Fig. 2.16 (a) Line transect record card. (b) Point transect record card.

      Source: Sara Vero.

Event Sampling

      Event sampling is perhaps most common in hydrology and related fields. This approach involves taking samples during or subsequent to specific target conditions. This frequently involves measurement of surface water quality in response to storms, which generate overland flow and runoff of potential contaminants such as sediment or pesticides to surface water, although subsurface leaching and preferential flow may also be triggered under such conditions. Event sampling will involve fairly typical techniques; the key difference is in preparedness and timing. As events can be both sudden and relatively brief, if you are not completely prepared in advance you may miss them. There are some steps which can help:

Grab Versus Composite Sampling

      Grab sampling is when a sample is taken at a specific location and single point in time that provides a “snapshot” of that specific moment. Frequently, grab samples are subject to environmental conditions prior to sampling and may be strongly influenced by incidents occurring recently. However, grab sampling has a valuable role in environmental research. It can be used in scoping studies to indicate the suitability of a site for future research or to evaluate conditions subject to an event. Grab samples may be incorporated into case studies or site characterization, which can provide useful additional background data to support analysis. Heterogeneity is the enemy of grab sampling! Where sites are highly heterogeneous, an unstructured approach to characterization will rarely yield an accurate understanding. To make matters worse, if there is a significant element of sorting, you may be predisposed to sampling a specific component. Therefore, the more heterogeneous or dynamic a site, material or process is, the less suitable grab sampling is as a method of characterization. You should also consider the type of heterogeneity; compositional or distributional.

      Compositional heterogeneity is when a population is made up of several different components or elements, which can be in equal or differing proportions, but which is mixed. Consider a meadow in which grass and flower species are randomly distributed with no particular structure. In this instance, a single quadrat of 1 m² cut at any location in that meadow would be likely to harvest a variety of different species, however, because of randomness could not be guaranteed to reflect the overall composition of that sward.

      Distributional heterogeneity is when a population of different components is structured or distributed. Imagine if the same species from the meadow were separated out and each species planted in rows of only their kind. In that instance, a quadrat cut at any location would only harvest a single species, and definitely would not reflect the overall sward composition. Distributional heterogeneity also applies to variations which occur over time, for example, diurnal fluctuations.

      Both types of heterogeneity are poorly captured by grab sampling. Another example is loads in a watercourse. If the concentrations are relatively stable (i.e., do not fluctuate depending on flow or time), then grab sampling should be an acceptable indicator of water quality. However, if there is heterogeneity, such as what may arise from diurnal nutrient discharges, or if there is a dilution effect during high‐flow periods, then a grab sample could not reliably indicate quality or loads. However, a modified approach to grab sampling can be used to provide a synoptic snapshot; in other words, a more thorough picture of a scenario at a specific point in time. An example of this is taking a large number of water samples across a watercourse at the same time or within a very short period (hours) during which flow is stable. Each sample remains discrete and each are non‐replicated, but viewed altogether, can be used to investigate patterns across a watershed.

      Composite sampling consists of multiple samples taken over a period of time or across an area. In other words, composite sampling is essentially incorporation of multiple grab samples and treating this aggregate as a single unit. It is important that representative amounts of each grab sample are present in the composite, otherwise it will be biased. A composite approach may require greater effort but has the advantage of being more representative of the area or process. Examples of composite sampling are:

      Replicated sampling also involves taking several discrete measurements or samples, but unlike composite sampling, each replicate is treated as an individual and is not mixed with the others. The statistical difference between the replicates should be assessed.

Sampling for Laboratory Studies

      Fieldwork doesn't necessarily mean that the experiment itself is conducted outdoors. You may need to collect materials for use in controlled, laboratory tests. For example, studies of microbial respiration using incubation chambers need substrate such as soil, sediment, manure, etc. Unlike agar, purified water, or any other common laboratory material, you need to find, sample, and retrieve these samples from the field. The advantages of these studies include the ability to control microcosms to a degree which is largely impossible in situ, the opportunity to apply multiple treatments and the potential for replication and subsampling. Furthermore, you are not as logistically constrained as when you must return to the field for repeated sampling. Sounds ideal! However, you should not underestimate the challenges.

      Let us take an example. You want to investigate CO₂ emissions from a range of soil types treated with a commercial amendment. Each incubation chamber requires 150 g dry weight of soil and you want to apply three rates of amendment plus an untreated control. You plan on using four replicates and four different soil types. This means