Predicting regional densities from bird occurrence data: validation and effects of species traits in a Macaronesian Island

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.

Niche position and niche breadth effects on population abundances: A case study of New World Warblers (Parulidae)

Species abundance patterns are influenced by a myriad of factors, including habitat availability and ecological niche characteristics. However, the evidence concerning the specific impact factors such as niche position and niche breadth on mean and maximum abundances in vertebrates at a broad geographical scale remains inconclusive. In this study, we investigated the influence of niche position and breadth on the abundance of 47 species of birds belonging to the Parulidae family, commonly known as New World Warblers. We obtained data on abundance and presence records spanning the reproductive distribution of these species and employed the outlying mean index analysis to calculate niche position and niche breadth. We assessed the relationship between abundance metrics and niche descriptors using phylogenetic regressions to account for the non-independence resulting from phylogenetic ancestry. Initially, we developed individual models for each predictor and subsequently formulated a multi-predictor model encompassing niche position, niche breadth, and their interaction. Our findings revealed a negative relationship between niche position and both mean and maximum abundance, while niche breadth exhibited a positive relationship with these niche characteristics. Notably, the results of the multi-predictor models indicated that niche position exerted the most substantial influence on both mean and maximum abundance. Additionally, the interaction between niche position and niche breadth had the most positive and significant contribution to mean population abundance. This study underscores the need for future research in other vertebrates to delve into the mechanisms underlying these patterns. Such endeavors will not only enhance our understanding of ecological dynamics but also equip us with predictive capabilities to anticipate population responses to environmental changes effectively.

The effectiveness of species distribution models in predicting local abundance depends on model grain size

The use of species distribution models (SDMs) to predict local abundance has been often proposed and contested. We tested whether SDMs at different spatiotemporal resolutions may predict the local density of 14 bird species of open/semi-open habitats. SDMs were built at 1 ha and 1 km, and with long-term versus a mix of current and long-term climatic variables. The estimated environmental suitability was used to predict local abundance obtained by means of 275 linear transects. We tested SDM ability to predict abundance for all sampled sites versus occurrence sites, using N-mixture models to account for imperfect detection. Then, we related the R2 of N-mixture models to SDM traits. Fine-grain SDMs appeared generally more robust than large-grain ones. Considering the all-transects models, for all species environmental suitability displayed a positive and highly significant effect at all the four combinations of spatial and temporal grains. When focusing only on occurrence transects, at the 1 km grain only one species showed a significant and positive effect. At the 1 ha grain, 62% of species models showed (over both climatic sets) a significant or nearly significant positive effect of environmental suitability on abundance. Grain was the only factor significantly affecting the model's explanatory power: 1 km grain led to lower amounts of variation explained by models. Our work re-opens the debate about predicting abundance using SDM-derived suitability, emphasizing the importance of grains and of spatiotemporal resolution more in general. The incorporation of local variables into SDMs at fine grains is key to predict local abundance. SDMs worked out at really fine grains, approaching the average size of territory or home range of target species, are needed to predict local abundance effectively. This may result from the fact that each single cell may represent a potential territory/home range, and hence a higher suitability over a given area means that more potential territories occur there.

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.

Landscape-level heterogeneity of agri-environment measures improves habitat suitability for farmland birds

Agri-environment schemes (AESs), ecological focus areas (EFAs), and organic farming are the main tools of the common agricultural policy (CAP) to counteract the dramatic decline of farmland biodiversity in Europe. However, their effectiveness is repeatedly doubted because it seems to vary when measured at the field-versus-landscape level and to depend on the regional environmental and land-use context. Understanding the heterogeneity of their effectiveness is thus crucial to developing management recommendations that maximize their efficacy. Using ensemble species distribution models and spatially explicit field-level information on crops grown, farming practice (organic/conventional), and applied AES/EFA from the Integrated Administration and Control System, we investigated the contributions of five groups of measures (buffer areas, cover crops, extensive grassland management, fallow land, and organic farming) to habitat suitability for 15 farmland bird species in the Mulde River Basin, Germany. We used a multiscale approach to identify the scale of effect of the selected measures. Using simulated land-use scenarios, we further examined how breeding habitat suitability would change if the measures were completely removed and if their adoption by farmers increased to meet conservation-informed targets. Buffer areas, fallow land, and extensive grassland were beneficial measures for most species, but cover crops and organic farming had contrasting effects across species. While different measures acted at different spatial scales, our results highlight the importance of land-use management at the landscape level-at which most measures had the strongest effect. We found that the current level of adoption of the measures delivers only modest gains in breeding habitat suitability. However, habitat suitability improved for the majority of species when the implementation of the measures was increased, suggesting that they could be effective conservation tools if higher adoption levels were reached. The heterogeneity of responses across species and spatial scales indicated that a mix of different measures, applied widely across the agricultural landscape, would likely maximize the benefits for biodiversity. This can only be achieved if the measures in the future CAP will be cooperatively designed in a regionally targeted way to improve their attractiveness for farmers and widen their uptake.

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).

Species distribution models for invasive Eurasian watermilfoil highlight the importance of data quality and limitations of discrimination accuracy metrics

AIM

Availability of uniformly collected presence, absence, and abundance data remains a key challenge in species distribution modeling (SDM). For invasive species, abundance and impacts are highly variable across landscapes, and quality occurrence and abundance data are critical for predicting locations at high risk for invasion and impacts, respectively. We leverage a large aquatic vegetation dataset comprising point-level survey data that includes information on the invasive plant Myriophyllum spicatum (Eurasian watermilfoil) to: (a) develop SDMs to predict invasion and impact from environmental variables based on presence-absence, presence-only, and abundance data, and (b) compare evaluation metrics based on functional and discrimination accuracy for presence-absence and presence-only SDMs.

LOCATION

Minnesota, USA.

METHODS

Eurasian watermilfoil presence-absence and abundance information were gathered from 468 surveyed lakes, and 801 unsurveyed lakes were leveraged as pseudoabsences for presence-only models. A Random Forest algorithm was used to model the distribution and abundance of Eurasian watermilfoil as a function of lake-specific predictors, both with and without a spatial autocovariate. Occurrence-based SDMs were evaluated using conventional discrimination accuracy metrics and functional accuracy metrics assessing correlation between predicted suitability and observed abundance.

RESULTS

Water temperature degree days and maximum lake depth were two leading predictors influencing both invasion risk and abundance, but they were relatively less important for predicting abundance than other water quality measures. Road density was a strong predictor of Eurasian watermilfoil invasion risk but not abundance. Model evaluations highlighted significant differences: Presence-absence models had high functional accuracy despite low discrimination accuracy, whereas presence-only models showed the opposite pattern.

MAIN CONCLUSION

Complementing presence-absence data with abundance information offers a richer understanding of invasive Eurasian watermilfoil's ecological niche and enables evaluation of the model's functional accuracy. Conventional discrimination accuracy measures were misleading when models were developed using pseudoabsences. We thus caution against the overuse of presence-only models and suggest directing more effort toward systematic monitoring programs that yield high-quality data.

An Empirical and Mechanistic Explanation of Abundance-Occupancy Relationships for a Critically Endangered Nomadic Migrant

The positive abundance-occupancy relationship (AOR) is a pervasive pattern in macroecology. Similarly, the association between occupancy (or probability of occurrence) and abundance is also usually assumed to be positive and in most cases constant. Examples of AORs for nomadic species with variable distributions are extremely rare. Here we examined temporal and spatial trends in the AOR over 7 years for a critically endangered nomadic migrant that relies on dynamic pulses in food availability to breed. We predicted a negative temporal relationship, where local mean abundances increase when the number of occupied sites decreases, and a positive relationship between local abundances and the probability of occurrence. We also predicted that these patterns are largely attributable to spatiotemporal variation in food abundance. The temporal AOR was significantly negative, and annual food availability was significantly positively correlated with the number of occupied sites but negatively correlated with abundance. Thus, as food availability decreased, local densities of birds increased, and vice versa. The abundance-probability of occurrence relationship was positive and nonlinear but varied between years due to differing degrees of spatial aggregation caused by changing food availability. Importantly, high abundance (or occupancy) did not necessarily equate to high-quality habitat and may be indicative of resource bottlenecks or exposure to other processes affecting vital rates. Our results provide a rare empirical example that highlights the complexity of AORs for species that target aggregated food resources in dynamic environments.

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.