Where Did You Come From? Where Did You Go? Investigating the Origin of Invasive Leptocybe Species Using Distribution Modelling

Invasion risks presented by Gonopsis affinis and the use of Trissolcus mitsukurii as a biological control agent under present and future climate conditions

BACKGROUND

Gonopsis affinis (Uhler) is a stinkbug that represents a significant threat to the production of rice (Oryza sativa L.), sugarcane (Saccharum officinarum L.) and eulalia (Miscanthus sinensis (Andersson)), and has been listed as a sugarcane pest in Japan. Trissolcus mitsukurii Ashmead is an egg parasitoid of G. affinis. To determine the potential of T. mitsukurii to be a biological control agent for G. affinis, we aim to predict the current and future areas of suitable habitat for these two species and their overlap with areas of present crop production. We developed MaxEnt models using two different variable selection methods and compared the two for T. mitsukurii with a CLIMEX model.

RESULTS

The results showed extensive suitable areas for G. affinis under current climate conditions in East Asia, West Africa, Madagascar, and South America. These ranges overlap with areas currently being used for the production of the three crops in question. More than half overlap with areas of suitable habitat for T. mitsukurii. The most critical environmental variable determining habitat suitability for G. affinis was showed to be precipitation of warmest quarter, whilst for T. mitsukurii it was minimum temperature of the coldest month.

CONCLUSION

Based on our assessment we recommend the immediate implementation of monitoring and invasion prevention measures for G. affinis in southwest China, the Malay Archipelago and West Africa. We suggest that T. mitsukurii be considered for use as a biological control agent in East Asia, Madagascar, Florida and Brazil in the case of future invasions by G. affinis. © 2023 Society of Chemical Industry.

Computational biogeographic distribution of the fall armyworm (Spodoptera frugiperda J.E. Smith) moth in eastern Africa

The fall armyworm (FAW), Spodoptera frugiperda J.E. Smith, has caused massive maize losses since its attack on the African continent in 2016, particularly in east Africa. In this study, we predicted the spatial distribution (established habitat) of FAW in five east African countries viz., Kenya, Tanzania, Rwanda, Uganda, and Ethiopia. We used FAW occurrence observations for three years i.e., 2018, 2019, and 2020, the maximum entropy (MaxEnt) model, and bioclimatic, land surface temperature (LST), solar radiation, wind speed, elevation, and landscape structure data (i.e., land use and land cover and maize harvested area) as explanatory variables. The explanatory variables were used as inputs into a variable selection experiment to select the least correlated ones that were then used to predict FAW establishment, i.e., suitability areas (very low suitability - very high suitability). The shared socio-economic pathways, SSP2-4.5 and SSP5-8.5 for the years 2030 and 2050 were used to predict the effect of future climate scenarios on FAW establishment. The results demonstrated that FAW establishment areas in eastern Africa were based on the model strength and true performance (area under the curve: AUC = 0.87), but not randomly. Moreover, ∼27% of eastern Africa is currently at risk of FAW establishment. Predicted FAW risk areas are expected to increase to ∼29% (using each of the SSP2-4.5 and SSP5-8.5 scenarios) in the year 2030, and to ∼38% (using SSP2-4.5) and ∼35% (using SSP5-8.5) in the year 2050 climate scenarios. The LULC, particularly croplands and maize harvested area, together with temperature and precipitation bioclimatic variables provided the highest permutation importance in determining the occurrence and establishment of the pest in eastern Africa. Specifically, the study revealed that FAW was sensitive to isothermality (Bio3) rather than being sensitive to a single temperature value in the year. FAW preference ranges of temperature, precipitation, elevation, and maize harvested area were observed, implying the establishment of a once exotic pest in critical maize production regions in eastern Africa. It is recommended that future studies should thus embed the present study's modeling results into a dynamic platform that provides near-real-time predictions of FAW spatial occurrence and risk at the farm scale.

Biogeographic Distribution of Cedrela spp. Genus in Peru Using MaxEnt Modeling: A Conservation and Restoration Approach

The increasing demand for tropical timber from natural forests has reduced the population sizes of native species such as Cedrela spp. because of their high economic value. To prevent the decline of population sizes of the species, all Cedrela species have been incorporated into Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The study presents information about the modeled distribution of the genus Cedrela in Peru that aims to identify potential habitat distribution of the genus, its availability in areas protected by national service of protected areas, and highlighted some areas because of their conservation relevance and the potential need for restoration. We modeled the distribution of the genus Cedrela in Peru using 947 occurrence records that included 10 species (C. odorata, C. montana, C. fissilis, C. longipetiolulata, C. angustifolia, C. nebulosa, C. kuelapensis, C. saltensis, C. weberbaueri, and C. molinensis). We aim to identify areas environmentally suitable for the occurrence of Cedrela that are legally protected by the National Service of Protected Areas (PAs) and those that are ideal for research and restoration projects. We used various environmental variables (19 bioclimatic variables, 3 topographic factors, 9 edaphic factors, solar radiation, and relative humidity) and the maximum entropy model (MaxEnt) to predict the probability of occurrence. We observed that 6.7% (86,916.2 km2) of Peru presents a high distribution probability of occurrence of Cedrela, distributed in 17 departments, with 4.4% (10,171.03 km2) of the area protected by PAs mainly under the category of protection forests. Another 11.65% (21,345.16 km2) of distribution covers areas highly prone to degradation, distributed mainly in the departments Ucayali, Loreto, and Madre de Dios, and needs immediate attention for its protection and restoration. We believe that the study will contribute significantly to conserve Cedrela and other endangered species, as well as to promote the sustainable use and management of timber species as a whole.

Predictive Modelling of Current and Future Potential Distribution of the Spectacled Bear (Tremarctos ornatus) in Amazonas, Northeast Peru

The spectacled, or Andean, bear (Tremarctos ornatus) is classified as vulnerable by the IUCN due to climate change and human-induced habitat fragmentation. There is an urgent need for the conservation of spectacled bear at real time. However, the lack of knowledge about the distribution of this species is considered as one of the major limitations for decision-making and sustainable conservation. In this study, 92 geo-referenced records of the spectacled bear, 12 environmental variables and the MaxEnt entropy modelling have been used for predictive modelling for the current and future (2050 and 2070) potential distribution of the spectacled bear in Amazonas, northeastern Peru. The areas of "high", "moderate" and "low" potential habitat under current conditions cover 1.99% (836.22 km2), 14.46% (6081.88 km2) and 20.73% (8718.98 km2) of the Amazon, respectively. "High" potential habitat will increase under all climate change scenarios, while "moderate" and "low" potential habitat, as well as total habitat, will decrease over the time. The "moderate", "low" and total potential habitat are distributed mainly in Yunga montane forest, combined grasslands/rangelands and secondary vegetation and Yunga altimontane (rain) forest, while "high" potential habitat is also concentrated in the Jalca. The overall outcome showed that the most of the important habitats of the spectacled bear are not part of the protected natural areas of Amazonas, under current as well as under future scenarios.

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

The Andean-Amazonian landscape has been universally recognized for its wide biodiversity, and is considered as global repository of ecosystem services. However, the severe loss of forest cover and rapid reduction of the timber species seriously threaten this ecosystem and biodiversity. In this study, we have modeled the distribution of the ten most exploited timber forest species in Amazonas (Peru) to identify priority areas for forest conservation and restoration. Statistical and cartographic protocols were applied with 4454 species records and 26 environmental variables using a Maximum Entropy model (MaxEnt). The result showed that the altitudinal variable was the main regulatory factor that significantly controls the distribution of the species. We found that nine species are distributed below 1000 m above sea level (a.s.l.), except Cedrela montana, which was distributed above 1500 m a.s.l., covering 40.68%. Eight of 10 species can coexist, and the species with the highest percentage of potential restoration area is Cedrela montana (14.57% from Amazonas). However, less than 1.33% of the Amazon has a potential distribution of some species and is protected under some category of conservation. Our study will contribute as a tool for the sustainable management of forests and will provide geographic information to complement forest restoration and conservation plans.

Current and Future Distribution of Five Timber Forest Species in Amazonas, Northeast Peru: Contributions towards a Restoration Strategy

Forest and land degradation is a serious problem worldwide and the Peruvian National Map of Degraded Areas indicates that 13.78% (177,592.82 km2) of the country’s territory is degraded. Forest plantations can be a restoration strategy, while conserving economically important species affected by climate change and providing forestry material for markets. This study modelled the species distribution under current conditions and climate change scenarios of five Timber Forest Species (TFS) in the Amazonas Department, northeastern Peru. Modelling was conducted with Maximum Entropy (MaxEnt) using 26 environmental variables. Of the total distribution under current conditions of Cedrelinga cateniformis, Ceiba pentandra, Apuleia leiocarpa, Cariniana decandra and Cedrela montana, 34.64% (2985.51 km2), 37.96% (2155.86 km2), 35.34% (2132.57 km2), 33.30% (1848.51 km2), and 35.81% (6125.44 km2), respectively, correspond to degraded areas and, therefore, there is restoration potential with these species. By 2050 and 2070, all TFS are projected to change their distribution compared to their current ranges, regardless of whether it will be an expansion and/or a contraction. Consequently, this methodology is intended to guide the economic and ecological success of forest plantations in reducing areas degraded by deforestation or similar activities.