Landscape features exist at multiple spatial and temporal scales, and these naturally affect spatial genetic structure and our ability to make inferences about gene flow. This article discusses how decisions about sampling of genotypes (including choices about analytical methods and genetic markers) should be driven by the scale of spatial genetic structure, the time frame that landscape features have existed in their current state, and all aspects of a species' life history. Researchers should use caution when making inferences about gene flow, especially when the spatial extent of the study area is limited. The scale of sampling of the landscape introduces different features that may affect gene flow. Sampling grain should be smaller than the average home-range size or dispersal distance of the study organism and, for raster data, existing research suggests that simplifying the thematic resolution into discrete classes may result in low power to detect effects on gene flow. Therefore, the methods used to characterize the landscape between sampling sites may be a primary determinant for the spatial scale at which analytical results are applicable, and the use of only one sampling scale for a particular statistical method may lead researchers to overlook important factors affecting gene flow. The particular analytical technique used to correlate landscape data and genetic data may also influence results; common landscape-genetic methods may not be suitable for all study systems, particularly when the rate of landscape change is faster than can be resolved by common molecular markers.
Landscape genetics plays an increasingly important role in the management and conservation of species. Here, we highlight some of the opportunities and challenges in using landscape genetic approaches in conservation biology. We first discuss challenges related to sampling design and introduce several recent methodological developments in landscape genetics (analyses based on pairwise relatedness, the application of Bayesian methods, inference from landscape resistance and a shift from population-based to individual-based analyses). We then show how simulations can foster the field of landscape genetics and, finally, elaborate on technical developments in sequencing techniques that will dramatically improve our ability to study genetic variation in wild species, opening up new and unprecedented avenues for genetic analysis in conservation biology.
Understanding the genetic basis of species adaptation in the context of global change poses one of the greatest challenges of this century. Although we have begun to understand the molecular basis of adaptation in those species for which whole genome sequences are available, the molecular basis of adaptation is still poorly understood for most non-model species. In this paper, we outline major challenges and future research directions for correlating environmental factors with molecular markers to identify adaptive genetic variation, and point to research gaps in the application of landscape genetics to real-world problems arising from global change, such as the ability of organisms to adapt over rapid time scales. High throughput sequencing generates vast quantities of molecular data to address the challenge of studying adaptive genetic variation in non-model species. Here, we suggest that improvements in the sampling design should consider spatial dependence among sampled individuals. Then, we describe available statistical approaches for integrating spatial dependence into landscape analyses of adaptive genetic variation.
▼ Özet Kuzey Anadolu'da Karadeniz Bölgesi'nin Batı Karadeniz Bölümü'nde yer alan Sinop; dağlık ve engebeli yapısı, kalkınmayı güçleştiren kısıtlı ekonomik imkânları, iç ve dış pazarlara erişimi engelleyen zorlu ulaşım şartları ve diğer nedenlerle Türkiye'nin en fazla göç veren illerinden biridir. TÜİK tarafından yayınlanan bazı çalışmalarda ise Sinop Türkiye'nin yaşlı, mutlu ve huzurlu illeri arasında ön sıralarda yer almaktadır. Araştırmada aynı kurum tarafından yayınlanan verilerden nasıl böyle iki farklı sonuç çıktığı araştırılmış, Sinop il genelinde mekânsal analiz yöntemi ile bu çelişkili sonucun nedenleri ve sonuçları üzerinde durulmuştur. Sinop'ta iş imkânlarının yetersizliği genç nüfusu il dışına göçe teşvik ederken, bu durum il genelinde yaşlı nüfus oranının artmasında etkili olmaktadır. Yayınlanan son istatistiklerde Sinop'ta çoğunluğunu emeklilerin oluşturduğu yaşlı nüfus % 18,1'lik oranla Türkiye genelinde ilk sırada yer almıştır. Diğer yandan çalışma çağındaki nüfusun yine göçlerle sürekli il dışına gitmesi Sinop il genelinde işsizlik rakamlarının da çok düşük çıkmasına neden olmaktadır. Bu iki husus bir arada değerlendirildiğinde, bunlara bir de özellikle il merkezi Sinop'un; temiz havası, denizi, ormanı, küçük ve sakin şehir hayatı eklendiğinde, bu kez Sinop, yine TÜİK verilerine göre, % 77,7 oranla Türkiye'de insanların en mutlu olduğu il olarak karşımıza çıkmaktadır. Başta geçim sıkıntısı ve ek gelir ihtiyacı olmak üzere, çeşitli sebeplerle il 1 Samsun Ondokuz Mayıs Üniversitesi, Turizm Fakültesi,
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