Spatial genetic structure of a keystone long-lived semiarid shrub: historical effects prevail but do not cancel the impact of recent severe habitat loss on genetic diversity

Extensive pollen-mediated gene flow across intensively managed landscapes in an insect-pollinated shrub native to semiarid habitats

Our knowledge of the impact of landscape fragmentation on gene flow patterns is mainly drawn from tropical and temperate ecosystems, where landscape features, such as the distance of a tree to the forest edge, drive connectivity and mating patterns. Yet, the structure of arid and semiarid plant communities - with open canopies and a scattered distribution of trees - differs greatly from those that are well-characterized in the literature. As a result, we ignore whether the documented consequences of landscape fragmentation on plant mating and gene flow patterns also hold for native plant communities in arid and semiarid regions. We investigated the relative contribution of plant traits, pollinator activity, and individual neighbourhood in explaining variation in mating and gene flow patterns of an insect-pollinated semiarid arborescent shrub, Ziziphus lotus, at three sites embedded in highly altered agriculture landscapes. We used 14 SSRs, seed paternity analyses, and individual mixed effect mating models (MEMMi) to estimate the individual mating variables and the pollen dispersal kernel at each site. Individual spatial location, flower density, and floral visitation rate explained most of the variation of mating variables. Unexpectedly, individual correlated paternity was very low and shrubs surrounded by the most degraded matrix exhibited an increased fraction of pollen immigration and a high effective number of pollen donors per mother shrub. Overall, our results reveal that an active pollinator assemblage ensures highly efficient mating, and maintains pollen-mediated gene flow and notable connectivity levels, even in highly altered landscapes, potentially halting genetic isolation within and between distant sites.

Analysis of the Current and Future Prediction of Land Use/Land Cover Change Using Remote Sensing and the CA-Markov Model in Majang Forest Biosphere Reserves of Gambella, Southwestern Ethiopia

This study aimed to evaluate land use/land cover changes (1987-2017), prediction (2032-2047), and identify the drivers of Majang Forest Biosphere Reserves. Landsat image (TM, ETM+, and OLI-TIRS) and socioeconomy data were used for the LU/LC analysis and its drivers of change. The supervised classification was also employed to classify LU/LC. The CA-Markov model was used to predict future LU/LC change using IDRISI software. Data were collected from 240 households from eight kebeles in two districts to identify LU/LC change drivers. Five LU/LC classes were identified: forestland, farmland, grassland, settlement, and waterbody. Farmland and settlement increased by 17.4% and 3.4%, respectively; while, forestland and grassland were reduced by 77.8% and 1.4%, respectively, from 1987 to 2017. The predicted results indicated that farmland and settlement increased by 26.3% and 6.4%, respectively, while forestland and grassland decreased by 66.5% and 0.8%, respectively, from 2032 to 2047. Eventually, agricultural expansion, population growth, shifting cultivation, fuel wood extraction, and fire risk were identified as the main drivers of LU/LC change. Generally, substantial LU/LC changes were observed and will continue in the future. Hence, land use plan should be proposed to sustain resource of Majang Forest Biosphere Reserves, and local communities' livelihood improvement strategies are required to halt land conversion.