Quantifying unpredictability: A multiple-model approach based on satellite imagery data from Mediterranean ponds.

Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1) gathering long-term data and (2) handling the hard-won data. This paper takes advantage of the free access to long-term recordings of remote sensing data (27 years, Landsat TM/ETM+) to assess a set of environmental models for estimating environmental predictability. The case study included 20 Mediterranean saline ponds and lakes, and the focal variable was the water-surface area. This study first aimed to produce a method for accurately estimating the water-surface area from satellite images. Saline ponds can develop salt-crusted areas that make it difficult to distinguish between soil and water. This challenge was addressed using a novel pipeline that combines band ratio water indices and the short near-infrared band as a salt filter. The study then extracted the predictable and unpredictable components of variation in the water-surface area. Two different approaches, each showing variations in the parameters, were used to obtain the stochastic variation around a regular pattern with the objective of dissecting the effect of assumptions on predictability estimations. The first approach, which is based on Colwell's predictability metrics, transforms the focal variable into a nominal one. The resulting discrete categories define the relevant variations in the water-surface area. In the second approach, we introduced General Additive Model (GAM) fitting as a new metric for quantifying predictability. Both approaches produced a wide range of predictability for the studied ponds. Some model assumptions-which are considered very different a priori-had minor effects, whereas others produced predictability estimations that showed some degree of divergence. We hypothesize that these diverging estimations of predictability reflect the effect of fluctuations on different types of organisms. The fluctuation analysis described in this manuscript is applicable to a wide variety of systems, including both aquatic and nonaquatic systems, and will be valuable for quantifying and characterizing predictability, which is essential within the expected global increase in the unpredictability of environmental fluctuations. We advocate that a priori information for organisms of interest should be used to select the most suitable metrics estimating predictability, and we provide some guidelines for this approach

Post-Feeding Thermotaxis and Daily Vertical Migration in a Larval Fish

Many aquatic animals make daily vertical migrations, typically ascending into warm shallow strata for the night and descending to cooler, deeper layers of lakes or oceans for the day. Although some organisms may migrate to avoid predation(1−3) researchers have also suggested that daily migration is a thermoregulatory strategy allowing ectotherms to lower their metabolic rates in cold, deep waters, thus conserving energy(4,5). Tests of this hypothesis, however, have been equivocal(6−8). Here we suggest an alternative hypothesis: that fish ascend into warmer water after feeding to stimulate digestion, thereby allowing greater feeding and growth. We tested this hypothesis using the Bear Lake sculpin (Cottus extensus) which feeds on the bed of the lake during the day, and at night migrates into the water column where temperatures are 10 °C warmer. The warmer temperatures promoted digestion and allowed the fish to feed and grow three times faster than if they had remained in the cold hypolimnion. Thus, daily vertical migration in this species is an adaptation allowing them to exploit thermal gradients in their environment(9) to maximize energetic intake

Limnological Control of Brine Shrimp Population Dynamics and Cyst Production in the Great Salt Lake, Utah

In the Great Salt Lake of Utah, the brine shrimp Artemia franciscanaKellogg is an important food resource for birds and they produce dormant cysts that are harvested and used extensively in the aquaculture industry.We analyzed the limnological factors controlling Artemia growth and cyst production over 12 months in 1994 and 1995. Laboratory experiments showed that inter-brood intervals were highly dependent on temperature and slightly on food level. At optimal temperatures and nutritious food, juveniles reached reproductive size within 7 d in the laboratory. In winter when temperatures were less than 3 ◦C, Artemia were absent from the lake, phytoplankton abundance was high (≥13 Chl a μg l−1), and the dominant grazers were ciliated protozoans. In the spring, cysts hatched when phytoplankton was abundant (15–30 μg Chl a l−1), and the Artemia grew and produced large clutches of ovoviviparous eggs. Estimated naupliar production from these eggs was 80 l−1 from April to May. Despite the high production of nauplii, Artemia densities declined to 8 l−1by June and the growing shrimp population grazed down the phytoplankton resource to \u3c1 μg Chl a l−1. With the depleted phytoplankton food resource during the summer, Artemia growth slowed, lipid indices decreased, clutch sizes declined, and females switched primarily to oviparous cyst production. During the summer, there was limited production of ovoviviparous eggs, and limited recruitment of juveniles, probably due to low food. Although oviparous reproduction began in June, more than 90% of the cysts were produced after July when female densities had declined to 1.5 l−1, but nearly all of them were producing cysts. Estimated cyst production was 650 000 m−2, or 4.54 × 10^6 kg dry weight for the entire lake. The reported commercial harvest took 21% of the 1994 cyst production. That harvest had little impact on the subsequent year’s population, as Artemia densities were ultimately controlled by algal production in the lake