Evaluating collinearity effects on species distribution models: An approach based on virtual species simulation

Distribution Models of Timber Species for Forest Conservation and Restoration in the Andean-Amazonian Landscape, North of Peru

The Andean-Amazonian landscape has been universally recognized for its wide biodiversity, and is considered as global repository of ecosystem services. However, the severe loss of forest cover and rapid reduction of the timber species seriously threaten this ecosystem and biodiversity. In this study, we have modeled the distribution of the ten most exploited timber forest species in Amazonas (Peru) to identify priority areas for forest conservation and restoration. Statistical and cartographic protocols were applied with 4454 species records and 26 environmental variables using a Maximum Entropy model (MaxEnt). The result showed that the altitudinal variable was the main regulatory factor that significantly controls the distribution of the species. We found that nine species are distributed below 1000 m above sea level (a.s.l.), except Cedrela montana, which was distributed above 1500 m a.s.l., covering 40.68%. Eight of 10 species can coexist, and the species with the highest percentage of potential restoration area is Cedrela montana (14.57% from Amazonas). However, less than 1.33% of the Amazon has a potential distribution of some species and is protected under some category of conservation. Our study will contribute as a tool for the sustainable management of forests and will provide geographic information to complement forest restoration and conservation plans.

Species range shifts in response to climate change and human pressure for the world's largest amphibian

The Chinese giant salamander, Andrias davidianus, the world's largest amphibian, is critically endangered and has an extremely unique evolutionary history. Therefore, this species represents a global conservation priority and will be impacted by future climate and human pressures. Understanding the range and response to environmental change of this species is a priority for the identification of targeted conservation activities. We projected future range shifts of the Chinese giant salamander under the independent and combined impacts of climate change and human population density (HPD) variations by using ensemble species distribution models. We further evaluated the sustainability of existing nature reserves and identified priority areas for the mitigation or prevention of such pressures. Both climate change and increasing HPD tended to reduce the species range, with the latter leading to greater range losses and fragmentation of the range. Notably, 65.6%, 18.0% and 18.4% of the range loss were attributed solely to HPD change, solely to climate change and to their overlapping impacts, respectively. Overall, the average total and net losses of the species range were 52.5% and 23.4%, respectively, and HPD and climate changes were responsible for 71.4% and 28.6% of the net losses, respectively. We investigated the stability of the remaining species range and found that half of the nature reserves are likely vulnerable, with 57.1% and 66.7% of them likely to lose their conservation value in 2050 and 2070, respectively. To effectively protect this salamander, conservation policies should address both pressures simultaneously, especially considering the negative impact of human pressures in both contemporary periods and the near future. The species range shifts over space and time projected by this research could help guide long-term surveys and the sustainable conservation of wild habitats and populations of this ancient and endangered amphibian.

Current and Future Distribution of Five Timber Forest Species in Amazonas, Northeast Peru: Contributions towards a Restoration Strategy

Forest and land degradation is a serious problem worldwide and the Peruvian National Map of Degraded Areas indicates that 13.78% (177,592.82 km2) of the country’s territory is degraded. Forest plantations can be a restoration strategy, while conserving economically important species affected by climate change and providing forestry material for markets. This study modelled the species distribution under current conditions and climate change scenarios of five Timber Forest Species (TFS) in the Amazonas Department, northeastern Peru. Modelling was conducted with Maximum Entropy (MaxEnt) using 26 environmental variables. Of the total distribution under current conditions of Cedrelinga cateniformis, Ceiba pentandra, Apuleia leiocarpa, Cariniana decandra and Cedrela montana, 34.64% (2985.51 km2), 37.96% (2155.86 km2), 35.34% (2132.57 km2), 33.30% (1848.51 km2), and 35.81% (6125.44 km2), respectively, correspond to degraded areas and, therefore, there is restoration potential with these species. By 2050 and 2070, all TFS are projected to change their distribution compared to their current ranges, regardless of whether it will be an expansion and/or a contraction. Consequently, this methodology is intended to guide the economic and ecological success of forest plantations in reducing areas degraded by deforestation or similar activities.

Climate change models predict decreases in the range of a microendemic freshwater fish in Honduras

Despite their incredible diversity, relatively little work has been done to assess impacts of climate change on tropical freshwater organisms. Chortiheros wesseli is a species of Neotropical cichlid (Cichlidae: Cichlinae) restricted to only a few river drainages in the Caribbean-slope of Honduras. Little is known about this species and few specimens had been collected until recently; however, our work with this species in the wild has led to a better understanding of its ecology and habitat preferences making it an excellent model for how freshwater fishes can be affected by climate change. This study assesses the distribution and habitats of Chortiheros wesseli using a combination of field data and species distribution modeling. Results indicate this species is largely limited to its current range, with no realistic suitable habitat nearby. Empirical habitat data show that this species is limited to narrow and shallow flowing waters with rapids and boulders. This habitat type is highly influenced by precipitation, which contributed the greatest influence on the models of present and future habitat suitability. Although several localities are within boundaries of national protected areas, species distribution models all predict a reduction in the range of this freshwater fish based on climate change scenarios. The likelihood of a reduced range for this species will be intensified by adverse changes to its preferred habitats.

Climate change and bird extinctions in the Amazon

In recent years, carbon dioxide emissions have been potentiated by several anthropogenic processes that culminate in climate change, which in turn directly threatens biodiversity and the resilience of natural ecosystems. Tropical rainforests are among the most impacted biological realms. The Belém endemism center, which is one of the several endemism centers in Amazon, is located in the most affected area within the so-called “Deforestation Arc.” Moreover, this region harbors a high concentration of Amazonian endangered bird species, of which 56% of them are considered to be under the threat of extinction. In this work, we sought to evaluate the current and future impacts of both climate change and deforestation on the distribution of endemic birds in the Belém Area of Endemism (BEA). Thus, we generated species distribution models for the 16 endemic bird species considering the current and two future gas emission scenarios (optimistic and pessimistic). We also evaluated climate change impacts on these birds in three different dispersal contexts. Our results indicate that BAE, the endemic taxa will lose an average of 73% of suitable areas by 2050. At least six of these birds species will have less than 10% or no future suitable habitat in all emission scenarios. One of the main mechanisms used to mitigate the impacts of climate change on these species in the near future is to assess the current system of protected areas. It is necessary to ensure that these areas will continue being effective in conserving these species even under climate change. The “Gurupi Mosaic” and the “Rio-Capim” watershed are areas of great importance because they are considered climate refuges according to our study. Thus, conservation efforts should be directed to the maintenance and preservation of these two large remnants of vegetation in addition to creating ecological corridors between them.

Global occurrence data improve potential distribution models for Aedes japonicus japonicus in non-native regions

BACKGROUND

There is great interest in modelling the distribution of invasive species, particularly from the point of view of management. However, distribution modelling for invasive species using ecological niche models (ENMs) involves multiple challenges. Owing to the short time span since the introduction or arrival of a non-indigenous species and the associated dispersal limitations, applying regular ENMs at an early stage of the invasion process may result in an underestimation of the potential niche in the new ranges. This topic is dealt with here using the example of Aedes japonicus japonicus, a vector competent mosquito species for a number of diseases.

RESULTS

We found high niche unfilling for the species' non-native range niches in Europe and North America compared with the native range niche, which can be explained by the early stage of the invasion process. Comparing four different ENMs based on: (i) the European and (ii) the North American non-native range occurrence data, (iii) (derived) native range occurrence data, and (iv) all available occurrence data together, we found large differences in the projected climatic suitability, with the global data model projecting larger areas with climatic suitability.

CONCLUSION

ENM in biological invasions can be challenging, especially when distribution data are only poorly available. We suggest one possible way to project climatic suitability for Aedes j. japonicus despite poor data availability for the non-native ranges and missing occurrences from the native range. We discuss aspects of the lack of information and the associated implications for modelling. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Potential reduction of Hartweg´s Pine (Pinus hartwegii Lindl.) geographic distribution

Geographical distribution of forest species is closely regulated by environmental conditions, particularly temperature and precipitation. Climate change predicted by general circulation models is expected to modify the distribution of many species' distribution, especially those adapted to extreme environmental conditions, leading to large-scale migrations or local extinctions. The aim of this research was to determine the potential impact of climatic change on Pinus hartwegii geographic distribution and the niche breadth of its populations. Ecological niche models were used by generated with four different algorithms based on 19 bioclimatic variables in addition to altitude. Climatic niche breadth was delimited by the dispersion of species occurrence records within the intervals of the bioclimatic variables. We modelled future distribution based on three general circulation models, MIROC-ESM-CHEM, CCSM4 and HadGEM2-ES, using two representative concentration pathways (RCP) 2.6 and 8.5, for two-time horizons 2050 and 2070. Niche breadth analysis showed narrow ranges of suitability, indicating a strong relationship between the presence of P. hartwegii with the temperature of the warmest quarter and precipitation of the coldest quarter. In addition, the suitability area of P. hartwegii is predicted to be reduced up to 70% by 2070; the populations of the extreme northern and southern latitudes will be reduced in greater proportion than those of central Mexico. This suggest that environmental suitability area of P. hartwegii are reduced by the effect of the increase in environmental temperature. Therefore, it is necessary to monitor extreme populations of this species in the long term in order to establish efficient conservation strategies and well adaptive management facing climate change.

Vulnerability of Phyllocycla Species (Odonata: Gomphidae) to Current and Planned Anthropic Activities by the Brazilian Government

Although most species distribution modeling (SDMs) are constructed at the species level, an appreciation of evolutionary processes has led to modeling above this level. In view of the difficulty in estimating the impacts of human actions on rare or deficient data species, we proposed a new approach to vulnerability assessment based on concepts already well established in the literature (ecological niche, niche conservatism, and extinction thresholds). We used distribution modeling to predict where species of the genus Phyllocycla (Calvert 1948) are most vulnerable to local extinctions and how the implementation of planned anthropic activities by the Brazilian government may modify the potential distribution of the genus in Brazil. We chose that genus because its conservation status is little known, especially due to the data gap about its geographical distribution. We proposed modeling the whole genus and used the niche conservatism theory to justify our methods. The anthropic activities considered in our analysis were agriculture and livestock, rural settlements, energy production installations, transportation, oil extraction, mining, and urbanization. We found that only 55.3% of the original potential distribution of Phyllocycla in Brazil remains available. The area compromised by anthropic activities comprises mainly the Cerrado and Atlantic Forest biomes, with less impact on the Amazon. However, with the implementation of activities planned by the Brazilian government, it is possible that an additional 13.6% of this area will be unavailable to species of Phyllocycla, especially in the Amazon, where interest in mining and the implementation of new hydroelectric production have increased.

Using distribution models to estimate blooms of phytosanitary cyanobacteria in Brazil

Abstract: The multiple uses of aquatic ecosystems by humankind and the continuous interference of their activities have contributed to the emergence of potentially toxic cyanobacteria blooms. Here, we firstly created a database of occurrences of cyanobacteria blooms in Brazil through a systematic review of the scientific literature available in online platforms (e.g. Web of Science, Capes Thesis Catalogue). Secondly, we carried out ecological niche models with occurrence data obtained from these studies to predict climatically suitable areas for blooms. We select 21 bioclimatic variables input environmental data. We used five modeling methods for the current climate scenario: (1) Maxent; (2) Support Vector Machines; (3) Random Forest; (4) Maximum Likelihood e (5) Gaussian. We found that the number of publications about bloom events was higher in 2009 with a decline in the years 2012, 2013 and 2017. Furthermore, the years with the higher records of blooms in freshwater environments were 2005, 2011 e 2014. These events occurring mainly in public supply reservoirs and are mostly of the genera Microcystis Lemmermann, 1907, Dolichospermum (Ralfs ex Bornet & Flahault) P.Wacklin, L.Hoffmann & J.Komárek, 2009 and Raphidiopsis F.E.Fritsch & F.Rich, 1929. Modeling the potential distribution of blooms, we found sampling gaps that should be targeting for future researches, especially in the Amazon biome. Overall, the models did not predict highly suitable areas in the /north of Brazil, while other regions were relatively well distributed with a higher number of occurrence records in the Southeast region.

Camp site habitat preferences of the little red flying-fox (Pteropus scapulatus) in Queensland

Urban flying-fox camps are a major source of human–wildlife conflict, producing noise, odour, vegetation damage, property damage, and concerns about disease. Although there is a significant demand in many communities for bat camps to be dispersed, there is limited information on how such dispersal can be conducted effectively. Determining the habitat characteristics flying-foxes use when selecting a camp site is key to understanding why they establish camps where they do and to where they might move if dispersed. We characterised little red flying-fox (LRFF) camp habitat at two spatial scales: floristics and vegetation structure at the local scale, and climatic and landscape characteristics at the broad scale. We found weak associations with local-scale tree and shrub height and cover, and stronger associations with increased Normalised Difference Vegetation Index (a measure of ‘greenness’) and decreased distance to nearest watercourse. These relationships were not strong enough to explain all variation in the model, suggesting that there are other factors, such as social cues, that could also influence camp site selection. Our results suggest that minor modifications to existing or proposed camp sites will be unlikely to repel or attract LRFFs, as other factors are likely to play key roles in the formation of camp sites for this species.

Fluctuating fortunes: genomes and habitat reconstructions reveal global climate-mediated changes in bats' genetic diversity

Over the last approximately 2.6 Myr, Earth's climate has been dominated by cyclical ice ages that have profoundly affected species' population sizes, but the impact of impending anthropogenic climate change on species' extinction potential remains a worrying problem. We investigated 11 bat species from different taxonomic, ecological and geographical backgrounds using combined information from palaeoclimatic habitat reconstructions and genomes to analyse biotic impacts of historic climate change. We discover tightly correlated fluctuations between species' historic distribution and effective population size, identify frugivores as particularly susceptible to global warming, pinpoint large insectivores as having overall low effective population size and flag the onset of the Holocene (approx. 10-12 000 years ago) as the period with the generally lowest effective population sizes across the last approximately 1 Myr. Our study shows that combining genomic and palaeoclimatological approaches reveals effects of climatic shifts on genetic diversity and may help predict impacts of future climate change.

Collinearity in ecological niche modeling: Confusions and challenges

Ecological niche models are widely used in ecology and biogeography. Maxent is one of the most frequently used niche modeling tools, and many studies have aimed to optimize its performance. However, scholars have conflicting views on the treatment of predictor collinearity in Maxent modeling. Despite this lack of consensus, quantitative examinations of the effects of collinearity on Maxent modeling, especially in model transfer scenarios, are lacking. To address this knowledge gap, here we quantify the effects of collinearity under different scenarios of Maxent model training and projection. We separately examine the effects of predictor collinearity, collinearity shifts between training and testing data, and environmental novelty on model performance. We demonstrate that excluding highly correlated predictor variables does not significantly influence model performance. However, we find that collinearity shift and environmental novelty have significant negative effects on the performance of model transfer. We thus conclude that (a) Maxent is robust to predictor collinearity in model training; (b) the strategy of excluding highly correlated variables has little impact because Maxent accounts for redundant variables; and (c) collinearity shift and environmental novelty can negatively affect Maxent model transferability. We therefore recommend to quantify and report collinearity shift and environmental novelty to better infer model accuracy when models are spatially and/or temporally transferred.

Multi-Scenario Species Distribution Modeling

Correlative species distribution models (SDMs) are increasingly being used to predict suitable insect habitats. There is also much criticism of prediction discrepancies among different SDMs for the same species and the lack of effective communication about SDM prediction uncertainty. In this paper, we undertook a factorial study to investigate the effects of various modeling components (species-training-datasets, predictor variables, dimension-reduction methods, and model types) on the accuracy of SDM predictions, with the aim of identifying sources of discrepancy and uncertainty. We found that model type was the major factor causing variation in species-distribution predictions among the various modeling components tested. We also found that different combinations of modeling components could significantly increase or decrease the performance of a model. This result indicated the importance of keeping modeling components constant for comparing a given SDM result. With all modeling components, constant, machine-learning models seem to outperform other model types. We also found that, on average, the Hierarchical Non-Linear Principal Components Analysis dimension-reduction method improved model performance more than other methods tested. We also found that the widely used confusion-matrix-based model-performance indices such as the area under the receiving operating characteristic curve (AUC), sensitivity, and Kappa do not necessarily help select the best model from a set of models if variation in performance is not large. To conclude, model result discrepancies do not necessarily suggest lack of robustness in correlative modeling as they can also occur due to inappropriate selection of modeling components. In addition, more research on model performance evaluation is required for developing robust and sensitive model evaluation methods. Undertaking multi-scenario species-distribution modeling, where possible, is likely to mitigate errors arising from inappropriate modeling components selection, and provide end users with better information on the resulting model prediction uncertainty.