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

Abstract

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.

Predicting Suitable Habitats of Camptotheca acuminata Considering Both Climatic and Soil Variables

“…Such information can be used to guide management forest resources for adaptation to climate change [36,37]. Although most of the niche-based models involve only climatic variables [16], soil properties are often recommended to be considered, especially for practical applications [38]. In this study, we applied a novel two-step approach to incorporate the soil variables into the future projections without compromising the contribution of climate or soil variables.…”

Suitability of Habitats in Nepal for Dactylorhiza hatagirea Now and under Predicted Future Changes in Climate

“…In addition to habitat loss, which is characterized as the greatest threat to species [ 2 ], living creatures are also affected by the increase in human emissions of carbon dioxide due to burning fossil fuels and other greenhouse gases, which are causing climate change [ 1 ]. The potential effects of future climatic conditions on biodiversity have been widely investigated and a large number of publications exist that predict these effects on trees [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ], medicinal herbaceous plants and shrubs [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ], fungi [ 18 ], invasive plants [ 19 , 20 ], terrestrial orchids [ 21 ], etc.…”

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

“…In this way, SDM allows for the analysis of a variety of situations related to the geographical distribution of species, such as: (1) rare or endangered species distribution, (2) current areas that should promote the conservation of a set of species, (3) identifying the most cost-effective places to establish new species populations, and 4) the predicted distribution of these species in the future under global warming and climate change [9,10]. For such reasons, SDM aims to more effectively and generously support conservation actions [11] by predicting possible fragmentation or reduction in potential forest areas under future climate change scenarios [12].…”

“…In this study, we established the current and potential distribution of species using occurrence data through a Maximum Entropy (MaxEnt) model [14]. MaxEnt has been widely applied to studies of flora conservation [15], fauna [16,17], management of endangered species [18,19], conservation of endemic species [20], and invasive species control [21,22], as well as in forestry and agricultural zoning [12,23] [24] from local to global scales, allowing the development of "species distribution" maps and, finally, the estimation of a "suitability index" [25] for the Peruvian Amazon region. Though a few studies have been done over the Amazon region using MaxEnt models for evapotranspiration estimation [26], fire probability distribution [27], infrastructure expansion [24], and conservation of freshwater turtles [11], no such studies have been conducted for species distribution and its spatial modeling, which are the prime focuses of all conservation and restoration policies.…”