Question

1. You observe two species of fish that seem to consume the same resources, but somehow coexist despite limited food resources. You think it may have to do with their ability to avoid predation – one by hiding, the other by moving quickly. Design an experiment to test this observation.

1. What is your hypothesis? What is the ecological mechanism involved?
2. What will your experimental design look like?
3. What will you measure, and what analytical framework/analysis technique will you use?
4. What is your null hypothesis, and does the rejection of your null imply your hypothesis (a)?

Answer 1

a) In statistical hypothesis testing, two hypotheses are compared. These are called the null hypothesis and the alternative hypothesis. Here it is null hypothesis.In inferential statistics, the null hypothesis is a general statement or default position that there is no relationship between two measured phenomena or no association among groups. Testing (accepting, approving, rejecting, or disproving) the null hypothesis—and thus concluding that there are (or there are not) grounds for believing that there is a relationship between two phenomena (e.g. that a potential treatment has a measurable effect)—is a central task in the modern practice of science; the field of statistics, more specifically hypothesis testing, gives precise criteria for rejecting or accepting a null hypothesis within a confidence level.

The ecological mechanism of niche partitioning involves a complementarity effect resulting from facilitative interactions. This mechanism occurs when different species occupy unique niches, or habitat types, within an environment in a complementary way so that the collective resource use is ultimately enhanced.

In ecology, a community is a group or association of populations of two or more different species occupying the same geographical area at the same time, also known as a biocoenosis. The term community has a variety of uses. In its simplest form it refers to groups of organisms in a specific place or time, for example, "the fish community of Lake Ontario before industrialization". In interspecies competition, two species use the same limited resource. Competition has a negative effect on both of the species. A species' niche is basically its ecological role, which is defined by the set of conditions, resources, and interactions it needs (or can make use of).The competitive exclusion principle says that two species can't coexist if they occupy exactly the same niche (competing for identical resources).Two species whose niches overlap may evolve by natural selection to have more distinct niches, resulting in resource partitioning.

Competitive exclusion may be avoided if one or both of the competing species evolves to use a different resource, occupy a different area of the habitat, or feed during a different time of day. The result of this kind of evolution is that two similar species use largely non-overlapping resources and thus have different niches. This is called resource partitioning, and it helps the species coexist because there is less direct competition between them.Here the two species of fish that seem to consume the same resources, that is resource partitioning

b) Habitat-choice experiment. This experiment involved placing 2 fish of each species (separately) in aquana with solitary and colonial morphs at either side. Pairs of Premnas biaculeatus and groups of Amphiprion melanopus were collected and kept in tanks for at least 48 h to allow them to acclimatise to captivity before being used in experimental tnals. All fish used in this experiment were >30 mnl TL. On average, fish were kept in captivity for 7 d. Three specimens of solitary E. quadricolour and 3 Sets of colonial E. quadricolour were collected and allowed to attach to concrete blocks in circular (diameter = 1150 mnl, approx. water depth = 600 mm), fibre-glass tanks. Three of these tanks were established with a solitary anemone on one side and 5 or 6 colonial anemones (roughly matching the surface area of the solitary anemone) on the other side. Water flowed into each tank from a pipe placed oil one side of the tank (equal distance froin each of the anemone morphs) and out through a pipe at the bottom of the tank on the opposite side. Fish were introduced to the centre of the experimental tank through a PVC pipe attached to the bottom of an inverted bucket. Evenly spaced around the wall of the bucket were four mesh-covered holes. Two of these holes faced the anemones. Two fish (either a pair of P. biaculeatus or the 2 largest individuals from an A. melanopus social group) were introduced to the bucket at approximately 18:00 h and left for 15 min to acclimatise, after which the bucket was removed. The positions of the fish (i.e. occupying solitary or colonial anemones) were recorded after 1 h and again the following morning at approximately 06:30 h. Because the minimum size of social groups of anemonefishes in the field is 2, pairs of fish were used throughout these experiments. We assumed that behaviours exhibited by members of a pair were independent. Ten tnals were carned out for each of the 2 species; pairs of fish were used in only 1 trial each. The patterns of association between these 2 anemonefish species and the 2 anemone morphs could be the result of preferences of each species for each habitat or preferences for habitats occupied by conspecifics. If preference for a particular anemone morph is important in determining these patterns of association in the field, Premnas biaculeatus individuals would be expected to choose the solitary anemones and Amphiprion melanopus individuals would be expected to choose the colonial anemones more frequently than expected by chance. Otherwise, if habitats are selected based on the presence of conspecifics individuals should associate irrespective of the anemone morph selected. We tested for preference for anemone nlorphs by comparing the frequency with which each species selected each morph to that expected if no preference was exhibited. We then tested the possibility that habitats are selected based on the presence of conspecific individuals by comparing the frequency with which individuals occupied anemone morphs as pairs regardless of which morph they occupied. Binomial probabilities of obtaining results as extreme as those observed were estimated. These probabilities depend on 3 Parameters: the number of tnals, the probability of a success in each tnal, and the number of successes. When examining habitat preference, the choice by an individual of the anemone morph most frequently occupied by that species in the field was scored as a success. The number of trials was 20 (i.e. we treated each individual in the 10 pairs tested as an independent trial) for each species, and the probability of a success, if fish chose habitats at random, was 0.5. When examining whether habitats are selected based on the presence of conspecifics, 2 fish occupying the Same anemone morph (regardless of the morph chosen) was scored as a success. In this case, the number of tnals was 10 for each species and the probability of a success, if the fish occupied habitats at random, wds 0.5. Interspecific competition experiment.

c) There are two methods that a researcher can pursue: qualitative and quantitative.Qualitative research revolves around describing characteristics. It does not use numbers. A good way to remember qualitative research is to think of quality.Quantitative research is the opposite of qualitative research because its prime focus in numbers.

The Framework Method sits within a broad family of analysis methods often termed thematic analysis or qualitative content analysis. These approaches identify commonalities and differences in qualitative data, before focusing on relationships between different parts of the data, thereby seeking to draw descriptive and/or explanatory conclusions clustered around themes. The Framework Method was developed by researchers, Jane Ritchie and Liz Spencer, from the Qualitative Research Unit at the National Centre for Social Research in the United Kingdom in the late 1980s for use in large-scale policy research .It is now used widely in other areas, including health research . Its defining feature is the matrix output: rows (cases), columns (codes) and ‘cells’ of summarised data, providing a structure into which the researcher can systematically reduce the data, in order to analyse it by case and by code. Most often a ‘case’ is an individual interviewee, but this can be adapted to other units of analysis, such as predefined groups or organisations. While in-depth analyses of key themes can take place across the whole data set, the views of each research participant remain connected to other aspects of their account within the matrix so that the context of the individual’s views is not lost. Comparing and contrasting data is vital to qualitative analysis and the ability to compare with ease data across cases as well as within individual cases is built into the structure and process of the Framework Method.

d) The null hypothesis is generally assumed to be true until evidence indicates otherwise (similar to the case that a defendant of a jury trial is presumed innocent until guilty).

In statistics, it is often denoted H0, pronounced as "H-nought", "H-null", or "H-zero" (or, even, by some, "H-oh"), with the subscript being the digit 0.

The concept of a null hypothesis is used differently in two approaches to statistical inference. In the significance testing approach of Ronald Fisher, a null hypothesis is rejected if the observed data is significantly unlikely to have occurred if the null hypothesis were true. In this case, the null hypothesis is rejected and an alternative hypothesis is accepted in its place. If the data is consistent with the null hypothesis, then the null hypothesis is not rejected. In neither case is the null hypothesis or its alternative proven; the null hypothesis is tested with data and a decision is made based on how likely or unlikely the data is. This is analogous to the legal principle of presumption of innocence, in which a suspect or defendant is assumed to be innocent (null is not rejected) until proven guilty (null is rejected) beyond a reasonable doubt (to a statistically significant degree).

A possible null hypothesis is that the mean male score is the same as the mean female score:

H0: μ1 = μ2

where

H0 = the null hypothesis,

μ1 = the mean of population 1, and

μ2 = the mean of population 2.

A stronger null hypothesis is that the two samples are drawn from the same population, such that the variances and shapes of the distributions are also equal