scholarly journals Shifted distribution baselines: neglecting long-term biodiversity records risks overlooking potentially suitable habitat for conservation management

2019 ◽  
Author(s):  
Sophie Monsarrat ◽  
Peter Novellie ◽  
Ian Rushworth ◽  
Graham Kerley
Keyword(s):  
Habitat Suitability ◽  
Potential Distribution ◽  
Habitat Preferences ◽  
Suitable Habitat ◽  
Ecological Data ◽  
Distribution Models ◽  
Mammal Species ◽  
Biased Perception ◽  
Occurrence Records

ABSTRACTSetting appropriate conservation measures to halt the loss of biodiversity requires a good understanding of species’ habitat requirements and potential distribution. Recent (past few decades) ecological data are typically used to estimate and understand species’ ecological niche. However, historical local extinctions may have truncated species-environment relationships, resulting in a biased perception of species’ habitat preferences. This may result in incorrect assessments of the area potentially available for their conservation. Incorporating long-term (centuries-old) occurrence records with recent records may provide better information on species-environment relationships and improve the modeling and understanding of habitat suitability. We test whether neglecting long-term occurrence records leads to an underestimation of species’ historical niche and potential distribution and identify which species are more vulnerable to this effect. We compare outputs of species distribution models and niche hypervolumes built using recent records only with those built using both recent and long-term (post-1500) records, for a set of 34 large mammal species in South Africa. We find that, while using recent records only is adequate for some species, adding historical records in the analyses impacts estimates of the niche and habitat suitability for fourteen species (41%) in our dataset, and that this effect is significantly higher for carnivores. These results show that neglecting long-term biodiversity records in spatial analyses risks misunderstanding, and generally underestimating, species’ niche, which in turn may lead to ill-informed management decisions, with significant implications for the effectiveness of conservation efforts.

scholarly journals Shifted distribution baselines: neglecting long-term biodiversity records risks overlooking potentially suitable habitat for conservation management

2019 ◽  
Vol 374 (1788) ◽  
pp. 20190215 ◽  
Author(s):  
Sophie Monsarrat ◽  
Peter Novellie ◽  
Ian Rushworth ◽  
Graham Kerley
Keyword(s):  
Habitat Suitability ◽  
Potential Distribution ◽  
Habitat Preferences ◽  
Ecological Niches ◽  
Suitable Habitat ◽  
Ecological Data ◽  
Distribution Models ◽  
Mammal Species ◽  
Occurrence Records

Setting appropriate conservation measures to halt the loss of biodiversity requires a good understanding of species' habitat requirements and potential distribution. Recent (past few decades) ecological data are typically used to estimate and understand species’ ecological niches. However, historical local extinctions may have truncated species–environment relationships, resulting in a biased perception of species' habitat preferences. This may result in incorrect assessments of the area potentially available for their conservation. Incorporating long-term (centuries-old) occurrence records with recent records may provide better information on species–environment relationships and improve the modelling and understanding of habitat suitability. We test whether neglecting long-term occurrence records leads to an underestimation of species’ historical niche and potential distribution and identify which species are more vulnerable to this effect. We compare outputs of species distribution models and niche hypervolumes built using recent records only with those built using both recent and long-term (post-1500) records, for a set of 34 large mammal species in South Africa. We find that, while using recent records only is adequate for some species, adding historical records in the analyses impacts estimates of the niche and habitat suitability for 12 species (34%) in our dataset, and that this effect is significantly higher for carnivores. These results show that neglecting long-term biodiversity records in spatial analyses risks misunderstanding, and generally underestimating, species' niches, which in turn may lead to ill-informed management decisions, with significant implications for the effectiveness of conservation efforts. This article is part of a discussion meeting issue ‘The past is a foreign country: how much can the fossil record actually inform conservation?’

scholarly journals Potential distribution of Artemisia annua L.under climate change

2021 ◽  
Author(s):  
Hongjun Jiang ◽  
Ting Liu ◽  
Shiping Gao ◽  
Ruijun Wang ◽  
Ruchun Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Artemisia Annua ◽  
Dominant Factor ◽  
Suitable Habitat ◽  
Ensemble Model ◽  
Distribution Models ◽  
Ensemble Models ◽  
The Future ◽  
Occurrence Records

Aim:Artemisia annua L. is the one and only original plant used to isolate artemisinin which is a highly effective remedy to fight malaria. Climate change leads to change of distribution and suitable range for many species and A. annua is no exception. However, it is not clear that the potential distribution and suitable range change of this unique plant under climate change. Therefore, we present this research to study its change in the future. Location: Global. Methods: Since the accuracy of species distribution models was affected by occurrence records and environmental variables, 1062 presence records and 7 variables were picked out to build ensemble models with 10 different algorithms by means of biomod2 under current and future climate scenarios. Results: At present, except SRE, the AUC values of the rest models were greater than 0.8, and the TSS values were greater than 0.6, the values of ensemble model were 0.968 and 0.826 respectively. Mean temperature of driest quarter was the dominant factor to shape the range of A. annua and its optimum interval ranged from 4.8 to 23.3ºC. The high suitable habitats of A. annua were mainly located in Eastern Asia, Western Europe, Central Europe. In the future, the high suitable area would decline at 15.55% to 25.87%. Main conclusions: Ensemble models showed it performed better than any the single one. At present, the high suitable habitat simulated by ensemble model was in accordance with the actual occurrence records. In the future, the high suitable habitat for A. annua would move northeast, and disappear in North America. They would increase with time under each SSP, but sharply decline while comparing with the current one. This study can be used to protect wild resource and guide cultivation for A. annua, which would make modest contribution to fight malaria.

scholarly journals Predicting the potential distribution of the Endangered huemul deer Hippocamelus bisulcus in North Patagonia

Oryx ◽  
2016 ◽  
Vol 51 (2) ◽  
pp. 315-323 ◽  
Author(s):  
Paloma Quevedo ◽  
Achaz von Hardenberg ◽  
Hernán Pastore ◽  
José Álvarez ◽  
Paulo Corti
Keyword(s):  
Potential Distribution ◽  
Summer Precipitation ◽  
Suitable Habitat ◽  
Large Mammals ◽  
Distribution Models ◽  
North Patagonia ◽  
Predictive Variables ◽  
Hippocamelus Bisulcus ◽  
Best Fitting ◽  
Fitting Model

AbstractHabitat loss is one of the main threats to wildlife, particularly large mammals. Estimating the potential distribution of threatened species to guide surveys and conservation is crucial, primarily because such species tend to exist in small fragmented populations. The Endangered huemul deer Hippocamelus bisulcus is endemic to the southern Andes of Chile and Argentina. Although the species occurs in the Valdivian Ecoregion, a hotspot for biodiversity, we have no information on its occupancy and potential distribution in this region. We built and compared species distribution models for huemul using the maximum entropy approach, using 258 presence records and sets of bioclimatic and geographical variables as predictors, with the objective of assessing the potential distribution of the species in the Valdivian Ecoregion. Annual temperature range and summer precipitation were the predictive variables with the greatest influence in the best-fitting model. Approximately 12,360 km2 of the study area was identified as suitable habitat for the huemul, of which 30% is included in the national protected area systems of Chile and Argentina. The map of potential distribution produced by our model will facilitate prioritization of future survey efforts in other remote and unexplored areas in which huemul have not been recorded since the 1980s but where there is a high probability of their occurrence.

scholarly journals Habitat Suitability Study of Hylomecon Japonica Based on Maxent Model in China

2020 ◽  
Author(s):  
Cao Zhen ◽  
Zhang Xiaoyan ◽  
Xue Xuanji ◽  
Zhang Lei ◽  
Zhan Guanqun ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
Potential Distribution ◽  
Mean Annual Temperature ◽  
Suitable Habitat ◽  
Entropy Model ◽  
Factors Affecting ◽  
Jackknife Test ◽  
Maxent Model ◽  
Growth Area ◽  
The Mean

Abstract Background: To understand the potential distribution and habitat suitability of H. japonica in China. And to provide guidance for the wild cultivation and standardized planting of H. japonica. Methods: The maximum entropy model (Maxent) and geographic information system (ArcGIS) were applied to predict the potential suitable habitat of H. japonica species, and the contribution of variables were evaluated by using the jackknife test. Results: The AUC value confirmed the accuracy of the model prediction based on 101 occurrence records. The potential distributions of H. japonica were mainly concentrated in Jilin, Liaoning, Shaanxi and other provinces (adaptability index>0.6). Jackknife experiment showed that the precipitation of driest month (35.6%), precipitation of wettest quarter (13.4%), the mean annual temperature (7.8%) and the subclass of soil (7.8%) were the most important factors affecting the potential distribution of H. japonica. Conclusion: The niche parameters of the most suitable growth area (adaptability index>0.8) for H. japonica were precipitation of driest month (5 mm), precipitation of wettest quarter (400-490 mm), the mean annual temperature (-2-4 °C) and the subclass of soil (Glossy Chernozem, Gleyic Lime, Haplic Gypsisols).

scholarly journals Setting Favourable Habitat Reference Values for breeding birds: general principles and examples for passerine birds

2013 ◽  
Vol 24 (3) ◽  
pp. 263-271 ◽  
Author(s):  
MATTIA BRAMBILLA ◽  
CLAUDIO CELADA ◽  
MARCO GUSTIN
Keyword(s):  
Habitat Selection ◽  
Habitat Quality ◽  
Reference Values ◽  
Breeding Success ◽  
Suitable Habitat ◽  
Distribution Models ◽  
Species Population ◽  
Definition Of ◽  
Range Of Values

SummarySetting Favourable Reference Values (FRVs) can assist the definition of the conservation status of a species. FRVs may consider population, habitat, and range. FRVs can indicate a range of values for different parameters, which should allow the long-term persistence of a species/population. We propose a method for the definition of reference values for the habitat (FRV-H or HRV) of breeding bird species. HRV should cover habitat extent and quality, both required to ensure long-term persistence. Extent HRV should express a measure of suitable area, whereas quality HRV could be defined as the range of values for habitat variables known to affect habitat quality. To define an extent HRV, we built species distribution models (SDMs) and set extent HRV as the extent of potentially suitable habitat under a conservative approach. Quality HRV should refer to environmental determinants/correlates of occurrence and breeding success, and should be defined by the identification of the habitat factors affecting occurrence and reproduction. When habitat selection is adaptive, habitat suitability may approximate habitat quality, being correlated with breeding success. In that case, fine-scaled habitat/distribution models may be used to identify determinants/correlates of reproductive output, and such species-habitat relationships may help define quality HRV. We show examples using the Red-backed Shrike Lanius collurio as a model. The use of habitat selection models, which can be made spatially explicit generating distribution models, may assist the definition of both extension and quality HRVs. Species-habitat models can allow the individuation of factors and relative values affecting species occurrence/reproduction (quality HRV), and the definition of the spatial distribution and quantity of potentially suitable habitat (extent HRV). Our approach is one of the possible ones, aiming at finding a “suitable” trade-off between affordable data and scientific precision. HRVs should be used together with population and range FRVs to assess the status of a species/population.

scholarly journals Mapping the potential distribution of the Critically Endangered Himalayan Quail Ophrysia superciliosa using proxy species and species distribution modelling

2015 ◽  
Vol 25 (4) ◽  
pp. 466-478 ◽  
Author(s):  
JONATHON C. DUNN ◽  
GRAEME M. BUCHANAN ◽  
RICHARD J. CUTHBERT ◽  
MARK J. WHITTINGHAM ◽  
PHILIP J. K. MCGOWAN
Keyword(s):  
Land Cover ◽  
Species Distribution ◽  
Climate Model ◽  
Habitat Preferences ◽  
Species Distribution Modelling ◽  
Critically Endangered ◽  
Suitable Habitat ◽  
Distribution Models ◽  
Extant Species ◽  
Starting Point

SummaryThe Critically Endangered Himalayan Quail Ophrysia superciliosa has not been reliably recorded since 1876. Recent searches of historical sites have failed to detect the species, but we estimate an extinction year of 2023 giving us reason to believe that the species may still be extant. Species distribution models can act as a guide for survey efforts, but the current land cover in the historical specimen record locations is unlikely to reflect Himalayan Quail habitat preferences due to extensive modifications. Thus, we investigate the use of two proxy species: Cheer Pheasant Catreus wallechi and Himalayan Monal Lophophorus impejanus that taken together are thought to have macro-habitat requirements that encapsulate those of the Himalayan Quail. After modelling climate and topography space for the Himalayan Quail and these proxy species we find the models for the proxy species have moderate overlap with that of the Himalayan Quail. Models improved with the incorporation of land cover data and when these were overlaid with the Himalayan Quail climate model, we were able to identify suitable areas to target surveys. Using a measure of search effort from recent observations of other galliformes, we identify 923 km2 of suitable habitat surrounding Mussoorie in Northern India that requires further surveys. We conclude with a list of five priority survey sites as a starting point.

scholarly journals Predicting the potential distribution of striped hyena Hyaena hyaena in Iran

2020 ◽  
Vol 150 ◽  
Author(s):  
Amirhossein Dadashi-Jourdehi ◽  
Bahman Shams-Esfandabad ◽  
Abbas Ahmadi ◽  
Hamid Reza Rezaei ◽  
Hamid Toranj-Zar
Keyword(s):  
Potential Distribution ◽  
High Rate ◽  
Suitable Habitat ◽  
Distribution Models ◽  
Distribution Modelling ◽  
Maxent Model ◽  
Eastern Iran ◽  
Striped Hyena ◽  
Management Priorities ◽  
Hyaena Hyaena

Predictive potential distribution modelling is crucial in outlining habitat usage and establishing conservation management priorities. Association among species occurrence and environmental and spatial characteristics has been calculated with species distribution models. Herein, we used maximum entropy distribution modelling (MaxEnt) for predicting the potential distribution of striped hyena Hyaena hyaena in the entire country of Iran, using a number of occurrence records (i.e., 118) and environmental variables derived from remote sensing. The MaxEnt model showed a high rate of success according to AUC test scores (0.97). Our results are roughly congruent with previous studies suggesting that mountainous re-gions in northern and western Iran, and the plains in central and eastern Iran are a suitable habitat for H. hyaena.

scholarly journals Morphological and molecular evidence support the taxonomic separation of the medically important Neotropical spiders Phoneutria depilata (Strand, 1909) and P. boliviensis (F.O. Pickard-Cambridge, 1897) (Araneae, Ctenidae)

ZooKeys ◽  
2021 ◽  
Vol 1022 ◽  
pp. 13-50
Author(s):  
Nicolas A. Hazzi ◽  
Gustavo Hormiga
Keyword(s):  
Species Distribution ◽  
Species Delimitation ◽  
Species Distribution Models ◽  
Allopatric Speciation ◽  
Molecular Evidence ◽  
Niche Conservatism ◽  
Suitable Habitat ◽  
Distribution Models ◽  
Nucleotide Sequence Data ◽  
Occurrence Records

The species of the genus Phoneutria (Ctenidae), also called banana spiders, are considered amongst the most venomous spiders in the world. In this study we revalidate P. depilata (Strand, 1909), which had been synonymized with P. boliviensisis (F.O. Pickard-Cambridge, 1897), using morphological and nucleotide sequence data (COI and ITS-2) together with species delimitation methods. We synonymized Ctenus peregrinoides, Strand, 1910 and Phoneutria colombiana Schmidt, 1956 with P. depilata. Furthermore, we designated Ctenus signativenter Strand, 1910 as a nomen dubium because the exact identity of this species cannot be ascertained with immature specimens, but we note that the type locality suggests that the C. signativenter syntypes belong to P. depilata. We also provide species distribution models for both species of Phoneutria and test hypotheses of niche conservatism under an allopatric speciation model. Our phylogenetic analyses support the monophyly of the genus Phoneutria and recover P. boliviensis and P. depilata as sister species, although with low nodal support. In addition, the tree-based species delimitation methods also supported the separate identities of these two species. Phoneutria boliviensis and P. depilata present allopatric distributions separated by the Andean mountain system. Species distribution models indicate lowland tropical rain forest ecosystems as the most suitable habitat for these two Phoneutria species. In addition, we demonstrate the value of citizen science platforms like iNaturalist in improving species distribution knowledge based on occurrence records. Phoneutria depilata and P. boliviensis present niche conservatism following the expected neutral model of allopatric speciation. The compiled occurrence records and distribution maps for these two species, together with the morphological diagnosis of both species, will help to identify risk areas of accidental bites and assist health professionals to determine the identity of the species involved in bites, especially for P. depilata.

scholarly journals Interannual climate variability data improves niche estimates in species distribution models

2021 ◽  
Author(s):  
Dirk Nikolaus Karger ◽  
Bianca Saladin ◽  
Rafael O. Wueest ◽  
Catherine H. Graham ◽  
Damaris Zurell ◽  
...  
Keyword(s):  
Climate Variability ◽  
Spatial Variability ◽  
Species Distribution ◽  
Temporal Variability ◽  
Species Distribution Models ◽  
Essential Element ◽  
Spatial And Temporal Variability ◽  
Distribution Models ◽  
Mammal Species

Aim: Climate is an essential element of species' niche estimates in many current ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values. Yet, climate can also be described as spatial or temporal variability for variables like temperature or precipitation. Such variability, spatial or temporal, offers additional insights into niche properties. Here, we test to what degree spatial variability and long-term temporal variability in temperature and precipitation improve SDM predictions globally. Location: Global. Time period: 1979-2013. Major taxa studies: Mammal, Amphibians, Reptiles. Methods: We use three different SDM algorithms, and a set of 833 amphibian, 779 reptile, and 2211 mammal species to quantify the effect of spatial and temporal climate variability in SDMs. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). Results: Mean performance of SDMs with climatic means as predictors was TSS=0.71 and AUC=0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS=0.74, mean AUC=0.92), as does the inclusion of temporal variability (mean TSS=0.80, mean AUC=0.94). Including both spatial and temporal variability in SDMs shows similarly high TSS and AUC scores. Main conclusions: Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in exotherm groups such as amphibians and reptiles, while for endotermic mammals no such improvement was observed. These results indicate that more detailed information about temporal climate variability offers a highly promising avenue for improving niche estimates and calls for a new set of standard bioclimatic predictors in SDM research.

scholarly journals Anticipated climate changes reveal shifting in habitat suitability of high-altitude selaginellas in Java, Indonesia

2020 ◽  
Vol 21 (11) ◽  
Author(s):  
AHMAD DWI SETYAWAN ◽  
Jatna Supriatna ◽  
Nisyawati ◽  
Ilyas Nursamsi ◽  
SUTARNO SUTARNO ◽  
...  
Keyword(s):  
High Altitude ◽  
Habitat Suitability ◽  
Climate Changes ◽  
Anthropogenic Activities ◽  
Annual Rainfall ◽  
Suitable Habitat ◽  
Distribution Models ◽  
Climate Conditions ◽  
Presence Data ◽  
Pessimistic Scenario

Abstract. Setyawan AD, Supriatna J, Nisyawati, Nursamsi I, Sutarno, Sugiyarto, Sunarto, Pradan P, Budiharta S, Pitoyo A, Suhardono S, Setyono P, Indrawan M. 2020. Anticipated climate changes reveal shifting in habitat suitability of high-altitude selaginellas in Java, Indonesia. Biodiversitas 21: 5482-5497. High-altitude ecosystems with humid and cool climate are the preferred habitat for some Selaginella species (selaginellas). Such habitats are available in Java, Indonesia, which also has fertile soils with rich mineral contents resulted from volcanic activities. However, the high-altitude ecosystems in Java are threatened by various anthropogenic activities as well as changes in climate conditions, potentially affecting some Selaginella species. This study aimed to investigate the shift in suitable habitat of four species of high-altitude Selaginella spp. (Selaginella involvens, S. opaca, S. ornata, and S. remotifolia) in Java Island under current and future climate conditions predicted by several representative greenhouse gas concentration pathways. Presence data of Selaginella localities were collected from field survey between 2007 and 2014 across the island, as well as occurrence points from the Global Biodiversity Information Facility database. A total of 1,721 occurrence points data along with environmental and climate data were used to develop species distribution models using MaxEnt. Future habitat distributions were projected under four climate scenarios to see the shift in suitable habitat and altitudinal ranges. The results showed that the distribution of the four high-altitude Selaginella species are strongly influenced by altitude, annual average temperature, and annual rainfall. In the present time, 37.32% (48,974 km2) of the area of Java has been predicted to be suitable for high-altitude Selaginella. Under the optimistic climate scenario (RCP 2.6), the highly suitable area will likely to decrease by almost 35% in the year 2080, whereas the medium and low suitable areas will reduce by about 37.2% and 18.3%, respectively. Under the pessimistic scenario (RCP 8.5), about 21.2% of low suitable areas will be lost in 2080, whereas the medium and highly suitable areas are predicted to decrease by around 38.1% and 33.4%, respectively. Under the pessimistic scenario, there will be upward shift by 51.1 m in the year 2030 from the current’s mean altitude and will shift by almost 150 m in the year 2080. The maximum altitude of predicted suitable habitat is also predicted to increase to reach almost 3500 m asl in the year 2080. The results of this study imply that habitat shift of four high-altitude Selaginella species varies depending on the scenario, but in all cases, the losses are greater than gains.

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