scholarly journals Modelado de distribución de especies en los bosques de los andes meridionales

2021 ◽  
Author(s):  
Virginia Alberdi Nieves
Keyword(s):  
Climate Change ◽  
Maximum Entropy ◽  
Predictive Modelling ◽  
Entropy Method ◽  
Distribution Models ◽  
Environmental Diversity ◽  
Current Time ◽  
The Future ◽  
Current Area ◽  
Cordillera De Los Andes

La elevada biodiversidad junto con una gran variedad de ecosistemas convierten a la Cordillera de los Andes es una de las regiones de mayor diversidad ambiental del mundo, donde se encuentran los rangos más extremos de tipos de paisajes, clima y formaciones forestales de la Tierra, un área adecuada para estudiar los posibles efectos del cambio climático sobre la distribución espacial de las formaciones forestales. Para ello resulta imprescindible entender los efectos de cambio climático en la zona, dónde las observaciones climáticas indican diferentes escenarios climáticos en el futuro, para un periodo de tiempo actual y para el periodo 2040-2069, con variaciones de las temperaturas y precipitaciones. Se analiza la distribución de los bosques a través de modelado predictivo con el método de máxima entropía de MaxEnt. Los resultados señalan que la mayoría de las formaciones forestales de los bosques andinos analizados tendrán previsiblemente problemas importantes en un futuro próximo, consecuencia de la pérdida de idoneidad climática en el área actual de distribución y del cambio geográfico de las áreas potencialmente adecuadas en el futuro como reflejan los resultados. Palabras clave: biodiversidad, modelos de distribución de especies, cambio climático, bosques, máxima entropía. The high biodiversity along with a great variety of ecosystems turn Andes Mountain one of the regions of greater environmental diversity of the world, where are the most extreme ranges of types of landscapes, climate and forest formations of the Earth, an area suitable for studying the possible effects of climate change on the spatial distribution of forest formations. For this it is essential to understand the effects of climate change in the area, where climate observations indicate different climate scenarios in the future, for a current time period and for the period 2040-2069, with variations in temperatures and precipitation. The distribution of forests through predictive modelling is analyzed using MaxEnt’s maximum entropy method. The results indicate that most of the forest formations in the Andean forests analysed are expected to face significant problems in the near future, as a result of the loss of climate suitability in the current area of distribution and the geographic change of potentially suitable areas in the future as reflected in the results. Keywords: biodiversity, species distribution models, climate change, forests, maximum entropy

scholarly journals Using climate change models to inform the recovery of the western ground parrot Pezoporus flaviventris

Oryx ◽  
2019 ◽  
Vol 54 (1) ◽  
pp. 52-61
Author(s):  
Shaun W. Molloy ◽  
Allan H. Burbidge ◽  
Sarah Comer ◽  
Robert A. Davis
Keyword(s):  
Climate Change ◽  
Habitat Degradation ◽  
Climate Change Impacts ◽  
Fire Regimes ◽  
Suitable Habitat ◽  
Distribution Models ◽  
Conservation Action ◽  
Change Models ◽  
Introduced Predators ◽  
The Future

AbstractTranslocation of species to areas of former habitat after threats have been mitigated is a common conservation action. However, the long-term success of reintroduction relies on identification of currently available habitat and areas that will remain, or become, habitat in the future. Commonly, a short-term view is taken, focusing on obvious and assumed threats such as predators and habitat degradation. However, in areas subject to significant climate change, challenges include correctly identifying variables that define habitat, and considering probable changes over time. This poses challenges with species such as the western ground parrot Pezoporus flaviventris, which was once relatively common in near-coastal south-western Australia, an area subject to major climate change. This species has declined to one small population, estimated to comprise < 150 individuals. Reasons for the decline include altered fire regimes, introduced predators and habitat clearing. The establishment of new populations is a high priority, but the extent to which a rapidly changing climate has affected, and will continue to affect, this species remains largely conjecture, and understanding probable climate change impacts is essential to the prioritization of potential reintroduction sites. We developed high-resolution species distribution models and used these to investigate climate change impacts on current and historical distributions, and identify locations that will remain, or become, bioclimatically suitable habitat in the future. This information has been given to an expert panel to identify and prioritize areas suitable for site-specific management and/or translocation.

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.

Considerations for predicting climate change implications on future spatial distribution ranges of ticks.

2021 ◽  
pp. 38-43
Author(s):  
Ram Raghavan ◽  
Roman Ganta
Keyword(s):  
Climate Change ◽  
Spatial Distribution ◽  
Careful Consideration ◽  
Climate Change Scenarios ◽  
Field Observations ◽  
Distribution Models ◽  
Distribution Ranges ◽  
The Future ◽  
Tick Distributions

Abstract This chapter focuses on spatial distribution models (SDMs) that are essential to producing reliable models of tick distributions, both in the present time and in the future, under climate change scenarios. It highlights the opinion that careful consideration of the methods is necessary in building SDMs, model assumptions, the limitations in predictions and making a careful interpretation of predictions, if possible, supported by field observations.

scholarly journals The Potential Distribution of Tree Species in Three Periods of Time under a Climate Change Scenario

Forests ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 628 ◽  
Author(s):  
Pablo Antúnez ◽  
Mario Suárez-Mota ◽  
César Valenzuela-Encinas ◽  
Faustino Ruiz-Aquino
Keyword(s):  
Climate Change ◽  
Tree Species ◽  
Potential Distribution ◽  
Climate Change Scenario ◽  
Wide Distribution ◽  
Change Scenario ◽  
Slight Reduction ◽  
Distribution Models ◽  
The Future ◽  
Climatic Change Impact

Species distribution models have become some of the most important tools for assessment of impact of climatic change, impact of human activity and for the detection of failure in silvicultural or conservation management plans. In this study, we modeled the potential distribution of 13 tree species of temperate forests distributed in the Mexican state Durango in the Sierra Madre Occidental, for three periods of time. Models were constructed for each period of time using 19 climate variables from the MaxEnt (Maximum Entropy algorithm) modelling algorithm. Those constructed for the future used a severe climate change scenario. When comparing the potential areas of the periods, some species such as Pinus durangensis (Martínez), Pinus teocote (Schiede ex Schltdl. & Cham.) and Quercus crassifolia (Bonpl.) showed no drastic changes. Rather, the models projected a slight reduction, displacement or fragmentation in the potential area of Pinus arizonica (Engelm.), P. cembroides (Zucc), P. engelmanni (Carr), P. leiophylla (Schl), Quercus arizonica (Sarg), Q. magnolifolia (Née) and Q. sideroxila (Humb. & Bonpl.) in the future period. Thus, establishing conservation and reforestation strategies in the medium and long term could guarantee a wide distribution of these species in the future.

scholarly journals Snow Vulnerability Analysis in the Korean Peninsula using RCP Climate Change Scenarios

2020 ◽  
Vol 20 (4) ◽  
pp. 251-259
Author(s):  
Joonhyeok Ha ◽  
Heeseong Park ◽  
Gunhui Chung
Keyword(s):  
Climate Change ◽  
Vulnerability Analysis ◽  
Entropy Method ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
State Response ◽  
Thiessen Polygon ◽  
The Future ◽  
Polygon Method

Snow vulnerability analysis was implemented using 400 years of controlled RCP 2.6, 4.5, 6.0, and 8.5 scenarios in the following divided periods: the former period (2011-2040), middle period (2041-2070), and later period (2071-2100). Data from a total of 74 meteorological stations were used and the Thiessen polygon method was applied in the areas without stations. The indicators were classified into the Pressure-State-Response (PSR) structure, and the weight for vulnerability analysis was calculated using the entropy method. As snow vulnerability analysis was implemented for the future scenarios, it was difficult to determine social and economic factors as indicators; thus, only predicted weather data and population trends were considered. As a result, the rankings for snow vulnerable areas were determined for each period and scenario. Overall, snow vulnerability would decrease due to the decrease in long-term heavy snowfall in climate change scenarios. However, increased snow vulnerability is also expected in Sejong-si and the western coastal area due to a rise in population and snow depth in the future. Based on this, disaster prevention projects considering the characteristics of the region in the future could be implemented.

scholarly journals Predictions of potential geographical distribution and quality ofSchisandra sphenantheraunder climate change

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2554 ◽  
Author(s):  
Yanlong Guo ◽  
Haiyan Wei ◽  
Chunyan Lu ◽  
Bei Gao ◽  
Wei Gu
Keyword(s):  
Climate Change ◽  
Medicinal Plants ◽  
Fuzzy Theory ◽  
Plant Distribution ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Distribution Models ◽  
Entropy Model ◽  
Intergovernmental Panel ◽  
The Future

Climate change will significantly affect plant distribution as well as the quality of medicinal plants. Although numerous studies have analyzed the effect of climate change on future habitats of plants through species distribution models (SDMs), few of them have incorporated the change of effective content of medicinal plants.Schisandra sphenantheraRehd. et Wils. is an endangered traditional Chinese medical plant which is mainly located in the Qinling Mountains. Combining fuzzy theory and a maximum entropy model, we obtained current spatial distribution of quality assessment forS. spenanthera. Moreover, the future quality and distribution ofS. spenantherawere also projected for the periods 2020s, 2050s and 2080s under three different climate change scenarios (SRES-A1B, SRES-A2 and SRES-B1 emission scenarios) described in the Special Report on Emissions Scenarios (SRES) of IPCC (Intergovernmental Panel on Climate Change). The results showed that the moderately suitable habitat ofS. sphenantheraunder all climate change scenarios remained relatively stable in the study area. The highly suitable habitat ofS. sphenantherawould gradually decrease in the future and a higher decline rate of the highly suitable habitat area would occur under climate change scenarios SRES-A1B and SRES-A2. The result suggested that in the study area, there would be no more highly suitable habitat areas forS. sphenantherawhen the annual mean temperature exceeds 20 °C or its annual precipitation exceeds 1,200 mm. Our results will be influential in the future ecological conservation and management ofS. sphenantheraand can be taken as a reference for habitat suitability assessment research for other medicinal plants.

scholarly journals Impacts of climate change on infestations of Dubas bug (Ommatissus lybicus Bergevin) on date palms in Oman

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5545 ◽  
Author(s):  
Farzin Shabani ◽  
Lalit Kumar ◽  
Rashid Hamdan Saif al Shidi
Keyword(s):  
Climate Change ◽  
Climatic Variability ◽  
Regression Tree ◽  
Distribution Models ◽  
Boosted Regression Tree ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Palm Trees ◽  
The Future ◽  
Sensitivity Specificity

Climate change has determined shifts in distributions of species and is likely to affect species in the future. Our study aimed to (i) demonstrate the linkage between spatial climatic variability and the current and historical Dubas bug (Ommatissus lybicus Bergevin) distribution in Oman and (ii) model areas becoming highly suitable for the pest in the future. The Dubas bug is a pest of date palm trees that can reduce the crop yield by 50% under future climate scenarios in Oman. Projections were made in three species distribution models; generalized linear model, maximum entropy, boosted regression tree using of four global circulation models (GCMs) (a) HadGEM2, (b) CCSM4, (c) MIROC5 and (d) HadGEM2-AO, under four representative concentration pathways (2.6, 4.5, 6.0 and 8.5) for the years 2050 and 2070. We utilized the most commonly used threshold of maximum sensitivity + specificity for classifying outputs. Results indicated that northern Oman is currently at great risk of Dubas bug infestations (highly suitable climatically) and the infestations level will remain high in 2050 and 2070. Other non-climatic integrated pest management methods may be greater value than climatic parameters for monitoring infestation levels, and may provide more effective strategies to manage Dubas bug infestations in Oman. This would ensure the continuing competitiveness of Oman in the global date fruit market and preserve national yields.

What we can learn from the parallels between the COVID-19 and the future climate change crises

2020 ◽  
Author(s):  
Rubén D. Manzanedo ◽  
Peter Manning
Keyword(s):  
Climate Change ◽  
Global Economy ◽  
Global Climate ◽  
Future Climate Change ◽  
Substantial Portion ◽  
Preventative Measures ◽  
The Future ◽  
Behavioral Norm ◽  
Climate Crisis ◽  
Global Population

The ongoing COVID-19 outbreak pandemic is now a global crisis. It has caused 1.6+ million confirmed cases and 100 000+ deaths at the time of writing and triggered unprecedented preventative measures that have put a substantial portion of the global population under confinement, imposed isolation, and established ‘social distancing’ as a new global behavioral norm. The COVID-19 crisis has affected all aspects of everyday life and work, while also threatening the health of the global economy. This crisis offers also an unprecedented view of what the global climate crisis may look like. In fact, some of the parallels between the COVID-19 crisis and what we expect from the looming global climate emergency are remarkable. Reflecting upon the most challenging aspects of today’s crisis and how they compare with those expected from the climate change emergency may help us better prepare for the future.

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