Name: patch use in optimal foraging
Uploaded: 2019-01-29T11:04:46.000Z
Duration: 3 min 37 s
Channel: JoVE

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Heredity: Inheritance and Variation of Traits

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Optimal Foraging

Çoğu zaman yaşamda, bir bireyin ihtiyaç duyduğu şeyler hemen kavranamayabilir. Bu nedenle, organizmaların yiyecek araması gerekir. Yiyecek arama, basitçe yiyecek veya daha genel olarak kaynak arama süreci olarak tanımlanır. Yiyecek muhtemelen akla gelen ilk örnek olsa da, organizmalar barınak veya eşler gibi diğer kaynakları aramak zorundadır ve hayvanlar genellikle ihtiyaç duyduklarını elde etmek için büyük çaba harcarlar. Bununla birlikte, yiyecek arama eyleminin kendisi enerji gerektirir. Esasen, bireyler kalori yakmayı onları elde etmekle dengelemelidir. Basitçe söylemek gerekirse, yiyecek aramak bir strateji gerektirir. Ekolojistler, bir organizmanın yiyecek aramak için harcanan enerji, yani iki meşe palamudu değeri ile altı yeni meşe palamudu gibi elde edebileceği potansiyel enerji arasındaki optimum dengeyi karşıladığı koşulları modellemek için en uygun yiyecek arama teorisini yarattılar. 
Yiyecek aramanın bir özelliği, kaynakların her zaman bir habitat içinde eşit olarak dağılmamasıdır. Daha tipik olarak, kaynaklar, toplayıcıların arasında hareket etmesi gereken yamalar halinde bulunur. Peki, toplayıcılar bu kaynak yamalarında tam olarak nasıl gezinmeli? 1976'da evrimsel ekolojist Eric L. Charnov, organizmaların yiyecek aramalarını nasıl optimize ettiklerini açıklamak için marjinal değer teoremini veya MVT'yi buldu. MVT'nin optimum yiyecek arama için beş ana tahmini vardır. İlk olarak, toplayıcıların yüksek av yoğunluğuna sahip yamalarda, düşük av yoğunluğuna sahip yamalara göre daha fazla av yakalaması gerektiğini belirtir. İkincisi, teori, toplayıcıların yüksek av yoğunluğuna sahip yamalarda kaynak aramak için daha fazla zaman harcaması gerektiğini öngörüyor. Daha sonra, toplayıcı, birbirine yakın paketlenmiş yamaların bulunduğu yoğun ortamlarda, birbirinden daha fazla yayılmış yamaların bulunduğu seyrek ortamlara göre daha yüksek bir av yakalama oranına sahip olmalıdır. Dördüncü tahmin, toplayıcıların bu yoğun ortamlarda yiyecek aramak için seyrek ortamlara göre daha fazla zaman harcayacaklarını belirtir. Son olarak, bir toplayıcı, yakalama hızı tüm yamaların ortalama hızına düştüğünde bir yama bırakmalıdır. İşte bu noktada zamandan vazgeçme veya GUT adı verilen bir kavram devreye giriyor. GUT'u hesaplamak için, bireyin yamadan ayrıldığı zamandan son av öğesinin elde edildiği zamanı çıkarmanız yeterlidir. Bu nedenle, GUT, bir toplayıcının ziyaret ettiği tüm yamalar için aynı olmalıdır. 
Bu laboratuvarda, birkaç farklı yapay kaynak yamasında yiyecek arama simülasyonlarını tamamlayacak ve ardından sınıfınızın toplayıcı olarak nasıl performans gösterdiğini ve marjinal değer teoreminin kurallarına uyup uymadığınızı ölçmek için hesaplamalar yapacaksınız.

optimal yiyecek arama

<h4>Optimal Yiyecek Arama</h4>
Organizmalar hayatta kalabilmek için çevrelerindeki kaynakları edinmeli ve kullanmalıdır. Gıda, organizmaların araması gereken birincil kaynaklardan biri olsa da, bireylerin de yaşam alanı, barınak ve eş araması gerekir. Bu kaynak arama süreci, bir dizi maliyet ve fayda içeren yiyecek arama olarak bilinir. Daha spesifik olarak, bir kaynak elde etmek organizmaya bir fayda sağlar, ancak kaynağı aramak ve yakalamak zaman ve enerji harcamayı gerektirir. Bu nedenle, organizmalar, en düşük maliyetle en fazla faydayı sağlayarak net kazancı en üst düzeye çıkaran yiyecek arama stratejilerini benimser. Ekolojistler, bir organizmanın yiyecek arama maliyetleri ve faydaları arasındaki optimum dengeyi karşıladığı durumları modellemek için "Optimal Yiyecek Arama Teorisi" ni geliştirdiler.
<h4>Marjinal Değer Teoremi</h4>
Kaynaklar çevrede eşit olarak dağıtılmaz. Örneğin, bir orman ekosisteminde, orman boyunca eşit olarak dağılmak yerine bir araya toplanmış ağaç türlerini bulmak çok daha olasıdır. Kaynak kullanılabilirliğindeki bu heterojenlik, kaynakların "yamalarını" oluşturur. Bu nedenle, toplayıcılar hem bir yamanın getirisini hem de yamalar arasındaki mesafeyi, dolayısıyla başka bir yamaya geçmenin maliyetini göz önünde bulundurmalıdır. Marjinal Değer Teoremi (MVT), optimal toplayıcıların yaşam alanlarındaki kaynak parçalarını nasıl kullandıklarını ve bunlar arasında nasıl hareket ettiklerini açıklar 1. MVT'nin beş ana tahmini vardır: 
<ol class="referanslar">
	<li>Toplayıcılar, düşük av yoğunluğuna sahip yamalara göre yüksek av yoğunluğuna sahip yamalarda daha fazla av yakalamalıdır.</li>
	<li>Toplayıcılar, düşük av yoğunluğuna sahip olanlara göre yüksek av yoğunluğuna sahip yamalarda yiyecek aramak için daha fazla zaman harcamalıdır.</li>
	<li>Toplayıcılar, yoğun yamalarda birbirinden daha uzağa yayılmış olanlardan daha yüksek bir av yakalama oranına sahip olmalıdır.</li>
	<li>Toplayıcılar, yamaların kümelendiği yoğun ortamlarda, seyrek ortamlara göre daha fazla zaman harcamalıdır.</li>
	<li>Toplayıcılar, yakalama oranı tüm yamaların ortalama hızına düştüğünde bir yama bırakmalıdır.</li>
</ol>
Son avın yakalanması ile toplayıcının yamayı terk etmesi arasındaki zaman aralığı, Verme Zamanı veya GUT olarak bilinir. MVT bağlamında, GUT her bir toplayıcı için tüm yamalarda aynı olmalıdır. Bu, yapay çam kozalaklarında gizlenmiş un kurdu için yiyecek arayan büyük bir büyük kuş kafesinde siyah şapkalı bülbüllerle yapılan bir deneyde test edildi, burada kuşlar her tür yama için aynı GUT'a sahipti, bu da tüm çevre için ortalama yakalama oranıyla ters orantılıydı 2. 
Bir organizma yiyecek aramak için ne kadar uzun süre harcarsa, o kadar fazla enerji harcar ve kendisini yırtıcılara ve elementlere o kadar uzun süre maruz bırakır, bu nedenle kaynak edinimi için en uygun yiyecek arama stratejisi geliştirmek çoğu organizma için çok önemlidir. MVT'nin ilkeleri, çeşitliliği, korumayı ve hatta insan davranışını teşvik etmek için birçok gerçek yaşam uygulamasına sahiptir.
<h4>Değişen bir ortamda optimum yiyecek arama</h4>
Çeşitlilik ve koruma açısından, MVT, türlerin ancak bir organizmanın enerji ihtiyaçlarını yeterince karşılayacak yamalar varsa var olabileceğini tahmin eder, bu nedenle hayatta kalmak için onlara bağımlı olan organizmalar için kullanılabilirlik ve kaynaklar arasındaki mesafe önemlidir. Habitat kaybı, kirlilik ve çevredeki diğer değişiklikler, bir organizmanın en iyi şekilde yiyecek arama yeteneğine müdahale edebilir ve bu nedenle zindeliğini azaltabilir. Böylece, bir ekosistemdeki habitatlar yok edildiğinde, yamalar veya tüm topluluklar kaldırılır. Bu kaldırma, bir ekosistemin geri kalanının sakinleri için mevcut kaynakları sınırlar. Kaynaklarla daha az yama, daha yoğun rekabet yaratır ve belirli türleri ortadan kaldırabilir. Bu, habitat kaybı nedeniyle nesli tükenme tehdidi altında olan ve habitatlarının çoğu tahrip olursa yiyecek arama ihtiyaçlarını karşılayamayacak olan türler için özellikle önemlidir. 
İnsanlar, yiyecek arama ihtiyaçlarını sınırlamak için karmaşık gıda depolamaları geliştirdiler, ancak uygun fiyatlı konut aramak, iyi maaşlı bir iş aramak veya diğerleri arasında uygun bir tarih bulmak gibi yiyecek aramanın gerekli olduğu birçok başka durum vardır. Yakın zamanda yapılan bir çalışma, Pratisyen Hekimlerin bilgi arama yeteneklerini kullanarak MVT'nin tahminlerini test etti. Pratisyen hekimlerin bir hastayı teşhis ederken en iyi şekilde bilgi aradıklarını buldular; Birden fazla bilgi kaynağı arasında hızlı bir şekilde geçiş yaptılar ve hem internet gibi yüksek yoğunluklu kaynakları hem de meslektaşları da dahil olmak üzere sık sık kolay ulaşılabilir kaynakları kullandılar 3. Benzer şekilde, Optimal Yiyecek Arama Teorisi, tüketicilerin nasıl alışveriş yaptıkları veya bir satın alma işlemi yaparken ürünler ve bilgiler için "yem" yaptıkları ekonomi için de geçerlidir 4. Bu çalışmalar, insanların çeşitli bağlamlarda optimal yiyecek arama teorisinin tahminlerine nasıl bağlı kaldıklarını göstermektedir.
<h4>Başvuru</h4>
<ol>
	<li>Charnov, E. L. ptimal toplayıcılık: marjinal değer teoremi. Teorik Populasyon Biyolojisi. 1976, Cilt 9, (129-36).</li>
	<li>John Krebs, John Ryan, Eric Charnov. Beklentiye göre avlanma veya optimal yiyecek arama: Bülbüller tarafından yama kullanımı üzerine bir çalışma. Hayvan Davranışı. 1974, Cilt 22, (953-64).</li>
	<li>Mai Dwairy, Anthony C Dowell, Jean-Claude Stahl. Yiyecek arama teorisinin pratisyen hekimlerin bilgi arama davranışlarına uygulanması. BMC Aile Hekimliği. 2011, Cilt 12, 90.</li>
	<li>Kuyular, V.K. Toplayıcılık: Tüketici davranışının ekolojik bir modeli mi? Pazarlama Teorisi. 2012, Cilt 2, 12 (117-136).</li>
</ol>

Optimal Yiyecek Arama

Optimal Yiyecek Arama
Organizmalar hayatta kalabilmek için çevrelerindeki kaynakları edinmeli ve kullanmalıdır. Gıda, organizmaların yapması gereken birincil kaynaklardan biri olsa da...

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patch use in optimal foraging

Patch use in optimal foraging explains how organisms balance food gain against the time and energy needed to search for it. Foraging is not limited to food. Animals also search for habitats, shelter, and mates. Each choice has costs and benefits. A resource provides a benefit, but finding and capturing it takes effort. Optimal Foraging Theory models how organisms reach the best balance between those costs and gains.

A key idea in this theory is that resources are often clumped into patches rather than spread evenly through an environment. Forest trees, for example, are more likely to occur in groups than as single, evenly spaced trees. Because of this patchiness, foragers must think about both the value of a patch and the distance to the next one. Moving between patches also has a cost. The Marginal Value Theorem helps explain when an organism should keep feeding in a patch and when it should move on.

The Marginal Value Theorem predicts that foragers should capture more prey in dense patches than in sparse ones. They should also spend more time in patches with more prey, and they should have a higher prey capture rate there. In dense environments, where patches are closer together, foragers should spend more time foraging than in sparse environments. A forager should leave a patch when the capture rate falls to the average rate for the whole environment. The time between the last prey capture and leaving the patch is called the Giving-Up-Time, or GUT.

The GUT should be the same across patches for a single forager. This prediction was tested with black-capped chickadees in a large aviary. The birds searched for mealworms hidden in artificial pine cones. They showed the same GUT in all patch types, and that GUT was inversely related to the average capture rate in the environment. The result supported the Marginal Value Theorem.

Optimal foraging matters because searching takes time, uses energy, and can expose organisms to predators and the elements. It also helps explain real-world ecology and conservation. Habitat loss, pollution, and other environmental changes can disrupt foraging and lower fitness. If habitats are destroyed, patches and even whole communities may disappear. That reduces the resources available to the rest of the ecosystem and can increase competition. Species at risk of extinction may be especially affected if most of their habitat is lost.

The same ideas also apply to human behavior. Humans reduce foraging needs through food storage, but they still forage in other ways. People may search for affordable housing, a well-paying job, or a suitable date. A study of general practitioners found that they foraged for information while diagnosing patients. They moved quickly between sources and used both high-density sources, such as the internet, and easier sources, including colleagues. Optimal Foraging Theory also helps explain how consumers search for products and information when making purchases.

Patch Use in Optimal Foraging

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Patch use in optimal foraging explains how organisms balance food gain against the time and energy needed to search for it. Foraging is not limited to food. Animals also search for habitats, shelter, and mates. Each choice has costs and benefits. A resource provides a benefit, but finding and capturing it takes effort. Optimal Foraging Theory models how organisms reach the best balance between those costs and gains. A key idea in this theory is that resources are often clumped into patches...

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Learn how optimal foraging theory explains patch use, Giving-Up-Time, and the Marginal Value Theorem using chickadees, conservation, and human examples.

Patch Use in Optimal Foraging | JoVE K12

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Optimal Yiyecek Arama öğretimine bu 3 dakikalık eğitmen rehberiyle hazırlanın. JoVE Lab Manual üzerindeki Biology laboratuvarı için temel hazırlık adımlarını kapsar.

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6 dakikalık bu öğrenci protokol videosunda Optimal Yiyecek Arama prosedürlerini adım adım takip edin. JoVE Lab Manual üzerindeki Biology koleksiyonunun bir parçasıdır.

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Pleiotropy

Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause ...

Ask questions to clarify relationships about the role of DNA and chromosomes in coding the instructions for characteristic traits passed from parents to offspring. [Assessment Boundary: Assessment does not include the phases of meiosis or the biochemical mechanism of specific steps in the process.]

HS-LS3-1

genome-size-and-the-evolution-of-new-genes

Genome Size and the Evolution of New Genes

Gene Families

Gene Evolution - Fast or Slow?

types-of-genetic-transfer-between-organisms

Types of Genetic Transfer Between Organisms

What is Meiosis?

Meiosis I

Meiosis is the division of a diploid cell into haploid cells forming sperm and eggs in animals through differentiation. Meiosis I is the first stage of ...

Meiosis II

Meiosis II entails cell division and segregation of the sister chromatids, resulting in the production of four unique haploid gametes. The steps for ...

Meiosis vs. Mitosis

Cell division is necessary for growth and reproduction in organisms. Mitosis aids cell growth and development by dividing somatic cells. In contrast, ...

Crossing over

Nondisjunction

Replication in Eukaryotes

Overview

In eukaryotic cells, DNA replication is highly conserved and tightly regulated. Multiple linear chromosomes must be duplicated with high ...

Proofreading

Synthesis of new DNA molecules starts when DNA polymerase links nucleotides together in a sequence that is complementary to the template DNA strand. DNA ...

Mismatch Repair

Overview

Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires ...

Nucleotide Excision Repair

Overview

Exposure to mutagens can damage DNA and result in bulky lesions that distort the double-helix structure or impede proper transcription. Damaged ...

Cancer Prevention

Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular ...

cancers-originate-from-somatic-mutations-in-a-single-cell

Cancers Originate from Somatic Mutations in a Single Cell

Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate ...

DNA Distortion and Damage
Cells are regularly exposed to mutagens&#8212;factors in the environment that can damage DNA and generate mutations. UV ...

comparing-copy-number-variations-and-snps

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist ...

Gene Conversion

Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the ...

Mutations

Overview

Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. ...

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions ...

Make and defend a claim based on evidence that inheritable genetic variations may result from (1) new genetic combinations through meiosis, (2) viable errors occurring during replication, and or (3) mutations caused by environmental factors. [Clarification Statement: Emphasis is on using data to support arguments for the way variation occurs.] [Assessment Boundary: Assessment does not include the phases of meiosis or the biochemical mechanism of specific steps in the process.]

HS-LS3-2

Patch Use in Optimal Foraging

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