Temperature Characteristics of Two Fomitiporia Fungi Determine Their Geographical Distributions in Japan

Two morphologically similar fungi, Fomitiporia torreyae and Fomitiporia punctata, are causal fungi of various tree diseases in Japan and are speculated to be distributed in different climatic zones. Clarifying their distribution ranges and climatic preferences would contribute to the prediction of disease occurrences and consideration of controls. In this study, we predicted the present geographical distributions of F. torreyae and F. punctata in Japan using a Maxent species distribution model to analyze our data and previously published collection records. In addition, we examined the importance of temperature on these predictions via jackknife analysis and evaluated the effects of temperature on mycelial growth and survival to elucidate determinants of their distribution. The predicted potential distributions showed that F. torreyae is mainly distributed in warmer areas compared to F. punctata. Jackknife analysis indicated the high importance of temperature variables for each fungal prediction. The two fungi were usually found at locations within upper or lower temperature limits for the growth and survival of each species. These results suggest that temperature is a key determinant of their distributions in Japan. This is the first report to predict fungal distribution based on species distribution modeling and evaluation of fungal physiological characteristics. This study indicates that the projected global warming will influence the future ranges of the two fungal species.

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Quantification of land-sea nutrient fluxes supplied by allis shad across the species' range

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2021-0012 ◽

2021 ◽

Author(s):

Camille Poulet ◽

Betsy L. Barber-O'Malley ◽

Géraldine Lassalle ◽

Patrick Lambert

Keyword(s):

Ecosystem Services ◽

Species Distribution ◽

Large Scale ◽

Western Europe ◽

Species Distribution Model ◽

Distribution Model ◽

Nutrient Loads ◽

Allis Shad ◽

Distribution Ranges ◽

Nutrient Subsidies

Diadromous species act as nutrient vectors between their marine and freshwater habitats. Few valuations of this regulating service exist and none at the scale of species distribution ranges. This large-scale approach seems particularly relevant for species moving and exchanging individuals across borders and territories as these populations may strongly depend upon each other in terms of population viability and provision of ecosystem services. The development of a new nutrient routine within an existing mechanistic species distribution model provided estimates of the 'maximum potential' of the anadromous allis shad (Alosa alosa) to provide nitrogen and phosphorous subsidies throughout Western Europe. During their seasonal reproductive migration, shad provided low amounts of nutrient subsidies when compared to North-American anadromous species and annual riverine nutrient loads. However, these subsidies are delivered as pulses concentrated in space and time, suggesting that more work is needed to figure out the significance of these shad-derived nutrients in terms of riverine ecosystem functioning. The evidence of a substantial flow of strayers delivering nutrient subsidies in several rivers confirmed the need for large-scale management of migratory species to ensure a sustainable provision of ecosystem services.

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Protected areas’ effectiveness under climate change: a latitudinal distribution projection of an endangered mountain ungulate along the Andes Range

PeerJ ◽

10.7717/peerj.5222 ◽

2018 ◽

Vol 6 ◽

pp. e5222 ◽

Cited By ~ 3

Author(s):

Carlos Riquelme ◽

Sergio A. Estay ◽

Rodrigo López ◽

Hernán Pastore ◽

Mauricio Soto-Gamboa ◽

...

Keyword(s):

Climate Change ◽

Protected Areas ◽

Species Distribution ◽

Climate Models ◽

Species Distribution Model ◽

Global Climate Models ◽

Distribution Model ◽

Suitable Habitat ◽

Climate Change Scenarios ◽

Distribution Ranges

BackgroundClimate change is one of the greatest threats to biodiversity, pushing species to shift their distribution ranges and making existing protected areas inadequate. Estimating species distribution and potential modifications under climate change are then necessary for adjusting conservation and management plans; this is especially true for endangered species. An example of this issue is the huemul (Hippocamelus bisulcus), an endemic endangered deer from the southern Andes Range, with less than 2,000 individuals. It is distributed in fragmented populations along a 2,000 km latitudinal gradient, in Chile and Argentina. Several threats have reduced its distribution to <50% of its former range.MethodsTo estimate its potential distribution and protected areas effectiveness, we constructed a species distribution model using 2,813 huemul presence points throughout its whole distribution range, together with 19 bioclimatic layers and altitude information from Worldclim. Its current distribution was projected for years 2050 and 2070 using five different Global Climate Models estimated for scenarios representing two carbon Representative Concentration Routes (RCP)—RCP4.5 and RCP6.0.ResultsBased on current huemul habitat variables, we estimated 91,617 km2of suitable habitat. In future scenarios of climate change, there was a loss of suitable habitat due to altitudinal and latitudinal variation. Future projections showed a decrease of 59.86–60.26% for the year 2050 and 58.57–64.34% for the year 2070 according to RCP4.5 and RCP6.0, respectively. Protected areas only covered only 36.18% of the present distribution, 38.57–34.94% for the year 2050 and 30.79–31.94% for 2070 under climate change scenarios.DiscussionModeling current and future huemul distributions should allow the establishment of priority conservation areas in which to focus efforts and funds, especially areas without official protection. In this way, we can improve management in areas heavily affected by climate change to help ensure the persistence of this deer and other species under similar circumstances worldwide.

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A Robust Prediction Model for Species Distribution Using Bagging Ensembles with Deep Neural Networks

Remote Sensing ◽

10.3390/rs13081495 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1495

Author(s):

Jehyeok Rew ◽

Yongjang Cho ◽

Eenjun Hwang

Keyword(s):

Neural Networks ◽

Species Distribution ◽

Best Practice ◽

Deep Neural Networks ◽

Species Distribution Models ◽

Species Distribution Model ◽

Environmental Data ◽

Distribution Model ◽

Distribution Models ◽

Robust Prediction

Species distribution models have been used for various purposes, such as conserving species, discovering potential habitats, and obtaining evolutionary insights by predicting species occurrence. Many statistical and machine-learning-based approaches have been proposed to construct effective species distribution models, but with limited success due to spatial biases in presences and imbalanced presence-absences. We propose a novel species distribution model to address these problems based on bootstrap aggregating (bagging) ensembles of deep neural networks (DNNs). We first generate bootstraps considering presence-absence data on spatial balance to alleviate the bias problem. Then we construct DNNs using environmental data from presence and absence locations, and finally combine these into an ensemble model using three voting methods to improve prediction accuracy. Extensive experiments verified the proposed model’s effectiveness for species in South Korea using crowdsourced observations that have spatial biases. The proposed model achieved more accurate and robust prediction results than the current best practice models.

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