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opencc-by-4.0Dec 2020View details →

Рис. 2. Размерная структура G. lacustris в ΛитораΛьной зоне озера АрахΛей: 1 — июнь; 2 — август; 3 — октябрь Fig. 2. G. lacustris population size structure in the Lake Arakhley littoral zone: 1 — June, 2 — August, 3 — October in The life cycle of Gmelinoides fasciatus (Stebbing, 1899) and Gammarus lacustris (Sars, 1863) amphipods in the lake Arakhley littoral during the extreme low-water phase of the hydrological cycle

Рис. 2. Размерная структура G. lacustris в ΛитораΛьной зоне озера АрахΛей: 1 — июнь; 2 — август; 3 — октябрь Fig. 2. G. lacustris population size structure in the Lake Arakhley littoral zone: 1 — June, 2 — August, 3 — October

opencc-by-4.0Dec 2020View details →

Рис. 1. Размерная структура Gm. fasciatus в ΛитораΛьной зоне озера АрахΛей: 1 — в июне; 2 — в августе; 3 — в октябре; 4 — в Αекабре 2017 г. и июне 2018 г. Fig. 1. Gm. fasciatus population size structure in the Lake Arakhley littoral zone: 1 — June; 2 — August; 3 — October; 4 — December, 2017 and June, 2018 in The life cycle of Gmelinoides fasciatus (Stebbing, 1899) and Gammarus lacustris (Sars, 1863) amphipods in the lake Arakhley littoral during the extreme low-water phase of the hydrological cycle

Рис. 1. Размерная структура Gm. fasciatus в ΛитораΛьной зоне озера АрахΛей: 1 — в июне; 2 — в августе; 3 — в октябре; 4 — в Αекабре 2017 г. и июне 2018 г. Fig. 1. Gm. fasciatus population size structure in the Lake Arakhley littoral zone: 1 — June; 2 — August; 3 — October; 4 — December, 2017 and June, 2018

opencc-by-4.0Aug 2019View details →

Fig. 1 in Rodent population cycle as a determinant of gastrointestinal nematode abundance in a low-arctic population of the red fox

Fig. 1. Map showing the sampling sites on Varanger peninsula in northern Norway. Red triangles denote the sites where the 612 red foxes included in the analyses were. sampled. White squares denote sites where rodents were trapped for the purpose of monitoring their population dynamics. Dark areas are sub-arctic birch forest, while areas with different shading of grey show tundra at different altitudes. The meteorological station from which the climate data were derived, is denoted with a blue star. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

opencc-by-4.0Aug 2019View details →

Fig. 2 in Rodent population cycle as a determinant of gastrointestinal nematode abundance in a low-arctic population of the red fox

Fig. 2. Time series of annual climate variables, rodent density and egg counts of gastrointestinal parasites (i.e. number of eggs recorded) in red foxes faeces in Varanger Peninsula. A) The mean summer temperature (̊C) for July, August and September from the weather station in Vardø (see Fig. 1). Horizontal broken lines show the 1960–1990 normal for temperature. B) Rodent density indexed as number of individuals caught per 100 trap nights in early September based on the trapping sites shown in Fig. 1 and number of foxes culled each winter season and local hunter (grey). Note that 2005 represents the foxes culled winter 2005–2006. C) Abundance (mean number of eggs per gram with standard error) of the three parasite species in the annual fox samples. Note the left (red) y-axis represents T. leonina while the right (black) y-axis represents T. canis and U. stenocephala. D) Prevalence (proportion of foxes with parasites, with standard error) of the three parasite species in the annual fox samples. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

opencc-zeroAug 2021View details →

Slower environmental cycles maintain greater life-history variation within populations

Populations in nature are comprised of individual life histories, whose variation underpins ecological and evolutionary processes. Yet the forces of environmental selection that shape intrapopulation life-history variation are still not well understood, and efforts have largely focused on random (stochastic) fluctuations of the environment. However, a ubiquitous mode of environmental fluctuation in nature is cyclical, whose periodicities can change independently of stochasticity. Here we test theoretically-based hypotheses for whether shortened ('Fast') or lengthened ('Slow') environmental cycles should generate higher intrapopulation variation of life history phenotypes. We show, through a combination of individual-based modelling and a multi-generational laboratory selection experiment using the tidepool copepod Tigriopus californicus, that slower environmental cycles maintain higher levels of intrapopulation variation. Surprisingly, the effect of environmental periodicity on variation was much stronger than that of stochasticity. Thus, our results show that periodicity is an important facet of fluctuating environments for life-history variation.

Figure 4 A-E in LIFE CYCLE OF NATURAL POPULATIONS OF METRIOCNEMUS (INERMIPUPA) CARMENCITABERTARUM LANGTON & COBO 1997 (DIPTERA: CHIRONOMIDAE) IN THE NETHERLANDS: INDICATIONS FOR A SOUTHERN ORIGIN? Abstract

Figure 4 A-E. Numbers of adults, egg strings and pupal exuviae of Metriocnemus (Inermipupa) carmencitabetarum recorded between April and December in 2012 and 2013 at Appingdam and Nijmegen and of 4th instar larvae at Nijmegen in 2013: 4A number of adults and egg strings at Appingedam, 2012; 4B number of adults and pupal exuviae at Appingedam 2013; 4C number of adults and egg strings at Nijmegen 2012; 4D number of adults and pupal exuviae at Nijmegen 2013; 4E numbers of 4th instar larvae recorded in the upper 50 cm of the water butt at Nijmegen, 2013. Horizontal brackets indicate periods of adult activity of one generation. Periods with no observations are shaded.

Figure 3 in LIFE CYCLE OF NATURAL POPULATIONS OF METRIOCNEMUS (INERMIPUPA) CARMENCITABERTARUM LANGTON & COBO 1997 (DIPTERA: CHIRONOMIDAE) IN THE NETHERLANDS: INDICATIONS FOR A SOUTHERN ORIGIN? Abstract

Figure 3. Emergence pattern of the wintering generation from the Appingedam vase in spring 2014 (black dots and solid line) and hypothetical emergence pattern when larval development would have been interrupted by a diapause (dotted line). Number of pupal exuviae are added up per week.

Figure 5 in LIFE CYCLE OF NATURAL POPULATIONS OF METRIOCNEMUS (INERMIPUPA) CARMENCITABERTARUM LANGTON & COBO 1997 (DIPTERA: CHIRONOMIDAE) IN THE NETHERLANDS: INDICATIONS FOR A SOUTHERN ORIGIN? Abstract

Figure 5. Seasonal length differences in male and female pupal exuviae in Nijmegen in 2013, with a binomial fit (left y-axis). The two wavy lines represent mean weekly minimum and maximum temperatures from April to October (right y-axis).

Figure 1 in LIFE CYCLE OF NATURAL POPULATIONS OF METRIOCNEMUS (INERMIPUPA) CARMENCITABERTARUM LANGTON & COBO 1997 (DIPTERA: CHIRONOMIDAE) IN THE NETHERLANDS: INDICATIONS FOR A SOUTHERN ORIGIN? Abstract

Figure 1. Distribution of Metriocnemus (I.) carmencitabertarum in the Netherlands and the location of the two research sites Appingedam and Nijmegen.

Figure 2 in LIFE CYCLE OF NATURAL POPULATIONS OF METRIOCNEMUS (INERMIPUPA) CARMENCITABERTARUM LANGTON & COBO 1997 (DIPTERA: CHIRONOMIDAE) IN THE NETHERLANDS: INDICATIONS FOR A SOUTHERN ORIGIN? Abstract

Figure 2. Head width and head length of wintering larvae collected in the Appingedam vase in December 2013 and February 2014. Results are projected in a HW-HL graph of the four M. (I.) carmencitabertarum instars obtained from Kuper (2015) revealing wintering in 3rd and 4th larval stage in the Appingedam vase.

Figure 6 in LIFE CYCLE OF NATURAL POPULATIONS OF METRIOCNEMUS (INERMIPUPA) CARMENCITABERTARUM LANGTON & COBO 1997 (DIPTERA: CHIRONOMIDAE) IN THE NETHERLANDS: INDICATIONS FOR A SOUTHERN ORIGIN? Abstract

Figure 6. Correlation between mean ambient temperature during development and skin size for males and females from the Nijmegen water butt in 2013.

opencc-zeroSep 2023View details →

Numerical response of predator to prey: Dynamic interactions and population cycles in Eurasian lynx and roe deer

The dynamic interactions between predators and their prey have two fundamental processes; numerical and functional responses. Numerical response is defined as predator growth rate as a function of prey density or both prey and predator densities [dP/dt = f(N, P)]. Functional response is defined as the kill rate by an individual predator being a function of prey density or prey and predator densities combined. Although there are relatively many studies on the functional response in mammalian predators, numerical response remains poorly documented. We studied numerical response of Eurasian lynx (Lynx lynx) to various densities of its primary prey species, roe deer (Capreolus capreolus), and to itself (lynx). We exploited an unusual natural situation, spanning three decades where lynx, after a period of absence in central and southern Sweden, during which roe deer populations had grown to high densities, subsequently recolonized region after region, from north to south. We divided the study area into seven regions, with increasing productivity from north to south. We found strong effects of both roe deer density and lynx density on lynx numerical response. Thus, both resources and intraspecific competition for these resources are important to understand the lynx population dynamic. We built a series of deterministic lynx–roe deer models and applied them to the seven regions. We found a very good fit between these Lotka-Volterra-type models and the data. The deterministic models produced almost cyclic dynamics or dampened cycles in five of the seven regions. Thus, we documented population cycles in this large-predator-large-herbivore system, which is rarely done. The amplitudes in the dampened cycles decreased towards the south. Thus, the dynamics between lynx and roe deer became more stable with increasing carrying capacity for roe deer, which is related to higher productivity in the environment. This increased stability could be explained by variation in predation risk, where human presence can act as prey refugia, and by a more diverse prey guild that will weaken the direct interaction between lynx and roe deer.

publicAug 2024View details →

Data and code for: Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next cycles

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publicSep 2023View details →

Numerical response of predator to prey: Dynamic interactions and population cycles in Eurasian lynx and roe deer

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