeast Asia. However, it has invaded many countries in temperate regions, causing serious threats to honeybees and human health. With a growing demand for estimating the potential distribution of this species, multiple studies have resorted to occurrence-based models. However, they are less informative for predicting local abundance patterns associated with the species' impact. Thus, we aimed to develop an abundance-based distribution model for V. v. nigrithorax in Korea to support the forecast of its impact and associated management strategies. The abundance data of V. v. nigrithorax were collected from 254 sites for 4 years covering the country and used to develop a model with bioclimatic and land composition variables. Along with the abundance model, the classical occurrence model was tested to determine whether it could provide a reasonable prediction on the estimation of local abundance. As a result, the abundance model provided higher discriminative power and accuracy than the occurrence model to evaluate the impacts caused by V. v. nigrithorax. On the other hand, the occurrence model was not able to discriminate abundance in the areas occupied by V. v. nigrithorax, indicating an unclear occurrence-abundance relationship or oversimplification of the estimated niche created by the occurrence model. Based on the final abundance model, risk indices for human health and honeybee losses were suggested. These results could help to provide support for risk management of V. v. nigrithorax in Korea and to give biological information to other countries where this species has already become established or which it is likely to invade in the near future.

Mechanisms underpinning community stability along a latitudinal gradient: Insights from a niche-based approach

At large scales, the mechanisms underpinning stability in natural communities may vary in importance due to changes in species composition, mean abundance, and species richness. Here we link species characteristics (niche positions) and community characteristics (richness and abundance) to evaluate the importance of stability mechanisms in 156 butterfly communities monitored across three European countries and spanning five bioclimatic regions. We construct niche-based hierarchical structural Bayesian models to explain first differences in abundance, population stability, and species richness between the countries, and then explore how these factors impact community stability both directly and indirectly (via synchrony and population stability). Species richness was partially explained by the position of a site relative to the niches of the species pool, and species near the centre of their niche had higher average population stability. The differences in mean abundance, population stability, and species richness then influenced how much variation in community stability they explained across the countries. We found, using variance partitioning, that community stability in Finnish communities was most influenced by community abundance, whereas this aspect was unimportant in Spain with species synchrony explaining most variation; the UK was somewhat intermediate with both factors explaining variation. Across all countries, the diversity-stability relationship was indirect with species richness reducing synchrony which increased community stability, with no direct effects of species richness. Our results suggest that in natural communities, biogeographical variation observed in key drivers of stability, such as population abundance and species richness, leads to community stability being limited by different factors and that this can partially be explained due to the niche characteristics of the European butterfly assemblage.

Selfing rate variation within species is unrelated to life-history traits or geographic range position

PREMISE

In plants, populations and species vary widely along the continuum from outcrossing to selfing. Life-history traits and ecological circumstances influence among-species variation in selfing rates, but their general role in explaining intraspecific variation is unknown. Using a database of plant species, we test whether life-history traits, geographic range position, or abundance predict selfing rate variation among populations.

METHODS

We identified species where selfing rates were estimated in at least three populations at known locations. Two key life-history traits (generation time and growth form) were used to predict within-species selfing rate variation. Populations sampled within a species' native range were assessed for proximity to the nearest edge and abundance. Finally, we conducted linear and segmented regressions to determine functional relationships between selfing rate and geographic range position within species.

RESULTS

Selfing rates for woody species varied less than for herbs, which is explained by the lower average selfing rate of woody species. Relationships between selfing and peripherality or abundance significantly varied among species in their direction and magnitude. However, there was no general pattern of increased selfing toward range edges. A power analysis shows that tests of this hypothesis require studying many (i.e., 40+) populations.

CONCLUSIONS

Intraspecific variation in plant mating systems is often substantial yet remains difficult to explain. Beyond sampling more populations, future tests of biogeographic hypotheses will benefit from phylogeographic information concerning specific range edges, the study of traits influencing mating system (e.g., herkogamy), and measures of abundance at local scales (e.g., population density).

Geographic abundance patterns explained by niche centrality hypothesis in two Chagas disease vectors in Latin America

Ecoepidemiological scenarios for Chagas disease transmission are complex, so vector control measures to decrease human–vector contact and prevent infection transmission are difficult to implement in all geographic contexts. This study assessed the geographic abundance patterns of two vector species of Chagas disease: Triatoma maculata (Erichson, 1848) and Rhodnius pallescens (Barber, 1932) in Latin America. We modeled their potential distribution using the maximum entropy algorithm implemented in Maxent and calculated distances to their niche centroid by fitting a minimum-volume ellipsoid. In addition, to determine which method would accurately explain geographic abundance patterns, we compared the correlation between population abundance and the distance to the ecological niche centroid (DNC) and between population abundance and Maxent environmental suitability. The potential distribution estimated for T. maculata showed that environmental suitability covers a large area, from Panama to Northern Brazil. R. pallescens showed a more restricted potential distribution, with environmental suitability covering mostly the coastal zone of Costa Rica and some areas in Nicaragua, Honduras, Belize and the Yucatán Peninsula in Mexico, northern Colombia, Acre, and Rondônia states in Brazil, as well as a small region of the western Brazilian Amazon. We found a negative slope in the relationship between population abundance and the DNC in both species. R. pallecens has a more extensive potential latitudinal range than previously reported, and the distribution model for T. maculata corroborates previous studies. In addition, population abundance increases according to the niche centroid proximity, indicating that population abundance is limited by the set of scenopoetic variables at coarser scales (non-interactive variables) used to determine the ecological niche. These findings might be used by public health agencies in Latin America to implement actions and support programs for disease prevention and vector control, identifying areas in which to expand entomological surveillance and maintain chemical control, in order to decrease human–vector contact.

Quantifying range decline and remaining populations of the large marsupial carnivore of Australia’s tropical rainforest

Large predators are particularly susceptible to population declines due to large area requirements, low population density, and conflict with humans. Their low density and secretive habits also make it difficult to know the spatial extent, size, and connectivity of populations; declines hence can go unnoticed. Here, we quantified decline in a large marsupial carnivore, the spotted-tailed quoll (Dasyurus maculatus gracilis), endemic to the Wet Tropics rainforest of northeast Australia. We compiled a large database of occurrence records and used species distributional modeling to estimate the distribution in four time periods (Pre-1956, 1956–1975, 1976–1995, 1996–2016) using climate layers and three human-use variables. The most supported variables in the distribution models were climatic, with highly suitable quoll habitat having relatively high precipitation, low temperatures, and a narrow annual range in temperature. Land-use type and road density also influenced quoll distribution in some time periods. The modeling revealed a significant decline in the distribution of D. m. gracilis over the last century, with contraction away from peripheral areas and from large areas of the Atherton Tablelands in the center of the distribution. Tests of the change in patch availability for populations of 20, 50, and 100 individuals revealed a substantial (17–32%) decline in available habitat for all population sizes, with a particular decline (31–40%) in core habitat (i.e., excluding edges). Six remaining populations were defined. Extrapolating capture–recapture density estimates derived from two populations in 2017 suggests these populations are small and range from about 10 to 160 individuals. Our total population estimate sums to 424 individuals, but we outline why this estimate is positively skewed and that the actual population size may be < 300 individuals. Continued decline and apparent absence in areas of highly suitable habitat suggests some threats are not being captured in our models. From our results, we provide management and research recommendations for this enigmatic predator.

Relationships between population densities and niche-centroid distances in North American birds

Correlational ecological niche models have seen intensive use and exploration as a means of estimating the limits of actual and potential geographic distributions of species, yet their application to explaining geographic abundance patterns has been debated. We developed a detailed test of this latter possibility based on the North American Breeding Bird Survey. Correlations between abundances and niche-centroid distances were mostly negative, as per expectations of niche theory and the abundant niche-centre relationship. The negative relationships were not distributed randomly among species: terrestrial, non-migratory, small-bodied, small-niche-breadth and restricted-range species had the strongest negative associations. Distances to niche centroids as estimated from correlational analyses of presence-only data thus offer a unique means by which to infer geographic abundance patterns, which otherwise are enormously difficult to characterise.

An evaluation of the error and uncertainty in epibenthos cover estimates from AUV images collected with an efficient, spatially-balanced design

Efficient monitoring of organisms is at the foundation of protected area and biodiversity management. Such monitoring programs are based on a systematically selected set of survey locations that, while able to track trends at those locations through time, lack inference for the overall region being "monitored". Advances in spatially-balanced sampling approaches offer alternatives but remain largely untested in marine ecosystems. This study evaluated the merit of using a two-stage, spatially-balanced survey framework, in conjunction with generalized additive models, to estimate epifauna cover at a reef-wide scale for mesophotic reefs within a large, cross-shelf marine park. Imagery acquired by an autonomous underwater vehicle was classified using a hierarchical scheme developed under the Collaborative and Automated Tools for Analysis of Marine Imagery (CATAMI). At a realistic image subsampling intensity, the two-stage, spatially-balanced framework provided accurate and precise estimates of reef-wide cover for a select number of epifaunal classes at the coarsest CATAMI levels, in particular bryozoan and porifera classes. However, at finer hierarchical levels, accuracy and/or precision of cover estimates declined, primarily because of the natural rarity of even the most common of these classes/morphospecies. Ranked predictor importance suggested that bathymetry, backscatter and derivative terrain variables calculated at their smallest analysis window scales (i.e. 81 m2) were generally the most important variables in the modeling of reef-wide cover. This study makes an important step in identifying the constraints and limitations that can be identified through a robust statistical approach to design and analysis. The two-stage, spatially-balanced framework has great potential for effective quantification of epifaunal cover in cross-shelf mesophotic reefs. However, greater image subsampling intensity than traditionally applied is required to ensure adequate observations for finer-level CATAMI classes and associated morphospecies.

Habitat suitability-density relationship in an endangered woodland species: the case of the Blue Chaffinch (Fringilla polatzeki)

BACKGROUND

Understanding constraints to the distribution of threatened species may help to ascertain whether there are other suitable sectors for reducing the risks associated with species that are recorded in only one protected locality, and to inform about the suitability of other areas for reintroduction or translocation programs.

METHODS

We studied the Gran Canaria blue chaffinch (Fringilla polatzeki), a habitat specialist endemic of the Canary Islands restricted to the pine forest of Inagua, the only area where the species has been naturally present as a regular breeder in the last 25 years. A suitability distribution model using occurrences with demographic relevance (i.e., nest locations of successful breeding attempts analysed using boosted classification trees) was built considering orographic, climatic and habitat structure predictors. By means of a standardized survey program we monitored the yearly abundance of the species in 100 sectors since the declaration of Inagua as a Strict Nature Reserve in 1994.

RESULTS

The variables with the highest relative importance in blue chaffinch habitat preferences were pine height, tree cover, altitude, and rainfall during the driest trimester (July-September). The observed local abundance of the blue chaffinch in Inagua (survey data) was significantly correlated with habitat suitability derived from modelling the location of successful nesting attempts (using linear and quantile regressions). The outcomes of the habitat suitability model were used to quantify the suitability of other natural, historic, pine forests of Gran Canaria. Tamadaba is the forest with most suitable woodland patches for the species. We estimated a population size of 195-430 blue chaffinches in Inagua since 2011 (95% CI), the smallest population size of a woodland passerine in the Western Palearctic.

DISCUSSION

Habitat suitability obtained from modelling the location of successful breeding attempts is a good surrogate of the observed local abundance during the reproductive season. The outcomes of these models can be used for the identification of potential areas for the reintroduction of the species in other suitable pine forests and to inform forest management practices.

Understanding transmissibility patterns of Chagas disease through complex vector–host networks

Chagas disease is one of the most important vector-borne zoonotic diseases in Latin America. Control strategies could be improved if transmissibility patterns of its aetiologic agent, Trypanosoma cruzi, were better understood. To understand transmissibility patterns of Chagas disease in Mexico, we inferred potential vectors and hosts of T. cruzi from geographic distributions of nine species of Triatominae and 396 wild mammal species, respectively. The most probable vectors and hosts of T. cruzi were represented in a Complex Inference Network, from which we formulated a predictive model and several associated hypotheses about the ecological epidemiology of Chagas disease. We compiled a list of confirmed mammal hosts to test our hypotheses. Our tests allowed us to predict the most important potential hosts of T. cruzi and to validate the model showing that the confirmed hosts were those predicted to be the most important hosts. We were also able to predict differences in the transmissibility of T. cruzi among triatomine species from spatial data. We hope our findings help drive efforts for future experimental studies.