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The South-west Floristic Region (SWAFR) by interim biogeographic regionalisation of Australia (IBRA) regions (Thackway and Cresswell 1995).
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Spatial modelling is increasingly being embraced by conservation practitioners and community groups to guide natural-asset management. Despite this boom in popularity, little guidance is often available on choosing the most applicable technique, and the relative merits and drawbacks of each approach. We present a case study in the biodiversity hots...
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... SWAFR (Fig. 1), is recognised internationally as a 'biodi- versity hotspot,' not only for the biological richness and uniqueness of species, but also for the high level of threat faced by these species (Myers et al. 2000;Hopper 2009). In 2013, it was found that there was ,20% of native vegetation remaining on the heavily urbanised southern Swan ...
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Madagascar is one of the most biodiverse countries in Africa, due to its level of endemism and species diversity. However, the pressure of human activities threatens the last patches of natural vegetation in the country and conservation decisions are undertaken with limited data availability. In this study, we use free online datasets to generate d...
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... Pertumbuhan laba menjadi perhatian penting bagi mereka yang ingin menanamkan modal atau memberikan pinjaman kepada perusahaan. Perubahan laba dapat dipengaruhi oleh beberapa faktor, seperti penjualan yang menurun, perubahan harga jual, perubahan jumlah unit yang terjual, kenaikan beban operasional, dan perubahan lainnya dalam laporan laba rugi (Molloy, Davis, & Van Etten, 2016). ...
Penelitian ini bertujuan untuk menganalisis hubungan antara perputaran piutang (X1), perputaran persediaan (X2), dan margin laba kotor perusahaan PT Summarecon Agung Tbk. Data keuangan dari periode 2019-2022 digunakan dalam analisis regresi untuk mengetahui pengaruh kedua variabel independent terhadap variabel dependent. Hasil analisis regresi menunjukkan bahwa terdapat hubungan negatif yang signifikan antara perputaran piutang dan margin laba kotor perusahaan (koefisien regresi: -0.195259, p-value: 0.0034). Artinya, peningkatan perputaran piutang mengakibatkan penurunan margin laba kotor perusahaan. Selain itu, juga ditemukan hubungan negatif yang signifikan antara perputaran persediaan dan margin laba kotor perusahaan (koefisien regresi: -0.377539, p-value: 0.0302). Ini menunjukkan bahwa peningkatan perputaran persediaan juga berdampak negatif terhadap margin laba kotor. Hasil penelitian ini memberikan pemahaman bahwa pengelolaan piutang dan persediaan yang efisien sangat penting dalam mencapai tingkat margin laba kotor yang optimal di PT Summarecon Agung Tbk. Manajemen perusahaan perlu memperhatikan dan mengoptimalkan kebijakan yang berkaitan dengan penagihan piutang dan pengendalian persediaan guna meminimalkan dampak negatif terhadap margin laba kotor.
... In this study, various models yielded equivalent predictive performances, which prevented distinguishing a single 'best' model. It is, thus, good practice for any conservation exercise to start by using different statistical methods for species distribution modeling, and to evaluate the predictive performance of the models obtained [58]. ...
Species distribution models (SDMs) provide robust inferences about species-specific site suitability and are increasingly used in systematic conservation planning (SCP). SDMs are subjected to intrinsic uncertainties, and conservation studies have generally overlooked these. The integration of SDM uncertainties in conservation solutions requires the development of a suitable optimization algorithm. Exact optimization algorithms grant efficiency to conservation solutions, but most of their implementations generate a single binary and indivisible solution. Therefore, without variation in their parameterization, they provide low flexibility in the implementation of conservation solutions by stakeholders. Contrarily, heuristic algorithms provide such flexibility, by generating large amounts of sub-optimal solutions. As a consequence, efficiency and flexibility are implicitly linked in conservation applications: mathematically efficient solutions provide less flexibility, and the flexible solutions provided by heuristics are sub-optimal. To avoid this trade-off between flexibility and efficiency in SCP, we propose a reserve-selection framework, based on exact optimization combined with a post-selection of SDM outputs. This reserve-selection framework provides flexibility and addresses the efficiency and representativeness of conservation solutions. To exemplify the approach, we analyzed an experimental design, crossing pre- and post-selection of SDM outputs versus heuristics and exact mathematical optimizations. We used the Mediterranean Sea as a biogeographical template for our analyses, integrating the outputs of eight SDM techniques for 438 fish species.
... One type of regression that is well tested in ecological data is generalised dissimilarity modelling (GDM). GDM is a multivariate regression method that has been applied widely in conservation planning and biodiversity assessment (Mokany and Ferrier 2011;House et al. 2012;Molloy et al. 2016;Ferrier et al. 2020;Mokany et al. 2020). Abiotic variables are used to model patterns in species turn-over at the community level and the following three methods are possible: predict then assemble, assemble then predict, or predict and assemble simultaneously (Ferrier 2002;Ferrier and Guisan 2006). ...
Conservation reserve selection is guided by vegetation classification and mapping. New survey data and improvements in the availability of archived data through online data-sharing platforms enable updated classifications and the critique of existing conservation criteria. In the Northern Jarrah Forest Region of south-western Australia, percentage-based targets using ‘forest ecosystem units’ (15% of each unit) and the systematic conservation planning principles of ‘comprehensiveness, adequacy and representativeness’ underpin the State’s reserve network. To assess the degree of community-level heterogeneity within the forest ecosystem units, new survey data for the forest (30000 plots) were classified using a non-hierarchical clustering algorithm. Results were assigned to the National Vegetation Information System, and community groups defined at the Association level (Level V). Significant community level heterogeneity was found, including 15 communities in the dominant ‘jarrah woodland’ unit, and 13 in the ‘shrub, herb and sedgelands’ unit. Overall, this research highlights limitations in the current reserve system, including the influence of scale on percentage-based targets and ‘representativeness’. A multi-scale approach to reserve selection, based on a quantitative, floristic, hierarchical classification system, would improve the level of scientific rigour underlying decision-making.
... In this study, various models yielded equivalent predictions performances, which prevented to distinguish a single "best" model. It is thus crucial for any conservation exercise to start by testing different statistical methods for species distribution modeling, and to evaluate the predictive performance of the models obtained (Molloy et al., 2016). ...
Species distribution models (SDMs) have been proposed as a way to provide robust inference about species-specific sites suitabilities, and have been increasingly used in systematic conservation planning (SCP) applications. However, despite the fact that the use of SDMs in SCP may raise some potential issues, conservation studies have overlooked to assess the implications of SDMs uncertainties. The integration of these uncertainties in conservation solutions requires the development of a reserve-selection approach based on a suitable optimization algorithm. A large body of research has shown that exact optimization algorithms give very precise control over the gap to optimality of conservation solutions. However, their major shortcoming is that they generate a single binary and indivisible solution. Therefore, they provide no flexibility in the implementation of conservation solutions by stakeholders. On the other hand, heuristic decision-support systems provide large amounts of sub-optimal solutions, and therefore more flexibility. This flexibility arises from the availability of many alternative and sub-optimal conservation solutions. The two principles of efficiency and flexibility are implicitly linked in conservation applications, with the most mathematically efficient solutions being inflexible and the flexible solutions provided by heuristics suffering sub-optimality. In order to avoid the trade-offs between flexibility and efficiency in systematic conservation planning, we propose in this paper a new reserve-selection framework based on mathematical programming optimization combined with a post-selection of SDM outputs. This approach leads to a reserve-selection framework that might provide flexibility while simultaneously addressing efficiency and representativeness of conservation solutions and the adequacy of conservation targets. To exemplify the approach we a nalyzed an experimental design crossing pre- and post-selection of SDM outputs versus heuristics and exact mathematical optimizations. We used the Mediterranean Sea as a biogeographical template for our analyses, integrating the outputs of 8 SDM techniques for 438 fishes species.
Translocation 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.
