scholarly journals Predicting Hotspots and Prioritizing Protected Areas for Endangered Primate Species in Indonesia under Changing Climate

Biology ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 154
Author(s):  
Aryo Adhi Condro ◽  
Lilik Budi Prasetyo ◽  
Siti Badriyah Rushayati ◽  
I Putu Santikayasa ◽  
Entang Iskandar

Indonesia has a large number of primate diversity where a majority of the species are threatened. In addition, climate change is conservation issues that biodiversity may likely face in the future, particularly among primates. Thus, species-distribution modeling was useful for conservation planning. Herein, we present protected areas (PA) recommendations with high nature-conservation importance based on species-richness changes. We performed maximum entropy (Maxent) to retrieve species distribution of 51 primate species across Indonesia. We calculated species-richness change and range shifts to determine the priority of PA for primates under mitigation and worst-case scenarios by 2050. The results suggest that the models have an excellent performance based on seven different metrics. Current primate distributions occupied 65% of terrestrial landscape. However, our results indicate that 30 species of primates in Indonesia are likely to be extinct by 2050. Future primate species richness would be also expected to decline with the alpha diversity ranging from one to four species per 1 km2. Based on our results, we recommend 54 and 27 PA in Indonesia to be considered as the habitat-restoration priority and refugia, respectively. We conclude that species-distribution modeling approach along with the categorical species richness is effectively applicable for assessing primate biodiversity patterns.

2019 ◽  
Vol 28 (14) ◽  
pp. 4123-4124
Author(s):  
Michał Bełcik ◽  
Jakub Goczał ◽  
Michał Ciach

We present here a revised version of Fig. 1 from our paper as it lacked some information used for the species distribution modeling as the original might be found misleading by some readers. This omission did not influence the results of our modeling process, for which the full set of observations was used. It does not therefore compromise our conclusions, or affect the other figures and tables we presented.


Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381
Author(s):  
B Liu ◽  
F Li ◽  
Z Guo ◽  
L Hong ◽  
W Huang ◽  
...  

2021 ◽  
pp. 1-8
Author(s):  
Thaísa Araújo ◽  
Helena Machado ◽  
Dimila Mothé ◽  
Leonardo dos Santos Avilla

Abstract Climatic and environmental changes, as well as human action, have been cited as potential causes for the extinction of megafauna in South America at the end of the Pleistocene. Among megamammals lineages with Holarctic origin, only horses and proboscideans went extinct in South America during this period. This study aims to understand how the spatial extent of habitats suitable for Equus neogeus and Notiomastodon platensis changed between the last glacial maximum (LGM) and the middle Holocene in order to determine the impact that climatic and environmental changes had on these taxa. We used species distribution modeling to estimate their potential extent on the continent and found that both species occupied arid and semiarid open lands during the LGM, mainly in the Pampean region of Argentina, southern and northeastern Brazil, and parts of the Andes. However, when climate conditions changed from dry and cold during the LGM to humid and warm during the middle Holocene, the areas suitable for these taxa were reduced dramatically. These results support the hypothesis that climatic changes were a driving cause of extinction of these megamammals in South America, although we cannot rule out the impact of human actions or other potential causes for their extinction.


2018 ◽  
Vol 80 (6) ◽  
pp. 457-461
Author(s):  
Carlos A. Morales-Ramirez ◽  
Pearlyn Y. Pang

Open-source data are information provided free online. It is gaining popularity in science research, especially for modeling species distribution. MaxEnt is an open-source software that models using presence-only data and environmental variables. These variables can also be found online and are generally free. Using all of these open-source data and tools makes species distribution modeling (SDM) more accessible. With the rapid changes our planet is undergoing, SDM helps understand future habitat suitability for species. Due to increasing interest in biogeographic research, SDM has increased for marine species, which were previously not commonly found in this modeling. Here we provide examples of where to obtain the data and how the modeling can be performed and taught.


2021 ◽  
Vol 257 ◽  
pp. 109148
Author(s):  
Leonardo de Sousa Miranda ◽  
Marcelo Awade ◽  
Rodolfo Jaffé ◽  
Wilian França Costa ◽  
Leonardo Carreira Trevelin ◽  
...  

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