Microscale patterns of habitat fragmentation and disturbance events as a result of chemical applications:

Transcription

1 Microscale patterns of habitat fragmentation and disturbance events as a result of chemical applications: effects on Folsomia candida (Collembola) populations Mattia Meli Annemette Palmqvist, Valery E. Forbes 1

2 Introduction In assessing soil quality and the ecological risk of contamination by chemicals, homogeneous contamination is often assumed However, soils are a very heterogeneous environment Both contamination and the response of soil organisms can be assumed to be heterogeneous, too Consequences for the exposure of soil organisms and for the extrapolation of risk from the individual to the population level 2

3 Approach Model organism: Folsomia candida (Willem, 1902), Collembola - Standard test arthropod (OECD-guideline 232, 2009) - Common & widely distributed - Parthenogenetic - Life cycle parameters well known Spatially explicit individual-based population model - individuals sense and avoid contaminated habitat with defined probability - Rules and parameters based on data from the literature - Parameterized and evaluated using Pattern Oriented Modeling (POM) Meli M., Auclerc A., Palmqvist A., Forbes V.E. and Grimm V. Population-level consequences of spatially heterogeneous exposure to heavy metals in soil: an individual-based model of springtails. Ecological Modelling 250,

4 Model contaminant Copper sulphate (CuSO 4 ) - Persistent - Extensively used as fungicide - Most widely distributed pollutant among metals Individual-level toxicity data - Reproduction Fecundity reduction (normalized to control) = ln concentration R 2 = Survival Survival reduction (normalized to control) = ln concentration Sandifer & Hopkin, Chemosphere, 1996: Effects of ph on the toxicity of cadmium, copper, lead and zinc to Folsomia candida Willem, 1902 (Collembola) in a standard laboratory test system R 2 = Egg viability % eggs hatching (normalized to control) = ln concentration R 2 = Xu et al., Insect Science, 2009: Effects of copper, lead and zinc in soil on egg development and hatching of Folsomia candida - Avoidance % avoidance = ln concentration Boiteau et al., Environmental Pollution, 2011: Avoidance tests with Folsomia candida for the assessment of copper contamination in agricultural soils R 2 =

5 Conceptual model Energy < threshold? FORAGE Survive? DIE AGIG DESIT-DEPEDET OVIPOSITIO Age maturation time? Time since last reproduction = Time between broods? REPRODUCE Eggs ewborn juveniles HATCH Age hatching time 5

6 Movement & Avoidance behaviour Food heterogeneously distributed: typically, 10 % of grid-cells are food sources Sense food? Turn random angle Turn towards food cell Cell in front of you contaminated? Avoid? Move 1 step Turn toward an uncontaminated cell Energy spent for moving > threshold? OR Found food? Move 1 step and increase exposure counter EXIT 6

7 Sensitivity analysis Sensitivity analysis of parameters not directly determined from literature Directly determined Sensitive (inversely determined) Insensitive (initial values maintained) 7

8 Pattern oriented parameterization Excess food Slightly limiting food Limiting food Log population size Days Observed data from Usher et al.. Oecologia, 1971: Studies on populations of Folsomia candida (Insecta: Collembola). The productivity of populations in relation to food and exploitation observed simulated 95% CL Resulting mean density Range Estimated r Range Observed 463,21 207,62 774,67 0,178 0,166 0,199 Simulated 548, ,163 0,158 0,175 Observed data from Seifert et al., J Kans Entomol Soc, 1979: estimation of the intrinsic rate of increase (r) and density-dependent population size of F. candida cultures 8

9 Model performance 28-days exposure in artificial soil 20 ± 1 C temperature Mean ± Standard Error of mean for 4 replicates Instantaneous population growth rate 0,10 0,08 0,06 0,04 0,02 0,00-0,02-0,04-0,06-0,08-0, , Concentration (mg kg -1 ) observed simulated Observed data from Herbert et al., Ecotoxicology and Environmental Safety, 2004: Comparison of instantaneous rate of population increase and critical-effect estimates in Folsomia candida exposed to four toxicants 9

10 Simulation scenarios - Midpoint displacement algorithm used to generate fractal landscapes - 3 degrees of spatial autocorrelation of contaminated habitat (H) - Varying % of uncontaminated habitat (0-30%) H=0 H=0.72 H=1 - Simulation of a 30 day drought period - Progressive reduction of soil relative humidity - Effects of drought on F. candida derived from empirical observations Waagner et al, Soil biology & biochemistry, 2011: Recovery of reproduction after drought in the soil living Folsomia candida (Collembola) Relative humidity (%) , , , , , Time since beginning of drought period (days)

11 Results - Constant temperature - Initial population: 100 individuals (adults and juveniles) - Varying % of uncontaminated habitat (0-30%) - Same concentration (4500 mg Cu kg -1 ) 6000 With avoidance Without avoidance Final abundance (individuals m -2 ) H=0 H=0.72 H= % clean habitat Error bars: Standard Error of mean for 10 replicates H=0 H=0.72 H= % clean habitat

12 Results -20% clean habitat - Varying degrees of spatial autocorrelation of contaminated habitat - Same concentration (4500 mg Cu kg -1 ) - Drought period from day 200 to day 230 Abundance (individuals m- 2 ) With avoidance H=0 H=0.72 H=1 Without avoidance Mean ± Standard Error of mean for 10 replicates Time (days) 12

13 Conclusions Application method of a pesticide influences its distribution in soil. This can affect the impact on soil-dwelling organisms: scattered or clumped distributions of toxicant in soil do not have the same impact on F. candida populations. Avoidance should also be taken into account Modelling can add ecological realism to ERA by incorporating effects of natural stress that occur in the field, such as drought or food scarcity, and that may delay population recovery Models can be used in an exploratory way to predict the effects of different risk management options 13

14 Thank you For your attention! ACKOWLEDGEMETS: This research has been financially supported by the European Union under the 7 th Framework Programme (project acronym CREAM, contract number PIT-GA )