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    Privately protected lands have outsized benefits

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    As plant and animal species disappear at breakneck speed owing to human activity, researchers reveal that privately owned protected areas are helping to halt the loss of biodiversity, particularly in overlooked regions1.

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    doi: https://doi.org/10.1038/d41586-022-00984-w

    ReferencesPalfrey, R., Oldekop, J. A. & Holmes, G. Nature Ecol. Evol. https://doi.org/10.1038/s41559-022-01715-0 (2022).Article 

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    Glycoside hydrolase from the GH76 family indicates that marine Salegentibacter sp. Hel_I_6 consumes alpha-mannan from fungi

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    Trajectory to local extinction of an isolated dugong population near Okinawa Island, Japan

    Deterministic logistic modelThe following population dynamics model was applied to reconstruct the initial dugong population size in 1894 from fishery statistics between 1894 and 1914:$$N_{t + 1} = N_{t} left( {1 , + r{-}r , N_{t} /K} right) – C_{t} ,$$where r is the intrinsic rate of population increase, Nt is the population size in year t, K is the carrying capacity, and Ct is the number of individuals removed from the waters near the Ryukyu Islands in year t. The carrying capacity (K) in 1893 was sufficient to sustain the initial population of dugongs at that time (N1894). The intrinsic rate of population increase (r) was given between 1 and 5% within a range of natural one.Approximate Bayesian calculationWe conducted approximate Bayesian calculation (ABC)32 to estimate the number of individuals in 1979 based on bycatch data between 1979 and 2019, and the constraints of the numbers of individuals were 11 in 1997, three in 2007, and almost extinct in 2019. We denoted fecundity as f, the survival rate until 1 year old as s0, the annual survival rate after 1 year old as s, the age at maturity as am, and the physiological longevity as A. We assumed that the sex ratio at birth was 1:1 on average; the age at maturity am was eight years of age33, and the physiological longevity A was 73 years6. We ignored environmental stochasticity because no mass deaths caused by infectious diseases or changes in survival or mortality rates due to environmental fluctuations have not been recorded during this period. We also ignored density effects because the carrying capacity of the location was sufficiently greater than the initial population size, and our goal was to investigate the possibility of population recovery after a decrease in population using a population dynamics model and estimate the natural growth rate during this period. The detailed extinction risk depends on age structure.According to the life history parameters, except the physiological longevity compiled by (ref.33), the annual survival probability of an a year-old individual is s for a = 1, 2, …, 72; s0 for a = 0, and 0 for a = 73; the reproductive probability of an adult female  > 8 years old is 2f. As the number of years for a population to become extinct or recover depends on age composition, age-specific survival, and reproductive rates, we obtain the population growth rate by the maximum eigenvalue of the following Leslie matrix, L = {Lij} (i = 1,…73, j = 1,…,73) as:$$L_{i1} = s_{0} f/2quad {text{for}}quad i ge a_{m} ,L_{i+ 1,i} = squad {text{for}}quad i = 1, ldots ,72,quad {text{and}}quad L_{ij} = 0,{text{otherwise}}{.}$$We used the population growth rate λ, defined by the maximum eigenvalue of L, as an indicator of the population growth rate.We assumed that the sex of each individual in 1979 was randomly sampled by the 1:1 sex ratio, and its age was randomly sampled by the stable age structure that is given by the eigenvector of the Leslie matrix with the maximum eigenvalue. We assumed that the number of individuals at age 1 year in year t + 1, denoted by N1,t+1, is determined by the binomial distribution:$$Prleft[ {N_{1,t + 1} = x} right] = left( {begin{array}{*{20}c} {N_{f} } \ x \ end{array} } right)left( {s_{0} f} right)^{x} left[ {1 – left( {s_{0} f} right)} right]^{{N_{f} – x}} ,$$where Nf represents the number of adult females in year t. We assumed that no twins were born. We assumed that the probability that an individual with age x survived in the next year is s if x = 1 or s0 if x = 0. We also assumed that Ct individuals who died by bycatch were randomly chosen from any sex and age because the age of individuals caught by bycatch is rarely known. We do not know the sex of some individuals.We assumed the following prior distributions for N1997, f, and s: N1979 (in) U(11, 80), f (in) U(1/14, 1/6) if at least one adult male existed in the population, s0 (in) U(0.1, 0.85); and s (in) U(0.8, 0.97), where U(a, b) is the uniform random variable between a and b. These probabilities were constant for each simulation trial from 1997 to 2019. We selected the set of parameters with the population growth rate (λ) obtained when the maximum eigenvalue of the Leslie matrix was between 0.96 and 1.01.We rejected trials that did not satisfy the following summary statistics: N1997 ≥ 11 (intensive survey in 1997), Nt ≥ 3 during 2004–2017 (monitoring), and N2019 ≤ 1 (“local extinction”). We obtained the prior distributions of N1997, f, s0, s, and N2004, and of the  > 130,000 trials in the prior distribution with natural population growth rates λ of 96.1–98.8%, 99.3% were rejected. For 95% of the 1000 adopted trials, N1979 ranged from 14 to 58. If λ  > 98%, N1997 was ≤ 45 for the adopted trials (Extended Data Fig. 7. Even if all the stranding deaths were due to anthropogenic factors, such as the release of dugongs after bycatch or boat strike, the range of N1997 changed to  98%, with only a slight upward shift, but positive natural growth rate (or λ  > 1) was again very unlikely (0.3%) among the adopted trials.Population viability analysis to assess the impact of bycatch on the extinction riskWe re-evaluated the extinction risk with and without bycatch using the 1000 parameter sets of N1979, f, s0, and s that satisfied the summary statistics in the ABC and stochastic individual-based model, beginning from N1979 for the corresponding parameters. For each parameter set, 100 trials were conducted for each scenario to compare the extinction risks. More

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    Direct effects of elevated dissolved CO2 can alter the life history of freshwater zooplankton

    Animal culture and mediumFive different clonal lineages of the water flea Daphnia magna were sampled from two ponds on agricultural land in Belgium (Vleteren: 50°55′06.7″ N, 2°43′27.0″ E and De Haan 51°13′53.8″ N, 3°01′49.2″). They were cultured separately in 210 ml glass jars under optimized laboratory conditions (20 ± 1 °C, 14:10 h light:dark cycle). Seed shrimp and rotifer resting eggs were obtained from a commercial supplier (MicroBioTests Inc., H. incongruens strain MBT/1999/10, product code TB36; B. calyciflorus, product code TK21, Belgium) and represent laboratory cultured, single clonal lineages. More details on animal culture are reported in the online supplementary methods (Appendix 3).Natural pond water was used as medium both in animal cultures and the experiment. It was extracted from a Belgian region (50°59′00.92″ N, 5°19′55.85″ E, Zonhoven) with soft, poorly buffered water (Alkalinity 3–8°d; pH 6.5–8.5) which is likely to be susceptible to acidification under elevated pCO2. More information on medium and mineral composition is reported in the online supplementary information (Appendix 3; Table S3, Appendix 1).Experimental set-upOrganisms were exposed to three pCO2 treatments, an ambient control (C; 1,520 ppm ± 702 SD), an elevated (T1; 25,609 ppm ± 4,541 SD) and an extreme pCO2 level (T2; 83,201 ppm ± 15,533 SD). The control pCO2 level represents the current global mean that is measured in lentic freshwaters considering most ponds and lakes are already supersaturated10,12. The T1 level is currently only observed in more extreme cases11. However, it reflects a pCO2 level that could be encountered more commonly in the field in the future. The T2 treatment represents an extreme test of the tolerance limits of extant species. These treatments are a necessary simplification of reality since pCO2 can experience strong fluctuations in ponds and lakes. An overview of freshwater pCO2 concentrations from literature can be found in Table S1 (Appendix 1).The elevated pCO2 concentrations were manipulated in the water by injecting pure CO2 (99.998% pure, ALPHAGAZ CO2 SFC * B50-N48, Airliquide, Belgium) from gas cylinders into the water (cf.49) at a constant flowrate, using a high-pressure regulator (HBS 200–10.2,5; AirLiquide, Belgium) and a flow controller (Sho-rate model 1350G, Brooks Instruments, USA). In the control treatment, ambient air was supplied at a similar rate as the CO2 to ensure equal perturbation levels across all containers. Water of all experimental containers (including control) were also injected with ambient air to keep the water oxygenated. A relatively constant pCO2 was ensured by continuously monitoring pH and kept between a range of ~ 20,000–30,000 ppm (pH 6.9–6.7) for T1 and ~ 70,000–120,000 ppm (pH 6.4–6.1) for T2 (Figure S2, Appendix 2).Each treatment included 13 replicate 210 mL glass jars per species, resulting in a total of 117 experimental units. Per replicate, one mature water flea (8–11 days old) was inoculated in a jar containing aerated pond water. The five clonal lineages were distributed evenly over the experimental conditions so that each condition had the same number of replicates per clone. Seed shrimp replicates each contained one newly hatched ( More