Innovative approaches for measuring organism stress and behavioural integrity in flume facilities: Deliverable D8-IV

HYDRALAB+ aims to improve the usefulness and value of hydraulic laboratory facilities and is developing experimental guidelines that will allow researchers to successfully investigate complex scenarios representative of natural environments in a context of climate change. Within this framework it is often important to incorporate relevant biological elements in physical experiments, including the use of live vegetation. Notwithstanding efforts to maintain their health by careful husbandry, plants typically degenerate when introduced to flume settings. Physiological responses to degenerating health can affect their interactions with the flow so that experimental conditions are not representative of healthy specimens in situ. There is therefore a need to measure and evaluate the health of plants being used in hydraulic facilities, especially since behavioural integrity might be reduced before there are obvious signs of degeneration. Such measurements are not routinely made so there is a need to identify measurement techniques and methodological protocols for assessing vegetation health status in hydraulic laboratories. This deliverable identifies a technique established in plant physiology and horticulture for monitoring vegetation health status and shows how it can be applied in hydraulic laboratories with minimal impact on organisms. A simple and suitable test among those established in the relevant literature is validated by conducting experiments on freshwater macrophytes. From the relevant literature and the results of experiments reported herein, this deliverable provides an overview of the technique identified and establishes practical guidance on how to properly apply it in hydraulic experiments. The methodological protocol developed can potentially be integrated into established protocols used in ecohydraulics studies as a simple proxy of vegetation health status

Summary table of the effects of food shortage on female reproductive parameters in the present study.

<p>The non-detection – or positive – statistical effects of food shortage (in bold) are considered as indicative of resilience of the allocation to reproduction to food shortage. ‘Exp.’ holds for Experiment.</p

Effect of food availability to mothers (Food effect: females fed <i>ad libitum</i> or exposed to a 40% chronic caloric restriction) and of litter size on gestation length, fetal growth and gestational effort (N = 11 females from Experiment 1).

<p>Estimates (mean ±SE) and tests were obtained from linear mixed models. Significant differences are indicated in bold.</p

Reproductive parameters of females fed <i>ad libitum</i> (AL) or exposed to either a 40% chronic caloric restriction (CR60) or a 80% acute caloric restriction (CR20).

<p>Reproductive parameters of females fed <i>ad libitum</i> (AL) or exposed to either a 40% chronic caloric restriction (CR60) or a 80% acute caloric restriction (CR20).</p

Effect of food availability on body mass over (A) gestation and (B) lactation.

<p>Body mass (±SEM) of females fed <i>ad libitum</i> (AL) and calorie restricted females (CR60) (A) during the two months following oestrus, and (B) during the 45 days after birth.</p

Effects of food availability on female condition (body mass), fertility (timing of oestrus, urinary estradiol level at oestrus - noted urinary E2) and mating success.

<p>‘Experiment’ accounts for potential differences in baseline levels among experiments 1 and 2. ‘Food effect’ accounts for the effect of food shortage (CR individuals, whatever the level of food shortage) <i>versus</i> no food limitation (AL individuals). ‘Food × Experiment’ interaction accounts for a difference in the impact of chronic <i>versus</i> acute caloric restriction (see methods for more details). Estimates (mean ±SE) and tests were obtained from linear models for body mass and E2 (after log-transformation), and with generalized linear models with a log-link (date of oestrus) or a logit-link function (Mating success). Significant differences are indicated in bold. Urinary E2 values were expressed in pg of E2 per mg of Creatinine.</p

Individual information and mortality/survival data for control and accelerated captive grey mouse lemurs

Data_Microcebus_murinus.csv contains individuals’ characteristics and the dates each individual enters and exits each season, from birth to death or censoring time, collected on captive grey mouse lemurs living under a control versus accelerated seasonal rhythm

Visual representation of the metapopulation structure for white storks in France during the five periods considered.

<p>The curves thickness is proportional to the number of individuals dispersing between the populations. Each node represents one population and is positioned in its center. The size of the nodes is proportional to the number of individuals. Codes for the populations are: W for West, S for South, C for Centre, NE for North-East and NW for North-West.</p

Temporal evolution of the asymmetry of links, cophenetic correlation coefficients (CCC), maximum modularities (Max. Mod.), and consecutive cluster determinations for the metapopulation.

<p>Statistically significant results are presented in bold. For the asymmetry tests, “<b>»</b>” indicate the direction of the asymmetry. Codes for the populations are: W for West, S for South, C for Centre, NE for North-East and NW for North-West.</p

Number of dispersal events (links) occurring inside (In) and outside (Out) of the clusters for each population and the corresponding ratio between them, “Out/In”.

<p>Codes for the populations are: W for West, C for Centre, NE for North-East and NW for North-West.</p